Measuring and improving productivity in a job shop...

Eindhoven, August 2007

Student identity number 0576606

in partial fulfilment of the requirements for the degree of

Master of Science

in Operations Management and Logistics

Supervisors:

Dr. ir. H.P.G. van Ooijen, TU/e, OPAC

Dr. ir. P.A.M. Kleingeld, TU/e, HPM

Measuring and improving productivity in a job shop

environment: the applicability of the ProMES

methodology

By

T. de Boer

Measuring and improving productivity in a job shop environment

T. de Boer 2

TUE. Department Technology Management.

Series Master Theses Operations Management and Logistics, nr.11

ARW 2007 OML / 11

Subject headings: Human performance, Production processes, productivity measurement,

productivity improvement.


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Preface

The final project in the Master of Science program is the Master Thesis Project. The master thesis

project is the final part of the Operations Management and Logistics (OML) master’s degree

program. The project consists of a research and design assignment to be independently carried out

by the student. First, the student has to prepare himself for this project during the periods

preliminarily to this actual Master Thesis Project. This period is called the Master Thesis

Preparation. The assignment for this preparation is to conduct a literature study about the

graduation topic and second, to write a research proposal. At the time of writing this report, the

Master Thesis Preparation is finished.

This report is the result of the graduation project conducted as a scientific research within the

Technical University of Eindhoven. The Master Thesis Project is conducted in order of the

Operations Planning Accounting and Control (OPAC) group of the department Technology

Management. The first supervisor is dr. ir. H.P.G. van Ooijen and represents the OPAC research

domain; production control in capital goods industry. The second supervisor is dr. ir. P.A.M.

Kleingeld and represents the Human Performance Management group.

I want to thank the people of Exerion Precision Technology for their cooperation and time for this

research project. It was not always easy to make appointments in-between the normal working

times, but when finally the conversations took place, they were very enthusiastic and willingly to

cooperate. Second I want to thank my thesis mentor, dr. ir. H.P.G. van Ooijen. I am very grateful

to him for the provided cooperation what led to a sufficient development and execution of the

master thesis project. I also want to thank the second supervisor dr. ir. P.A.M. Kleingeld for the

cooperation on this project.


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Abstract

This thesis describes a research about productivity measurement and improving in a production

process situation called a “job shop”. A job shop is a system in which various machines

manufacture various products. A typical job shop is defined by the number of jobs, the number of

machines and the many different routings in which the jobs are processed and is commonly used

to meet specific customer orders and there is great variety in the type of work done in the plant.

This research tried to apply the performance measurement system called “ProMES”, which stands

for “Productivity Measurement and Enhancement System” to a job shop situation. The main

problems which showed up at applying a ProMES system to a job shop situation at unit level are

the difficult decomposition of departmental productivity, the low controllability on productivity

and the increasing risks at sub-optimization. The purpose of this paper is to describe the results of

the literature study, discuss ideas for applying ProMES to a job shop situation, describe the

possibilities within the research company and finally to present solutions and recommendations

about how ProMES should be applied in a job shop production process.


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Management abstract

THE MASTER THESIS PROJECT

The project is based on the following research objective:

“The objective of the Master Thesis Project will be to analyse the applicability of ProMES into a

job shop setting; thus to study whether and in what way ProMES could help to improve

productivity in a job shop production process”.

Four research questions are stated according to the research objective. The four research

questions are formulated as following:

1. What are the characteristics of a job shop production process?

2. What are the characteristics of ProMES?

3. Can productivity be measured in a job shop situation?

4. How can ProMES be applied to a job shop situation?

Question one and two are both discussed according to a literature study and question three and

four are discussed according to both a practical analyses of the research company and analysis of

the literature research results.

A JOB SHOP PRODUCTION SYSTEM

A job shop system is a classification of discrete production systems in which various machines

manufacture various products and the manufacturing of a single product may require several

successive process steps, each on another machine. In a job shop environment machines are

ordered in groups, having the same functionality. Typical for a job shop system is that not every

manufactured product requires the same process steps on the same machines in the same order.

The production process of a single product is generally referred to as a job and a single process

step required is referred to as an operation. A typical job shop is defined by the number of jobs,

the number of machines and the many different routing in which the jobs are processed.

According to Pritchard, Jones, Roth, Stuebing and Ekeberg (1989), productivity is a combination

of both effectiveness and efficiency. Efficiency is an output to input ratio and effectiveness is the

relationship of outputs to some standards or expectations. Thus efficiency is how well the

organization uses its resources to produce its products or services. Effectiveness is how well the

organization is reaching its goals. This study will define productivity as “how well a system uses

its resources to achieve its goals” (Pritchard, 1992, p. 455).

We studied scientific literature about current ways of measuring performance in job shops. We

conclude the objective of both the measurement systems described in current scientific literature

and the ProMES approach is to improve productivity, but the ProMES approach (which is used in

this research) motivates people to change their working behaviour by themselves to improve

productivity.

THE PROMES METHODOLOGY

The concern of the ProMES (Productivity Measurement and Enhancement System) approach is

how to structure work so that people can and will want to behave in a way that will maximize

their productivity (Pritchard, 1995).


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The purpose for measuring productivity, according to the ProMES approach is used as a

motivational tool. “The objective is to improve productivity and the assumption is that if

individuals change their behaviour appropriately, productivity will increase” (Pritchard, 1990, pp.

10). Here it is assumed that the personnel have a great impact on productivity. They work more

efficiently because their effort is more directly related to organizational objectives and they

improve work strategies.

The department constructs the system by defining their objectives, identifying productivity

indicators for each objective, developing utility curves or contingencies for each indicator and

specifying the overall and relative value to the organization of different performance levels on

each indicator. The performance what subsequently is achieved is than fed back by means of a

feedback report. Productivity enhancement is thus tried to achieve by setting difficult, but

reachable goals and subsequently giving feedback on the performance on these goals. This will

lead to changes in motivation which on his turn will lead to increased productivity of the

employees.

The ProMES system is based on three principles from the motivation literature; goal setting,

feedback and reinforcement. The design of a ProMES system is characterized by a bottom-up

design process, a bottom-up design process means that the system is developed by the lower level

of the organization.

ProMES has been successfully implemented in different organisations, departments and setting,

but has only been implemented once in the situation of complex interdependencies between

machines and teams such as a job shop production process (Huve, 2005).

PRODUCTIVITY MEASUREMENT IN JOB SHOPS ProMES can in theory be developed and applied to different group sizes and at three levels

(Pritchard 1990). The three levels that can be determined are individual level, group level and

department level. Evaluating both job shop processes and the ProMES methodology with its

requirements, we could identify four aspects (the between-group dependencies, shifting operators,

varying orders, and the different interests of units) which are related to three main

problems/difficulties for applying ProMES to a job shop:

1. Decomposition of departmental performance - Departmental performance can hardly be

decomposed into the performance of independent units.

2. Low controllability - Groups can have a substantial, but not major influence on system

performance.

3. Risks at sub-optimization - Job shops consists of multiple compositions of groups with

different interests.

Due to the theoretically stated problems and difficulties which show up at applying ProMES to a

job shop, we do not know what the possibilities in a practical situation are. That’s why we

formulated several ideas for applying ProMES to a job shop. The ideas are set up from the point

of view of the desired situation and it is also tried to solve the problems by these ideas.

The main goal of the ProMES methodology is to improve the productivity of the employees in

order to achieve the organisational objectives. For example; manufacture more and innovative

products in a safe environment at low cost. The changes in productivity will at first be

recognizable at departmental level. When productivity changes are recognized at departmental

level, in for example; processing times, lateness and quality, we want to be able to determine

which factors at unit level influenced these changes.


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And the other way around, when changes are applied on unit level, we want to be able to

determine to which changes that will lead in total departmental productivity. From this point of

view, we formulated the first idea. The other three ideas are formulated to try to overcome the

problems showed up at the preceding ideas. The ideas are tested according to the situation at the

research company. The four ideas are:

1. Develop a ProMES system for the department, and measure each functional unit

individually

2. Expand idea 1 with measures on departmental level

3. Develop a ProMES system for the department, and measure a group of functional units

4. Develop a ProMES system for the department, and measure on departmental level

MAIN RESULTS OF THE PRACTICAL ANALYSIS The main results of analyzing the research company are:

1. It is possible to decompose the departmental productivity into single unit’s productivity. This

means that at the research company it is possible to develop a ProMES system at unit level

2. The chances at sub-optimization of the units are low at the research company

3. The problem of low control over the productivity of the employees due to interdependencies

is minimal

4. The problem of getting enough historical experience to make any judgments about what is

low or high output is not that difficult as found in literature

5. The problem of unreliable measures due to shifting and working with several shifts could be

solved by enlarging the measurement period to average out the fluctuations in productivity

per day or week.

The outcome of the literature research and the analysis at the research company is that the desired

situation can be created. Thus the conclusion is that the best idea is to develop the ProMES

system at departmental level and information about productivity is measured and evaluated at unit

level.

RECOMMENDATIONS

Along with the solution about the most optimal level of measurement (which is also possible in

practice) we provide recommendations about how to apply and develop a ProMES system to a

job shop, as outcome of this research. The main recommendations are as following:

1. The ProMES system has to be developed by determining common products and indicators for

each unit, contingencies will be drawn for each unit, and the feedback report contains the

overall departmental score and also shows the individual unit contribution to that score.

2. This general feedback report is then build-up out of the unit scores and represents the overall

score of the department on each product and a total departmental productivity score.

3. Remove the interdependency relationships by; proper development of indicators, by detailed

planning and scheduling processes and by the use of a central warehouse.

4. Rescale contingencies so each unit’s productivity can be summed up.

5. The responsibilities, roles and activities have exactly to be appointed and applied to one of

the functional units.

6. Develop an information system for; exchange of information, increase cooperation between

units, generating and registering productivity and decreasing time and effort to maintain the

system.

7. Decrease chances at sub-optimization between units and create a cooperative organization.


T. de Boer 8

8. Enlarge the measurement period to average out the uncontrollable variation in productivity.

9. Restrict the responsibility to tasks that are completely controllable (e.g. do not cover all parts

of the unit’s tasks).

THE DEVELOPED PROMES SYSTEM FOR A JOB SHOP

To explain and clarify the outcomes of the research we developed a design of a ProMES system

as it should be applied to the job shop production process of the research company. We worked

out (a part of) the presented solutions and recommendations in this design.

CONCLUSIONS By matching the theoretically developed statements with the results of the practical analysis, we

were able to determine how the ProMES system has to be developed, and how it leads to

increases in motivation and the highest gain in total productivity of the overall job shop floor,

thus representing a successful measurement and enhancement system

This research shows that the characteristics of both the job shop production process of the

research company and the ProMES methodology can be matched so productivity can be

measured and a ProMES system can properly be applied. We were able to do this because the

situation of the research company did not lead to the difficulties and problems as were assumed in

literature. Some of the theoretical stated assumptions (e.g. the complex interdependencies

between units) were not valid at the research company, so it was possible to apply ProMES at unit

level, in comparison with the study of Huve (2005). We also analyzed the research company

along with scientific literature to define recommendations. These can generally be applied to

other situations to help to increase the effectiveness and success of ProMES because these are not

dependent on this specific situation. On the other hand, the design of the system is applicable to

the research company because of the specific situation in which the study is conducted.

Even though we have designed an effective and efficient ProMES system for the research

company, and determined some important recommendations, people have to bear in mind that the

implementation of a ProMES system is also dependent on other factors which are not considered

in this research


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Table of content

Preface............................................................................................................................................. 3 Abstract ........................................................................................................................................... 4 Management abstract....................................................................................................................... 5 Table of content............................................................................................................................... 9 1. Introduction ........................................................................................................................... 11 2. The master thesis project ....................................................................................................... 12

2.1 Motive of the research.................................................................................................. 12 2.2 Overview of the Master thesis preparation .................................................................. 12

2.2.1 Literature research ................................................................................................... 12 2.2.2 Deliberations of the alternative PM systems ........................................................... 13 2.2.3 Conclusion ............................................................................................................... 14

2.3 Definition of the final research objective and questions .............................................. 14 2.4 Research design and approach ..................................................................................... 15 2.5 Narrow the scope of the project ................................................................................... 15

3. The job shop production system............................................................................................ 16 3.1 What is a job shop production system?........................................................................ 16 3.2 Some concepts defined................................................................................................. 16 3.3 Interdependencies within work groups ........................................................................ 18 3.4 Difficulties for measuring and evaluating productivity in job shops ........................... 19 3.5 Current methods of measuring productivity in job shops ............................................ 22

4. The ProMES methodology .................................................................................................... 23 4.1 A description of the system.......................................................................................... 23 4.2 Theory and basic principles of ProMES ...................................................................... 24

4.2.1 The NPI Theory ....................................................................................................... 24 4.2.2 The accepted control loop........................................................................................ 25

4.3 Requirements for developing and implementing ProMES .......................................... 27 4.4 The ProMES approach ................................................................................................. 27 4.5 Past experiences with ProMES .................................................................................... 28

4.5.1 ProMES in manufacturing settings .......................................................................... 28 4.5.2 ProMES in service settings...................................................................................... 29 4.5.3 Differences between previous cases and a job shop case ........................................ 29

4.6 Advantages and disadvantage of the ProMES approach.............................................. 30 4.7 Conclusion ................................................................................................................... 31

5. Productivity measurement in job shop situations .................................................................. 32 5.1 Discussion of the levels of measurement ..................................................................... 32 5.2 Factors influencing the success of ProMES................................................................. 33

5.2.1 The interdependencies between units ...................................................................... 33 5.2.2 Shifting operators between units ............................................................................. 35 5.2.3 The rapidly changing orders .................................................................................... 35 5.2.4 Different interests of the units ................................................................................. 35 5.2.5 The relational model ................................................................................................ 36

5.3 Generating ideas for developing and applying ProMES.............................................. 38 6. Description of the research company .................................................................................... 45

6.1 Short description of the company ................................................................................ 45 6.2 Overview of the production process ............................................................................ 45 6.3 The four functional units.............................................................................................. 46

6.3.1 Metal sheet cutting................................................................................................... 46


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6.3.2 Parts production....................................................................................................... 46 6.3.3 Kitting...................................................................................................................... 47 6.3.4 Welding ................................................................................................................... 47 6.3.5 Automatic warehouse .............................................................................................. 47

6.4 The job shop within the production department .......................................................... 47 6.5 Current way of measuring at the production department............................................. 48 6.6 The meaning of ProMES in the framework of the whole organization ....................... 49

7. Assessing the research company on the applicability of ProMES ........................................ 50 7.1 Results of the practical analysis ................................................................................... 50

7.1.1 Method..................................................................................................................... 50 7.1.2 Comparing theory with practice .............................................................................. 50

7.1.2.1 Level of measurement..................................................................................... 50 7.1.2.2 The interdependencies between units ............................................................. 51 7.1.2.3 Shifting operators between units..................................................................... 53 7.1.2.4 The rapidly changing orders ........................................................................... 53 7.1.2.5 Different interest of the units .......................................................................... 54

7.2 Evaluation of the results............................................................................................... 55 8 Matching ProMES with a job shop ....................................................................................... 57

8.1 When is ProMES applicable ........................................................................................ 57 8.2 Determining the best idea ............................................................................................ 58 8.3 Description of the system and recommendations......................................................... 58

8.3.1 Description of the system ........................................................................................ 58 8.3.2 Recommendations.................................................................................................... 59

8.3.2.1 Recommendations for reducing dependency relationships............................. 59 8.3.2.2 Recommendations to overcome the problem of low controllability ............... 60 8.3.2.3 Recommendation to reduce the chances at sub-optimization of units ............ 61

9 Developing ProMES for a job shop production process ....................................................... 62 10 Conclusions and recommendations ................................................................................... 69 11 List of references ............................................................................................................... 72


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1. Introduction

This report is the result of the graduation project conducted as a scientific research within the

Technical University of Eindhoven. The topic of the graduation project is about performance

measurements and improvements in a job shop production process.

Improving organizational productivity has been an issue for some time and will continue to be

important. All types of organizations need to be as productive as possible to optimally use their

precious resources, to meet their customers’ needs and to stay competitive with similar

organizations. There are two ways to improve productivity: one can change the technology or one

can change how people work. The concern of the ProMES approach is the second: how to

structure work so people can and will want to behave in a way that will maximize their

productivity (Pritchard, 1995). The ProMES method has been developed and implemented very

successful in many manufacturing and service settings (Pritchard, 1995), but has only been

implemented once in the situation of complex interdependencies between machines and teams

such as a job shop production process (Huve, 2005). This study showed that it very difficult to

implement this performance measuring and improving system in a job shop situation, because this

kind of production processes results in a highly complex order and material flow with lots of

transitions between the different workshops. A main shortcoming of the ProMES method is that it

is less applicable in situations of complex interdependencies between work teams (Pritchard,

1990). So it will be a difficult task to implement the ProMES approach in a complex production

situation as a job shop. The fact that performance measurement and enhancement for this kind of

complex production processes have only been described in literature by one study (Huve, 2005)

gave rise to a research in this specific area. The objective of this Master Thesis Project is

formulated as follows:

The objective of the Master Thesis Project will be to analyse the applicability of ProMES into a


productivity in a job shop production process.

The content of the report is as following. In chapter 2 we describe the motive of this research,

present an overview of the results of the literature review, (which was preliminarily conducted to

the master thesis project). The research objective and the questions and the boundaries of the

research are also described in this chapter. In chapter 3 we determine the main characteristics of a

job shop production process, discuss the problems about measuring productivity in job shops and

present some methods about how productivity is currently been measured in job shops. The

underlying theory, basic principles and the methodology of ProMES discussed in chapter 4. The

past experiences of ProMES are also discussed in this chapter. The factors which influence the

application of ProMES to a job shop and the generated ideas to deal with these factors are

determined in chapter 5. Chapter 6 is a description of the research company. Chapter 7

determines if and how the ProMES system could be applied to the production situation of the

research company by combining the results of both the literature and practical analyses. We

develop solutions and recommendations about applying ProMES to a job shop in chapter 8.

Chapter 9 provides a global design of the ProMES system applied to the productivity department

of the research company, to explain and clarify how the solutions and recommendations have to

be applied. This report ends with a conclusions and recommendations in chapter 10.


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2. The master thesis project

The motive of the Master thesis project is described in paragraph 2.1. The main results of the

literature research conducted in order of the master thesis preparation are described in paragraph

2.2. The objective and the research questions are determined according to the results of the master

thesis preparations and are described in paragraph 2.3. According to these research questions the

design and approach of the research are shortly described in paragraph 2.4. Paragraph 2.5

discusses the scope of this research.

2.1 Motive of the research

The initial paper used for this research is the master thesis report of Huve (2005). This report

describes the development of ProMES for a company in the Netherlands which manufactures

wooden furniture. The researcher studied the applicability of the ProMES methodology to the

complex production process of the company, characterized as a job shop and how the system has

to be developed and implemented within the production department of the company. After

studying and analysing the report of Huve (2005) we concluded that the study did not lead to the

most effective measurement and enhancement system; the system is developed at departmental

level (highest), which leads to smaller chances in productivity than when applied on a lower

level. The most important reasons to develop a system on a highest level were the complex

relationships between work groups and the limited availability of production data. This system

leads to minimum increases in people’s motivation that changes their working behaviour, and will

lead to less productivity improvement. We assume that it was the best solution possible in the

situation of that company, but it could probably be different in other situations, where ProMES

could be more effectively. The study of Huve (2005) gave interest to further research the area of

performance measurements in a job shop production process by using the ProMES methodology.

In the initial phase, we studied several performance measurement systems and classes of

production processes to determine if the ProMES methodology is best the option to be applied to

a job shop, and not another PM system. This research is conducted during the master thesis

preparation period. An overview and the results of that study are described in paragraph 2.2.

2.2 Overview of the Master thesis preparation

2.2.1 Literature research

The literature research preliminarily conducted to this research was to study different classes of

production processes and the most well known and often used performance measurement

systems. The literature study concerned one specific part of an organisation; the production

department. A production department is often a part of a large production organisation with other

departments as; sales, purchase, production development, etc. The transformation process

operated in the production department generally involves a sequence of steps called production

operations. “Each production operation is a process of changing the input into outputs while

adding value to the entity”, (Viswanadham and Narahari, 1992, p.31). This transformation

process is also called manufacturing. Manufacturing is a broad term and includes many various

types of production operations and products (Viswanadham and Narahari, 1992). The results of

the literature study showed that four general configurations can be recognized based on the

number of products and volume (Viswanadham and Narahari, 1992).


T. de Boer 13

Another way to define the different production categories is to distinguish between capacity

complexity and material complexity (Bertrand, Wortmann and Wijngaard, 1998). The results

showed that four types of categories can be distinguished:

- Job shops - A job shop consists of a number of functionally organized work centres and

each job requires a number of operations in different work centres at many different

routings (Silver, Pyke and Peterson, 1998).

- Batch production - “A process business which primarily schedules short production runs

of products” (Fransoo and Rutten, 1994, p.48) .

- Assembly lines - A manufacturing process in which interchangeable parts are added to a

product in a sequential manner to create a finished product (Viswanadham and Narahari,

1992).

- Continuous flow processes - “Process manufacturing involves a continuous flow of raw

materials through a series of sequential operations, where these operations transfer the

raw materials into a final product” (Viswanadham and Narahari, 1992).

The next part of the literature study concerned the often used and most successful performance

measurement systems. It turned out that many different theories, tools and frameworks are

developed, which all have different goals and working methods for measuring performance. The

performance measurement systems studied are: the Balanced scorecard, the Performance prism,

SMART, ProMES and the Business excellence model.

2.2.2 Deliberations of the alternative PM systems

The goal of the Business Score Card is providing strategic management information needs

(Kaplan and Norton, 1992). The performance prism is a comprehensive measurement framework

that addresses the key business issues (Neely, Adams and Crowe, 2001). The SMART approach

combines elements of a control system with elements of strategic planning (Cross and Lynch,

1988). The main goal of ProMES is measurement and improvement of productivity (Pritchard et

al., 1989). The business excellence index can be used to measure how well different areas of the

organisations are performing (Kanji, 1998). The result of the literature research was that ProMES

analyses performance on a lower level and directly improves productivity of the employees itself

in comparison with the other PM systems. All other PM systems are considering the visions and

strategy of the organisation, thus these systems seems to be effective at the organisational level,

and ProMES seems effective at the plant level. The PM systems, except ProMES, are all intended

to be applied on a higher level, for example for generating business strategies and increasing

business growth and competitiveness. Thus it all serves a much broader business decision support

system in comparison with the ProMES approach which serves to actually improve productivity

on the plant. In comparison with the other systems, ProMES is really a practical approach which

aims at improving productivity. Thus the advantage of ProMES is that it actually improves

productivity. This broader aim also implies that the PM systems consider several aspects of

performance measurement such as stakeholder satisfaction, management strategies, technologies,

processes, market, financial, customer, etc, thus productivity improvement is not the main goal of

these PM systems. In comparison, the main goal of ProMES is to gain improvements in

productivity. Thus applying the ProMES system is much more relevant to improve productivity

of (in this situation) a job shop department instead of applying other PM systems which considers

much more (irrelevant) aspects and only slightly productivity.

The main problems and difficulties as logistics, scheduling, strongly varying orders and demand

and complex material routings showing up at managing and controlling a job shop system are

indirectly tried to be solved or prevented by implementing a PM system.


T. de Boer 14

The ProMES approach is the best alternative in comparison with the others, because it motivates

people to improve their productivity which on his turn creates solutions and strategies to solve the

problems on the plant.

We conclude that the ProMES methodology is best suitable to be applied on operational level and

to improve productivity of a job shop production department, and the other PM systems are more

suitable when applied on an organizational level to improve business strategies. Thus we have

chosen to study the applicability of the ProMES methodology to a job shop situation.

2.2.3 Conclusion

The ProMES system has been successfully implemented many times, in different organisations

and production situations (Pritchard, 1990), but has only been implemented once in the situation

of complex interdependencies between machines and teams as in a job shop production process

(Huve, 2005). Job shop production processes are characterised by a very complex environment

due to the high product differentiation, different routings and low level of automation. ProMES

seems to be the best potential (in comparison with the other PM systems) to improve productivity

of a job shop production department. The situation at other companies might be different to the

situation of the study of Huve (2005). The study of Huve (2005) gave interest to further study

how a ProMES system can be matched with a job shop. So in the master thesis project we analyse

if ProMES can be applied to a job shop situation and whether it can lead to productivity

improvements in a job shop setting.

It is very interesting to conduct a study about measuring and improving productivity in a job shop

production process along with applying the ProMES methodology because:

- ProMES has been developed for work teams and also for individual jobs;

- ProMES is a bottom up approach, thus participated by employees;

- ProMES’ main goal is to improve productivity;

- ProMES has proven to be successful in practice.

Accordingly, all PM systems showed to be accepted on the floor and all people can participate

(Pritchard, 1995), but only by the use of ProMES, the employees really are involved in the whole

process of setting up and maintaining the system, which will result in high acceptance and

commitment.

2.3 Definition of the final research objective and questions

The final research objective is formulated according to the results of the preliminary literature

study. The objective of the master thesis project is as follows:

There are four research questions defined according to the research objective. These are based on

the possibilities of the student within the research domain of the University. The four major

research questions are formulated as follows:

The objective of the Master Thesis Project will be to analyse the applicability of ProMES to a


productivity in a job shop production process.


T. de Boer 15

2.4 Research design and approach

According to the four research questions, a research design and approach is set up. The research

can be divided up into four phases:

Phase 1: Literature research - studying job shops and ProMES

Phase 2: Generating ideas - solutions for measuring productivity

Phase 3: Analysing practice – assessing the research company

Phase 4: Implementation - matching ProMES and job shops

For gathering information about a job shop production process, generating ideas and testing

solutions we have contacted a manufacturing company. The management of that company is

willing to cooperate in the project. The name of the company is “Exerion Precision Technology”,

located in Ulft, the Netherlands. Exerion designs and manufactures precision metal frames and

mechanical parts for printing and medical equipment. A part of the production department

situated at the research company can be characterized as a job shop production process. The

complete description of the research design and approach can be found in appendix A.

2.5 Narrow the scope of the project

In this part we will make some assumptions and determine some basic points of view. These are

important for the study and especially for analyzing the research objective and questions. When

considering other or more aspects, the research will be influenced so the solutions and

recommendations at the end will not be appropriate for the specific research objective. But also

the research is time, knowledge and skills constrained.

The following assumptions and statements narrow the scope of this research:

- Only the option of applying the ProMES system is evaluated, so no other performance

measurements systems are discussed;

- The research only concerns a job shop production process, so no other production

configurations will be evaluated;

- We will use one company as a research company concerned for this research, so

conclusions will be drawn from only this company;

- The system will be evaluated on the applicability to the production department, so no

other departments of the company will be discussed;

- We consider if and how the ProMES system could be applied to a job shop, so the system

will not fully be developed and implemented.






T. de Boer 16

3. The job shop production system

This chapter discusses different facets of job shop systems. Paragraph 3.1 describes the method of

manufacturing according to a job shop. Paragraph 3.2 defines different performance measures

like productivity and efficiency, etc. to overcome misunderstanding or misinterpreting. In

paragraph 3.3 is discussed which different dependency relationships exist between work groups,

which are very important to understand at measuring productivity in job shops. The specific

production structure of a job shop results in difficulties/problems what causes a job shop hard to

be measured and evaluated on productivity what is described in 3.4. Finally an overview of

current scientific literature about productivity and performance measures in job shops is provided

in 3.5.

3.1 What is a job shop production system?

We will shortly describe here what a job shop production system is; a more detailed description

of a job shop system is described in appendix B. A job shop system is a classification of discrete

production systems in which various machines manufacture various products and the

manufacturing of a product requires several process steps, each on another machine. A typical job

shop is defined by the number of jobs, the number of machines and the many different routing in

which the jobs are processed. Job shops are characterized by the difficulty of planning and

controlling due to the high complexity of scheduling jobs on the different machines.

Viswanadham and Narahari (1992) state that job shops are commonplace in mechanical

engineering, with low to medium volumes and with a wide range of products.

3.2 Some concepts defined

The terms “performance” and “productivity” are two very important characteristics used in this

research. These two, but also some other terms are often defined differently by many researchers.

To overcome the problems of misunderstanding and misinterpreting these terms, we will give the

exact definitions of these terms, as used in the current research.

In the literature studied, authors often talked about the term productivity (improvement) instead

of performance (improvement). Improving the productivity is referred in most of the papers

interchangeable with improving performance, or some authors even confuse both terms. There

has to be a clear distinction between both terms according to Sink, Tuttle and De Vries (1984),

because they stated that productivity represents a critical component of performance and not a

synonym for it. “Productivity needs to be viewed as one of a group of performance criteria

against which managers can assess, evaluate and base decisions regarding the organizational

systems they are managing” (Sink et al., 1984, p.265). Productivity represents a critical

component of the performance definition. Productivity can be evaluated at the work group,

function, division, plant or firm level.

Performance is typically output such as number of pieces finished, but productivity is an output

relative to inputs, or outputs relative to objectives or goals (Pritchard et al. 1989).According to

Pritchard et al. (1989) productivity is a combination of both effectiveness and efficiency.

Efficiency (also called productivity) is an output to input ratio (monthly manufacturing output

divided by number of labour hours used) and effectiveness is the relationship of outputs to some

standard or expectation (e.g. monthly output expressed as a percentage of the unit’s goal).


T. de Boer 17

Thus efficiency is how well the organization uses its resources to produce its products or services.

Effectiveness is how well the organization is reaching its goals. This study will define

productivity as “how well a system uses its resources to achieve its goals” (Pritchard, 1992, p.

455). This definition will be applied in this study to view productivity mostly from a behavioural

perspective.

As told above, productivity is a component of performance. According to Sink et al. (1984) the

performance of an organizational system is comprised of seven criteria; effectiveness, efficiency,

quality, productivity, quality of work life, innovation and profitability/budgetability. These terms

will be explained below.

Effectiveness - Doing the right things on time, and in the right manner, in terms of goals,

objectives, activities, goods, products, services, etc, thus it focuses on what we should be doing

and have done. ectedoutput

observedoutputessEffectiven

exp=

Efficiency - It focuses on the relationship between what we felt should have been consumed and

what was actually consumed. ectedinput

observedinputEfficiency

exp=

Quality - The products and/or services have been performed conformance to the specifications.

Productivity - It is the ratio of quantities of output to quantities of input resources; the ratio of

quantity at the desired quality level to resources actually consumed. observedinput

observedoutputoductivity =Pr

Quality of work life - This is the human beings’ affective response/reaction to working and living

in organizational systems.

Innovation - The creative process of adaptation of product, service, process, structure, etc. in

response to internal as well as external pressures demands, changes, needs, etc. it is extremely

hard to measure something that implies effective implementation of a creative new idea.

Profitability/budgetability - A measure or set of measures that assess attributes of financial

resource utilization.

Figure 3.1: The seven criteria are causally related, source: Sink et al. (1984).


T. de Boer 18

3.3 Interdependencies within work groups

The team members of the various functionally units in a job shop situation are interdependent on

each others task fulfilment. Team members are very dependent of the outputs of other team

members, and the way the work flows between unit members. “Work flows are the materials,

objects, or clients that are sent or transported between people within organizational units”, (Van

de Ven and Ferry, 1980, p. 166). The amount of work flow indicates the degree of task

interdependence between people in a unit. “Task interdependence is the work connectedness of

unit personnel or the extent to which people in a unit are dependent upon one another to perform

their individual jobs”, (Van de Ven and Ferry, 1980, p. 166). Tesluk, Mathieu, Zaccaro and

Marks (1997) state that interventions aimed at improving team performance are likely more

successful when they take into account the team’s specific task functions and requirements. This

is an important statement when considering the groups (functionally units) within a job shop. The

group members are working closely together and exchange information to fulfill the group’s

tasks. At assessing the performance of the unit, we have to take into account that, additional to the

performance of various individuals, the ultimate effectiveness of the team depends on well-

coordinated transitions between team members (Tesluk et al., 1997). According to the authors,

critical team levers (the most important factors or work processes that underlie a particular team’s

performance) have to be defined for the measurement and diagnoses of team performance.

Understanding the nature of the task performed by the team is critical for proper diagnoses of

problems in team performance. If the critical levers for the team performance are not identified,

measurement efforts may be targeted at the wrong level of analysis. For example, when team

members are working independently of each other, one can decide to measure performance of

each individual on their tasks and summing across individuals. Four basic work flow

arrangements can be distinguished. Below we describe these four arrangements that are used to

characterize the work of different types of team interdependencies (Tesluk et al., 1997, Van de

Ven & Ferry, 1980). The four arrangements are graphically shown in figure 3.2.

Figure 3.2: Taxonomy of team work processes. Source: Tesluk et al. (1997).

Pooled interdependence - in pooled tasks, each individual contributes incrementally to overall

task completion, and team performance and work does not flow between members of the team.

Each individual’s performance is a function of his or her efforts and does not depend directly on

the performance of others.


T. de Boer 19

Sequential interdependence - work moves from one member to another, and mostly in one

direction. Work flows in a consistent unidirectional through each of the members.

Reciprocal interdependence - interactions are more dynamic in nature and work flows back and

forth between team members. Team performance is a function of more complex forms of

coordination.

Intensive - team members closely work together to diagnose, solve problems and collaborate in

performing a task. The nature of the task is dynamic and complex.

When the critical levers of team performance are identified (what to measure), the particular

method of measuring has to be determined that is most appropriate for assessing team

performance (how to measure). There are various methods of measuring team performance. A

choice has to be made about the source of information (who provides the information of the

team’s performance) and the method(s) of measuring (how data on team performance are

collected) (Tesluk et al., 1997).

“An important factor in team performance assessment is that the nature of the team’s task and

particular processes or aspects of performance that are being measured should play an important

role in determining which particular method of measurement to use” (Tesluk et al., 1997, p.210).

The study describes some trends about the target of a human resource program by assessing

different kinds of teams. We describe which specific motivational human resource program to use

accordingly to the four different team characteristics. Motivational programs for pooled team

should be designed to facilitate and reward the contributions of individuals (e.g. piece rate

compensation). Motivational programs for teams operating in sequential task settings should

emphasize individuals’ contribution but also focus on the exchange sequences between members.

Motivational efforts for reciprocal teams should be directed to the team as a whole. Reward and

feedback programs should be based less on individual contribution and more on team

performance. Motivational programs for intensive designs should focus on team level processes

and outcome by providing team-level feedback and incentives (Tesluk et al., 1997).

3.4 Difficulties for measuring and evaluating productivity in job shops

The production structure within a job shop can be characterized as a functionally oriented

structure with the functional units at where the products and parts are manufactured. The

functional units characterize a layout in which machines and people handle similar operations and

are grouped together in a workshop. The functional oriented layout is required because each of

the production operations requires different operational means and skills. The different units

within the functional production organization do represent its own task. The disadvantage of this

kind of production processes is that this results in highly complex order and material flow with

lots of transitions between the different workshops. Thus a job shop system represents a highly

complex production environment with complex dependency relationships between the different

units, so the units are strongly dependent of each other if it comes to exchange of information and

products and changes of any kind. These dependencies can be seen as sequential dependency

(work on the result of previous units) and reciprocal dependency (work flows back and forth

between units). Examples of interdependencies relationships are: work on a part when another

unit is finished with that, the quality of preceding work, speed of doing work is dependent on the

speed of getting parts or material when needed, how efficiently the output is produced depends on

how production scheduling has arranged the orders (Pritchard, 1990).


T. de Boer 20

Due to these dependencies between units, the departmental performance can hardly be

decomposed into the performance of independent units. So the main question here is: “At which

of the three levels (individual, group or department) it is best to measure and evaluate

productivity so the most successful measurement system will be developed?” Another problem

which shows up point due to the interdependencies between the units is that the control over the

unit’s productivity decreases when units are individually being measured and evaluated. It is a

problem because each individual unit has to be able to influence their unit’s output when a

performance measurement system is applied at unit level. Thus one of the most important

decisions is the decision about the level at which the measurement system is developed. When

measured on individual or group level it will take much time and effort the develop and maintain

the measurement system because a system has to be developed for each unit or individual, but

will have more impact on productivity than when measuring on department level what will take

less time and effort to develop and maintain. Providing feedback to each individual or a small

group of people will lead to higher changes in motivation and productivity because then people

can easily recognize there individual (or unit) contribution. This is difficult to recognize when a

large group is provided with feedback about the overall productivity performed by the whole

group. Thus the less people are covered in one measurement system, the more effective it is, but

the more the development time will increase.

A main characteristic of a job shop production system is that a lot of various products are

manufactured. Because of the varying products, the processing times will also vary. The

manufacturing lead time is mainly defined by the waiting times in front of the work centres and

the processing times at the machines. Due to the strong varying routings and occupation times,

the number of orders arriving at the units strongly varies per time unit (day or week). So when is

chosen to measure the number of produced parts in a period, it will be difficult to define a

standard or desired level of production and also it will be difficult to compare the performed

productivity between periods. This is because each order has different processing times and thus a

different total lead time in comparison with other orders. For example a work group maximized

its productivity a specific day and produced three parts, and the next day it also maximized its

productivity and produced ten parts. The effectiveness was equal at both days, but the number of

parts was unequal, which is caused by the differences in jobs. What can be done is to use the

actual number of hours worked relative to the standard working hours. When one determines the

time it takes to fulfil a task, the actual time it took to fulfil that task can then compared with that

standard processing time. In this way, the productivity of both days can be compared fairly,

because for example the three parts were calculated to be processed in eight hours and also the

ten parts were calculated to be processed in eight hours. Other productivity factors, as for

example quality, amount of waste material, etc, are also influenced by the various orders. A

problem, because of the vast changing orders, is the fact that it is difficult to control the output

(productivity) of the operators, units and department over time and as told above, each individual

unit has to be able to influence their unit’s output when a performance measurement system is

applied at unit level.

The incoming orders do vary in amount, design, urgency and processing time, which result in a

very complex material flow control. It is very hard to define how the different orders will be

distributed among the machines in next periods. Machine utilization and variation of the orders

will generally lead to long waiting times for orders on the floor. A difficulty is the production

speed of a work centre is dependent of another unit. In fact, the amount of work to be done by a

unit varies a lot per period. An example is that the orders for a specific period requires much

more capacity of unit 1 and less capacity of unit 2, whereas orders in the next period can be vice

versa. Thus there are continuously changing bottlenecks in the production department.


T. de Boer 21

This unknown distribution and machine utilization leads to a difficult determination of

productivity standards and goals for the coming periods and the control on productivity over time.

In a job shop production environment, it is usual (when demand is high at a specific functional

unit) to shift one or more employees from a less demanding unit to a high demanding unit. We

assume that these persons are less familiar with the handlings and operations at that unit than the

“fixed” employees, so the result is that the scores on the performance indicators (e.g. speed and

quality) will not be as high as normal for that unit. The productivity and thus the scores on the

performance indicators of a specific functional unit are not representative anymore for the

actually possible achievable performance of that unit by shifting employees. The functional units

cannot fully control the output of their unit over time when persons are transferred to an

“unfamiliar” functional unit when capacity requirements are high. This has to be considered when

a performance measurement system is developed at individual or unit level.

A difficulty at measuring productivity and subsequently comparing the results with previous

productivity achievements or norms is that people do not have the full control over some factors

such as machine breakdown and lateness of delivered raw material. The measurement system

may not be valid, because it is difficult to take the factors which can not be influenced into

account.

The probability of individualistic behaviour among units increases when the individual unit

productivity is measured, because the achievements of each of the units will be compared with

each other. The goals for the units will become independent when the unit productivity is

measured. Van Vijfeijken, Kleingeld, Schmidt, Kleinbeck, Pritchard and Algera (2002) state that

goal interdependence reflects the way in which goal attainment of an individual (a unit in this

situation) is influenced by goal attainment of other. Goal interdependence can vary from (highly)

negative to (highly) positive. Neutral goal interdependence means that achieving the pre-defined

goals by one group does not influence the attainment of the same goal by the others. Contrarily to

the neutral interdependency, the case of positive goal interdependency, the attainment of one’s

goal is positively influenced by the attainment of goals by others. And in the case of negative goal

interdependency, the attainment of one’s goal is negatively influenced by the attainment of goals

by others (Van Vijfeijken et al., 2002). We assume that the goal interdependency is neutral in our

situation. Van Vijfeijken et al. (2002) state that groups performing a highly interdependent task

performed significantly worse when confronted with an individual goal compared to a group goal,

a group plus an individual goal, or no specific goal. Neutral goal interdependency leads to

individualistic behavior of the units because under a individual goal condition the group members

direct all their action and attention to the attainment of the individual goal. Individualistic

behavior can lead to sub-optimization because little energy will be used to develop cooperation

strategies (Van Vijfeijken et al., 2002) and sub-optimization can on his turn lead to competition

between units. Competition means that units try to increase productivity what can be of

disadvantage of other units

An example of sub-optimization is that a unit decides to increase the batch sizes with

subsequently less set ups what implies a decrease in total processing time. The speed of

production will increase at this specific unit, but leads to a decrease in production speed at the

succeeding unit, because now they have to wait before all parts are delivered. A second example

is the decision of a unit to slightly change the design of a part to increase the production speed,

but resulting in an increase of processing time of the succeeding unit. The production speed of

one specific unit increases, but the overall processing time will decrease.


T. de Boer 22

As conclusion we can state that it is difficult to measure group productivity at a valid and reliable

way in a job shop situation. The main reasons are the interdependencies within and between units,

the changing skills of the employees due to shifting, the low controllability ad the risks at sub-

optimization. The insecure and vast changing environment makes it difficult to apply a system on

each of the three possible levels.

3.5 Current methods of measuring productivity in job shops

In this part, we will give an overview of current scientific literature about the area of productivity

measurements in job shop production processes. The first conclusion we can state here is that

very little work is conducted in this area of research, because very few scientific papers about

productivity measurements in job shops could be found. The majority of the research in the area

of performance measurement in job shops has used time based performance measures to evaluate

the system (Rohleder and Scudder, 1993). The often used measures are lateness, tardiness, flow

time, percent tardy. Managers consider these kinds of performance measures because of the view

that time is money according to the authors. Recent research in scheduling and performance

measurement in job shops used the profit measure; Net Present Value (NPV) which is the present

value of net cash flows (Rohleder and Scudder, 1993).

In the study of Bertrand (1983), productivity is measured by the mean and the standard deviation

of the lateness of the jobs. The lateness of the job is defined as the delivery time minus the due

date of that job. In the study of Lee and Posner (1997) two productivity measures are used; cycle

time and makespan which are closely related. The makespan is a measure according to the time it

takes to complete all jobs. According to Viswanadham and Narahari (1992), the following

performance measures are often used: manufacturing lead time, work-in-process, throughput

time, machine utilization, capacity, flexibility, performability and quality. According to them, job

shop characteristics are; large setup times, large WIP inventory, large manufacturing lead time,

high machine utilization and high quality. Only one paper describes the use of the ProMES

approach for measuring and improving the productivity of a job shop (Huve, 2005). This paper

describes the development of ProMES for the production department of a Dutch company. The

study resulted in a system developed on a high level (departmental). It was not possible to

develop the system on group level mainly due to the complex mutual dependencies between the

working units and the limited availability of production data.

The difference between methods of measuring productivity in job shops as described by current

scientific literature and the ProMES approach is that the ProMES approach, which aims at the

human aspects, uses goals and feedback (to group and/or individuals) as a motivational tool, so

people themselves can change their working behaviour to improve productivity. We conclude the

objective of both the measurement systems described in current scientific literature and the

ProMES approach is to improve productivity, but the difference is that the ProMES approach

(which is used in this research) motivates people to change their working behaviour by

themselves to improve productivity. It is about letting people work more efficiently and

effectively to increase the productivity of a department or organization.


T. de Boer 23

4. The ProMES methodology

This chapter describes the underlying theory, basic principles and the methodology of ProMES.

The generally description of the ProMES system is given in 4.1. When the system is generally

described, we explain the underlying theory of the measurement system in 4.2. The requirements

for a successfully and accepted implementation of the system are described in paragraph 4.3. The

ProMES system has to be developed and implemented according to four succeeding phases which

are described in 4.4. The past experiences with implementations of the ProMES system in

different companies and departments are discussed in 4.5. In paragraph 4.6 we provide the

advantages and disadvantages of the measurement system. The chapter ends with a short

conclusion in paragraph 4.7.

4.1 A description of the system

All types of organizations need to be as productive as possible to best use their expensive

resources, to meet their customers needs and to stay competitive with similar organizations. There

are two ways to improve productivity: you can change the technology or you can change how

people work. The concern of the ProMES approach is the second: how to structure work so that

people can and will want to behave in a way that will maximize their productivity (Pritchard,

1995). “Enhancing productivity has been seen as important for our quality of life, our economy,

and our competitive position in the world marketplace”, (Pritchard, Jones, Roth, Stuebing and

Ekeber, 1988, pp. 337). ProMES has its theoretical foundations within a theory of behaviour in

organizations. The idea behind ProMES can be seen in figure 4.1.

Figure 4.1: The basic ProMES approach, source: Pritchard (1990).

ProMES is an intervention that relies on feedback to let personnel know their levels of

performance; this knowledge then serves as a tool that leads to more efficient and effective ways

of performing tasks (Pritchard, 1990). The system is developed and accepted by both employees

and management, and provides an overall index of productivity. An organizational unit constructs

the system by defining their objectives, identifying productivity indicators for each objective, and

developing utility curves or contingencies for each indicator, specifying the overall and relative

value to the organization of different performance levels on each indicator. The performance what

subsequently is achieved is than feedback by means of a feedback report. Productivity

enhancement is thus tried to be achieved by setting difficult, but reachable goals and subsequently

giving feedback on the performance on these goals. This will lead to changes in motivation which

on his turn will lead to increased productivity of the employees.

The goal of the ProMES method is to measure and improve productivity. The application of the

system begins with clear statements or organizational objectives. Productivity can be generally

defined as the degree in which a system uses its means to reach its goals (Pritchard 1992).

Organizational objectives Productivity

measurement system

Feedback system

Increased productivity Meeting organizational

objectives


T. de Boer 24

ProMES can be used as a measurement and enhancement system for individuals, groups and

departments as well. The system urges people to work smarter, not (necessarily) harder.

There are generally three characteristics of ProMES at which it can be distinguished from other

performance measurement systems. The first is the fact that ProMES is developed by a so called

bottom-up approach; the participation of employees in the design of the system plays a major

role. The second is that the employees are actually participating in the development of the system

to increase the acceptation and willingness to cooperate. The third characteristic is that meetings

are held by the employees and management for development of the system and agreement about

the goals.

4.2 Theory and basic principles of ProMES

The literature on performance appraisal distinguishes three basic approaches managers can use to

tell their employees to working a performance sessions: ‘tell and sell’, ‘tell and listen’ and

‘problem solving’ (Algera, Kleingeld and Van Tuijl, 2002). The ‘tell and sell’ style is a one-way

approach; the manager presents his assessment of the performance achieved and explains what he

wants to see in the future. In the ‘tell and listen’ style, the manager not only presents his opinion,

but also listens to the opinions of his employees. The ‘problem solving’ style gives employees

plenty of opportunity for active participation in developing ideas for improving performance in

the future. This approach is the most appropriate one for the ProMES sessions (Algera, et al.,

2002).

4.2.1 The NPI Theory

The conceptual foundation behind ProMES is the “theory of work behavior” developed by

Naylor, Pritchard and Ilgen in 1980, also called the NPI theory (Pritchard, Holling, Lammers and

Clark, 2002). ProMES maximizes motivation and thereby performance that comes from this NPI

theory. We will now explain this NPI theory. “Motivation in NPI is seen as a resource allocation

process where the resource is a person’s time and energy. This time and energy is allocated across

possible actions or tasks” (Pritchard et al., 2002, p.4). The NPI motivational process is shown in

figure 4.2.

Figure 4.2: The basic NPI Theory, source: Pritchard et al. (2002).

The process is a motivational sequence or chain composed of the following elements: acts,

products, evaluations, outcomes, and need satisfaction. People anticipate the amount of need

satisfaction that will occur when outcomes are received (motivation). “Acts, products,

evaluations, outcomes and need satisfaction are combined into motivational force which is

defined as the degree to which a person believes that changes in the amount of personal resources

in the form of time and energy (effort), devoted to different acts (tasks) over time, will result in a

change in anticipated need satisfaction” (Pritchard et al., 2002, p. 5). NPI views motivation as a

process, each stage of the process must function well for the outcome of the process (motivation)

to be high, thus to maximize motivation, each component of the theory must be maximized

(Pritchard et al., 2002).

Figure 4.3 adds contingencies, which indicates, for example, the amount of a product produced is

to some degree contingent on the effort devoted to the acts that generate it.


T. de Boer 25

Figure 4.3: The NPI Theory with contingencies added, source: Pritchard et al. (2002).

Figure 4.4 graphically shows the connection between NPI and ProMES. The ProMES objectives

and indicators (which will be discussed in paragraph 4.4) are the operationalization of the NPI

products. ProMES contingencies are the operationalization of NPI product-to-evaluation

contingencies (the person’s perceived relationship between the amount of the product and the

expected level of the evaluation as a result of this level of product). Feedback indicates how much

of each product was done, and how good that amount was.

Figure 4.4: ProMES components and NPI, source: Pritchard et al. (2002).

ProMES can produce improvements in productivity by increasing motivation, because between

the development of the system, receiving feedback and using feedback to make improvements

there are direct connection between ProMES components and the NPI motivational chain

(Pritchard et al., 2002). ProMES is designed to affect all the variables influencing the

motivational process simultaneous, what leads to large changes in productivity.

4.2.2 The accepted control loop

According to van Tuijl (1997) ProMES can be interpreted as a method for the development of

control loops for self-management, called “accepted control loops”. But ProMES does not

automatically lead to accepted control loops, this depends on the way in which the development

process is completed and the characteristics of the control loop designed.

The idea behind the accepted control loop for self management is that in essence “motivation

stems from people’s own choices”. By using the ProMES method, a group can develop a system

so the productivity of the employees can be measured. The control loop occurs when the

measured productivity is compared with the goals that are determined and is fed back to the

group. The feedback tells to what extent these concrete goals are being realized. Then, these goals

are transformed into new more difficult goals. In this way reduction of discrepancy leads to the

production of discrepancy (van Tuijl, 1997). The accepted control loop for self management is

shown in figure 4.5.


T. de Boer 26

Figure 4.5: The accepted control loop, source van Tuijl (1997).

The lower half is the input-transformation-output model, in which the responsibilities of a group

are presented (goods or services). The degree to which these responsibilities are realized

(feedback) is passed on to a regulatory mechanism (upper half), which compares the feedback

with the target goals. The goals are transformed into new and more difficult goals if the goals are

met or surpassed (discrepancy production). Then the process of discrepancy reduction begins,

where people put in time and effort to reach the goals. Results from the area of motivation

research state that feedback and goal setting have a strong effect on individuals and teams. Van

Tuijl (1997) states that people motivate themselves by formulating goals that lead to a situation of

imbalance (discrepancy production), and then put in time and energy which are necessary to

reach the goals (discrepancy reduction). According to van Tuijl (1997), the reactions to the

ProMES method can be; acceptance, compliance or rejection. Acceptance means that the

accepted control loop is complete. When the initial goal is satisfied, the group or individual sets a

new, more difficult goal and is striving to reach that new goal. At compliance, the control loop is

not complete; the individual or group does not make effort to reach a higher goal when the initial

goal is reached thus the group only tries to hold on to that initial goal. Rejection means that the

people do not make any use of the system and the feedback method and there is no effort towards

reaching goals.

When the ProMES method leads to an accepted control loop, it can lead to an increase of the

organizational effectiveness. The first reason for this is that employees get a better understanding

of their roles and responsibilities during development of the system. The second reason for

productivity improvement during development is that people already get informal feedback about

their performance. Productivity improvement after implementation of the system can be

explained through the use of feedback reports. The already improved productivity at this moment

can even be more increased by the use of incentives such as intrinsic and extrinsic rewards.

According to van Tuijl (1997) three conditions have to be present so employees are encouraged to

achieve the goals of the organizations: goals, feedback and endorsement. Goals have to be

functionally related to the goals of the organization. Employees want feedback because they are

interested in the degree to which these goals are achieved. They will adjust their work when the

goals are not fully achieved and may set higher goals when goals have been attained. The third

condition represents the degree in which the organization appreciates the performance. These

three conditions have to meet some requirements to be effective (van Tuijl, 1997):

- goals have to be specific, difficult, but attainable;

- feedback has to be specific;

- endorsement has to be consistently related to the goal achievement.


T. de Boer 27

4.3 Requirements for developing and implementing ProMES

Time, effort, and acceptance are required to make sure that the ProMES method will be a valid

and reliable measuring system in an organization. The chances at acceptance and at a successful

implementation and development increases when (some of) the following conditions are satisfied

(Pritchard, 1990):

- dominant attitude in the department on the necessity of improvement of performance;

- all people involved endorsing the importance of productivity improvement;

- the personnel subsystems being viewed as critical for success;

- minimum level of trust between management and the work force;

- be sure that management really wants to invest in the system, e.g. by providing resources;

- willingness to measure performance and to be measured;

- visible commitment of management;

- in case of lacking skills, provide training before and during development;

- no “not invented here” culture;

- check whether the system is compatible with other organizational control systems, e.g.

reward systems.

The conditions mentioned above concern the human aspects preliminary to the development of

the system. The criteria mentioned below are required to the ProMES system itself, to increase

the chances at a successful measuring and enhancing system (Van Tuijl, 1997):

- The system has to be able to represent one single score for the total performance of the

group or department.

- The system has to be able to show how the total score is build up from the sub-scores,

which represents the productivity of the different activities.

- The responsibilities have to be represented by the system and the system has to show

these responsibilities at a valid way.

- The system has to be flexible, what means that the system can response and adapt to the

changes in circumstances and policies of the organization.

- The system has to be accepted both by employees and by management.

4.4 The ProMES approach

The design of a ProMES system is characterized by a bottom-up design process, leading to four

elements of the system (Algera and van Tuijl, 2004). A bottom-up design process means that the

system is developed by the lower level of the organization; the employees participate in designing

the system instead of the management (top down approach). A detailed description of each of the

four elements of the system can be found in appendix C. The four elements of the system are:

1. key result area (called products): a limited number of result areas that are essential for

performance (e.g. quality, costs, safety, etc);

2. performance indicators: one or more indicators that reflect the performance in the related

key result area;

3. contingencies: utility functions that express the relation between a score at a specific

performance indicator and the value for the organization (effectiveness);

4. feedback report: a report that gives regular feedback on performance and effectiveness.


T. de Boer 28

4.5 Past experiences with ProMES

ProMES is successfully implemented in many different industries, companies and departments.

Some of these studies will be discussed in this paragraph. Over the last twenty years, a large

database of ProMES projects has been developed (Pritchard et al., 2002). Most of the data are at

the group or unit level. The sample of jobs is diverse, including photocopier repair technicians,

university professors, police officers, and circuit board manufacturers. The types of organizations

are diverse, ranging from the military to educational settings. In general, ProMES has proven to

be a very successful methodology. Pritchard (1995) describes studies about development and

implementation of the ProMES system. He distinguishes between implementation in

manufacturing settings and service settings. We first discuss some examples of the manufacturing

studies and end discussing the service settings.

4.5.1 ProMES in manufacturing settings

ProMES is implemented in an electronic computer components assembly plant for the aerospace

industry in the US. The unit in which ProMES is developed consisted out of five members and

the activities performed by that unit included inspection of end products, correcting problems,

apply coatings and final inspection. The researchers were successful in using the ProMES

approach in an organization engaged in team-based manufacturing. The exact gain in

effectiveness is not known because only anecdotal data could be used at the company.

The next company in which ProMES is implemented is “Vandra Corrugated Fibreboard”. It is a

medium sized firm that produces corrugated packaging for a large variety of customers. The

development group included a group of employees operated a die cut machine that produces

various kinds of corrugated board boxes and consisted of four people. The production process is

simple and straightforward. Two years after implementation of the system, is has resulted in an

effectiveness increase of 37% as a percentage of the maximum scores, thus the ProMES system

was successfully implemented.

Another study describes the development and implementation of ProMES in a factory for the

production of safety devices for electric control systems. The research setting was one of the

manufacturing centres of the production department and was characterized by a high degree of

automation. The group (five people) assembled circuit breakers in a flexible assembly centre,

with main activities as maintenance, (un-)loading parts, tool change and control. The conclusion

was that ProMES could successfully be developed in an advanced manufacturing system, because

the effectiveness of the experimental group doubled.

The fourth study described in the textbook (Pritchard, 1995) was about implementing ProMES in

a manufacturing department of a small corporation in an outdoor sports industry in the US. The

measurement system was implemented in the manufacturing department, where raw materials

were purchased, cut and sewed, and where inspection and packaging took place. The

effectiveness at the department improved with 15%, which was determined by dividing the actual

improvement by the maximum possible improvement.

The final study about ProMES in a manufacturing setting was about a manufacturing facility in

the US. The development group consisted of fourteen people and was working in a chemical

processing assembly line. The group blends, compacts, and granulates powdered chemicals

together. The study gave an indication that ProMES can successfully be implemented even in a

private sector organization that is already performing well, because there was a 24% gain in

overall effectiveness.


T. de Boer 29

4.5.2 ProMES in service settings

The developer of the ProMES system, Pritchard et al., 1988, developed the system with the help

of field studies at five organizational units at an Air Force base in the US. One was the

maintenance section (repairing electronic equipment) and the other four sections made up the

material storage and distribution branch. The number of people involved in the project ranged

from 29 to 35 and from 47 to 54 respectively. The outcome of the study was that ProMES appears

to be a very effective way of measuring productivity: the system is successful in aggregating

productivity measures across units, feedback has a strong effect (productivity increase of 77%) on

productivity and goal setting and incentives (total productivity increase of 79%) increased

productivity over feedback.

ProMES is implemented in a branch of a service division of a multinational computer systems

organization. The service groups are responsible for the maintenance and repair of the computer

systems where the ProMES system resulted in a 25% increase of productivity. ProMES is also

developed and implemented in a field service department of technicians servicing photocopiers at

client offices (Kleingeld, Van Tuijl and Algera, 2004). They tested which of the two methods

(participation vs. tell-and-sell) resulted in the highest increase in performance. The participation

method resulted in higher performance increases. ProMES is also implemented at a major US

university for evaluating the teaching effectiveness of professors. Receiving feedback about the

scores of the instructors from ProMES caused a productivity increase of about 86%. Other studies

described by Pritchard (1995) are about the development of ProMES at a large Dutch bank and in

units of a small oil trading company (clerical support and sales). The final study described was

about an organization of commercial painters. The activities performed by the work organization

were painting (buildings etc.), installing glass, heat insulation and handling administration.

4.5.3 Differences between previous cases and a job shop case

The manufacturing settings in which ProMES is implemented up till now can be generalized as a

straight line production process at which a group of employees work together on one product. The

studies mainly involved only one group of employees at which ProMES is developed. No big

problems showed up by developing the ProMES system in these situations. In table 4.1 we give

an overview of the main differences between the situations in which ProMES has successfully

been implemented and the situation of a job shop. We highlight the factors which make it difficult

to implement a ProMES system. As can be seen, difficulties arise at a job shop (sign X) in

comparison with the flow line and assembly line (sign O).

Factors Job shop Flow line Assembly

Scheduling X O O

Flexibility X O O

Varying routings X O O

Varying capacity X O O

Level of automation X O O

Number of work groups X O O

Table 4.1: Differences between job shops and other production configurations

We can conclude that the ProMES has been successfully implemented in different organisations

and production situations, but has only been implemented once in a situation of complex

interdependencies between machines and teams such as a job shop production process (Huve,

2005).


T. de Boer 30

4.6 Advantages and disadvantage of the ProMES approach

In most cases ProMES has been developed for groups of employees and also for individual jobs

(bank and university employees). “The main advantage of the ProMES method is that the

complexity and uncertainty of collaborative relations is made clear and a common frame of

reference is developed so that communication about what is happening is greatly simplified and

improved”, (Van Tuijl, 1997, pp. 353). The most important advantages according to Pritchard,

Lawrence, Goode and Jensen (1990) are:

1. The ability to provide a single index of productivity as well as sub-indices

2. The system is valid (complete and accurate system), because several components are

involved in a valid system

3. Flexibility, it can respond to changes in organization’s priorities

4. The ability to aggregate across units

5. Acceptance of organizational personnel

6. Positive motivational properties. ProMES measures and improves productivity by

increasing the amount and quality of the feedback, positive feedback, and enables

employees to see the results of their efforts.

7. Role clarification. By proceeding through the first three steps of the system (product,

indicators and contingencies), employees are helped to more clearly understand their

roles, which on his turn has a positive motivational effect

8. The ability to provide a considerable amount of information about the work to be done. It

guides employees by indicating which activities they should be doing and their

importance.

The major risks and disadvantages of the system will now be discussed. It is essential that the

department is working in such a way as to maximize the objectives of the broader organization.

By the use of a bottom up approach (such as ProMES) it is difficult to insure that this consistency

between the group’s products and the overall organizational objectives exists. For example if

higher management is not clear on their goals, it will be difficult for them to assess whether the

group’s products are consistent with these broader goals. Another situation is where management

itself is not comfortable with the typical ProMES bottom up approach. They may not have trust in

the lower level groups when these people have to develop the measuring system, or they may

want to implement some changes in the business strategy and want to use the top down approach

to communicate these changes. This suggests that in some situations a top-down approach can be

a valuable addition to the standard ProMES approach.

But on the other hand, a too much top down approach may limit the acceptance of the system by

the employees, so participation is an essential element of the design process. By the use of

ProMES, the employees really are involved in the whole process of setting up and maintaining

the system, which will result in high acceptance and commitment (Pritchard, 1995). Thus to

increase the acceptance of the system by the employees a bottom up approach, as used by

ProMES, is required. An alternative of both approaches is the tell-and-sell approach (Kleingeld,

et al., 2004). In this study, the tell-and-sell approach was used for the implementation of ProMES.

The tell-and-sell style can lead to acceptance because then it is told that other employees are

developing the indicators and do have the control over these indicators. The tell-and-sell approach

turned out to be slightly less successful than the participative method, because there is no

personal involvement in developing and controlling the indicators by those to whom the system is

told and sold, but it may satisfy in some specific situations.


T. de Boer 31

Another aspect which has to be taken into account is that the system will probably not survive

when the system is not compatible with other control systems (Kleingeld, et al, 2004). Another

problem is the time span needed for development of the system. It takes a lot of meetings of the

design team what will result in development duration of about 6 to 18 months, what may lead to

that design team members lose interest (Pritchard, 1995). A main characteristic of the system that

can be taken as a disadvantage is that the system of ProMES only provides outcome feedback,

and does not provide suggestions how to change task strategies, cooperation and exchange of

information to improve productivity.

4.7 Conclusion

ProMES has been successfully developed for different organisations, departments and settings, as

described in this chapter. The system is applied to different types of industries, the technologies

varied greatly and included personal service, high and low technology manufacturing in

individual, team and assembly line settings, technical repair and professional service. Also the

jobs themselves varied greatly. The conclusion is that the ProMES system is applied to situations

which differ from the job shop situation (except the study of Huve, 2005). Because the job shop is

a different production process with its specific difficulties/problems as mentioned in chapter 3,

we will determine how the ProMES system and the production process can be matched, so the

system leads to reliable measures and to effective improvements in productivity.


T. de Boer 32

5. Productivity measurement in job shop situations

In this chapter we provide ideas and solutions how to develop a ProMES system for a job shop

situation. In paragraph 5.1, we discuss the level at which ProMES could be applied. The level of

measurement is dependent on job shop specific factors which influence the success of the

ProMES system. We explain why these factors are negatively influencing the implementation and

maintenance of a ProMES system and put that into a model in paragraph 5.2. Ideas and solutions

for these stated difficulties are generated in paragraph 5.3. General, these ideas are concerning the

level (individual, group or departmental) at which it is most optimal to measure productivity and

give feedback to.

5.1 Discussion of the levels of measurement

ProMES can in theory be developed and applied to different group sizes and at three levels

(Pritchard 1990). The three levels that can be determined are:

1. Individual level

2. Group level

3. Department level

At distinguishing the levels to which the system has to be applied, two factors have to be

analyzed (Pritchard, 1990):

- The kind of work and company

- The consideration between the effect of the feedback and the ease with which the

system is developed and maintained

In general, feedback about individual performance is more effective than feedback about

performance of a group of people. Providing feedback to each individual or a small group of

people will lead to higher changes in motivation and productivity because then people can easily

recognize there individual contribution, which is difficult to recognize when a large group is fed

back at once. The difficulty here is that is takes a lot of time to generate detailed information and

data of each person individually. Thus the trade off is between the level of measurement and the

time and effort of generating feedback, to make the performance measurement system efficient.

Another problem is that it is not always possible to separate the activities and productivity of an

individual from the activities and productivity of a group. Generally in a job shop, the individuals

within a unit are commonly responsible for the same tasks and have the same activities to

perform, so it is probably not needed to separate the activities and productivity of each individual

within a unit. Also the within-group task independencies are high, so it is not preferable to

measure on individual level. Individuals are performing as an intensive team and according to

Tesluk et al. (1997), motivational programs for these kind of teams should focus on team level

processes and outcomes. A ProMES system at individual level can only be applied when each

individual employee is responsible for a specific operation or task and the within-group task

independencies are low. Generally this is not the case in a job shop situation. Because a group of

employees are responsible for a similar operation(s); common products, performance indicators,

contingencies and a feedback report can be developed. For example, all employees who are

situated at the saw unit perform about the same activities (sawing parts on the machines) and are

as a group responsible for the output of that unit.


T. de Boer 33

In general, the rule is to give feedback to the smallest possible group in which the internal

dependency relationships are stronger than the extern dependency relationships. Results of

previous studies (Pritchard, 1990) showed that it is most effective to give feedback to a group of

five to thirty people. Thus concluding, due to the intensive characteristics of the group (tasks

interdependency within the group is high) and due to the difficulties of applying ProMES to each

individual employee of each unit, we leave out this option for the remainder of the research and

we state that in a job shop situation ProMES can only be developed and applied at two different

levels:

1. A ProMES system for each functional unit (which can also be a one-person group);

2. A ProMES system for the whole production department.

When measured at group level it will take more time and effort the develop and maintain the

measurement system because a system has to be developed for each unit, but will have more

impact on productivity than when measuring on department level what will take less time and

effort to develop and maintain. It is difficult to recognize the unit contribution when a large group

is provided with feedback about the overall productivity performed by the whole group. Applying

on group level and on departmental level has both its advantages and disadvantages. It is clear

that applying on departmental level will be easiest, but is the least effective option. Up till now

we can not make a valid choice about which of the both levels is possible and the most effective

in a job shop.

To be able to make a valid choice about the most optimal level of measurement, we will discuss

the problems/difficulties which will show up at applying a ProMES system to a job shop process

in the next paragraph.

5.2 Factors influencing the success of ProMES

A main shortcoming of the ProMES method is that it is less applicable in situations with complex

interdependencies between groups. So it will be a difficult task to implement the ProMES system

in a complex production situation as a job shop at unit level. When productivity of units is

measured, it automatically leads to comparisons between these units, what leads to individualistic

behaviour and increases the risks of sub-optimization (and competition). Another aspect what

could lead to problems at implementing the system at unit level is that the operators do not have

the complete control over there productivity. Showing these examples indicated that some typical

job shop characteristics are influencing the success of the ProMES system.

5.2.1 The interdependencies between units

A job shop system represents a highly complex production environment with complex

dependency relationships between the different units, so the units are strongly dependent of each

other if it comes to exchange of information and products and changes of any kind. These

dependencies can be seen as sequential dependency (work on the result of previous units) and

reciprocal dependency (work flows back and forth between units). Examples of interdependencies

are: work on a part when another unit is finished with that, the quality of preceding work, speed

of doing work is dependent on the speed of getting parts or material when needed, how efficiently

the output is produced depends on how production scheduling has arranged the orders (Pritchard,

1990). For this kind of relationships, interventions aiming at improving performance should be

focusing on the contribution of the units and also focus on the exchange sequences between units

and on departmental performance as a whole (Tesluk et al., 1997).


T. de Boer 34

When measuring and evaluating on unit level, the individual unit contribution has to be

visualized. This is needed for obtaining detailed production data of each unit. But the problem is

that due to the dependencies between units, the departmental performance can hardly be

decomposed into the performance of independent units. The requirement of the ProMES

methodology is that the activities and tasks of the employees have to be controllable so the group

has the ability to influence the score on the indicator. Thus another problem for the development

of a ProMES system at unit level is that due to the interdependencies between units, the activities

and output of each single unit can not be fully controlled by each unit itself.

The productivity of the employees is influenced by some factors which they can not control.

These uncontrollable factors have to be ruled out or have to be taken into account by

implementing a measurement system. Factors influencing the controllability on the productivity

of the operators are for example; machine breakdowns, changes in production planning and

quality of raw material.

When a ProMES system is developed for each functional unit, all roles, activities and

responsibilities within the production department of the company must exactly be appointed and

applied to one of the functional units. Then no misunderstandings will exist about who is

responsible for which operation. This means that the units only have to work on those specific

operations at all times to be able to carefully measure their score on the performance indicators.

On this turn, it implies that other units may not (want to) work on the operations of another units

because this can have a negative influence on their productivity. This process leads to an increase

of productivity of that unit, but a decrease of the overall productivity of the department.

A practical difficulty is that is takes a lot of time and effort to develop a ProMES system for each

individual functional unit. Because then for each unit; products, performance indicators,

contingencies, the method of measuring and the relative importance for the company have to be

determined several times. With other words, each of the four development steps of the ProMES

system has to go through several times for each functional unit. But also the time required for

measuring the productivity each period at each single unit is much higher in comparison with

measuring on departmental level. This increase in development and maintenance time will

decrease the effectiveness of the application of the measurement system and will lower the trust

of the employees to the system.

The alternative is to develop a system for the whole production department with common

products, performance indicators, contingencies and one feedback report and measures take place

departmental level. According to the problems described above does it seem that a system for the

whole production department will be a better option, because among other things; the

interdependencies will not be removed, cooperation stay intact, it is less time demanding and

roles and activities do not have to be exactly appointed to a specific unit. The cooperation

between the different functional units will stay intact when a common system for the whole

production department is developed. Thus the employees will share the same feeling of strong

commitment to achieve a high as possible productivity for the whole department because

everyone is responsible for the overall result. A major disadvantage of developing and applying a

ProMES system to the whole production department is that the feedback report represents a

general feedback for all units in common. When information about the performance is fed back to

the whole department, it is difficult to recognize what the individual contribution was to the total

performance. An additional drawback of applying the system to the whole department is that

some units will perform less work when their unit productivity is not confirmed. This will lead to

a decrease in total productivity and an unfair situation because some units have to compensate for

the less performing units.


T. de Boer 35

5.2.2 Shifting operators between units

Often in job shop production processes operators are shifted between various functionally units.

Operators are shifted to a high demanding unit when the demand at “their” unit is low. The

problem is that the scores on the indicators will be influenced because changing the number of

operators and also the skills of the operators influences the outcome of that specific unit. The

achieved productivity is then not representative anymore for the possible achievable productivity

of that unit. The fact that operators are shifted between units influences the possibilities to apply

ProMES at unit level. The result of the varying unit output is that it is difficult to decompose the

departmental productivity into single unit productivity, thus it would be a problem when the

system is applied at unit level.

The output of the units will depend on the personnel working at a specific unit. This implies that

the personnel of the functional units can not fully control the output of the unit when the amount

and skills of the personnel is constantly being changed. Thus shifting operators between the

functionally units, which happens often in a job shop, decreases the ability to influence the

outputs and productivity of the functional units.

5.2.3 The rapidly changing orders

As described in chapter 4, at development phase 3 of the ProMES system, contingencies have to

be established. The contingencies show the amount of an indicator, ranging from worst feasible

level to best feasible level of productivity that could be scored on an indicator and also the

effectiveness value which represent what the achieved productivity (score on indicator) means for

the whole organization. A job shop production situation is characterized as a vast changing

production environment as described in paragraph 3.4. Thus in job shops, historical production

data is not always present due to much varying demand and nature of the orders each period,

which changes the possibilities of the units per period. And historical production data is just what

is needed to define the standards (worst and best feasible performance levels) which are required

by determining the contingencies. The unstable and unpredictable situation which is typical for a

job shop is caused by some various reasons. The first reason is that at job shops many different

products and parts (and of few amounts) are manufactured. Thus various orders and tasks have to

be processed by the functional units per period. Each order has its specific design and

requirements, which leads to different achievements in productivity over a specific period of

time. Thus it is hard to obtain historical experiences to make any judgments as to what is low or

high output due to the large variations in orders. The output varies each period, depending on the

nature and the demand of the work. This negatively influences the control the operators have on

the output of their units. The more the orders are varying, the more variations in output, what

implies decreasing control on unit’s productivity.

5.2.4 Different interests of the units

When ProMES is developed for each functional unit within the production department each

having its own (different) products, performance indicators and contingencies; the dependencies

between groups will partly be removed. Unit goals will become independently of the goals of

other unit when the productivity of the units are measured and evaluated separately from the rest.

Due this independent goal relationship; the interest of each unit will differ from the interest of

other units. Van Vijfeijken et al. (2002), state that goal interdependence reflects the way in which

goal attainment of an individual (a unit in this situation) is influenced by goal attainment of

others. In our situation, the goal interdependency is neutral (Van Vijfeijken et al., 2002).


T. de Boer 36

Neutral goal interdependency leads to individualistic behavior of the units, what on his turn can

lead to sub-optimization because little energy will be used to develop cooperation strategies (Van

Vijfeijken et al., 2002). Sub-optimization could lead to competition between units what will lead

to decreased coordination and productivity. Sub-optimization means that a functional unit on its

own does perform well, but the performance of the whole production department will likely not

increase. Units try to score high on their own products and performance indicators when ProMES

is implemented for each functional unit, but this can have negative influences on the other

functional units and the score on their indicators. It is stated by Van Vijfeijken et al. (2002) that in

this situation, the development of cooperation strategies can be stimulated by setting common

goals which create positive goal interdependence, and individual unit goals, because this

combination resulted in the highest productivity improvements. Thus by setting both goals for the

units and joint goals for the whole department, the units also try to reach these common goals

along with their own specific goals, so sub-optimization can be overcome.

Productivity achieved by one unit can have less meaning to the overall company than another

unit. Thus the contingencies have to be adjusted by concerning the relative importance of each

functional unit. A solution to this problem is a method called “scaling”, developed by Pritchard et

al. (1990). Scaling means that the contingencies developed for each unit have to be rescaled to the

relative importance of the units. The relative importance of each unit can be used when taking the

individual conditions at each unit into account. If it is possible to convert the contingencies to the

relative importance of each unit, we are able to combine the unit’s measures into a single measure

for the whole department. Factors that influence the productivity of the functional units are for

example the number of tasks the unit is performing, the nature of the work, number of machines

and operators and the production speed of machines and people.

But the scaling strategy is developed in the early phase of ProMES and the view of Pritchard has

been changed over time (Pritchard, 1995). Pritchard believes that the strategy will not optimally

work because not all the responsibilities of a department are contained into the measurement

system. An example is the responsibility to manage the coordination between different functional

units. A solution according to Pritchard (1995) might be to measure both on unit level and on

departmental level. The scaling strategy can still be used as we attended to do; the productivity

measures of each of the units can be combined and give an index of the average total productivity

of the units (thus how the units are doing as a group). But a comment we can place is that when

one optimally wants to make use of the scaling strategy, should also take the responsibilities for

the department as a whole into account.

5.2.5 The relational model

When we summarize the problems described above into a model; each of the described factors is

commonly related to three main factors. These three main factors are on their turn indirectly

influencing the success of a ProMES system for a job shop. These factors are negatively related

to the success and can be identified as:

1. Decomposition of departmental performance - Departmental performance can hardly be

decomposed into the performance of independent units.

2. Low controllability - Groups can have a substantial, but not major influence on unit

performance.

3. Risks at sub-optimization - Job shops consists of multiple compositions of groups with

different interests.


T. de Boer 37

These three factors are influenced by other related factors. We can define four factors which are

directly related to the three main factors and which are indirectly related to success; the between-

group dependencies, shifting operators, varying orders and the different interests of units. The

degree to which the success of the system decreases depends on how strong the influences of

these factors and relationships are at a specific job shop situation. The relationships between the

factors can be made clear in a model, which is presented in figure 5.1. The relationships are

represented by the arrows between the eight factors.

Figure 5.1: Relationships between factors influencing success of ProMES.

Decomposition is required when a system is applied on unit level. The interdependencies between

the functional units are negatively influencing the degree to which the departmental productivity

can be decomposed into single unit productivity. The interdependencies do also negatively

influence the control over the productivity, which is one of the most important requirements of

ProMES. Shifting operators between units negatively influences the ability to decompose

departmental productivity and the control over productivity. The many different orders that have

to be processed, which is typical for a job shop, are related to the control over productivity. Risks

at sub-optimization increase because the goals for each unit will become independent of each

other when the units are individually being measured. The three main factors are all related to the

success of the implementation of a ProMES system. The stronger these problems are, the lower

the chances at a successful implementation.

Up till now, we have described the difficulties and problems for applying ProMES which are

specific for a job shop situation. The developers of the ProMES methodology have determined

requirements for a successful development and maintainability of the ProMES system. The job

shop situation leads to these difficulties/problems because the specific characteristics and

conditions of a job shop can probably not satisfy these requirements. Application of ProMES to a

job shop can lead to problems because the situation can probably not satisfy the following

requirements (Van Tuijl, 1997):


T. de Boer 38

- the system is able to represent one single score for the total departmental productivity;

- the system is able to show how the total score is build up from sub-scores;

- the responsibilities have to represented by the unit and show these responsibilities at a

valid way.

The facts discussed above require us to create a situation in which the total departmental

productivity is decomposed into single unit productivity, so one is able to individually recognize

and measure the productivity of each single unit. Thus one of the most important trade-offs is the

level at which productivity is measured and at which information is feed back (unit or

departmental). Additional requirements are stated for the development of products, indicators and

contingencies which are probably difficult to satisfy by the job shop situation (Van Tuijl, 1997):

- employees have to be in control so they are able to influence their productivity;

- stable work environment and conditions for reliable determination of the contingencies.

In this paragraph we have explained why it is hard to satisfy these requirements when ProMES

have to be applied to a job shop. Due to these problems, we do not know what the possibilities of

applying ProMES to a job shop are at this moment and how strong the relationships of the model

are. In the next paragraph we formulate some ideas to solve the problems stated above. And in the

next chapters we try to find out if the causal relationships as presented in figure 5.1 are valid for

the research company.

5.3 Generating ideas for developing and applying ProMES

One of the research questions of this research was; “How to define productivity in a job shop

situation and how can it be measured?” Productivity can be defined and measured as described by

Pritchard (1990), thus we do not only determine the definition of productivity of a job shop, but

we will combine that with the determination of the level to which it is best to develop and apply

ProMES. At generating ideas for applying ProMES and measure the productivity we concentrate

on what level (unit or departmental or a combination) it is best to measure productivity instead of

defining productivity. In other words; the question; “What is productivity in a job shop?” will be

answered in combination with the determination of the level at which it is best to develop and

apply ProMES.

The objective of this idea generating phase is to come up with a solution about the level at which

it is best to development of a ProMES system. The ideas are determined according to the

possibilities within a job shop, and the trade off between the development time and time to

maintain the system and the highest possible improvement of overall productivity. We want to

create a situation where it is possible to recognize the changes (increase or decrease in

productivity) at departmental level by knowing which factors at unit level caused these changes.

The main goal of the ProMES methodology is to improve the productivity of the employees so to

achieve the organisational objectives. For example; manufacture more and innovative products in

a safe environment at low cost. The changes in productivity will at first be recognizable at

departmental level. When productivity changes are recognized at departmental level, in for

example; processing times, lateness and quality, we want to be able to determine which factors at

unit level influenced these changes, see figure 5.1. And the other way around, when changes

applied on unit level, we want to be able to determine to which changes that will lead in total

departmental productivity.


T. de Boer 39

Figure 5.1: Relationships between unit and departmental level

We want to visualize and measure the productivity at each unit to gain improvements in total

departmental productivity, but we do have to bear in mind what the possibilities and difficulties

for such a system are. At this moment we do know what the difficulties in theory are, but we do

not know what the possibilities in practice are. The situation described above is the most optimal

situation and is the objective of the idea generating phase, but again, we do not know what the

possibilities in practice are. That is why we generate ideas by considering the difficulties of a job

shop and possibilities of the ProMES system. We first determine the idea which creates the

situation as described above, this would then be the idea what leads to the most optimal situation.

After explaining this first idea, we will determine if there are any difficulties or disadvantages

implied, which are then tried to be solved by introducing a new idea. After analysing a job shop

system at the research company we can determine which of the ideas are possible and is the best

option for the development of the ProMES system, but this will be discussed in chapter 7 and 8.

IDEA 1 The objective is that we want to be able to know to which changes in total departmental

productivity it leads when changes are applied on unit level. Thus we have to apply ProMES to

the smallest possible group in a job shop, to determine which and/or who influenced the changes

in productivity at departmental level. An additional advantage is that a performance measurement

system is most effective when the achieved performance is fed back to a “small” group of people.

The production department characterized as a job shop can be split up into different functional

units. This is the smallest group of people that can be measured and evaluated (we already left out

the option of a system for each individual person). The first idea is to develop a ProMES system

for the department, and measures takes place at each individual functional unit, as graphically

shown in figure 5.2.

Figure 5.2: Idea 1

The same products, indicators and contingencies are determined for all the units, because then it

is possible to compare and sum up the unit scores and to obtain scores representing the overall

productivity of the department.

Department

Feedback

Measure Measure

Measure Measure

Unit

Unit Unit

Unit


T. de Boer 40

One general feedback report must be set up which represents the total departmental scores on the

indicators which are build up out of the scores of each single unit. This leads to decreasing

chances at sub-optimization because employees are forced to maximize the overall departmental

score. The first idea for measuring productivity and developing a ProMES system is:

Idea 1: Develop a ProMES system for the department, and measure each

functional unit individually

We will now analyse if difficulties show up at each of four development phases of ProMES. The

idea causes no problems at the first phase; key result areas (products) can be defined because

products stem from the organizational objectives and goals. Products which can be determined for

example are production speed and machine utilization. No problems will occur at development

phase 2; developing indicators. An indicator is a measure of how well the unit is generating the

product in question. Indicators for the two given products above can be for example the number

of products processed and the time the machines were on divided by the time the machines were

off. In phase 3 where low and high productivity must be determined is not dependent on the level

of measuring, so no specific problem caused by this idea. Phase 4, where the actual productivity

has to be measured and recorded in a feedback report can hardly be performed due to this idea.

Each kind of output per unit has to be made visible and measurable what will be difficult due to

the interdependencies between the units. And as told before in this chapter, measuring on unit

level involves some other disadvantages such as; scores will not represent the actually possible

achievable performance due to shifting employees, it takes much time to develop and maintain

the system, the cooperation between the units is partly removed which can lead to a decrease of

overall productivity.

IDEA 2 Due to the described problems above we now come up with an idea which takes out some of

these problems. Generally, the next idea is to measure both at unit and departmental level, thus by

setting unit goals with additionally some departmental goals. This will decrease the chances at

sub-optimization, it will increase the cooperation between the units and the relationships between

the units stay intact. The design team has to analyze which productivity aspects can not or are

hard to separate into unit’s productivity, and choose to measure these aspects at departmental

level. Products to be set up at unit level can be for example; the number of products produced,

quality and machine utilization and on departmental level for example; lateness of delivery and

total energy use. Products, indicators and contingencies have to be set up for both the units and

the production department when this idea is implemented. Goals have to be set on unit level

because this mostly motivates people to work more efficiently and information can be fed back to

each individual unit and also goals have to be set on departmental level to take away the

difficulties described above. This second idea is graphically shown in figure 5.3.

Figure 5.3: Idea 2

Measure Department

Feedback

Measure Measure

Measure Measure

Unit

Unit Unit

Unit


T. de Boer 41

The idea is thus to maintain the first idea and expand that idea with some measures on

departmental level. The second idea for measuring productivity and developing a ProMES system

is:

Idea 2: Expand idea 1 with measures on departmental level

Development phase 1 of the ProMES system (identifying products) will not cause any problems.

The difference now is only that on both levels (unit and department) products have to be defined.

The same counts for phase 2 and 3; no problems will show up after implementing this second

idea, it will only take more time to determine and set up the indicators and contingencies at both

levels. The difference this idea makes in comparison with idea 1 is that fewer problems will show

up at the measurement and feedback phase (phase 4). This is because now some productivity

aspects which can not be decomposed into unit’s productivity will be measured on departmental

level. So it is not required anymore to visualize and measure all the productivity aspects at each

single unit. A comment here is that it may not be possible to visualize and measure any kind of

productivity at each single unit, what implies that this idea is not an improvement over the first

idea.

When this idea is applied to the ProMES system, it will require much more development time,

because products, indicators and contingencies must be defined on both unit level and

departmental level. Also the maintenance time will increase drastically because productivity has

to be measured and fed back on both levels. It might be still the case that productivity cannot be

measured at unit level because none of the productivity aspects can be separated and ascribed to

single units. The problem of shifting employees remains so unit scores will not represent the

actually possible achievable performance.

IDEA 3

Due to the problems showing up at both ideas described above, it turns out that it would be better

to measure on a higher level. The improvement is that measuring on higher level leads to better

cooperation between the units and the interdependencies between the units will not be removed.

A disadvantage of measuring on a level which is too high is that the individual unit contribution

can not be recognized anymore what leads to fewer changes in motivation and productivity. It

might be possible to combine units which are closely cooperating and to measure and apply

feedback to as a whole group. According to Pritchard (1990) a group is formed with the criterion

that the smallest possible combination is formed in which the intern dependency relationships are

stronger than the extern dependency relationships. Thus we want to keep the measurement group

as small as possible (most effective), but the measurement level has to be increased. Thus we first

propose the idea to form a cluster of units, instead of developing a system at departmental level.

Other advantages in comparison with idea 2 are the decrease in measurement time and the most

important relationships will stay intact. Forming a cluster of functional units is only possible

when that specific set of units are very closely cooperating and having together the

responsibilities for manufacturing specific parts. Thus they are together performing tasks and

operations which results in a common measurable outcome. Often in job shops operators are

transferred between the units when demand is low on one unit and high on another, and because

the have the skills to operate other machines. The thought behind this third idea is thus that due to

closely cooperation between some units and shifting of operators, a group of units can be

combined and be taken as one group. An example is to combine a saw unit with the milling unit,

because they are tightly joint together, have a narrow cooperation, and the operators perform

activities on both units. The idea is thus to develop a ProMES system for the department, and

measure a group of functional units. The third idea is graphically shown in figure 5.4.


T. de Boer 42

Figure 5.4: Idea 3

The same products and indicators have to be set up for the groups, and then the group scores can

be summed up as one score representing the score of the whole department. The general feedback

report is built up out of the group scores which are summed up to the total department

productivity. The third idea for measuring productivity and developing a ProMES system is:

Idea 3: Develop a ProMES system for the department, and measure a group of

functional units

Considering the four development phase of ProMES, we can state that the first phase will not

cause any problems; products can still be defined for the units. This idea does not change

anything on the performability of development phases 2 and 3 in comparison with the previous

ideas; indicators and contingencies can be set up without influences of this third idea. Still

problems might show up at development phase 4 where the actual scores on the indicators have to

be measured and fed back to the floor. We can state that this third idea is an improvement in

comparison to idea 1 and 2 concerning the problem of recognizing and measuring the

productivity of each single unit, only if there is a situation of closely cooperating units.

A disadvantage of this idea is that the motivational efficiency decreases, because feedback is

given to a larger group of people. A drawback of this third idea is that we do not know if it is

possible to form a group of units. Other problems which emerge are the same as emerged at idea

1 and 2; scores do not represent the possible achievable performance (changing production

environment), it still takes much time to develop and maintain the system and maybe it is till not

possible to remove all the relationships between the units even though groups are formed.

IDEA 4

Due to the remaining problems of this third idea, we will enlarge the measurement level to

department level. The improvements in comparison with the previous ideas is that it is not needed

to separate the production department into smaller groups, so relationships and cooperation will

stay intact and eventually increases, development and maintenance time drastically decreases

(measure only at departmental level), sub-optimization and shifting of employees do not cause

problems any more. So the next idea provided (see figure 5.5), is to develop one measurement

system by which the overall productivity of the department is measured and fed back. The idea is

thus to develop and implement one ProMES system, with common products, indicators and one

feedback report. The fourth idea for measuring productivity and developing a ProMES system is:

Idea 4: Develop a ProMES system for the department, and measure on

departmental level

Department

Feedback

Measure Measure

Unit

Unit Unit

Unit


T. de Boer 43

Figure 5.5: Idea 4

When the ProMES system is applied according to this idea, no problems will occur at the four

development phases; products, indicators, contingencies can all be defined and it is easy to

measure the productivity of the whole department at the end of the final production step, and a

feedback report can be set up easily. The departmental score on each of the indicators is fed back

as a whole to the department. But even this fourth idea implies some problems when implemented

into the company; a major disadvantage of this fourth idea is that it is the least effective idea (less

motivation thus small changes in productivity) because the measurement group is probably too

large. The disadvantage is that people or units cannot recognize their individual contributions

when the scores are fed back to the whole group, because they are not enough motivated to

improve their productivity. Also, it can not be assumed that each employee and unit works as

hard and do one’s best as another to maximize his or her productivity, because he or she does not

have the intention (not enough motivated) or the possibilities to do that. The problem is thus that

the total overall productivity can not fairly be seen as the sum of productivity of all units because

units do not always (try to) maximize their productivity.

After describing the succeeding ideas it turned out to be that each idea does not overcome all the

problems. Thus maybe the first idea will still be best performable, because the other ideas do also

encounter important problems. The advantages and disadvantage we mentioned at the four

described ideas are concerning a job shop situation which is the “worst case scenario”, thus the

situation with the most difficult interdependencies, complex material flow, low control on

productivity, etc. The advantages and disadvantage of each of the provided ideas are summarized

in table 5.1.

The conclusion is that at this moment we can not make a grounded and reliable judgment about

which of the ideas is best possible. First we have to analyze the production department of the

research company before evaluating the four ideas. We will analyse the practical possibilities of a

ProMES system according to the research company in chapter 7 and the best idea is determined in

chapter 8.

Measure Department

Feedback

Unit

Unit Unit

Unit


T. de Boer 44

Ideas Advantages Disadvantages

Idea 1 - This is the most optimal situation. Thus

one is able to know which changes to

apply on unit level, to recognize the

desired changes in productivity on

departmental level.

- Hard to measure each unit individually

- Much development and maintenance time

- Fact of shifting employees

- Chances at sub-optimization

- Cooperation between units might be

removed

Idea 2 - The most important relationships stay

intact

- Better cooperation between units

- Decreasing chances at sub-optimization

- Still not possible to measure each unit

individually

- Much development and maintenance time

- Fact of shifting employees

Idea 3 - Better cooperation between units

- Interdependencies between units are only

partly removed

- Decreasing measurement time

- Shifting employees is no problem

- Less motivational

- Still some chances at sub-optimization

- Difficult to combine specific units

Idea 4 - No separation of units

- Cooperation and relationships stay intact

- Shifting employees is no problem

- Development and maintenance time

drastically decreases

- No sub-optimization

- Least motivational idea, thus small

changes in productivity is expected

- No fair measurement system

Table 5.1: Advantages and disadvantages of the generated ideas


T. de Boer 45

6. Description of the research company

The theory described in previous chapters will be tested in the practical situation of the research

company; “Exerion Precision Technology”, Ulft, the Netherlands. Also the ideas presented in

chapter 5 will be checked and tested according to the situation at that company. Paragraph 6.1

shortly describes the company. In paragraph 6.2 we give a general overview of the production

process. The production department can generally be divided up to four work centers, which are

described in 6.3. The part of the production department which can be characterized as a job shop

system is described in 6.4. The question; “Does and how does the company measure the

productivity of the production department?” is answered in paragraph 6.5. In paragraph 6.6 is

explained what the implementation of the ProMES system means for the remaining departments

of the research company.

6.1 Short description of the company

Exerion precision technology designs and manufactures metal chassis and mechanical parts for

printing and medical equipment and the demand is stable and predictable. It operates three

production facilities in Czech Republic, the Netherlands and Malaysia. The market can be

characterized as a business to business one. There are working around 250 employees in the

production facilities in the Netherlands, Czech Republic and Malaysia. The project is

concentrating on the production facility in Ulft (Netherlands). The product assortment can be

defined as low volume and high variety. The acceptance of ordering is according to a yearly

agreement at which the customers provide Exerion with a forecast of their requirements. The

actual demand is realized by means of call-offs or single orders. The major part of the demanded

volume is rather stable from week to week. Exerion jointly designs new products for its

customers.

6.2 Overview of the production process

The project will be concentrated on the “parts production department” of the company, where a

large number of parts and operations are to be managed, and where most of the metal parts are

manufactured for later assembly at the welding lines. This department can best be characterized

as a job shop. At the production department, the process can generally be divided into four steps;

metal-sheet cutting, parts production, kitting and welding. All products manufactured by the

production department do not necessarily require each of these steps, and are often processed

through varying routings. After welding, the frames may be sent to an external supplier for

surface treatment, to module building (where additional components are affixed to them) or

directly to the customer. The general production process is sketched in figure 6.1.

Figure 6.1: The general production process at Exerion

The general production process will now be described. The main raw material consists of metal

sheets which are first cut into smaller flat parts and holes are punched into these part. These parts

are then further processed (bending and/or clinching) depending on the specific customer order.


T. de Boer 46

After the parts are processed at the bending and/or clinching unis, the finished parts are kitted

(collection of different part in a box, called a kit) and welded together forming sub-frames. These

sub-frames are next welded together which forms the final frame. In most cases, the frames are

transported to an external company for surface treatment. The treated frames are returned to

Exerion where additional parts are assembled to the frame or sometimes a couple of frames are

assembled together to form a “module”. The frames and modules are packed and sent to the

customers.

6.3 The four functional units

6.3.1 Metal sheet cutting

The end-products stem from large metal sheets. Thus at first the metal sheets are cut into smaller

pieces and also holes and large figures are made into the metal sheets by punching and laser

machines. Some parts are now ready for welding, other parts are first to be processed at the other

functional units. Three cutting machines are placed at this unit:

• One machine which cuts the large metal sheets by “punching”. Manual labour is required

to load and unload the machine

• Two laser cutters which can run unmanned. When the tools have been placed in the

machine, the machines automatically retrieve metal sheets from the automated

warehouse, cut the parts, and the parts are send back to the warehouse

This unit is working in two shifts, with three persons per shift. The required capacity is according

to the machines running, so there is no opportunity to increase the productivity at this unit by

adding more people. Sometimes, people are transferred from this unit, when more capacity is

required at one of the other units. The laser cutters can work unmanned, so when required to work

outside the normal working days, the operators set up the machines and let them run for example

in the weekends. A part of the metal parts are automatically stored at the warehouse and the other

part is manually collected in a box or carrier.

6.3.2 Parts production

Many of the parts that are processed at the cutting unit require further processing before they are

welded into a frame at the welding unit. Two main processes take care the parts production:

clinching (where a metal nut is attached to the flat part), and bending. It is preferred to firstly

perform the clinching activity before bending, because the parts will take more storage space after

they are bend, and flat parts are easier to handle at the clinching unit, when this is not performable

the sequence is vice versa.

Clinching At this clinching unit are two large machines and some smaller machines situated. The first large

machine is an automatic machine and the second is a manual machine. The automatic machine is

to operate big flat parts, thus no bended parts can be loaded on this machine. The parts are

horizontally positioned on a bench which can move in two dimensions, so the flat parts are

positioned to be automatically clinched according to the programmed coordinates. The manual

machine is loaded with parts one by one by the operator, where he or she manually positions the

parts and executes the clinch.


T. de Boer 47

All parts required to be clinched after bending have to be processed by this manual machine. The

remainder of the machines and equipment are used for smaller parts which require few

operations.

Bending

Four bending benches are located at this unit. Not all parts that previously are processed at the

cutting and clinching machines can be loaded at all the benches. The parts are processed one by

one and the bending benches are loaded manually by the operators. The setup of the bending

benches is precise and requires specific handlings by the operators. Mainly, there are two

activities which have to be performed in behalf of the set up. The first activity is preparing and

placing the tooling into the bench. Time required is more dependent on the thickness of the metal

sheets than on the shape or size of the parts: when thickness remains unchanged, only little time is

needed to change the tooling. The second activity consists of controlling the correctness of the

first bended parts. If correct, the remainder of the batch can be processed.

6.3.3 Kitting

The parts are stored at the automatic warehouse after the parts are cut and/or processed at the

bending and clinching units. These parts and parts from external suppliers are collected at this

unit. The parts arriving at this unit are collected in a “kit” and are prepared to be welded. This kit

is a metal box with compartments where the parts are put in.

6.3.4 Welding

There are five different welding stations placed at this unit:

1. A manual station, used when the geometry of the product(s) are not able to be welded

automatically by a robot

2. A dedicated robot

3. A flexible welding robot for small subassembly’s

4. A flexible welding robot for bigger subassembly’s

5. A flexible welding robot for welding the subassembly’s welded at the above mentioned

stations

The parts from the kits are positioned in welding moulds. The parts are manually fixed at a metal

tray, with presses for fixation of the parts. More than one sub-assembly can be obtained from one

welding mould. The flexible robots can proceed welding without changes in tooling or other set

ups, but loading the stations requires operators.

6.3.5 Automatic warehouse

The automatic warehouse is located in the centre of the production department. Material can be

flown via five different inlets and outlets. Two are assigned to the cutting units, two to the

bending and clinching units, each for one unit, and one to the kitting unit. A single lift in the

warehouse receives and passes on carriers from the units, with the highest priority for the cutting

machines, kitting and parts production (bending and clinching unit) respectively.

6.4 The job shop within the production department

The production department at Exerion contains the following operations in random order:

warehouse, cutting, bending, clinching, kitting, other operations, welding and module building. A

specific part of the production department can be characterized as a job shop system. The job

shop system itself contains four functionally divided units; these are the bending, clinching,

kitting and “other operations” units.


T. de Boer 48

The material can flow in different routings through the system depending on the specific orders.

Examples of these different routings for different orders are graphically shown in figure 6.2. The

produced parts at each of the units are stored in the automated warehouse before the parts are

further processed at other functional unit(s).

Figure 6.2: Examples of various material routings due to various orders in the job shop

6.5 Current way of measuring at the production department

Examining if and how management measures the productivity of the production department and

which aspects are measured can give some insights and ideas about the possibilities of ProMES in

the job shop. Exerion only measures one productivity aspect, which is the efficiency of the

working hours. The actual working hours are compared with the norm which stands for the

working hours. We will now explain this method. The first production run of new parts and

products is observed and the time span in which these parts and products can be processed is

registered. The set up times (for loading the machine with the tooling and the parts), the design of

the product and operating speed of the machines and operators are taken into account for

determining the standard working time. The management set this required time as a standard and

enters it in a database. This pre-calculation is performed at the cutting, bending, clinching, and

welding units.

Orders for the day and the week are announced to the operators by the use of memo’s, along with

the standard for each order. The employees have to register the starting and finishing time of

processing an order. The actual time which is used to manufacture the products, is compared with

the standard of that order. The efficiency is calculated according to these two figures by dividing

the standard by the actual working time. When it turns be that the efficiency was too low at a

specific unit in a specific period; the management reports it to the responsible person(s) and they

try to figure out what the problem caused.


T. de Boer 49

The outcome is that the management is able to measure the amount of time spend on processing

orders at each functional unit. This positive and very important outcome of the practical analysis

is that at Exerion it is possible to visualize and measure “productivity” at each single unit, thus

they are able to decompose the departmental productivity into single unit’s productivity when the

factor “efficiency of working hours” is considered. The management also explained that it is

probably possible to set up a kind of information system which will enhance registering more

than one productivity aspect at each functional unit, such as machine utilization, quality, safety,

etc. These results show that the current situation looks like the desired situation presented at idea

1 and indicates that it is probably possible to execute idea 1.

6.6 The meaning of ProMES in the framework of the whole organization

Companies are often composed of several departments. The overall goal of implementing the

ProMES system to a job shop is to improve productivity at the production department and on his

turn to better achieve the organizational goals or objectives, so the organization benefits from the

system. ProMES cannot independently be applied to the job shop department without influences

of other departments. Other departments do influence the development of the ProMES system

because the goals defined during the development of ProMES have to be corresponding to the

goals of other departments. The goals defined during the development of the ProMES system

should stem from the organizational goals, just as at the other departments but it has to be

controlled that the goals of ProMES are corresponding to the goals of the other departments. An

example of conflicting goals between two departments is that the productivity department focuses

on manufacturing high quality products in spite of the increasing manufacturing time, so the sales

department can not fulfill its goal to deliver products within due date. Both departments have

conflicting goals, because one department is aiming at quality and the other at the due date. We

believe that ProMES cannot be applied without any influences from other departments, because

there is a risk that the activities and goals, defined in order of the ProMES system, are in conflict

with the activities and goals of the other departments. Concluding; departments cannot be seen as

self-working-units, so ProMES cannot be applied to a department without taking the influences of

the other departments into account.

This study only implies improving productivity at a job shop department but it can also be applied

to other departments. The productivity improvements gained at the job shop department will lead

to better achievements of the organizational goals, and when ProMES is implemented in the other

departments it will probably result in even more benefits for the organization. But this has to be

researched in other studies.


T. de Boer 50

7. Assessing the research company on the applicability of ProMES

After analysing the situation at the research company we are able to determine if the theoretically

stated assumptions are confirmed by practise and to determine which of the ideas generated in

chapter 5 will be best possible. In this chapter we will asses the research company on the

applicability of the ProMES system. The question is thus whether and how ProMES can be

applied at Exerion. The results of the practical analysis at the research company are described and

compared with theory in paragraph 7.1. In paragraph 7.2 we evaluate the results and summarize

the possibilities of applying ProMES to the job shop of Exerion.

7.1 Results of the practical analysis

7.1.1 Method

We analysed the production department of the research company and interviewed employees of

the company to get insights of production process. The analysis was built up out of two parts; we

visited the research company and analysed the production department and interviewed people

(both operators and management) a few times. By analysing the production department we

concentrated on the part which can be characterized as a job shop. Things that became clear were

among other things material flow, batch sizes, shifting personnel, material waste etc. Next we

interviewed the manufacturing manager and the supervisors/planners of the production

department. The focus during the visits was on the difficulties of applying ProMES to a job shop;

the measurement level, variation in workload, dependencies between functional units, etc. The

questions stated during an interview can be found in appendix D.

7.1.2 Comparing theory with practice

In this part we will compare the results of the analysis of the job shop at the research company

with the theoretical findings which are described in chapter 3, 4 and 5. We will focus on the

difficulties/problems for applying ProMES to a job shop situation and compare that with what we

found in practise. The question to be answered here can be determined as: “Does the practical

situation confirm or reject the theoretically found difficulties/problems for applying ProMES to a

job shop?” We will discuss the results of the practical analysis according to the three main

difficulties for applying ProMES, mentioned in chapter 5.

7.1.2.1 Level of measurement

During the interviews we asked the management about the consideration of the level of

measuring. As described before, the ProMES system can be developed at three different levels:

individual, group and department. We have already taken out the option of developing at

individual level, but in spite of that, we search for the possibilities and asked for the opinion of

the management.

We presented the option of developing a ProMES system for each individual and thus separately

measure the productivity of each person at the production department. The people made clear that

it will probable take too much time and effort to develop and maintain a measurement system for

each individual employee. Then the implementation of the system will not be efficient, because

the time it will take to develop and maintain the system will not surpass the benefits of the

system. This is confirming what we found in literature.


T. de Boer 51

The second point is that a ProMES system at individual level has only to be applied when each

individual employee is responsible for a specific activity or task, what was not the case at the

company. Thus another result of the interviews why a system for each individual is not a good

option is because the employees at the units are performing about the same activities and have the

same responsibilities. Thus the people within a group can generally be placed under one activity

(e.g. bending or clinching) because of their common activities and responsibilities. This is partly

confirming the literature because in literature it is stated that it is difficult to separate the activities

and productivity of an individual with the activities and productivity of a group. But the

additional outcome was that it is not needed to do so, because the employees within a unit are

performing about the same activities. Within the units, people are also dependent on each other so

they closely have to cooperate, exchange information and make together decisions. Thus the

people within the units are much more interrelated than with people between the units, because

they do not take too much care of other unit’s responsibilities.

The fourth reason is that management believes that people just cannot be compared, because each

employee has different capabilities and skills. For example, one’s doing its very best can result in

more/less manufactured parts at a day than the result of another one’s doing its best. The fifth

reason why employees cannot separately be measured is because at the company often operators

are shifted between the working units, thus they are not always performing the same activities.

This is necessary when demand is low at unit A and demand is high at unit B. The system cannot

take into account all these constantly changing activities of each of the operators. These latter two

disadvantages of a ProMES system for each individual employee is not stated in literature, but are

very clear and good reasons to take this option out.

7.1.2.2 The interdependencies between units

Next, questions are asked about the possibility of developing the system for each functional unit

and the possibility of separating units from each other. First we want to highlight the fact that the

company is actually registering performance measures at unit level, but these measurements are

different and not as extensive as the ProMES methodology is meant to do. Management is only

measuring the efficiency of the working hours of the operators and slightly the waste of material

at each working unit. As described earlier in this report, a job shop situation represents a high

complex production environment with complex relationships between the different units and the

employees within these units. The main dependencies which cause productivity hard to measure

are that a unit continues to work on the result of the previous units and is dependent on the

performance of that previous unit and products continually flow between the different functional

units. The results of analysing the company showed us that this was not really the case and the

dependencies are not of that nature what causes large difficulties/problems for measuring each

unit individually.

We will now explain why the complexity and dependencies were not really a problem at the

research company for measuring productivity. Actually, there were not many relationships

between the working units which could cause difficulties for visualizing and measuring the

productivity at each unit. The first reason is that the persons who are responsible for preparing

and planning the manufacturing processes are creating an optimal manufacturing process and

conditions so operators are not highly dependent on others achievements. An example is that

when parts are not ready at the right time; different orders are scheduled so the operators do not

have to wait. The second reason is that the material flow at the job shop is structured so the

employees are as low as possible dependent on other units; after an operation at each of the

working units, the products and parts are stored at the automated warehouse and are not directly

flown to other units. Thus with other words, the working units are decoupled by storing parts in-

between the process.


T. de Boer 52

The rule of the company is that only products can be stored and taken out of the warehouse when

the right products are ready, with the right amount and quality. The big advantage is that when

parts are stored in the warehouse, people can always assume that the right products are present at

the right amount and quality, which decreases the dependencies between the working units. The

third reason is that each operator has access to an information system, were each of his or her

handlings are registered. So at each time the newest information can be looked up for by each of

the employees. This enhances the exchange of information and decreases the required closely

cooperation and thus the dependencies between the working units. The three reasons described

above make clear that no complex dependencies between functional units are present at the

research company, which increases the possibility of applying the ProMES system at unit level.

Additionally, the information system used, in which several software packages are linked to each

other takes out another major problem, which is called time efficiency. It was assumed that

measuring productivity at each unit will take a lot of time. On the one hand does it take time to

set up the system, but on the other hand, a sophisticated information system in which the

production aspects are registered will decrease the required effort to maintain the system very

much. But at maintaining a ProMES system, a much more sophisticated automated measurement

system has to be developed.

We now summarize the three reasons. Proper preparing and planning at the research company

result in fewer dependencies between units. The second is that the material flow at the job shop

decreases the dependencies between the units, because the parts and products are stored only

within the right amount and the right quality at the warehouse each time. The third is that each

operator has access to a database in which each of his or her handlings are registered which

enhances (faster and better) exchange of information. When some dependencies do still cause

problems, a solution is to form the indicators such that the interdependent relationships are

removed. After analyzing the company, it can be concluded that it is possible to decompose the

departmental productivity into single unit’s productivity. The management was able to visualize

and measure the individual productivity of the units because the complex interdependencies were

reduced as much as possible, operators can easily be appointed to a specific unit, each operator at

the units is responsible for the same activities and tasks. Thus the practical analysis showed us

that the factor “task interdependencies between units” was weak and does not reduce the ability to

decompose departmental productivity into single unit’s productivity and the productivity can be

influenced by the units itself which increases the controllability over output.

Developing and maintaining one ProMES system for the whole production department is the

option which implies the minimum amount of development time and effort. This is also

confirmed after analysing the company and interviewing employees. Then only once a list of

products, indicators and contingencies have to be determined and one feedback report can be

provided to the whole department because productivity is only measured at departmental level.

According to the problems caused by the complex production environment and interdependencies

between the units, it seems that a system for the whole production department will be a good

potential. It was assumed that the complexity of the production situation as a job shop department

will cause difficulties at measuring productivity, but as told above, we can not really speak of that

high complexity at the research company. Thus, at only considering the complexity and

interdependencies between the functional units of the research company, the solution to measure

on departmental level is not explicitly necessary anymore. The people of the research company

did support the very important disadvantage of one feedback report for the whole department.

They confirmed that is would be difficult to recognize what the individual contribution of the

units was when one measurement system was set up and feedback was provided to the whole

department.


T. de Boer 53

An example is a general score of three functional units on production speed of 80% in a specific

period, but two units maximized their performance and one unit did not. The average was 80%,

but the employees can not see that one unit had actually a lower score than 80% and the other two

units scored 80% or higher. Thus the effectiveness of the ProMES system is low when the people

of the department can not recognize their individual unit contribution. The conclusion we can

draw after comparing the theoretically stated problems with the analysis of the research company

is that the problems of measuring at departmental level are for the most part confirmed by the

research company. And additionally, it turned out to be that it is not explicit necessary to set up

one system for the whole production department because departmental productivity can be

decomposed into single unit’s productivity in the situation of the research company.

7.1.2.3 Shifting operators between units

Often in job shops operators are working at different units because the workload at “his” unit is

low and at another unit high and they are acquainted with more than one activity. Shifting

operators leads to varying production achievements, because each employee has different skills

and capabilities. A second reason why the productivity differs per day is that often the company

is working with more than one shift, so the achievements are shift-dependent. The problem stated

in theory is that when the productivity at each unit is measured; the measures are not reliable and

can not be compared with the productivity in other periods because of the changing operators.

The situation of shifting operators and several shifts a day is the same at the research company.

The fact that operators are shifted between units, what leads to fluctuations in unit output,

influences the possibilities to apply ProMES at unit level. But despite the fact that not all the

employees do have the same skills, what results in varying production speed, quality, etc,

analyses of the company showed that enlarging the measurement period will average out the

fluctuations in unit productivity. Thus it will be easier to decompose the departmental

productivity and to apply ProMES on unit level at the research company by ruling out the varying

productivity. The problem of the low control at the units due the changing output can also be

overcome by enlarging the measurement period. Thus the research company confirmed the

influence shifting of operators has on both the difficult decomposition and decreasing control.

7.1.2.4 The rapidly changing orders

In a vast chancing environment of the job shop, orders, tasks and batch sizes are strongly varying

each week or month or even per day. This unstable and unpredictable situation is typical for a job

shop. Historical production data is required for the ProMES methodology, but these are not

available due to continuously changing orders and demand. Then it is hard to set any productivity

standards or norms (worst and best feasible performance levels) which are required by

determining the contingencies. Analyses of the research company confirmed the problem of vast

changing design and amount of orders which have to be processed by the operators. The orders at

the research company do vary a lot, even per day. About 3000 different parts are currently

processed by the manufacturing department at Exerion. These highly varying orders do lead to

changes in workload, production speed, quality, waste of material, etc. Not only the design of the

orders is varying, also the amount of orders does vary a lot per period. In a specific period often

the demand at unit A is much higher than at unit B, but the next period vice versa. This leads to

periods in which the units are not able to fully use their resources and to achieve their optimal

productivity. The company anticipates on the changes in design of orders and workload by first

changing the production planning or by letting the employees work in the evenings. When it

seems that the amount of work to be done is high/low for a longer period of time, the company

adapts to this by hiring and firing temporary workers.


T. de Boer 54

Analysing the company showed that the majority of the parts and products to be manufactured are

standard products. Thus besides that the analyses of the research company confirmed the problem

of highly varying orders, the amount of standard products is that high that they can use

productivity standards. Also each new product which is to be manufactured, often as a project,

will become a standard product. The company has a large database with all the productivity

norms of each of his products and continuously adds new norms for new products. Thus the

problem of getting enough historical experience to make any judgments as to what is low or high

output is not that difficult at the research company. Relatively many standard products are being

manufactured at the research company, thus the control the operators have on the unit output is

not that low as assumed.

Concluding, even though the variations in productivity in periods and between units, for this

situations we are able to determine the best and worst possible output for a unit due to many

standard products, the presence of historical data and enlargement of the measurement period.

This makes it possible to translate the productivity to an effectiveness value for the company and

a higher control on unit productivity.

7.1.2.5 Different interest of the units

When measuring each single functional unit separate, it is stated in literature that the functional

units will then first try to reach their own goals and prefer to optimize their own performance

without taking their responsibilities for the other units into account. One system for the whole

department is a solution to increase cooperation, which could be low when measuring at unit

level. The interviews at the research company showed that the risks at individualistic behaviour

of the units are low at the research company. The organisation strives to create an environment

and culture in which employees together want to achieve a high as possible productivity. The

employees do not only have to take care of their own functional unit with its tasks and

responsibilities, but also look outside the unit to strive together to solutions which results in

productivity improvement of the total department. Thus we might state that the solution of setting

overall goals for the department is not necessary because of the cooperative culture within the

organisation. But setting goals and providing feedback at unit level can still lead to individualistic

behaviour because the goal interdependency between the units are neutral (Van Vijfeijken et al.,

2002). So even within a cooperative culture units will probably act in individualistic behaviour

what can lead to sub-optimization. Thus a cooperative culture is a necessary condition, but will

only partly prevent sub-optimization. Concluding, the relationship between “different interests”

and “risks at sub-optimization” was confirmed by the research company, but is not that strong as

assumed to be.

A difficulty which resulted from the research company is that, when separately measuring the

units, it seemed impossible to compare the productivity of each unit, because each unit has its

specific importance. For example, the amount of parts produced per day by one unit can not

objectively be compared with the amount of parts produced by another unit, because less

operators and machines are placed at that unit. A solution is to rescale the contingencies, which

also came out the literature study. The employees of the company found it a good idea to rescale

the scores on the indicator dependent on the working environment and possibilities, so the scores

of the functional units can subjectively be compared and summed up as one overall score.

A result from the company which is not specified in literature is the problem of “social loafing”.

Social loafing means that people are profiting by the success which other people of the

department have achieved. This will result in a unfair situation and decreases the effectiveness of

ProMES.


T. de Boer 55

7.2 Evaluation of the results

After comparing the theoretical findings about applying ProMES to a job shop system with a

practical situation, we are now able to give an overview and conclude what the possibilities in our

situation are. With other words, we will give an overview of what is best possible by aiming at

creating the desired situation.

As we conclude in chapter 5, also in the setting of the research company it is not optimal and

even not required to measure the productivity of each individual employee within the production

department. The reasons which resulted from the research company corresponded with stated

reasons in literature. It will imply too much time and effort to set up and maintain a measurement

system for each individual, what is even not required because employees within a unit are closely

cooperating and together responsible for the same tasks and responsibilities. Shifting employees

between functional units will make it very complex to measure and evaluate at individual level.

Thus definitely, the option of developing ProMES at individual level will be left out.

Some major contradictions to the literature resulted from the practical analysis, which is positive

for the situation which we desire to create: visualize and measure productivity at unit level and

sum up the scores in one feedback report. The main contradiction to the literature and an

advantage for the current research is that the assumed dependencies, cooperation and

relationships between the functional units at the research company are not that complex or do not

cause that major problems as was assumed. This is because the proper production process,

structured material flow, continuously anticipation production planning and the availability of an

information system. It turned out that the importance and possibilities differed at each of the

functional units, thus the contingencies at each unit have to be rescaled to be able to compare and

sum up the unit scores. So it can be concluded that it is possible to decompose the departmental

productivity into single unit’s productivity at the company.

Most of the advantages and disadvantages found in literature about developing and applying a

ProMES system at departmental level were confirmed by the practical analysis. The big

advantage what also resulted from the practical situation, is that developing at departmental level

drastically decreases the development and maintenance time and effort of the system. Another

result is that it is not required to set up a system for the whole department because the option of

developing on unit level seemed very good possible. Developing and applying a ProMES system

at departmental level is a good possibility, but due to the large disadvantage of departmental

feedback and the very good possibilities for development at unit level; this option is not an

improvement in comparison with measuring on unit level.

High control over productivity is one of the most important requirements for a successful

implementation of the ProMES system because employees must be able to influence the scores on

the indicators. In literature it is assumed that especially job shops causes problems because in job

shops the employee’s productivity is influenced by uncontrollable factors, such as dependencies

between machines and humans, the environment in which they are operating and some other

factors. But the problems of these uncontrollable factors did not seem that high and we came up

at solutions to rule out the remaining low controllable factors. Also shifting operators is not a

problem when the measurement period is enlarged. Thus at considering the point of low

controllability at the research company, we can conclude that it is possible to implement a

ProMES system in a job shop, because the controllability is reasonably high and some solutions

are determined to decrease the influence of the remaining uncontrollable factors.


T. de Boer 56

It is assumed in literature (Van Vijfeijken et al., 2002) that there is a chance at individualistic

behaviour of the units when the productivity of each individual unit is measured, which on his

turn can lead to sub-optimization. The interviews made clear that these chances are low, because

each of the employees is managed to always do his best, to achieve a high productivity level and

to help his colleagues. The meaning of this to the project is that it is possible to separate the

production department into single units with low risks at individualistic behavior. But a comment

we can place is that, even if managed well, units will probably act in individualistic behaviour

when individually being measured and evaluated. The degree to which this problem can be

overcome is dependent on the specific situation. A cooperative culture is a necessary condition,

but will only partly prevent sub-optimization.

We will now discuss the relational model we presented in chapter 5 combined with the results

from the research company. The departmental productivity can almost fully be decomposed so

unit’s productivity can separately be measured, because the units were not as dependent on others

as supposed. This also increases the ability to influence the output of the units by the units

themselves, which increases the control over productivity. Additional findings, which were not

assumed in theory, but was a result of the practical analysis was that a central production

planning and control system and the use of a central warehouse to store parts in-between the

process, separates the units from each other. These could be defined as a factor which is related to

decomposition of departmental productivity and should be implemented in the model. The

relationships between the factor “shifting operators” with “decomposition of departmental

productivity” and “controllability” are confirmed by the research company. The difficulties which

are caused by shifting the operators between units are confirmed by the practical analyses, but can

partly be reduced by enlarging the measurement period defining the right indicators. Practical

analysis confirmed the relationship between the varying orders and control. Orders are not that

much varying as assumed in literature because a lot of standard products are being manufactured

what increases the control on productivity. Thus the relationship between “varying orders” and

“control” is weak at the research company. The fact that independent unit goals do influence

individualistic behavior is confirmed by the practical analysis. Sub-optimization will probably be

always present when units are individually being measured, but a solution to decrease chances at

sub-optimization (and competition) is to create a cooperative organization.

The conclusion is that it is possible to apply a ProMES system at the job shop of the research

company and to measure and enhance productivity at unit level, because the theoretically stated

difficulties were not that hard as assumed; departmental productivity can be decomposed into unit

productivity, control over productivity is reasonably high and chances at sub-optimization can be

kept to a minimum.


T. de Boer 57

8 Matching ProMES with a job shop

After stating the possibilities for the system at the previous chapter, we determine how the

ProMES system has to be developed for a job shop situation in this chapter. First we discuss the

minimal conditions which are required for the application of a ProMES system in paragraph 8.1.

We determine in paragraph 8.2 which of the generated ideas will be the best. Paragraph 8.3

globally describes what the system should be and presents recommendations about applying a

ProMES system to a job shop situation.

8.1 When is ProMES applicable

We approach the applicability of ProMES to a job shop on a higher level in this paragraph.

According to the literature study and the analysis of the research company, we can state what the

minimum required situation/conditions have to be for developing a reliable measurement and

enhancement system. The first that are required are the acceptance of the system and the trust in

the system by the management and the unit personnel and also the willingness to measure

productivity and to be measured. But all this is not within the objective of the current research so

we leave these facts out of consideration and assume that these requirements are satisfied.

The study of N. Huve (2005) did not lead to the desired situation as described in paragraph 5.2.

The researcher was not able to create a situation in which to recognize which changes at unit level

resulted in which changes at departmental level. The most important reasons why that system was

developed on a (too) high level were the specific situation at the company with its complex

relationships between groups and the limited availability of production data. Thus the researcher

was forced to develop one general system on departmental level, what is not most the effective,

because a system on that level does lead to fewer increases in people’s motivation to change their

working behaviour, what will lead to less productivity improvements. Thus the study of N. Huve

(2005) indicated that for an effective ProMES system for a job shop (thus on unit level), the

availability of detailed production data is highly required. So we state that the most general and

important element what is required, is the ability to really measure productivity, because this is

the basic element required for the development and implementation of the ProMES methodology.

One has to be able to exactly determine what and how the operators are performing at each

functional unit at each day, is able to measure what is required, administers everything correctly

and uses a detailed information system. The outcome from the chapter described up till now is

that it is not possible to develop a reliable and valid measurement system when only productivity

data is available in detail. A second aspect what is of major influence is the controllability over

the unit’s productivity. The second most important requirement for the development of the system

is that employees are able to influence their productivity, thus are in control over their activities

and output. When the units are measured and evaluated on indicators which are beyond their

control, it is very frustrating to employees because they will not be (enough) motivated and will

decrease the effectiveness of the system.

We conclude that when detailed production data is available and the indicators are developed in a

way that these can be influenced by the operators, the ProMES system can be applied to a job

shop with the highest probability of success (i.e. substantial productivity improvement). These

required conditions are satisfied by the production situation at the research company. But the

degree of applicability and success of a ProMES system is dependent on much more elements

which have to be developed, adjusted or optimized to be an effective and successful measurement

system.


T. de Boer 58

8.2 Determining the best idea

Before we analyze which of the four ideas proposed in chapter 5 is the best option and thus the

most optimal for the situation of the research company, we shortly repeat the situation which we

want to be created. That situation is; when productivity changes are recognized at departmental

level, we want to be able to determine which factors at unit level influenced these changes. And

also, when changes applied on unit level, we want to be able to determine to which changes in

total departmental productivity that will lead. Note that the proposed ideas are only considering

the level of measurement and application, thus the main result at this stage is the level at which it

is best to measure productivity.

This desired situation led to the proposal of the idea 1: “Develop a ProMES system for the

department, and measure each functional unit individually”. The first question which immediately

rose at this proposal was if the total departmental productivity could be decomposed to single

unit’s productivity so the units could be measured individually. The practical analysis at the

research company showed some contradictions to assumptions from literature and it is very good

possible to measure productivity at each functional unit. The interdependencies and relationships

between the units are not very complex. Also the assumed difficulties of shifting employees,

chances at sub-optimization and the removed cooperation between units do not cause important

problems or difficulties what would hinder the development and application of a ProMES system

at unit level. A small disadvantage of this option is that it requires more effort to maintain the

measurement system because the scores on each indicator have each period to be registered at

each functional unit. Thus the idea which we desired is practically possible. The best idea is thus

to develop one ProMES system for the department and information about productivity is gathered

and evaluated at unit level. This implies that the desired situation can be created, and also it is not

needed to further evaluate the remaining three ideas here, because these ideas all had

disadvantages and were less effective than the initial idea. Concluding we can state that the first

idea; a ProMES system for the department and measure each functional unit individually is the

best potential to be used for developing a ProMES system for a job shop system of the research

company.

8.3 Description of the system and recommendations

8.3.1 Description of the system

The outcome of the previous chapters was that measuring productivity at each individual

functional unit is the most optimal and is also possible in practice. The application of the system

begins with clear statements or organizational objectives. The characteristics of the system are

that productivity of each unit is measured at each unit and feedback is provided according the

sum of the unit’s productivity. Thus we want to make clear that the ProMES system has to be

developed according to common products and indicators which for each unit, contingencies will

be drawn for each unit, and the feedback report contains the departmental score, but also shows

the individual contribution to the overall score. At each functional unit, periodically

measurements have to take place, which measures the scores on the indicators. Then according to

the contingencies it can be determined what the productivity of each of the units was in that

period. The individual unit scores on the products have to be summed up and have to be recorded

in one feedback report. This general feedback report is then build-up out of the unit scores and

represents the overall score of the department on each product and a total departmental

productivity score. Employees are forced to maximize both unit and departmental productivity by

using one feedback report.


T. de Boer 59

In other words, the system indirectly provides departmental goals and feedback which enhances

strategy development and coordination among units and within units.

We have also considered defining products and indicators which are different for each functional

unit. What follows is that each functional unit gets feedback according to a single feedback

report. But this is NOT a good idea because:

- Product are derived from departmental goals which are related to organizational goals,

thus units together have to try to maximize the same productivity aspects, which will be

summed up and represents scores on the departmental goals

- Then the scores on the indicators of each unit can not be compared and summed up, so it

recognizable who is responsible for which changes in overall productivity

- It will require much more time and effort for determining different products and

indicators and measuring and giving feedback to each unit separate

- Unpractical to form a design team for each single unit

8.3.2 Recommendations

The recommendations which will lead to the most effective application of the system will be

described below. The recommendations presented here can generally be applied to situations

which differ from the situation of the research company.

8.3.2.1 Recommendations for reducing dependency relationships

A job shop is a highly complex production environment with complex dependency relationships

between the different units (work on the result of previous units). This leads to the fact that the

units are strongly dependent of others if it comes to exchange of information and products.

When for example a preceding unit is the bottleneck in the production process, thus cannot finish

tasks on time, products are not present at the right time at the succeeding unit. The result is that

the measured score on an indicator that period does not represent the actual possible productivity

of that unit, because they cannot work on the right products. This can be ruled out by specifying

the indicators in the way that the measurement takes place from the moment the right amount of

orders are present at the concerning unit till the time the unit finishes its work. Another

recommendation for removing the dependency relationships is to take care for a good production

planning and scheduling process, which decreases the dependency on the work of a preceding

unit, by anticipating on the changes in production, what resulted from that preceding unit. When

units do have to cooperate to fulfill a task, a recommendation is to define one or more indicators

in a way that these measures the degree to which the different units cooperate and enables each

other to improve productivity. Then the indicator(s) define the way parts and products have to be

transferred between working units and additionally the tasks a unit are responsible for. An

example of an indicator is the percentage correct amount transferred to the succeeding unit, or the

percentage correctly stacked up.

Also, a the use of a central warehouse, in which products and part may only be stored when

satisfying the requirements, decreases the dependent relationships between the functional units. A

recommendation is also to develop an information system, were each of operator’s handlings and

product conditions can be registered. This enhances the exchange of information and decreases

the dependency relationships between the units. This information system also provides improves

the cooperation between units, what was partly removed by exactly appointing tasks and

responsibilities to each unit.


T. de Boer 60

The complex material flow and the many different routings have to be ruled out for the most part,

to be able to separate the unit’s productivity from the overall departmental productivity. When

developing a ProMES system at which productivity is measured at unit level, the organization has

exactly to clarify the roles of the people within the units. The responsibilities, roles and activities

have exactly to be appointed and applied to one of the functional units, so no misunderstanding

exists about who is responsible for which operation. This is recommended because the

productivity which is measured at the units is really the outcome of that specific unit, and not of

any other unit. But as told above, the units together have to maximize the productivity of the total

department, at which good cooperation between units is indispensable, so there are always some

aspects which others have to take care for.

Because all the scores on the indicators have to be measured and recorded at each functional unit,

it would be very helpful to develop a information system and a database in which the information

about the productivity, such as hours worked, parts passed quality check and machine utilization,

etc, can be stored. This increases the cooperation between separated units. It would be effective

when all employees do have access to this information system, so he or she can enter his or her

productivity at each place and time.

The contingencies have to be rescaled because all the units are often performing different

activities, have different interests and work in different situations and circumstances. When the

contingencies are rescaled, the relative importance and the circumstances of each unit are taken

into account, so it is possible to compare and sum up the individual productivity of each

functional unit to one overall departmental score.

8.3.2.2 Recommendations to overcome the problem of low controllability

Employees do not have high control over the outputs of the units due to the dependencies

between units, shifting operators and the vast changing production orders. To create the situation

in which the employees can influence their productivity scores, so have a high control over their

work is to: enlarge the measurement period to average out the variation in productivity, restrict

the responsibility to tasks that are completely controllable (e.g. do not cover all parts of the tasks)

and/or form the indicators such that the interdependencies are removed (e.g. start measuring at the

right time), (Algera and Van Tuijl, 2004). But disadvantages are involved at these three solutions.

The measurement period should not be too long; otherwise the provided feedback does not have

the motivational power. This is because when feedback is provided after a too long time, it does

not have enough meaning to the employees anymore. There is a possibility that not the most

important productivity aspects are being measured and evaluated when only the indicators are

measured which are fully controllable. The disadvantage is than that the company will not profit

optimally by the system and not in accordance to the organizational goals. When too many

interdependencies are removed, the total departmental productivity decreases because it might be

that some vital dependencies can not be removed. The solutions to enlarging the measurement

period and define indictors such that interdependencies are removed, are both preferred, because

these solutions will slightly influence the success of the system. Increasing control by defining

only indicators which can be influence by the personnel increases the change that not the most

important indicators are used, thus that option is less preferred.

One of the basic needs for the development of the ProMES system is the availability of historical

production data. But a job shop is typically characterized as a production process in which

demand and the nature of the orders at the units are highly varying between periods. We

recommend making use of a constantly updated data base. So more productivity data will become

available and increases the control over the unit’s output over time.


T. de Boer 61

8.3.2.3 Recommendation to reduce the chances at sub-optimization of units

Individualistic behaviour of the functional units and sub-optimization can partly be prevented by

management. Chances at individualistic behavior can be kept low by creating a cooperative

culture, at which people are willing to help each other and together are striving to both maximum

unit and department productivity. This will result in a situation in which employees also to look

outside his or her unit, what results in better cooperation and higher departmental productivity.

This recommendation will not fully overcome the problem of sub-optimization because units act

in individualistic behavior when goals are set and feedback is provided to each units individually

(Van Vijfeijken et al., 2002), even though the management “requires” a cooperative culture. So

even within a cooperative culture units will probably act in individualistic behaviour what can

lead to sub-optimization and competition. Thus a cooperative culture is a necessary condition, but

will only partly prevent sub-optimization.

A second recommendation is that individual unit scores have to be summed up to one overall

departmental score. This will contribute to closer relationships and better cooperation between

units which on his turn will lead to higher improvements of departmental productivity and

decreasing chances at individualistic behavior (Van Vijfeijken et al., 2002).

To explain what we have described in this chapter and to show how to apply the solutions and

recommendations, we present a global design of the ProMES system in the next chapter. In that

chapter we describe how the ProMES system should be applied to a job shop production process

with the characteristics of the research company.


T. de Boer 62

9 Developing ProMES for a job shop production process

This chapter provides a global design of a ProMES system as it could be applied to the job shop

of the research company. We do not actually implement the system, because that is not within the

objective of the project and the time it would take would exceed the time available for the project.

According to this design we explain how the system has to be developed for a job shop situation

and give the recommendations and requirements which resulted from the current research.

The basic method of ProMES is to work with a design team which develops the productivity and

measurement system for the units of the department. The design team is composed of facilitators,

supervisors and unit members and their role is to be responsible for designing and implementing

the system. But because we do only set up a general design with some aspects in detail for the

remainder of this research, we do not appoint a design team at the research company which is

responsible for the development of the system. We recommend involving (at least) one member

of each working unit to act as representative for each unit. It is not needed to involve more than

one person because often a small amount of operators belong to one functional unit.

IDENTIFYING PRODUCTS The first step in the development of the ProMES system is to identify the products. Products are a

set of activities the unit/organization is expected to perform, or a set of objectives or results that is

expected to accomplish by the unit. By identifying the products, the people at the units can state

some questions which help to identify the products. The questions are; “What are some of the big

things the organization expects you to accomplish?” and “What are the groups of tasks you are

expected to do?” The criteria for identifying good products, stated by Pritchard (1990) are:

- they have to be clearly defined;

- they have to be complete, the list of products have to contain all the unit’s work;

- the unit has to be able to influence them;

- the unit has to be responsible for these products, not other people;

- if the unit did exactly what the products say, the organization would benefit.

The design team has to make sure that the list of products is complete. The result may be that too

many products are defined, thus they have to decrease the number of products on the list. At the

end of this phase, the units will have between three and six products. The products provided by

the people of the research company are explained below.

Production speed is of high importance for a company like the research company. The production

department has to satisfy the production planning and so products can be delivered within the due

date. Thus the first product which is identified is to produce the amount of products/parts planned

for each unit. This product can be influenced by the personnel because they are responsible for

processing the products at the units by themselves. At each unit the production speed can be

measured, thus the measures on this product are the result of the concerned unit and not the result

of other people or units. The influences of others are ruled out by measuring from the moment the

parts are available and by comparing the planned processing time with the actual working time.

The operators at the units are responsible for producing products with the quality in conformance

with specs. Products and parts have to satisfy the quality which is agreed with the customer. Thus

the second product identified is to manufacture product with the quality in conformance with the

specs.


T. de Boer 63

The unit is able to influence this product, because they are themselves responsible for the

delivered quality of their work. The quality of the delivered work will not be dependent on the

quality of the work performed by the preceding units when the quality is only checked on the

performed work by the actual responsible units. If the specific responsibilities are appointed to

each specific unit, is it easy to determine which specific unit is responsible for the eventual

decrease in quality. This partly removes the dependency between units, so this product is not

influenced by other units. The company requires an as high as possible attendance of employees.

Production problems occur, like not satisfying the production planning, when employees are not

attendant due to illness or accidence at the company. The third product is to maintain high

attendance. The people at the units are fully able to influence the level of attendance, because this

product concerns the people itself. This product is only influenced by the unit’s personnel

because attendance can simply not be influenced by other people or units. Another important

aspect which is objected by the organization is the degree of occupations of the machines at the

different units. This is most important for the cutting unit, because here are big and costly

machine situated. This product can be influenced by the unit’s personnel, because they are

operating the machines by themselves, thus personnel can influence the time the machine is

running (except at machine breakdowns). This product will not be influenced by other units,

when the measurement is properly executed; the planned utilization should be compared with the

actual utilization. So the eventually delays or other problems resulting from other units do not

influence the score of the concerning unit so dependency between units is removed. Thus the

fourth product is to maintain a high level of machine utilization. The final product is about the

safety the employees are working with. The employees are responsible to safely operate the

machine and “live by the rules of the house”. The employees have to work according to safety

rules and procedures which prevent accidences and complaints of the operators. Thus the fifth

product is to correctly follow housekeeping and safety rules. The people of the units are assumed

to know what the safety rules are, thus they can influence the way they follow these rules. The

way the safety rules are followed is measured at each unit and can be followed without influences

of other units, so the measured score on this products is exactly the output of the concerning unit.

The list of products that could be used for the research company is the following:

Product 1: Maintain a high level of production;

Product 2: Make products with the quality in conformance with specs;

Product 3: Maintain high attendance;

Product 4: Maintain a high level of machine utilization;

Product 5: Correctly following housekeeping and safety rules.

We believe that the criteria for good products are satisfied. The products are clearly defined, and

highly probable understandable for the employees. The list of products is provided by the

research company and contains the most important aspects the organization is aiming at. Each of

the products can be influenced by the employees of the unit, so they have control over their

performed work as told by explaining the products. Thus at each unit it is clear that only the

unit’s personnel is responsible for each of its own products, so no people of other units are

responsible for the activities of other units. Finally, the products stem from organizational goals,

so if the unit does exactly what the products say, the organization would benefit from it.

DETERMINING INDICATORS When the products are defined, the second step in the development of the system is to develop the

indicators. There can be one or several indicators for each product. An indicator is a concrete

measure of how well the organization was generating the product.


T. de Boer 64

The questions that can be stated by the personnel at the units to help developing the indicators can

be; “how would you measure how well the unit was doing on each of the products?”, “what

would you point to show your boss how well you are doing? Typically the number of indicators

ranges from five to fifteen (Pritchard, 1990). The numbers of indicators have to be that high that

it is still manageable, otherwise the system will become too complex. The criteria for developing

good indicators, stated by Pritchard (1990) are:

- the indicators are relevant for the products;

- the set of indicators has to be complete; cover all the products and cover each product;

- they are valid (what is measured is an accurate index of product accomplishment);

- they are controllable; the group has the ability to influence the score on the indicator;

- collecting scores of the indicators is costs effective;

- they are understandable and meaningful to the personnel of the unit;

- productivity is both on a short and long term of importance for the company;

- the essence of the tasks and responsibilities have to be measured by the set of indicators.

The indicators to measure how well the unit is doing on each of the products are provided by the

people of the research company. We present the list of indicators belonging to each of the

products below.

Product 1: Maintain a high level of production Indicator: Efficiency of working hours – Planned working hours divided by actual

working hours

Product 2: Make products with the quality in conformance with specs Indicator 1: Percent passed inspection – Products passed divided by all products

Indicator 2: Number of customer complaints – Complains made by customers

Product 3: Maintain high attendance

Indicator: Percent hours present – Hours present divided by maximum hours possibly

present

Product 4: Maintain a high level of machine utilization

Indicator: Machine utilization - The time a machines is in use divided by the maximum

possible run time of the machines

Product 5: Correctly following housekeeping and safety rules Indicator: Number of violations – Violations of the housekeeping and violation rules

Efficiency of working hours - This indicator is already used by the research company. The

company has calculated a maximum processing time required for each product or part. This

processing time encompasses all activities and tasks required for the operation, the so called

planned working time. The actual time required for processing the products is registered. Then,

the efficiency is determined by dividing the planned working hours by the actual worked hours.

The higher the efficiency is, the better it is. To remove the dependency with other units and to

obtain more control over this indicator, should the planned working time be calculated as

following: the time required for processing the parts, should be measured from the moment the

parts are available till finishing the parts.

Percent passed inspection - The products produced at the company, go through a quality

inspection before they are shipped to the customer. When a product does not pass the quality

inspection, it is returned to the production department and the problem has to be fixed. The

people of the inspection have to determine which functional unit was responsible for which part

of the product, and thus responsible for a fault in production. The indicator is determined by

dividing the number of products which did pass inspection by the total number of products

checked. The higher this value is, the better the score on the indicator.


T. de Boer 65

Number of customer complaints - Customer can be unsatisfied with the results after shipping and

installing the products at the customer site. The customer will probable contact the company and

explains the problem. The number of these complaints has to be as low as possible. The lower the

number of complaint is, the better the score on the indicator. This indicator is defined by the

number of complaints per delivered product.

Percent hours present - Employees working at the company can sometimes be not attendant

because they are ill or have other reasons not showing up. The indicator is determined by the

number of hours the employees were present in a specific period divided by the maximum

possible hours the employees could be present.

Machine utilization - From an economic viewpoint it is required to let the machines run as much

as possible, because idle machines do only cost money. Thus the more time the machines are

running, the higher the score on this productivity indicator will be. The indicator is determined by

dividing the number of hours the machine were actual running by the number of hours the

machine was possible to run. The possible run time is defined by taking the preventive

maintenance time, set up time, etc, into account.

Number of violations – for the safety of the employees itself and his or her colleagues, it is best to

strictly follow the safety rules determined by the company. The violations of these rules have to

be noticed and counted. The number of violations has to be kept as low as possible.

The indicators are determined so they satisfy the criteria for good indicators. The indicators are

relevant for the product and are valid, because the score on the indicator is a measure of how the

units are doing on the product. The most important and clear indicators are used, thus we assume

that the list of indicators is complete. The people at the units are themselves responsible for the

output of the unit, thus unit is fully able to influence the indicators as the processing time, quality,

attendance, machine utilization and the following of safety rules. It is difficult to analyze the

effectiveness of the system when it is about the costs of maintaining the system compared to the

profit the system gains. We assume that the indicators are not difficult to understand by the

employees of the company. The indicators are developed according to the products, which on his

turn stems from the organizational goals. Often these goals are determined for the short and long

term, so we assume that the measured productivity is both on a short and long term of importance

for the company. The same counts for the essence of the tasks and responsibilities; they are

measured by the set of indicators because these are the main things the organization is aiming at

and the main expected activities to be accomplished by the units.

ESTABLISHING CONTINGENCIES After the products and indicators are determined and reviewed and approved by the higher

management, the next step is to establish the contingencies. At this stage for each indicator a

function has to be generated that shows how much the different amount of the indicator

contribute to the overall effectiveness (productivity) of the unit. Contingencies are graphs that

show the different levels of the indicator on the horizontal axis and the contribution of that level

of the indicator on the vertical axis. “A contingency is the relationship between the amount of an

indicator and the effectiveness of that amount of the indicator”, (Pritchard, 1990, p. 22). The first

step in developing the contingencies is determining the maximum and minimum values and the

zero point of the indicators. The maximum value is “the best possible performance a group could

expect on an indicator if they did everything correctly for a given time period” and the minimum

value is “the worst possible performance the group could imagine actually happening to

them”.The zero point is “the expected level of performance or the level that is neither good nor

bad performance”, (Pritchard, 1990). The maximum, minimum and zero point values for the

indicators are partly determined by the research company.


T. de Boer 66

The values for the percentage passed quality inspection and the number of violations are assumed

to be as in the table 9.1.

Indicator Max. possible value Min. possible value Zero point

Efficiency of working hours 90% 75% 80-85%

Percentage passed

inspection

100% 95% 97%

Customer complaints 0 per product 1 per product 0,25 per product

Percentage hours present 97% 95% 96%

Machine utilization 95% 90% 85%

Number of violations 0 15 5 Table 9.1: Indicator values

The second step in developing the contingencies is ranking the maximums and minimums. We

start with the maximums. The question here is: “which of the maximums would contribute the

most to the effectiveness of the organization?” The design team has to rank order the maximums

in terms of the contribution of each indicator to the overall effectiveness of the unit.

That maximum that contributed most to the organizational effectiveness is rank with 1; the

maximum which contributed second most receives a 2, and so forth. The maximum with the

highest importance rank is then given an effectiveness value of +100 and the other maximums are

ranked as percentage of the +100 maximum. The maximums of the indicators could be ranked

and rated as following:

Maximum Effectiveness score

90% Efficiency of working hours +100

100% Percentage passed inspection +70

0 Customer complaints +50

3% Percentage hours present +30

95% Machine utilization +75

0 Number of violations +10 Table 9.2: Effectiveness values maximums

The reason why for example customer complaints could be rated with +50 is because this

indicator is half as important to the effectiveness of the unit.

Then the minimums have to be ranked. The minimum that detracts most from overall

effectiveness was given the ranking of 1, the minimum that detracts the second most is given a 2,

and so forth. The minimum that receives the highest rank (thus a 1) does not automatically

receive a value of -100 effectiveness points. Thus the question is: if the unit is producing the

maximum on an indicator, how low should producing the minimum at an indicator be rated? If

producing the minimum would harm the organization as much as producing the maximum would

help the organization, than maximum and minimum are rated with +100 and -100 respectively.

Minimum Effectiveness score

75% Efficiency of working hours -85

95% Percentage passed inspection -100

1 Customer complaints -65

5% Percentage hours present -75

85% Machine utilization -40

15 Number of violations -15 Table 9.3: Effectiveness values minimums


T. de Boer 67

An additional step in establishing the contingencies for each indicator at each unit is to think

about the relative importance of each unit to the overall productivity. It could be that the

maximum, minimum and zero point differs between the units, because the work of a unit is more

critical that that of the others, due to different conditions, possibilities and circumstances. Factors

influencing the productivity of the functional units are for example:

- the relative contribution of the units;

- the number of tasks the unit is performing;

- number of machines and operators;

- the nature of the work;

- production speed of machines and people.

Because the job shop department is composed of several units, is required and valuable to have a

measure for each unit and to combine the measures of each unit into a single measure for the

whole department. To be able to sum up the scores per unit, an additional step has to be taken,

called scaling, when it is assumed that the relative importance of the units differs. Thus to

overcome the problem of unequal possible productivity and importance of each unit, scaling has

to be done. Scaling has to be done because one unit’s effectiveness would contribute more to

overall effectiveness than that of the other unit(s). The improvement is that the relative

importance of each unit is considered, thus now we are able to sum up the performances of each

single unit and use a single measure for the whole department. We will shortly explain how the

values have to be rescaled. In the previous steps, each of the most important indicators at each

unit is given a value of +100. Assume that at each unit, the indicator which is given +100 is the

efficiency of working hours of 90%. Then the design team have to rank these levels, by asking

themselves which of the outcomes would make the greatest contribution to the production

department. For example, a unit which has more operators and produces more parts makes a

larger contribution to the overall productivity of the department. The design team decides which

unit is most important, second important, etc. The most important indicator maintains the +100

score, and the remaining indicators are rated relative to this most important indicator in terms of

percentages. The next step is to rescale the contingencies of each indicator by reducing the

effectiveness score of each level of each indicator at each unit by the percentage its own

maximum indicator was reduced. For example, when a unit’s maximum score was reduced from

+100 to +90, the original positive values of that indicator have to be reduced by 10%. The same

rescaling process has to be done for the negative values.

The final step in this phase is drawing the actual contingencies. The first step is to determine the

size of the intervals between the maximum and the minimum points. The more intervals, the more

detailed the contingencies will be, but then (too) many fine judgments are required. The second

step is to place the maximum and minimum values on the contingency as is rated earlier. The

final step is to determine the points on the contingency from the zero point up to the maximum

and from the zero point down to the minimum. Contingencies can be both linear and nonlinear,

depending on the presence of a big step (increase or decrease) in effectiveness.

We will only draw the contingencies for two indicators because are drawn without accordance of

the research company and they do only have the meaning to explain how it could be. The

horizontal axis of the figure is the amount of the indicator which ranges from its worst feasible

level to the best level that is realistically possible. The effectiveness values of the various levels

of the indicator are shown on the vertical axis of the figure. For the example in the figure we have

chosen the efficiency of working hours and quality check passed. The best possible efficiency of

working hours is supposed to be 90% and the worst possible efficiency is supposed to be 75%.


T. de Boer 68

The zero point is determined at 80-85%. The best possible percentage passed inspection is

supposed to be 100% and the worst possible is supposed to be 95%. The zero point is determined

at 97%. The contingencies are shown in figure 9.1.

Figure 9.1: Contingencies for the indicators: “efficiency of working hours” and “quality check passed”.

PUTTING THE SYSTEM TOGETHER The final step is to put the system together by putting the measures into a formal feedback

system. This is done by collecting the indicator data for a given period of time. The time span

over which productivity is measured has to be determined by the design team. The length of the

measurement period depends on the degree of variations in productivity due to the highly varying

orders and demand and the amount and skills of operators in each period.

This final phase involves (Pritchard, 1990):

- developing a feedback report;

- obtaining management approval;

- training of a team to use a computer program to generate the feedback report.

The basic information in the feedback report is the indicator and effectiveness data for the period.

Thus the products with its indicators are listed and also the level of each indicator with the

resulting effectiveness values for the period is given. The total effectiveness for each product is

the sum of the indicators of each product and the overall effectiveness is the sum of the product

effectiveness. See appendix E for an example of the feedback report. The productivity scores are

added to the report after each period, so the personnel are able to compare productivity between

the periods and allow seeing improvements or decrements in productivity. Regular meeting have

to be hold to review the feedback reports. During these meetings, the feedback report would be

reviewed and areas where productivity increased or decreased can be explored. The group has to

focus on the reasons for improvements or decrement in each area. Points of discussion after

providing the feedback reports are (Pritchard, 1990):

- Causes of the low or high scores on the specific products and indicators

- Strategies to follow by the unit/department to maintain or improve the productivity

Production

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

10

20

30

40

50

60

70

80

90

100

110

75 77,5 80 82,5 85 87,5 90

Efficiency of working hours %

Eff

ecti

ven

ess

Quality

-110

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

10

20

30

40

50

60

70

80

90

100

95 97 100

Quality check passed %

Eff

ecti

ven

ess


T. de Boer 69

10 Conclusions and recommendations

We first start to repeat the objective of this research along with the stated research questions. The

objective of the Master Thesis Project was to analyse the applicability of ProMES into a job shop

setting; thus to study whether and in what way ProMES could help to improve productivity in a

job shop production process. The four research questions were:





After studying scientific literature about the characteristics of job shop production processes and

the ProMES methodology we were able to determine which difficulties arise and which

possibilities were available for matching both. We wanted to check the theoretically assumed

problems and the ideas in practise so we assessed the production department of the research

company to be able to check theory and to make statements about the practical possibilities of

applying a ProMES system to a job shop system. By matching the theoretically developed

statements with the results of the practical analysis, we were able to determine how the ProMES

system has to be developed, and how it leads to increases in motivation and the highest gain in

total productivity of the overall job shop floor, thus representing a successful measurement and

enhancement system. Productivity can valid and reliable be measured in the job shop situation of

the research company by applying the ProMES methodology, what also leads to productivity

improvements of the job shop department. Additionally, a ProMES system is designed for the job

shop department of the research company to explain and clarify how the developed ProMES

system and the recommendations have to be applied to a job shop situation. The

recommendations resulted from the research are determined as following:

1. The ProMES system has to be developed by determining common products and indicators for

each unit, contingencies will be drawn for each unit, and the feedback report contains the

overall departmental score and also shows the individual unit contribution to that score.

2. This general feedback report is then build-up out of the unit scores and represents the overall

score of the department on each product and a total departmental productivity score.

3. Remove the interdependency relationships by; proper development of indicators, by detailed

planning and scheduling processes and by the use of a central warehouse.

4. Rescale contingencies so each unit’s productivity can be summed up.

5. The responsibilities, roles and activities have exactly to be appointed and applied to one of

the functional units.

6. Develop an information system for; exchange of information, increase cooperation between

units, generating and registering productivity and decreasing time and effort to maintain the

system.

7. Decrease chances at sub-optimization between units and create a cooperative organization.

8. Enlarge the measurement period to average out the uncontrollable variation in productivity.

9. Restrict the responsibility to tasks that are completely controllable (e.g. do not cover all parts

of the unit’s tasks).


T. de Boer 70

We now shortly looking back on the solutions presented in the study by considering the four

presented ideas. Each of the four ideas are stated as a one-way solution, but can be worked out in

different ways, what creates alternative ideas. We believe that the four ideas we developed in this

research are really encompassing all possible options. Each alternative option will always be a

derivative of the four ideas defined in this study. For example, an option is to apply the ProMES

system at multiple organizational levels, with a top-down approach, as been described by De

Haas and Kleingeld (1999). This option can be interpreted as a derivative from the second idea

presented in this study and is an option for future research.

Another thing we want to look back on is to what extend the productivity department can be

interpreted as a self-working-unit (as we assumed). Then ProMES has to be focused on only the

work within the department without taking the external responsibilities into account. The question

is; “Does the ProMES system optimally improve the productivity of the production department

itself and does also the organization as a whole optimally benefit from the system?” Some

responsibilities of the production department are not included in the work of the units, but there

are some tasks the units are as a department responsible for.. Examples are the coordination with

the sales department and managing the inputs from, and outputs to other departments. We did not

focus on these relationships within this study, because we only focused on the inside of the

department. We analyzed the influence of a job shop structure on the success of the ProMES

system, and not on the relationships between departments. But these relationships have to be

taken into account to fully benefit, as an organisation, from a ProMES system. So we believe that

departmental productivity cannot optimally be improved without taking the responsibilities to

other departments into account. A solution according to Pritchard (1995) might be to measure

both on unit level and on departmental level, thus also to measure how well the department is

working together with other departments. This might be an option for future researches.

Even though we have designed an effective and efficient ProMES system for the research

company, and determined some important recommendations, people have to bear in mind that the

implementation of a ProMES system is also dependent on other factors such as: ProMES is labor-

intensive and takes a considerable amount of time to develop and maintain, both management and

lower level personnel have to trust and accept the system with its side effects, many meetings

have to be rearranged and it has to fit with eventually other performance measurement systems

already used by the organization. The reaction to the ProMES system can be, as described in

paragraph 4.2; acceptance, compliance or rejection. The design team has to take care for that the

system is accepted by all people involved, so the accepted control loop is complete (also over a

longer period of time). The organization can only optimally benefit from the productivity

measurement and enhancement system when the system is accepted.

This research shows that the characteristics of both the job shop production process of the

research company and the ProMES methodology can be matched so productivity can be

measured and a ProMES system can properly be applied. We were able to do this because the

situation of the research company did not lead to the difficulties and problems as were assumed in

literature. Some of the theoretical stated assumptions (e.g. the complex interdependencies

between units) were not valid at the research company, so it was possible to apply ProMES at unit

level, in comparison with the study of Huve (2005). After analyzing scientific literature, we

expected some important difficulties, but a part of these expectations were not be confirmed by

our research company. Thus more companies have to be analyzed to check if the part of the

literature which is not confirmed by our research company, is confirmed by other situations. Then

one able to develop more significant solutions and conclusions about the ability and the way

ProMES has to be implemented in a job shop.


T. de Boer 71

We also analyzed the research company along with scientific literature to define

recommendations. These can generally be applied to other situations to help to increase the

effectiveness and success of ProMES because these are not dependent on this specific situation.

On the other hand, the design of the system is applicable to the research company because of the

specific situation in which the study is conducted.

This research increases the chances at a successful development and implementation of the

ProMES system, but the success is also dependent on factors not considered here. This research

can be considered as a start which has to be further worked out in future studies because there are

some more interesting aspects which are not covered here and are required to be able to give

better and more detailed solutions and recommendations. Some recommendations for areas of

interest for future researches are:

- Research several companies to determine if job shops at these companies do differ from

the situation in this research.

- Actually develop and implement a ProMES system in detail because some unforeseen

problems might show up.

- An area of future research could be to research conditions which increase the trust and

willingness to cooperate in developing the system.

- Developing a ProMES system at both the unit level and the departmental level to take the

meaning of a department to the remainder of an organization into account.

- Another interesting aspect is the area of information systems. A sophisticated information

system has to be developed for optimizing the development and maintainability of the

ProMES system.


T. de Boer 72

11 List of references

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and feedback interventions”. In S. Sonnentag: “Psychological management of individual

performance”, John Wiley & Sons, Ltd, ISBN 0471877263, pp. 229-248;

J.A. Algera and H. van Tuijl, 2004, “Fifteen years of research on ProMES: State of the art in

performance management of work teams”. In J. Wegge and K.H. Schmidt: “Förderung von

Arbeitsmotivation und Gesundheit in Organisationen”, Hogrefe, ISBN 3801717828, pp. 267-277;

J.W.M. Bertrand, 1983, “The effect of workload dependent due-dates on job shop performance”,

Management science, Vol. 29, No. 7, pp. 799-816;

J.W.M. Bertrand, J.C. Wortmann and J. Wijngaard, 1998, “Productiebeheersing en material

management”, 2nd ed., Houten: Educatieve Partners Nederland, ISBN 9011043995;

K.F. Cross and R.L. Lynch, 1988, “The “SMART” way to define and sustain success”, National

productivity review, Vol. 8, Iss. 1, pp. 23-33;

M. de Haas and A. Kleingeld, 1999, “Multilevel design of performance measurements systems:

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