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The Implementation of Operational Excellence Program
at Phoenix Beverages Limited
A research report presented to
in partial fulfilment
of the requirements for the
Masters of Business Administration Degree
by
L.Hugues Rivet
11th December 2009
Supervisor: Dr. Hamieda Parker
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Acknowledgement
I would like to thank my supervisor, Dr. Hamieda Parker for her guidance and support
throughout this research report. Her prompt and valuable feedback at the different stages of
the research has been very helpful to me.
I am also very grateful to my company, Phoenix Beverages Limited for their financial support and
particularly to my team in the Supply Chain department for their contribution in this research report.
Special thanks also goes to my family, my wife Sonia, sons Lucas and Mahé for their ongoing moral
support. Thanks also to my brother Jean Marc for his guidance and to my dad Pierre for helping me
putting everything together.
Plagiarism Statement
1. I know that plagiarism is wrong. Plagiarism is to use another’s work and pretend that it is one’s
own.
2. I have used a recognized convention for citation and referencing. Each significant contribution
and quotation from the works of other people has been attributed, cited and referenced.
3. I certify that this submission is all my own work.
4. I have not allowed and will not allow anyone to copy this research report with the intention of
passing it off as his or her own work.
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Abstract
Operational Excellence (OE) is a program developed by the Coca-Cola Company to improve efficiencies
along their Supply Chain. This Action Research paper has been written on three projects implemented
simultaneously within the first phase of this OE program at Phoenix Beverages Limited (PBL), Mauritius.
These three projects are within a total of nineteen and are focused in the warehouse operations of the
company. The research shows quantitatively how real improvements in efficiencies have been achieved
through the implementation of lean principles and the use of Six Sigma problem solving methodology.
The paper also captures, through a survey with participants in the OE program, how present were the
key success factors needed in the implementation of such an operational management program. The
results highlight the benefits employees and managers experienced in working in teams and the
challenges of implementing the various tools proposed within the Six-Sigma DMAIC problem solving
methodology.
Key words: Operational Excellence, Lean, Six Sigma, Waste, Warehousing
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Table of Contents
Acknowledgement ............................................................................................................................ 2
Plagiarism Statement........................................................................................................................ 2
Abstract............................................................................................................................................ 3
List of figures, table and equation...................................................................................................... 7
1. Introduction .............................................................................................................................. 8
1.1 Research Area and Problem ...........................................................................................................8
1.2 Research Environment...................................................................................................................8
1.2.1 Phoenix Beverages Limited Company ......................................................................................8
1.2.2 OE program .................................................................................................................... 10
1.2.3 OE diagnostic, Opportunities identification and projects selection.................................. 11
1.3 Research Questions and Scope............................................................................................... 14
1.4 Research Assumptions ................................................................................................................. 15
1.5 Research Ethics............................................................................................................................ 15
2. Literature Review .....................................................................................................................17
2.1 Discussion.................................................................................................................................... 17
2.1.1 Lean ...................................................................................................................................... 17
2.1.2 Six Sigma............................................................................................................................... 23
2.1.3 Lean and Six Sigma Integration.............................................................................................. 25
2.1.4 Performance measures: ........................................................................................................ 26
2.1.5 Success factors, challenges and key benefits. ........................................................................ 27
2.2 Critique of the Literature........................................................................................................ 30
2.3 Conclusion ................................................................................................................................... 31
3. Research Methodology.................................................................................................................32
3.1 Research Approach & Strategy..................................................................................................... 32
3.2 Research Design, Data Collection Methods and Research Instruments......................................... 33
3.3 Sampling...................................................................................................................................... 34
3.4 Research Criteria.......................................................................................................................... 35
3.5 Data Analysis Methods ................................................................................................................ 35
3.6 Limitations................................................................................................................................... 36
4. The DMAIC projects and Green Belt Training.................................................................................37
4.1 Project 1 - Optimize Full Pick operations. ..................................................................................... 38
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4.2 Project 2 - Optimize Picking operations. ....................................................................................... 40
4.3 Project 3 - Optimise Sorting operations........................................................................................ 44
5. Two sample T test on the Outcome (Y) indicators..........................................................................53
5.1 Testing Y1p1 : % of pallet staged in Project 1. .............................................................................. 53
5.2 Testing Y1p2 : Picking rate in Project 2. ........................................................................................ 54
5.3 Testing Y2p2 : % loads outside in Project 2................................................................................... 54
5.4 Testing Y1p3 : sorting rate in Project 1. ........................................................................................ 55
6. Survey findings- OE implementation at PBL...................................................................................56
6.1 Section A: Leadership, Management support and commitment: .................................................. 58
6.2 Section B: Communication: .......................................................................................................... 58
6.3 Section C: Group / Team Problem solving: ................................................................................... 58
6.4 Section D: Worker empowerment and involvement:.................................................................... 59
6.5 Section E: Training, Tool and Time: .............................................................................................. 59
6.6 Section F: Key learnings, what went well and what went wrong:.................................................. 60
7. Discussion of Results ....................................................................................................................61
7.1 Results of quantitative part.......................................................................................................... 61
7.2 Results of Survey.......................................................................................................................... 62
7.3 Contribution to the literature....................................................................................................... 62
7.4 Implication for managers ............................................................................................................. 62
8. Conclusion ...................................................................................................................................63
9. Future research............................................................................................................................64
10. References: ................................................................................................................................65
Appendix 1: Value Stream Maps (Full Products and Empties) ............................................................69
Appendix 2: Action research Journal.................................................................................................70
Appendix 3: Online Survey Questionnaire........................................................................................77
Appendix 4: Y indicators...................................................................................................................80
Appendix 5: Answers to open ended questions.................................................................................83
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Glossary of Terms
Term Definition
OE Operational Excellence – Operational excellence is a Coca-Cola strategy to
achieve transformational results using one common language, tool and
processes
PBL Phoenix Beverages Limited- the company under study
JIT Just in Time
TQM Total quality management
AR Action Research - a research methodology where the researcher is also an
active participant of the project being implemented.
VSM Value Stream Map – A map of all the essential actions/steps (both value added
and non-value added) required to bring a product or service to a customer. It
shows material and information flows as a product makes its way through the
value stream.
DMAIC (Define- Measure- Analyse- Improve and Control) Six Sigma structured
methodology for problem solving
SKU Stock Keeping Units
LSS organisations Lean Six Sigma organisations, companies following both lean and Six-Sigma
management systems.
WMS Warehouse Management System
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List of figures, table and equation
Figure 1 - Karlsson Lean Model ........................................................................... 18
Figure 2 - A conceptual Model for improving the efficiency of warehousing operations .....................1
Figure 3 – Old/New process of Full Pick Operations ............................................................................1
Figure 4 – Process flow picking operations ........................................................................................1
Figure 5 - Cause and effect diagram Picking operations ................................................................ 43
Figure 6 - Process / Sub process Map - sorting operations ................................................................ 45
Figure 7 - Sorting process Map ..........................................................................................................1
Figure 8 – Volume by bottle types .................................................................................................1
Figure 9 - Cause and Effect diagram ................................................................................................ 49
Figure 10 - Pre-sorting Index .......................................................................................................... 50
Figure 11 - The Conveyor Table .................................................................................................... 51
Figure 12 - Simplified Process Flow .................................................................................................. 52
Figure 13 - t distribution curve............................................................................................................... 53
Table 1 - Survey results ................................................................................................................ 57
Equation 1- two sample T test with unequal variances .......................................................................... 53
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1. Introduction
1.1 Research Area and Problem
Phoenix Beverages Limited (PBL), a total beverage company in Mauritius, has engaged in early 2009 in
an operation management program of the Coca-Cola Company, called Operational Excellence (OE). This
program has been effectively implemented in various other Coca-Cola locations around the world and
its implementation at PBL, Mauritius, would be the first in the East and Central African division.
This paper will evaluate the implementation of the OE program at PBL with a special emphasis on the
warehousing activities of the company. In a first stage, this explorative research will be conducted on
three projects being implemented simultaneously at PBL’s warehouse. These projects form part of a
total of nineteen projects that have been identified and selected by a team of employees during the
diagnostic phase of the OE program. A second section of the research will evaluate the conditions in
which the OE program in general has been implemented at PBL.
These nineteen projects form only the first phase of the OE program at PBL and other phases will follow
in the future. The results of this research could thus serve as an evaluation of that first phase of the
program and could help in the design of the future ones within this program. It could also be used in the
future implementation of the same program at other Coca-Cola Bottlers around the world.
The projects developed in the warehouse operations all have for aim to reduce the cost of operations.
This initiative falls in line with PBL strategic initiative of driving down cost throughout its supply chain in
order to consolidate its leading position in the beverage market in Mauritius. As the paper was being
written, a new brewery was starting its operations in the Mauritian market.
1.2 Research Environment
1.2.1 Phoenix Beverages Limited Company
The company: PBL is a ‘Total Beverage provider’, by far the biggest in the Mauritian beverage market,
that produces/ brews, sells and distributes beer (99% market share), carbonated soft drinks (65%
market share) and table water (55% market share). The company is also involved in the import and
commercialization of wines mainly from France and South Africa. The company employs over 1100
employees working on four different sites namely the brewery, the soft drink plant, the commercial unit
and the head office. The company is divided into eight departments namely Brewery operations, Soft
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drink operations, Human Resources, Finance and Administration, IT, Technical, Commercial and Supply
Chain.
PBL was incorporated in 2001 after a merger of two companies, MBL (previously the brewery) and PCM
(previously the Coca-Cola plant). PBL is also opening this year a new brewery in Madagascar.
PBL Facilities: The brewery has a brewing capacity of around 550,000 hl p.a and three packaging lines;
two glass returnable lines and one canning line. The majority of production is for the local market but
PBL is developing rapidly its export market, mainly in Reunion Island where its market share has grown
from less than 2% to more than 10% during the last three years. PBL also export beer to Australia, UK,
Indonesia and some countries in Africa.
The soft drink plant (LIMO) produces all Coca-Cola carbonated soft drinks and table water, five
packaging lines, one for returnable glass bottles, two PET Lines, one bottled water line and another one
for water jars. The total capacity of production lines is around 850,000 hlts p.a. PBL also does some
contract manufacturing under license from Coca-Cola for some countries in the region, for instance in
produces coke in glass for Reunion Island and bottled water for Mayotte.
The Commercial Unit (CU): PBL has one small warehouse on each production site. The one on the
brewery site is a bonded warehouse under customs supervision. All products for the local market are
transferred on a daily basis to the Commercial Unit which is on another site. The warehouse of the
Commercial Unit is 10,000 square meters and has a holding capacity of around 4500 pallets equivalent
to some 350,000 cases of drinks. All PBL delivery trucks are dispatched daily from this unique
distribution centre. PBL has a fleet of around 60 delivery vehicles and uses from 10 to 15 further vehicles
from contractors daily depending of the sales volume
PBL also has its Head office which is located on the brewery’s site, its own garage for repair and
maintenance of its vehicle fleet and a workshop for all refrigeration equipment like coolers, water
dispensers, draught beer and carbonated soft drink dispensers.
As stated previously, this research will have a special emphasis on PBL’s warehousing operations. The
warehousing operations at PBL includes the storage and movement of finished goods as from the end of
the production lines until the goods leave the company’s distribution centre for delivery to customers.
Warehousing can be broken into three sub-processes which are: Forwarding; the transfer of goods from
production sites to the Commercial Unit, Storage and Load Preparation for distribution. These
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operations play a crucial role in PBL’s supply chain as logistics and distribution is a major competitive
advantage for the company. PBL benefits from considerable economies of scale in the commercialization
of their products and their portfolio allows the company to provide an attractive commercial offer. The
ordering / planning / preparation and distribution process is a highly synchronized one. All orders
(around 1200 daily) are taken one day prior to delivery, are processed, prepared (picked) and loaded
onto trucks on the same day.
Also critical at PBL is the reverse logistic of empty glass bottles and other returnable packaging
containers like beer kegs, soft drink and CO2 tanks. Over half of PBL’s volume is sold in returnable glass
and the collection of these empty bottles and crates from customers, sorting and return to the
production facilities is an essential and critical operation at PBL’s. The supply of glass worldwide being
under strain and due to its relative small demand in glass, it is a real challenge for PBL to source out the
needed glass bottles to run its business.
1.2.2 OE program
The Coca-Cola Company claims to have the worldwide biggest supply chain. OE is an initiative to ensure
the company becomes also the best supply chain in the world. OE is a Coca-Cola strategy to achieve
transformational results using one common language, tool and processes. It is their umbrella for
numerous improvement initiatives and aims to answer the question of ‘How’ to become green and lean
and develop their high potential talent. OE is basically an adapted toolbox of the best fit from Six Sigma
and lean management for the beverage industry.
OE is defined as the continuous Improvement through a structured and systematic approach, which
improves operating margins of a business by focusing on the elimination of waste and the reduction in
variation through standardized work. Taken from the lean jargon, OE defines waste as; “Those system
elements the customers would rather not pay for”
The OE principles are Value, Value Added Activities, Customer, Waste, Continuous Improvement and
Respect for People. OE uses the acronym ‘DOWNTIME’ to define the 8 types of waste namely: Defects,
Overproduction, Waiting, Not embracing change, Transportation, Inventory, Motion and Excess
production.
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OE starts with a diagnostic exercise which prioritizes opportunities to focus the work on the important
few. The diagnostic is jointly performed by the OE core team and the local leaders to
• Provide a detailed data based analysis of the value stream
• Help the organization to understand their current state and a range of opportunities to progress
along the journey to OE ,and
• Deliver a prioritized and resourced list of projects supporting the business strategy, project
implementation plans, resources and KPI targets and current state of the site based on multi-
dimensional maturity assessment.
Following the diagnostic, there are different waves of project implementation. In each wave, a series of
selected projects are implemented following the Six Sigma Define-Measure-Analyse- Improve- Control
(DMAIC) structured methodology of problem solving. The OE program is designed to be run
continuously in the operations.
1.2.3 OE diagnostic, Opportunities identification and projects selection.
The OE diagnostic phase had as purpose to identify opportunities in order to improve the operations at
all levels at Phoenix Beverages Limited. This exercise was coordinated by a core team of Coca-Cola
experts in the OE program and performed by eight different cross functional teams composed of forty
five PBL employees and managers. Each team was allocated with a specific area of the PBL operation.
The diagnostic phase started with training on the eight kinds of waste and each group was given a
template to fill in the waste identification in their respective area of study.
Each group had to present two days later a list of all the waste identified in their area. The following day,
all participants were trained on Value Stream Mapping (VSM), Value added / Non- Value added analysis
and process mapping. The two VSM’s obtained in the warehouse section are in Appendix 1. These tools
are later used by each team to analyse their operations and identify improvement opportunities that
could bring a positive financial impact to the company.
All opportunities identified were presented in a given format and the potential financial impact was
calculated with the help of company’s finance department. At the end of the OE diagnostic phase which
ran for two weeks, each team presented their opportunities to the management of the company, a total
of over 60 opportunities were identified by the eight teams. The OE steering committee, composed of
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senior managers and Coca-Cola representative, sat two days later to select the nineteen projects from
the list to be implemented in OE phase one. Within these, three were in the warehouse section namely;
‘Optimise full-pick operations’, ‘Optimise picking operations’ and ‘Optimise sorting operations’.
These opportunities were developed around a common objective, the ‘motto’ of department; “Move
less - Move smart”. For each project, one or more outcome indicator(s) would be tracked over time to
measure the efficiency of the process. The outcome indicators would be in the format ‘Yxpn’ where x is
the indicator number (one project could have more than two outcome indicators) and ‘pn’ represents
the project number. For instance Y1p1 would stand for the 1st
indicator of project 1.
Project 1 (p1): Optimise full-pick operations:
As loads are prepared in the warehouse for delivery, the pallets are stacked in a ‘staging’ location which
is inside the warehouse just next to the loading bays where delivery vehicles are loaded. Around 70% of
these prepared pallets are mixed pallets containing two or more Stock Keeping Units (SKUs). These
mixed pallets are prepared by a team of pickers who themselves move their completed pallets to the
staging lanes. The other 30% of pallets are full pallets, only one SKU. These are taken from the storage
location to the staging location by forklift. The truck load, which is normally composed of eight to ten
pallets, ‘mixed’ or ‘full’ is then checked and later loaded on the delivery vehicle as the latter enters the
warehouse. During the diagnostic phase, the team identified that this double handling of the full pallets
(from storage to staging and from staging to truck) could be eliminated. There is a possibility for these
full pallets to be transferred from the storage location directly on the truck, just in time when the latter
enters the warehouse. This project would save considerable forklift movement (on average 300 and 400
pallets daily) and will also imply a reduction in the amount of staging lanes needed (estimated to around
19%).
The outcome indicator for this project is Y1p1: ‘% of full pallet staged’ and the lower would be that
indicator, the more efficient would be the process.
Project 2 (p2): Optimise picking operations:
Picking operations, which is the preparation of the mixed pallets (two or more SKUs), starts daily at
13:00 and finishes around 22:00. A single team of 20 pickers works at PBL’s warehouse. As orders from
clients are received the distribution planning is done and loads details are sent to the warehouse. The
picking documents are then printed and given out to pickers for pallet preparation. It was observed
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during the diagnostic exercise that there was a high amount of idle time for these pickers as they were
working faster than the upstream processes (order entry and distribution planning). The documents
were received in big batches and once a batch was received, there was a rush in the picking area
creating congestion with 20 pickers working simultaneously. Several products are damaged during that
operation and must be repacked. The forklift responsible for the replenishment of the pick faces could
also not follow the pickers’ pace.
Another problem noted was the lack of staging lanes inside the warehouse. Some of the loads had to be
staged outside the warehouse involving a lot of extra transportation. The same pallets had to be later
brought back inside the warehouse for loading the trucks. The quality of products being stored outside is
also affected by being exposed to direct sunlight and rain. Among the loads being prepared for the next
day’s delivery, some would be leaving the warehouse early the next morning but others would only be
leaving the next day in the afternoon during the second trip. The opportunity identified was to reduce
idle time and staging of loads outside the warehouse. This would create a picking operation that would
work much more in a flow, rather than in large batches.
Two outcome indicators were selected for this project, namely; Y1p2: Picking rate (in Cases per hour)
and Y2p2: % of loads being staged outside warehouse. A higher Y1p2 and lower Y2p2 would indicate a
more efficient picking process.
Project 3 (p3): Optimise Sorting Operations:
As stated before, half of PBL’s sales are done in returnable glass bottles. PBL uses 19 different types of
bottles. As the empty bottles are returned to the company, the different bottles must be sorted at the
warehouse before being sent back to the two different production sites. The sorting of these empties is
very time, labour and space intensive as it is a completely manual operation. All unsorted pallets are
unloaded from the delivery vehicles as they enter the warehouse yard and placed in the sorting area. A
group of workers, called sorters, sort these bottles; put them in the appropriate cases which are then
palletised. The pallets are later taken off the sorting area and brought to a staging location before being
sent to production plants on trailers. The diagnostic team identified several opportunities in
restructuring the sorting process that could lead to considerable gain in efficiencies and be linked to a
reduction of the costs involved in the process.
The outcome indicator for this project is Y1p3: Sorting rate calculated in bottles per min
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1.3 Research Questions and Scope
The central question of this research will be to test the effectiveness of the lean and Six Sigma tools and
methodology used in the OE Program in the improvement of the warehouse operations at PBL. The
question is formulated as such:
Can the lean and Six Sigma tools and methodology used in the Operational Excellence Program (OE) at
PBL bring a significant improvement in its warehouse operations?
The hypothesis that will thus be tested throughout the research will thus be:
The use of lean and Six Sigma tools and methodology can significantly improve PBL’s warehouse
operations.
The outcome indicators as described in the previous section will be tracked down over the time of the
project. Two data sets of these outcome indicators will be taken, one before the ‘improve’ stage of the
project and one after. The mean value and standard deviation of the two data sets will then be
compared to determine if the indicators have significantly improved.
In the second part of the research, the participants in the OE program will be surveyed to evaluate the
conditions created at PBL for the OE program to be successful. A literature review will first be done on
the success factors necessary for a successful implementation of an Operational Management initiative
like the one implemented at PBL. From this review, a set of variables will be extracted and used as a
base for the survey questionnaire design. This section of the research will also capture the main
challenges and the key learning’s of the employees and management during the implementation
process.
The second main question of the research is thus:
At what level were the key success factors, necessary for a successful implementation, present during
the initial phase of the OE program at PBL?
Furthermore, two sub questions that will be answered in that section of the research report are:
What are the challenges faced by PBL in implementing the OE program at PBL?
What are the key learning points in the implementing the OE program at PBL?
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This research can have a significance importance for the future implementation stages of the
programme at PBL. There will also be the possibility for the report to share with other bottlers around
the world, thus providing them a good insight of the OE programme in action.
The scope of the first, quantitative section of the research is limited to the three warehousing projects.
On the other hand, for the survey section of the research covers the totality (19) of the projects selected
for the first phase of OE at PBL.
1.4 Research Assumptions
The first phase of implementation of the project was scheduled to run between June and September
2009. The fact that an external consultant had been contracted to support PBL in this implementation
also reinforced these deadlines. There was however a risk of the timing being moved for a major reason
that could compromise the research but fortunately the OE phase one was successfully closed at the
end of September.
The human factor and reluctance to change from employees constituted the biggest risk of the program.
For instance, a high percentage (around 30%) of the warehouse employee’s remuneration is in terms of
overtime. Improving efficiencies in operations aim to reduce cost via reducing these overtime payments.
During the implementation of these projects, considerable care would be given to the way the benefits
of better efficiency are exposed to the labour force. Fortunately, the warehouse functions with several
casual employees that are employed during several months in the year. Improvement in the processes
could be translated into employing less casual labour while insignificantly affecting full time employees.
Furthermore, as the company is expanding and the workforce is ageing PBL might not need to replace
them with the improvement in operations. A series of communication meetings has been organised with
workers in order to get their buy-in for the project implementation. The principle that has been agreed
in the company is that workers will be reallocated should a process be improved and require fewer
workers.
1.5 Research Ethics
The research subject was approved by both PBL’s Chief Executive Officer of the company and a
representative of the OE program coordinator from the Coca-Cola Company. It was unfortunately not
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possible to obtain any documentation from the Coca-Cola corporate office on past OE implementations
for confidentiality reasons.
As the OE program has been developed by Coca-Cola for the company to gain a competitive edge on the
competitors, considerable care should be given to the confidentiality aspect of this research paper. The
publication of the research paper to other bottlers will still have to be considered with the CEO after the
final write up.
Considerable care was also taken during the progress of the projects for all participants to be aware of
my double role of researcher and team leader. This was stressed in all meetings.
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2. Literature Review
This section will review the literature on lean and Six Sigma and their application in various operations
from different industries. In the lean section, special emphasis will be put on waste reduction and value
stream mapping as these were the key tools used throughout the development of the OE program. A
review of using these tools in warehousing operations is also done in that section. Both lean and Six
Sigma management systems are discussed separately first before a brief review of their
complementarities and how they can be integrated together in what is called lean sigma, or lean Six
Sigma management system. There is also a review of the literature on the various performance
measures used in operations management. These are particularly important in determining what needs
to be measured and what would be the best indicators to be used for each of the projects under study.
For the second part of the study, a review of literature is done on the important factors and challenges
faced by companies when implementing such operation management initiatives. The objective of this
section is to identify a set of variables from the literature that will be measured at PBL during the
implementation of OE. From these variables, a series of questions will be derived to set up the survey.
2.1 Discussion
2.1.1 Lean
The concept of lean management can be traced back to the Toyota production system (TPS), a
manufacturing philosophy pioneered by the Japanese engineers Taiichi Ohna and Shigeo Shingo (Inman,
1999). According to Hines et al (2004) lean is constantly evolving and its definition would only be a ‘still’
image of a ‘moving target’ that could be valid only at certain point in time. Petterson (2009) suggests
that this could be the explanation for the apparent differences in the definition of lean by various
authors on the subject in the literature and that these differences could be problematic on a practical
level when an organisation aims to implement the concept. Petterson (2009) reviewed available
literature on lean and compared this management concept with TQM. He comes to the conclusion that
at the philosophical level, both lean and TQM have many ideas in common, particularly concerning
continuous improvement and the system perspective approach. However he identified significant
differences between the two concepts at operational level and in their fundamental values, especially
regarding humanistic values. Petterson (2009) did not support the conclusion from Shah and Ward
(2003) that TQM and other bundles are part of lean. Karlsson et al (1996), also identified this lack of
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precise definition of what lean production is and developed a model that operationalises the different
principles in lean production, with a focus on the manufacturing part of the company. The development
of this model was developed from available theory on lean principles and is presented in Fig 1 below:
Figure 1 - Karlsson Lean Model source: Karlsson et al (1996)
Karlsson et al (1996) stressed the point that lean should be seen as a direction rather than as a state to
be reached after a certain time. They therefore argue that the focus lies in the change of the
determinants and not in their actual value. Similarly, Hayes et al (1994) proposed that we need to
measure progress made in an effort to become lean. They put much emphasis on the word ‘progress’
since lean can be seen as an intended direction and not as a state or as an answer to a specific problem.
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Lee-Mortimer (2006), in his study on a UK-based electronic product manufacturing operation
demonstrates the high benefits brought by lean. On effect the plant is helped to move from a batch and
queue production system to creating flow through the whole plant reducing WIP and lead time and
improving productivity, without compromising previous gains from the highly effective continuous
improvement program. He explains how these changes have been achieved by the creation of work cells
and the challenges faced by the necessity to break these ‘islands of excellence’ core processes in order
to achieve this transition from batch and queue to a flow production system.
Gunasekaran et al (1999) proposed a conceptual model to improve the efficiency of warehousing
operations. Their model is discussed from two perspectives, ‘Just-in-time’ (JIT) and Total Quality
Management (TQM). While JIT looks at reducing inventory levels and buffers, creating demand pull and
dealing with suppliers’ reliability, TQM focuses on the long term commitment against war on waste,
continuous improvement, training and ergonomics. Their model is graphically represented in figure 2
below:
Gunasekaran et al (1999) state that the proper approach to JIT implies co-operation between suppliers /
clients to make sure inventory is not just transferred from one location to another, but that it is rather
minimised throughout the supply chain. The demand pull system definition of JIT implies that planning
begins with the final stage and works backwards through every process up to the suppliers of primary
Figure 2 - A conceptual Model for improving the efficiency of warehousing operations Source : Gunsekaran et al , 1999
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raw material. For JIT to function, essential criteria are necessary like accurate forecasting, proper
communication and trust among partners, efficient communication channels, long term contracts with
suppliers for them to ‘play the game’ and removing non-value activities throughout the supply chain
(Gunasekaran et al, 1999).
TQM is a management approach centred on quality which needs the involvement of all organisation
members and aiming at long term success through customer satisfaction and benefits to all stakeholders
of the organisation (Gunasekaran et al, 1999). They also found that the processing of information plays a
vital role in warehousing activities and that the information flow is often separated from the physical
flow, resulting in buffers and delay in the process. They thus recommend a greater emphasis on the
information flow. While they agree that in general JIT bring considerable benefits in the running of a
warehouse, there are some constraints as this policy requires more transportation, thus traffic and
other associated problems may arise when safety stock is not held for certain products (Gunasekaran et
al, 1999).
Machinery Inc, a leading European manufacturer of food processing machines and equipment failed in
their first attempt to introduce lean management in 1997 (Sherrer-Rathje et al, 2009). They attributed
this failure to the lack of senior management commitment due to the bottom-up approach used in that
implementation. In 2006 however, a second attempt at introducing lean was initiated in order to match
demand and reduce production costs. This time Machinery Inc chose to do a pilot implementation in
one business unit only where all efforts had been concentrated. The project was then ‘sold’ to the rest
of the company when the implementation in this business unit had proved itself worthwhile.
Lean management has been successful in several industries apart from just manufacturing. Several
successful implementations of lean practices exist as for instance the OLA project, a reengineering
action based on lean thinking principles for hospital care, within six public hospitals in Florence, Italy
(Gemmi et al, 2009). In this project, when applying lean principles to reengineer their processes, they
achieved up to 10% reduction of average length of stay in surgery, up to 18% reduction in overall
preparatory permanence in hospital and up to 85% reduction of total out-of-ward days for surgery.
Waste
Waste (‘muda’ in Japanese) as defined by Fujio Cho, former Toyota President is “anything other than the
minimum amount of equipment, materials, parts, and workers (working time) which are absolutely
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essential to production” (Jacobs and Chase, 2008, p226). In shorter terms, it can be defined as any
activity that does not create value or for which the customer will not be prepared to pay for.
Taiichi Ohno, late Toyota executive categorized waste into seven types, namely overproduction, waiting,
transportation, inventory, processing, motion and defects. Womack and Jones (1991) argue that waste
is everywhere, visible to even the casual observer on an average day in an average organisation. They
themselves added an eighth category of waste which is the design of goods and services which do not
meet the needs of customers. They defined the lean philosophy as the ‘antidote’ to Muda (Womack and
Jones, 1997).
According to Slack et al (2006), one of the most significant parts of the lean philosophy is its focus on the
elimination of all forms of waste. In their model, they propose four methods of eliminating waste;
streamlined flow, match demand exactly, increase process flexibility and reduce the effects of
variability. A series of techniques and tools like ‘Pull controls’ or ‘Kanbans cards’ are used as support for
waste elimination.
Emiliani (1998) argues that the tracking of all form of waste is a continuous, never-ending process and
that it is regarded as one of the few things that non-production workers can do to add value to
products. In his paper ‘Lean Behaviour’ (1998), Emiliani interestingly defined another type of waste he
called ‘behavioural waste’ which refers to the tremendous amount of waste that normally exists in intra-
and interpersonal relationships. He explains the destructive effect that ‘fat behaviours’ (as opposed to
lean behaviours) can have on lean initiatives in the organization and the power of communication in the
creation of value.
Emiliani (1998) explains that batch and queue production methods are the intuitive way people think,
seeking for economical lot sizes, minimizing set up and change over times. These production methods
drive along in their process a large amount of waste. Similarly, he adds that ‘fat behaviours’ are also
intuitive and almost invisible to the people in the organization because their own mindset constitutes
the base of this mental model.
Karlsson et al (1996) argue that inventory; apart from being itself wasteful, also hides other problems,
preventing their solution. He adds that inventory should not be removed as such but it is rather the
reasons for the existence of inventory that should be removed.
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Value Stream Mapping
Value stream mapping (VSM) is a tool created by the lean production movement for redesigning the
productive system (Lasa et al, 2008). It has for purpose to help researchers or practitioners to identify
waste in individual value streams and find solutions for the elimination of these wastes (Hines and Nick,
1997). While VSM is mainly focused on the analysis and improvement of manufacturing environments
with disconnected flow lines (Rother and Shook, 1998), it can also be used in non manufacturing
operations and services.
Rother and Shook (1998) identified five phases in the use of VSM, namely; the selection of a product
family, drawing the current state mapping, the future state mapping, defining the working plan and
achieving the working plan. Lean thinkers provide some guidelines to assist in the drawing of the future
state map (Rother and Shook, 1998; Marchwinski and Shook, 2003). Some of these are:
• Production rate must be dictated by demand, ‘Takt’ time dictates that rate
• There should be continuous flow in-between the different work centres where possible, or else
to employ pull systems should be used.
• Only one process should command the production of the different parts, called the pacemaker
process. This process scheduling will deal with the maximization of production levelling on mix
and volume.
Lasa et al (2008), used a case study to assess the effectiveness of the VSM technique for the redesigning
of productive systems. They found the technique highly effective for the described purpose and
achieved a reduction in the lead time for the production of plastic parts being studied, from 26 to 22
days, within the first six months following the VSM exercise.
Hines et al (1998) pointed out several limitations of the value stream mapping process and introduce
value stream management as “a new strategic and operational approach to the data capture, analysis,
planning and implementation of effective change within the core cross–functional or cross-company
processes required to achieve a truly lean enterprise”(Hines et al, 1998, p 25). The authors claim that
Value Stream Management also includes various education and policy deployment stages which provide
a far better framework for pursuing company or supply chain development.
Luyster and Shuker (2002) emphasized that value stream management is about putting people first,
reducing the speed and effort required of workers and not making people work faster or harder. They
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identified the following four critical behaviours when performing value stream management; making a
true commitment, thoroughly understanding customer demands, accurately illustrating the current
position, and effective communication.
Arnheiter et al, (2005) identified a series of key misconceptions around lean management, the first of
which is that lean is associated with laying off employees, while the term ‘lean’ itself, especially when
associated with the term ‘mean’, might show that lean companies should, according to Emiliani (2001)
make every effort to re-assign and re-train employees in value-adding activities. Another misconception
is that lean is applicable only in manufacturing and to Japan only. Literature shows very successful lean
implementation outside Japan and in non-manufacturing industry. A last misconception discussed by
Arnheiter et al is that lean is applicable to certain specific environments only where the lot size of one
could be attained.
2.1.2 Six Sigma
“Six Sigma was founded by Motorola Corporation and subsequently adopted by many US companies,
including GE and Allied Signal” (Arnheiter et al, 2005, p 5). Many argue that Six Sigma is a repackage of
old quality management practices, principles and tools / techniques (Clifford, 2001: McManus, 1999). Six
Sigma takes from TQM the concept that everyone in the organisation is responsible for quality, the focus
on customer satisfaction and the significant investment in education and training. (Arnheiter et al,
2005). On the other hand, several other researchers recognise the Six Sigma approach as an emergent
structure for quality management that helps organisations to control process improvement activities
more rigorously (Schroeder et al, 2008). Schroeder et al (2008) recognised several distinctive features of
Six Sigma from traditional TQM approaches, as follows:
• Unique focus on financial and business results
• A distinctive use of structured methods for process improvement
• Use of specific metrics is new with Six Sigma
• Use of significant number of full time specialists inside the organisation
In their study to define Six Sigma and from the literature, Schroeder et al (2008) suggest and retain the
following four relevant constructs or element of their Six Sigma definition:
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• Parallel-meso structure: Like quality cycles as an example of parallel structure (e,g., Adler et al,
1999; Lawler, 1996), The Six Sigma approach creates in parallel to the organisation hierarchy,
another structure for the management of projects comprising of champions, black and green
belts. This structure is defined as a parallel-meso structure (Schroeder et al, 2008), integrating
both the micro and macro levels of analysis. This contrast with the traditional quality circle
structure where members of these teams have little authority and power to implement their
ideas and many suggestions are not implemented Lawler (1996). “Various mechanisms in Six
Sigma, such as strategic project selection and leadership engagement help achieve multilevel
integration” (Schroeder et al, 2008, p 540).
• Improvement specialists: many Six Sigma organisations employ full time ‘Black Belts’ whose
main responsibilities are to act as instructors and to provide technical assistance and mentoring
(Slater, 1999). The parallel-meso structure as defined above is also supported by green belts
who are employees that receive a basic training on Six Sigma methodology and tools. The black
belt normally reports to the project sponsor, known as the champion, who ensures the
availability of critical resources to the team.
• Structured method: Six Sigma uses a structured method which is patterned after the PDCA cycle
(Shewhart, 1931, 1939), called DMAIC (Define, Measure, Analyse. Improve and Control). This
structured method fosters emphasis on going to the root cause of the problem and allows the
use of a common methodology and framework for problem solving throughout the organisation
• Performance metrics: Performance metrics used in the Six Sigma methodology is twofold, first in
the customer-oriented metrics and secondly the financial metrics. Understanding the true
customer need is at the root of Six Sigma. “A fundamental aspect of Six Sigma methodology is
identification of critical–to-customer (CTQ) characteristics that are vital to customer
satisfaction” (Evans and Lindsay, 2005, p. 184). According to Smith et al (2002), a financial
analyst on a Six Sigma project will help to translate the performance of the team into dollars and
cents.
Arnheiter et al, (2005) discussed some misconceptions that are traditionally associated with Six Sigma,
the first being that the Six Sigma methodology is ‘the new flavour of the month’ (Arnheiter et al, 2005, p
12). Other misconceptions is that the absolute value of 3.4 defects per million opportunities is an
absolute goal and that Six-Sigma is a quality focus program only whereas it relates in reality to the entire
customer value equation.
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2.1.3 Lean and Six Sigma Integration
With disparate roots but similar goals, Lean and Six Sigma have both proven to be effective on their
own. Arnheiter et al, (2005) explain that companies embracing either of these management systems
face after some time diminishing returns. They can also experience some possible gains for lean
companies to apply Six Sigma systems and vice versa. Sheridan (2000) used the term Lean Sigma to
describe a management system that combines these two systems. Arnheiter et al (2005) use the term
Lean Six Sigma (LSS) organisation to describe an entity that integrates the two systems.
Arnheiter et al (2005) proposed that lean organizations should make use of more data in decision
making and use of methodologies that promote a more scientific approach to quality. Similarly, they
propose that Six Sigma organizations should include training in lean management methods that
eliminates all kinds of waste, reducing set up times and mapping the value stream.
Arnheiter et al (2005) suggested that Lean Six Sigma organizations would capitalize on the strengths of
both lean and Six Sigma management systems by including the three primary tenets of lean
management:
• Incorporate the philosophy that aims at maximizing the value added content of all operations
• Constantly evaluate incentive systems in place
• Incorporate a management decision-making process that bases every decision on its relative
impact on the customer
And the three primary ones from Six Sigma which are:
• Provide data driven methodologies in all decision making
• Promote methodologies that strive to minimize variation of quality characteristics
• Design and implement a companywide and structured education and training regimen.
Dahlgaard et al (2006) showed from their perspective that the lean production philosophy and the Six
Sigma steps are essentially the same and that both have developed from the same root, the Japanese
TQM practices. They argue that the concepts and tools of lean production and Six Sigma quality should
not be seen as alternatives to TQM but rather as a collection of concepts and tools which support the
overall principles and aims of TQM.
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2.1.4 Performance measures:
Taj (2008) argues that to stay competitive, enterprises should try to make their manufacturing facilities
more efficient and lean. He adds that traditionally, managers have relied heavily on accounting metrics
to determine efficiency but those metrics alone are inadequate for managing a lean manufacturing
operation. A profit and loss statement for instance is a result of a long chain of decisions that may go
back for years or even decades. Managing a lean factory requires key information that reflects what is
happening upstream in these chains of events.
Ahlstrom and Karlsson (1996) state that it is not always easy to justify the implementation of lean
production program due to some decrease in productivity indicators calculated from traditional
management accounting systems. They claim that there is a need for some intermediate indicators to
assess the changes taking place and the effort to introduce lean production. Sanchez et al (2001),
following the work of Ahlstrom and Karlsson (1996) introduced a check list of 36 ‘lean indicators’ broken
into six different indicator groups and tested their use a sample of manufacturing firms. Their study
concludes that sixty percent of the lean indicators were used by more than half of the surveyed
companies and that 17 percent were used by more than 75 percent of the companies. As expected, they
found that large companies significantly use more of these indicators than small and medium ones.
Gunasekaran et al (2001) found a need to study the measures and metrics used in supply chain
management because of a lack of balanced approach between financial and non-financial performance
measures. They also identified a lack of distinction between metrics at strategic, tactical and operational
levels. According to Kaplan and Norton, while some managers concentrate on financial measures, others
concentrate on operational measures and these inequalities does not lead to metrics that can represent
a clear picture of the organisation performance.
Maskell (1991) suggested that while financial measures are important for strategic decisions and
external reporting, non-financial operational measures are often more suitable for the day to day
control of the operations. Gunasekan et al also warned about the important choice to be made when
choosing the right number of metrics to be used and state that performance measurement can be
better addressed using a good few metrics rather than a large number of them.
Cavinato (1992) state that since logistics cut across functional boundaries, one should be careful during
decision making as the cost in one area can have an impact in other areas. When measuring the
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performance of logistics operations using financial measures, one should be careful to consider the cost
implication in all areas and use a trade-off based on a logistic-oriented cost accounting system that will
identify the cost associated with each unique activity as well as the influence on the other linked
activities (Gunasekaran et al, 2001). Lee and Billington (1992) argue that for effective performance
measurement, supply chain metrics must be linked to customer satisfaction. Gunasekaran et al (2001)
proposed to measure customer satisfaction and service by using as metrics flexibility, customer query
time and the post transaction measures of customer service.
In their study on supply chain performance metrics, Gunasekaran et al (2001) concluded that there is a
shift from the traditional cost accounting methods. New techniques take into account the cost of
individual activities in the supply chain and the impact of these activities on other functions such as
customer service, asset utilisation, productivity and quality.
Deming (1986, 1994) and others have stressed on the importance of understanding customers’ present
and future demands when designing products and services. Evans and Lindsay (2005) claim that a
fundamental aspect of Six Sigma methodology is the identification of the critical-to-quality (CTQ)
characteristics that are vital to customer satisfaction. Linderman et al (2003) support that argument by
adding that customer requirements help establishes project improvement goals and direct improvement
efforts of Six Sigma teams. According to Smith (2002), the use of financial metrics to quantify the
process improvement of the Six Sigma projects is also essential throughout the project different phases
and also upon completion of the project, for up to a year to make sure the benefits are realised.
2.1.5 Success factors, challenges and key benefits.
For many years, the main emphasis in the strategic manufacturing literature has been on the
formulation side of strategies (Grundy, 1998; Al-Ghamdi, 1998). The issue of implementation has
received less attention although the implementation of strategic initiatives has frequently been
considered to be the graveyard of strategy (Grundy, 1998). Grundy (1998) points out that strategic
management should move from a 90:10 concern with strategy formulation relative to implementation
to at least a 50:50 concern with each. Otherwise, no matter how good the strategic decisions are,
companies would not benefit from them (Al-Ghamdi, 1998). Beer et al (1990) also reinforce that idea by
attributing much of the shortcomings in the strategy area to failures in the implementation process
rather than in the formulation of the strategy itself. Van Der Merwe (2002) argued that strategies do not
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fail when they are being analysed or when the objectives are being set but during implementation and,
more particularly, due to the lack of proper project management.
Minarro- Viseras et al (2005) studied the various Key Success Factors (KSF) essential for the proper
implementation of strategic manufacturing initiatives. They found that the highest number of KSFs was
found under the project management element of the people category. The results of their study
demonstrate the importance of recruiting the right individual who is able to positively influence the
ultimate success of the SMI implementation project (Minarro- Viseras et al; 2005). Their results also
show that in the manufacturing environment, the successful implementation of the project require full,
continuous and visible support from the senior management. Senior management must be behind the
project, the project manager and the project team and everyone in the organization must be aware of
that (Minarro- Viseras et al; 2005). Another key finding in their studies is that the implementation
success comes more critically from the human or people side of project management as opposed to
organization and systems related factors.
Achanga et al (2006) identified leadership and management as the most critical success factor for lean
implementation within SMEs. They state that strong leadership and management allows a vision and
strategy while permitting a flexible organizational structure to facilitate the change process. Leadership
and management support is also critical for the provision of resources, foster the learning environment
and permits for the company to acquire new ideas and technologies. Achanga et al (2006) also identified
other critical success factors namely the financial capabilities, skills and expertise and organizational
culture.
Antony and Banuelas (2002) studied the key ingredients for the effective implementation of Six Sigma
programs. They identified a total of eleven critical success factors from the literature and went to see
how the organizations in the UK prioritise these key ingredients. They found the top three most
important ingredients to be respectively; managing involvement and commitment, understanding the
Six Sigma methodology and linking the program to a business strategy.
Bhasin et al (2006) examined the underlying reasons surrounding the low rates of successful
implementation of lean initiatives. They found that for a successful implementation of lean initiatives,
not only it is necessary to implement most of the technical tools but that an organisation’s culture needs
transforming too. They advocate that lean has a major strategic significance through its implementation
process and that viewing lean as a set of tactics rather than embracing it as a philosophy is highly
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responsible for the number of failures in lean initiatives. Bhasin et al (2006) stressed that whilst lean is
concerned with the reduction of waste at all levels, it is also about bringing change in the corporate
culture. They identified a list of cultural requirements necessary for successful lean implementation,
these being:
• Ensure that decisions are taken at lowest level in organisation
• Have a clear vision of the desired state
• Ensure that that there is a strategy of change whereby the organisation communicates how the
goals will be achieved.
• Assign responsibilities within a pilot programme and ultimately within whole organisation
• Develop supplier relationship based on mutual trust and commitment
• Nurture a learning environment
• Systematically and continuously focus on the customer
• Promote lean leadership at all levels observed by a number of lean metrics at all levels
• Maintain the challenge of existing processes
• Maximise stability in a changing environment.
• Assess the fraction of an organisation’s employees operating under lean conditions
• Observe the proportion of organisation’s departments pursuing lean
• Lean requires a long term commitment.
Boyer and Sovilla (2003) argue that top management should not only demonstrate commitment and
leadership but that they must also work to create interest in the implementation and ensure changes
are communicated to everyone in the organisation. A lack of investment from their part may also affect
the success of the project in a less visible ways as employees will experience discouragement if they do
not perceive top management’s total dedication’s in the implementation of the initiative (Boyer and
Sovilla, 2003).
Worley and Doolen (2006) studied the role of communication and management support in a lean
manufacturing implementation of an electronics manufacturing company in the northwestern USA. They
found that failures attributed to management support shared some common characteristics, namely:
• Executive management must provide more information on lean and the reason for
implementing
• More resources must be allocated to the lean initiative in terms of time and material
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• Employees need to be able to see the progress of results
• Management must create a plan so that the entire organisation moves towards a common goal.
They also found that while lean initiative was initially implemented as a customer’s request, more
success was realised at an employee’s perspective by creating better relationships between
management and employees on the manufacturing floor.
Worley and Doolen (2006) in the same study also found evidence that lean implementation had a
positive impact on the communication lines between management and employees. It was further
expected that this would extend to inter-departmental communication with the progress in the lean
implementation.
Boyer (1996) tested and confirmed the positive relationship between a company’s commitment to lean
production and its commitment to supporting investment in infrastructure. This research was done with
companies in the metalworking industry. He studied four infrastructural investments namely; quality
leadership, the use of small groups or team for problem solving, training and worker empowerment.
Dahlgaard et al (2006), found that in lean and Six Sigma implementation, there tends to be a large focus
on the tools and techniques used and at the same time too little focus on how to build the right
company culture, where basic human needs are understood and respected.
2.2 Critique of the Literature
The literature on Lean and Six Sigma as reviewed in the previous section is mainly based on surveys
capturing the perceptions about the effectiveness of these methods when applied in companies. The
literature on the subject is mainly focused on manufacturing operations. Literature on operations
management in warehousing operations is very rare. Apart from the conceptual model developed by
Gunasekaran et al (1999), the researcher during the review of the literature did not found any other
study in that specific field. This research aims to bring a very practical and concrete study of the
implementation of an operational management program, with hard figures to breach that gap.
Warehousing is by its nature a ‘non-value added activity’ and in the extreme case of Just-in-time should
be totally eliminated. The implementation of lean principles and Six Sigma methodology in a
warehousing operation is interesting as there is a big scope for cost reduction.
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2.3 Conclusion
Throughout the literature review, it is acknowledged that Lean and Six Sigma systems used separately or
together can bring improvement to any operation. These methodologies have to be adapted to the
business environment and their success relies heavily on the philosophy behind the systems and the
capacity of the organisation to adapt its culture to fit those methods. We saw that implementation of
Lean and Six Sigma is a ‘way of working’ rather than a project with a defined scope. These management
systems are described as journeys rather than destinations and that the absolute target should be set
with respect to the customer. The application of Lean and Six Sigma goes beyond manufacturing and the
principles and tools are being applied more and more in the service industry. The principles of Lean and
Six Sigma will be used in the research for the design and implementation of the different projects
through the action research methodology.
The importance of performance measures to track the progress of Lean and Six Sigma projects and the
importance of both the financial and non financial performance measures were also discussed. We must
be careful about the use of traditional performance measures as these could indicate some drop in
productivity when implementing lean initiatives, hence the importance of intermediate indicators. The
literature review allows an insight in determining the performance measures that will be used to track
down the progress of the projects being implemented and ultimately determine if these projects have
been successful or not.
In the last part of that section, , through a review of the critical success factors and challenges of
implementing lean and Six Sigma initiatives in the literature, we have identified a list of variables which
will be used in the development of the questionnaire to be used for the survey section of the research.
The variables identified are: quality leadership and management support and commitment,
communication, group/team problem solving, worker empowerment, training tools and time.
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3. Research Methodology
3.1 Research Approach & Strategy
The research will first use a deductive research approach to test the effectiveness of applying lean and
Six Sigma concepts in the warehouse operations of Phoenix Beverages Limited. In the first part of the
research, a quantitative strategy will be used to test the hypothesis. As outlined in the first section of
this paper, the comparison of the outcome indicators prior and post project implementation will aim at
determining the progress, if any, realised during the course of the project.
The second part of the research will use a more inductive approach using a survey approach to evaluate
the presence of success factors at PBL during the OE program. This section will also aim at capturing the
challenges and key learning points experienced by PBL’s employees and management during the
program. The main target of this section is to come out with a set of recommendations that could be
useful for the future phases of implementation of this program and / or the implementation on other
sites.
Westbrook (1994) says that while POM (Production and Operation Management) research has been
traditionally based on modelling techniques, there is a need to do research which will be of practical
value to managers and that will be integrated instead of being focused on sub-system techniques. This
raised the question of research method in this particular field. He further adds that since the POM field
is an area in need of a broader conceptual basis, the theory-building potential of action research should
make it a major method in the future.
An ‘Action Research’ Methodology will be used in the writing of this paper. Goughlan and Coghlan
(2002, p 220) defined Action Research (AR) as “an approach to research that both aims at taking action
and creating knowledge or theory about that action”. They claim that the core characteristic of Action
research is that it is a participative and integrative method where the researcher himself is both an
observer and a participant in the specific project he is researching. They added that Action Research is
about action ‘in’ research rather that action ‘on’ research, that it is concurrent with action and
participative. In the case of this paper, the researcher is an active participant in the projects under study
and a member of the senior management of the company. The OE projects are being implemented
between June and August 2009, which coincide with the writing of the research.
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3.2 Research Design, Data Collection Methods and Research Instruments
In the quantitative section of the research where the effectiveness of the lean and Six Sigma tools and
methodology are tested in PBL’s warehouse operations, a comparative research design will be used to
evaluate the different projects being implemented in the warehouse operations. In this section, the data
collected through the implementation of the different projects will be used to evaluate their relative
success. The performance measures that have been set up to track down the effectiveness of each
process will be kept beyond the project and be used as the KPI for the respective process.
Particular attention will be given to possibility of experiencing the ‘Hawthorne effect’ during the first
few weeks when the observations will be made, which could be a treat to the internal validity of the
research. Bryman and Bell (2007) described the effect of the experimenter or the fact of being studied
on the subject is commonly referred to as the “Hawthorne effect’ following the works of Hawthorne of
the Western Electric Company in the USA during the late 1920s and early 1930s.
As suggested by Coughlan P. and Coghlan D. (2002), an Action Research Journal has been kept
throughout the conduct of the research for the researcher to note the observations and learning points
at each stage of the implementation process. The journal used throughout the research can be found in
Appendix 2. The Six Sigma DMAIC (Define-Measure-Analyse-Improve-Control) methodology is used in
the implementation process of the OE projects and each of these five steps uses a set of Lean and Six
Sigma tools. According to Schroeder et al (2008, p 542), “the DMAIC method is consistent with the
problem-solving steps of the PDCA model and places more emphasis on integrating specific tools into
each step of the method”.
In the second, survey part of the research, a survey with the participants in the different OE projects will
be done to analyse the level of key success factors present, the challenges and key learning points of the
various actors of the first phase implementation of the OE project. In order to design the questions for
the survey, a study of the literature was done to identify the various factors necessary for a successful
implementation of an operation management initiative. From that study of the literature, which can be
found in section 3.1.5 above, a set of variables were determined which would each form a section of the
survey.
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The variables identified are:
• Leadership, management support and commitment
• Communication
• Group / team problem solving
• Worker empowerment and involvement
• Training, tools and time
The survey questions were then developed around these variables with a series of four to six questions
per section. A last section of the survey was added to capture the key learning’s, what went well and
what went wrong during the program implementation. The survey questionnaire developed has been
done using the GSB online survey tool and is accessible through the link (see appendix 3):
http://gsblive.uct.ac.za/projects/ssurvey/TakeSurvey.asp?PageNumber=1&SurveyID=9MMm73KI2o4K12
The survey has been designed to be self completed but some respondents needed help as they had no
access to the internet. The researcher took necessary precautions so that appropriate support was given
to respondents while limiting the risk of putting a bias by those helping. This constituted a definite risk
to the internal validity of the research. The respondents were guaranteed that the answers would stay
anonymous and confidential. This questionnaire was tested by four of the researcher’s direct reports
before implementation.
3.3 Sampling
In the first part of the research, the outcome indicators as described before are tracked over a period of
four months. Two sample sets are taken for each of the four outcome indicators. The first sets of records
comprise of the first 30 records on and after 1 June 2009. The second sets are the last thirty records on
or prior to 30September 2009.
The survey questionnaire was sent to the whole population of OE participant, a total of 37 employees
and managers. A minimum target of 30 responses for the survey was expected in order to have an
appropriate sample size of respondents: 27 were finally obtained. The challenge in the design of the
questionnaire resides in keeping the right balance between convenience and the richness of information
to be collected. The language barrier was also a problem in some cases where the employees are not
very conversant with the English language. Particular attention was given to that point when writing up
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the questions. Four direct subordinates of the researcher helped those without internet access to
answer the questionnaire.
3.4 Research Criteria
The outcome indicators have been developed to track down the progress of the projects. Particular care
has been taken in the determination of these outcome indicators as getting these wrong could lead to a
complete failure of the project. These outcome indicators were validated by the process owners, the
line managers and the Six Sigma Black Belt facilitating the implementation process, thus ensuring
reliability and validity. Furthermore, the outcome indicators will be in all cases calculated from hard data
thus limiting the risk of inter-observer inconsistency.
The findings from the survey part of the research could be helpful for PBL in the future implementation
phases of the OE program as this is meant to be a long term project, if not a new way of operating. The
research, even if very specific to PBL’s context and culture, could also be helpful for other bottlers going
through the implementation of the OE program. Detailed information about the context of operation
will be given to ensure the research covers a fair about of external validity and reliability so that findings
could be applied in other locations.
3.5 Data Analysis Methods
A two sample T-tests (unequal variance) is used to compare the two sets of outcome indicators and
determine if a significant progress is recorded in each of the processes under study. These tests are one
sided tests as the purpose of the hypothesis is to determine if there has been an improvement in the
process. The T-tests are run with a confidence level of 95%.
For the Survey section of the research, a single ‘Likert’ scale (strongly agree- 5, Agree – 4, Neutral – 3,
disagree- 2, totally disagree – 1) will be used for all closed ended questions. For each question, a score
from 1 to 5 will be calculated from the response. Ultimately, a mean and standard deviation is obtained
per section of the survey from the score of the individual questions. Coding is applied to the answers to
the open ended questions which compliment the results of the closed ended questions.
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3.6 Limitations
The projects are being implemented and evaluated within a period of four months only which is very
short to be properly evaluated. There is first a serious risk of experiencing the ‘Hawthorne effect’ as
described in section 4.2 of the paper. It must also be considered that PBL will be at the start of a learning
curve. More long term benefits that could be realised by PBL following the implementation of these
projects would not captured during the course of this study. It is also important to consider that PBL’s
operations are very seasonal due to the intrinsic nature of their business, that is, sales of beverages. A
short term analysis of the operations therefore might not capture appropriately the scale of
transformation in the processes.
The description of the context and different factors influencing the outcome indicators, are described as
far as possible so that the findings of the research could be put in context. In one particular project, p3 -
Optimise the sorting process, the outcome indicator has also been heavily influenced by the rainy
season. Also in the same project, operations were significantly affected by another important project
that ran in parallel, the light weight project that is discussed further.
The small population of participants in the OE project constitute a limitation to the survey part of the
research. There is also a risk, despite precautions taken, that the respondents do not feel secure enough
to talk freely about their experience in the OE program.
For both the quantitative and survey part of the research, a second reading of the Y indicators and
redoing the survey with participants on the second phase of the OE programme after a period of around
6 months would have brought considerable value to the study
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4. The DMAIC projects and Green Belt Training.
The projects were to be run in parallel with a ‘Green Belt Six Sigma’ Training. During that training, the
participants were introduced to the different tools within the DMAIC methodology. Team leaders and
project champions of the various projects were concerned by this ‘Green belt training’. The training
started with the first two steps of DMAIC, namely ‘Define’ and ‘Measure’, beginning of June 2009 and
the teams were requested to complete these two steps by the end of the month. After being reviewed,
the training was continued on the two next steps, ‘Analyze’ and ‘Measure’ that were due for end of July
2009. Similarly, the training on ‘Control’ was scheduled for beginning of August after review of ‘Analyse’
and ‘Measure’. The projects were closed at the end of August 2009.
The projects were classified into two groups, ‘Track 1’ projects were the ones with a pretty clear and
direct implementation, basically a project where the solution was obvious and which could be
completed within three to four weeks. The other group of projects would be classified as ‘Track 3’
projects; these would require a detailed and thorough study of each of the DMAIC step as described
above, using several tools to solve the problem at its root cause and implement sustainable solutions for
fixing the problem. These ‘Track 3’ projects would need three months of implementation. Our first
project under study, p1- Optimize Full Pick operations, has been classified as a ‘Track 1’ project whereas
the two other projects under study; p2 and p3 are ‘Track 3’ projects. While the ‘Track 1’ projects would
use a ‘DMAIC Quick Wins One Pager’, which is a single Excel sheet, and a few supporting slides to
document the five different steps, the ‘Track 3’ projects would need to update a complete ‘Storyboard’
with all tools used, data analysis, photos and findings and any other details that were used during the
implementation of the project. These storyboards are in PowerPoint format and around 10 slides per
step per project. A brief of each of the three projects under study has already been given in section 1.2.3
of this paper.
The next section will summarise the 5 DMAIC steps for each of the three projects under study with a
brief description of the tools used. Most importantly, this section reveals the findings and outcomes in
each of these steps. The following section will then analyses the sets of outcome indicators obtained,
before and after the implementation and a comparison of these data sets will be done in order to test
the hypothesis as described in section 1.3.
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4.1 Project 1 - Optimize Full Pick operations.
Define: In this first step, we had to define the important aspects of the project in order for everyone to
be clear about the scope of the project. We identified that there was a double handing of full pallets
which were taken from the storage area of the warehouse to the staging lanes and at a later stage,
these same pallets were taken from the staging lanes to be loaded on delivery trucks as they enter the
warehouse to be replenished. This operation was performed daily on all full pallets going out to the
trade. We identified the customer to be the distribution team and we talked to them about their CTQs
(Critical to quality) characteristics. These were: correct loading in terms of quantity per item but also
proper staking of the products in the racks for quick access while delivering, quick turnaround for
second trips loading, loads properly secured on trucks and fresh products available on trucks (proper
stock rotation and expiry date management). We then identified the various stakeholders that were
concerned by this process, first the forklift drivers who move the pallets, the checkers who are
responsible for checking the loads before these are loaded on delivery vehicles and the inventory
controller who prepares all the paper work and looks after the inventory at the warehouse.
Measure: In this step, we wanted to quantify the problem. The full pallets represent, on average
throughout the year, 31% of all pallets going out of the warehouse. Over 90% of these full pallets
consisted of the top four SKU’s (Stock Keeping Units) of the company. On a daily basis, this represents
between 300 and 400 pallets a day. The operation of ‘Full Picks’ which consisted of moving the full
pallets from the storage area to the staging lanes, was performed by two forklift drivers on a full time
basis. This ‘Full Pick’ operation was actually automatically controlled by the Warehouse Management
System (WMS) which sends a task for a pallet to be picked on the RF (Radio Frequency) terminal of the
forklift driver, indicating the pallet to be picked, its address location (Storage area) and destination
address (staging lane). Once the task is completed and validated by the forklift driver, the WMS allocates
another task to him. This task takes from 1.5 to 2 minutes per pallet. The second part of the process is
the loading of the full and the mixed pallets (those with two or more SKU’s) on the delivery vehicle. This
operation is much more rapid (about 30 seconds) as the loading bays are very close to the staging lanes.
The loading operation is done by a separate team of forklift drivers.
We also identified some idle time of forklift drivers during the loading operation, in between the loading
of the pallets, due to these being secured on the trucks by a team of helpers. In order for all the team
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members to be clear about the process, a process flow for the actual ‘Full Pick’ and ‘Loading’ operations
was drawn.
Analyze: Our initial thought was to eliminate completely the ‘Full Pick’ operation as described above.
The team of loading forklift drivers would take the full pallets directly for the storage location and load
them on the delivery vehicles as these are inside the warehouse, just- in- time. This would impact on
making the loading process a little bit longer, as the forklift drivers would have to fetch the full pallet in
the storage location, which are further than the staging lanes. Overall there would be an increase the
efficiency of the combined processes. In the analyze step, we had to segregate the first and second
delivery trips loading to fine tune our solution. For the first trip loading which was done at night, on the
eve of delivery, we could afford to delay the loading operation slightly without any significant impact on
the service given to distribution department but on the other hand, as per our client’s CTQ’s, this delay
in loading for the second trips would have an impact on truck turnaround time and would affect them
significantly.
Improve: Before any implementation, a pilot test was performed with a sample of full pallets just for
one day. The result was positive and all employees were convinced that the change could be applied.
The change to Just in Time full picks was thus applied, but to the full pallets of the first trips only. These
represent around 60 to 70 % of total full pallets of the day. The Warehouse Management System (WMS)
system configuration had to be slightly changed to cater for this transition. All full pick tasks for first
trips, instead of going on the forklifts RF guns, had to be confirmed manually in advance and a list of
these given to the fork lift drivers responsible for loading the delivery truck, to enable them to perform
the tasks when the trucks are there. A further synchronization was needed with the inbound
department as while these full pick tasks have been completed on the system, the latter recognizes the
space to be freed and allocate inbound goods in those locations whereas the pallets were still there.
Another change that had to be brought was for the checking of the loads. Previously these were done
on the staging lanes before the loading of the trucks. With the arrival of the full pallet at the last minute
only now, the checker has to check the load which has been loaded on the truck already. This is, in fact,
more convenient as it allows a better utilization of the staging lanes with more loads being staged in the
same lane than previously.
Control: In the control stage, a new detailed process flow was done with details of each process step. All
employees in the Administration Department and fork-lift drivers have been trained in the new way of
working. The change was relatively a smooth one with some minor problems on the first few days,
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when for instance a full pallet scheduled for one load went on another. The two forklift drivers who
were previously allocated to the ‘Full Pick’ task have been reallocated to other tasks in the warehouse,
thus significantly helping in improving the other operations, namely the receiving of products which is a
relatively slow operation and had to be improved. The figures below compare the old and the new
processes.
Old Process New Process
4.2 Project 2 - Optimize Picking operations.
Waving
Full Pallets Mixed Pallets (out of scope)
RF Full pick
Staging
Loading on truck
Checking
Is Full pallet for 1st trip?
Manual complete task on system
Figure 3 – Old/New process of Full Pick Operations source: Optimise Full Pick Operation storyboard, PBL, 2009
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Define: Similarly to the previous project, the client of the process is the Distribution department and the
suppliers are the production facilities. The first step of the project was thus to go and talk to the client
and identify their CTQ’s (Critical to Quality characteristics) in terms of picking. For recall, we refer to
picking as the preparation of mixed pallets, pallets containing two or more different items. The mixed
pallets represent 69% of all pallets on average, the difference being full pallets as seen previously. The
requirements for the clients were in terms of quality, quantity and timing. They required the right
quantity of each item, properly stacked on the pallets, for each to be available at any one time during
delivery, and these pallets should be ready on time. Most critical in terms of timing was the second trips
loads necessary to attain a proper lorry turnaround time in order to be able to deliver second trips. The
other steps in the define stage consisted of doing a process / sub process analysis, in order to segregate
all sub processes of the picking process. Following was the input / output and a stake holder analysis for
the process.
The Input / output analysis would be helpful in the next stage to identify exactly what would be needed
to be measured. The stakeholder analysis was essential for us to keep a track on everyone who could
eventually be affected by any change in the process, for us to be careful about the implication on that
particular stakeholder. Also this would be helpful for our future communication plan. The biggest
opportunity we identified in this project was to reduce or even eliminate the using of outside staging
lanes as we identified a lot of double handling of mixed pallets in that. The pickers who were completing
the mixed pallets would leave these near the warehouse door (as their equipment cannot transport
these pallets outside), forklift drivers would take them and put in the outside staging lanes. Later, at the
moment of loading, another forklift would take back the pallet from outside to be loaded on the truck
inside the warehouse. This was done because there were not enough staging lanes inside the
warehouse for all loads for the day. Staging products outside was also having an effect on the quality of
the products, these being exposed to direct sunlight. We also identified a lot of idle time within the
pickers teams. Out output indicators for this project would thus be the picking rate (in terms of cases
per hour per man) and a second one would be the percentage of loads staged outside the warehouse.
Measure: In the measure stage, we first did a process flow diagram, see fig 4 below, and identified the
different indicators that would need to be measured. We identified three input indicators which are
respectively; the dispatching delays, the absenteeism of pickers and number of mixed pallets. We refer
to dispatching at PBL as the load planning, where all orders received for the day are grouped together to
form loads that would each go on a delivery truck. The picking process was effectively highly affected by
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the delay in that planning, this being the immediate upstream process. This ‘dispatching’ was itself
affected by the delay in order taking. We named these three input indicators X1, X2 and X3 respectively.
We thus started measuring daily all these input and output indicators. This data set would be analysed
in the next step of the DMAIC process.
Process flow: Picking process:
Analyse: This step has for objective to determine the root causes of the problem. This is a critical step
which, if not done properly, can put at risk the entire project, as the focus could be put on the wrong
areas. This step started with a brainstorming of the different causes that was causing the problem. It
Figure 4 – Process flow picking operations source: Optimize Picking Operation storyboard, PBL
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was important at this sub step to let everything out and this brainstorming was done at all levels of the
hierarchy, from senior management, down to the floor employee doing the process. After some
elimination in the list, the brainstormed causes, were regrouped into six pre-defined categories, known
as the ‘5M and 1E’, which are Man, Machine, Method, Material, Measurement and Environment. Finally
a Cause and Effect diagram was populated see figure below,
Cause and Effect diagram:
Figure 5 - Cause and effect diagram Picking operations source: Optimize Picking Operation storyboard, PBL
After confirmation with data, the main root causes of the problems were identified to be the lack of
synchronisation between the different parties involved in the process, namely the telesales department,
distribution planning and warehouse administration but mainly that the loads were being processed in
too big batches.
Improve: That stage also started with a brainstorming where all potential solutions to solve the problem
were discussed and latter evaluated in terms of effectiveness, ease to implement and cost of
implementing. The risk involved in implementing these solutions would be evaluated using a FMEA
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(Failure Mode and Effect Analysis). The selected solutions were finally to reschedule slightly the working
hours of the pickers team, making them come one hour later than before, in order to reduce the idle
time, re-routing of some clients who were causing big delays in the load planning process and preparing
loads in smaller batches and better synchronisation with the loading of trucks, so that these staging
lanes could be used more effectively. These solutions allowed each staging lane inside the warehouse to
be used several times, reducing the needs to use the outside staging lanes. The first project of
optimising the full picks operations also considerably helped the picking operation in the sense that it
reduced the number of staging lanes needed as some loads with several full pallets could use half of a
lane only for the few mixed pallets to be staged.
Control: The operators and workers were trained and standard operating procedures were written in
order for the implemented solutions to be sustained over time. What was interesting in that project is
that as from the very start, in the diagnostic phase, one particular solution had been identified which
was to break the teams of pickers into two small pickers teams. The first team would work in the
evenings to prepare the first trip loads in the next morning and the other team would come in the
morning in order to prepare the second trips loads. This solution had been evaluated as risky for the
business as the second trips loads might not be ready on time and cause disruption in the warehouse.
This solution would have a lot of implications also on the workers current working hours that would
have to be renegotiated with them. Finally with the selected solutions, the target of significantly
reducing outside staging was achieved at minimum cost and disruption in the warehouse operations and
working hours. This example proved that going through the detailed DMAIC steps and getting down to
the real root causes is indeed very effective.
4.3 Project 3 - Optimise Sorting operations.
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Define: Unlike the two previous projects where the supplier of the processes was, in both cases,
production and client was the distribution department, in the sorting process, this relationship is simply
reversed. Sorting is the main reverse logistic operation of the company where all returnable packaging
(half of PBL’s sales volume is in returnable package) are brought back by distribution, sorted at the
warehouse before being sent back to production and serve as ‘raw material’ for future production.
Scarcity and price of glass on the world market makes this reverse logistic an essential and critical
component PBL’s business. All secondary packaging used for returnable products which is essentially
glass bottles inside plastic crates, will be referred as empties in the course of this paper. Empties are
very space consuming and are stocked in the yard of the various different sites of the company.
Production department needs accurate stock of empties available by location in order to plan their
production batches and sizes. Also they need these empties to be correctly sorted which mean that each
case should contain the only one type of bottle it should have. Another requirement is also to have the
cases properly stacked on pallets ready for production. When drawing the process/ sub process map for
the sorting operation, see fig 6, we found useful to include an upstream sub process we called ‘Pre-
sorting’ which is not directly in the process but has a very high influence on it. Pre-sorting is the
preliminary sorting of the empties by the delivery teams of distribution trucks.
Figure 6 - Process / Sub process Map - sorting operations source: Optimize Sorting Operation storyboard, PBL
PBL uses a total of 19 different types of bottles which are classified in four categories; brewery’s 65cl,
brewery’s 33cl, Limo 1lt and Limo 30cl bottles. The output indicator that would allow us to track the
performance of the process would be the ‘sorting rate’ which is calculated by bottles sorted per minute
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per employee. A stakeholder analysis was performed, like for the previous projects, in order for us to
check all those that would be concerned with any change in the process.
Measure: We started the measure stage with a detail process map of the sorting operation. This map
allowed us to differentiate between the value added and non-value added activities in the process, and
determine the various measurement points in the process. We thus identified three important input
indicators that would be track over time as these have a significant influence on the sorting operation.
The first input indicator X1 would be the number of trips being performed by distribution for the day. For
the second indicator, it was useful for us to develop what we called a ‘pre-sorting’ index to somehow
quantify the quality of sorting that has been performed by the distribution team before the pallets of
empties are unloaded at the warehouse. For this indicator, we sampled the pallets unloaded and
categorise them into type 1, type or type3 pallet according to how much they are sorted (type 1 has less
than 3 cases unsorted, type 2 has between 3 and 10 cases unsorted and pallets having over 10 unsorted
cases are defined as type 3 pallets. The pre-sorting indicator X2 is then calculated using the formula:
X2= 1 x %type 1 + 0.5 x %type 2 + 0 x %type3.
The higher would be the pre-sorting indicator X2; the better would be the pre-sorting quality.
The third indicator X3 would track the category of employee, casual or full time employee. This would be
very useful as casual employees are paid following a piece rate system, whereas the full time employees
are remunerated on a hourly basis. This difference in remuneration system has a considerable impact of
the employee’s performance, the casual employees being much more productive than the full time
ones.
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Sorting process Map:
We also found useful at this stage to do some stratification of data in order to differentiate between the
different types of bottles used by PBL. We did a ‘Pareto analysis’ on the average monthly volume of
bottles used at PBL and obtained the following:
Figure 7 - Sorting process Map source: Optimize Sorting Operation storyboard, PBL
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This exercise sheds light on an important aspect of the process. We were actually dealing with all
empties in the same way; all empties pallets were unloaded to the same sorting area. The initial idea
that came to us was that we could have different treatment for different pallets depending on the type
of bottles these contained. At the end of the measure stage, we were settled on all indicators we would
have to track for the projects, these would be also forming our KPI’s in the future for the sorting
process.
Analyse: In the analyse stage, we wanted to start with a brainstorming in order to determine the root
causes of the problem with the sorting operations. Two brainstorming sessions were organized, the first
one with management and supervisors, and the second one with supervisors and the employees
involved directly in the sorting process. We thought that a single brainstorming could not be very fruitful
as the employees would express themselves when they would be face to face with top managers.
Following the brainstorming sessions, we eliminated some of the ideas that we thought would be
outside the scope of the project and group the rest of these ideas into pre-defined categories and that
led us to populate a cause and effect diagram as shown below.
Figure 8 – Volume by bottle types source: Optimize Sorting Operation storyboard, PBL
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Figure 9 - Cause and Effect diagram source: Optimize Sorting Operation storyboard, PBL
The red circles in the figure represent what we selected on the main root causes that we would action
on. The next step was to validate these root causes with data where possible. Finally, a 5-why analysis
on these root causes allowed us to go down to the lowest level of the root causes. We completed these
steps with four main areas we decided we would focus on, these are: The remunerations system for the
full time employees, the enforcement of pre-sorting process with the distribution team by enforcing the
check at the gate, the ergonomic aspect of the sorting and the different treatment that would be given
to different types of pallets at the unloading bay.
Improve: This stage started with a solution matrix where again we brainstormed on the different
solutions that could be applied to improve sorting operations in the warehouse. The first root cause we
tackled was the poor pre-sorting and we did that by communicating with the distribution employees and
enforcing the check at the gates to make sure the crates being returned were being sorted correctly. We
used the pre-sorting index developed (as described in measure stage) to track down any improvement
and we effectively experienced a big change on a week over the previous, as demonstrated in the
following chart (fig 10)
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Figure 10 - Pre-sorting Index source: Optimize Sorting Operation storyboard, PBL
The second change we did was a creation of a ‘Fast Track’ sorting area for type 1 pallets. These pallets,
instead of being transported to the sorting area and go through the normal sorting process, were to be
brought to a special dedicated area between the unloading bays and the staging lanes and sorted by two
dedicated employees, while still being on the forklifts. These pallets have very few unsorted crates and
these get sorted very quickly and in a flow. This ‘fast track’ would considerably reduce the forklift driving
time, to and from the sorting area. The third solution implemented was one to deal with the ergonomics
of the workers performing the sorting operation. We realised that each sorter was doing three distinct
operations, de-palletising of the palettes of unsorted crates, sorting of the individual crates and re-
palletising the sorted crates. The sorters had to perform a lot of movements, working at different
heights and move several crates manually from one pallet to another. Our solution consisted of creating
a simple ‘Sorting table’ with two old crate conveyors from the production lines where the sorting of
crates would be performed. Instead of each employee doing the three sub operations in sorting, they
would be put in groups of three and perform the operations in a flow, each one performing one of
these. At the start of the conveyor, employee 1 would thus be loading the conveyor with unsorted
crates which would be sorted by employee 2. Once the crates are sorted, employee 3 put these on
pallets.
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Figure 11 - The Conveyor Table source: Optimize Sorting Operation storyboard, PBL
A FMEA (Failure Mode and Effect Analysis) was also performed during the improve stage in order to
evaluate the potential risks of failures of the solution being implemented.
Control: we wrapped up the projects by the control stage where we gave necessary training to all
employees and re-wrote all standard operating procedures for the new process. The simplified process
flow that follows show the changes applied in the sorting operations.
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Figure 12 - Simplified Process Flow source: Optimize Sorting Operation storyboard, PBL
A more detailed process flow has also been done and serves as the standard operating procedure (SOP)
for the sorting process at the warehouse. During the project, one major event which influenced the
sorting process was the introduction of the new single serve soft drink bottles in the lightweight project.
The lightweight project is a Coca-Cola project where the glass bottles used for packaging soft drinks are
changed to lightweight bottles in order to reduce use of glass and thus the cost in the manufacture of
the bottles. During the course of the project, a new Coke and Sprite 300ml bottle was introduced in
replacement of the old ones (weight of 305grms instead of 380grms) while the Coke light 300ml bottle
was replaced by a 250ml bottle. These changes had a significant impact on the operations as the old
bottles had to be sorted and removed from the circuit to be destroyed or packed for export. The Coke
and Coke Light bottles being the same bottles with just two different prints made the sorting process
much more difficult and time consuming and this affected considerably the outcome indicator. We also
noted big variances in our outcome indicators over days, due to the weather. The sorting of empties
being done in the open air is significantly affected by rain and operations have to be slowed or even
stopped at times.
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5. Two sample T test on the Outcome (Y) indicators.
A two sample t test will be used to test if there is a significant difference between the two set of sample
means for each of the y indicator. The standard deviation also being different for these samples, the
‘unspooled test’ will be used, thus using the formula below to calculate the t statistic:
( )
2
2
2
1
2
1
21221
n
s
n
s
differenceedhypothesisxxt nn
+
−−=
−+
Equation 1- two sample T test with unequal variances
As all sample size is 30 for all Y indicators, the degree of freedom that will be used generally will be 58
(30+30-2). A one-sided t-test will be done on each pair of sample at a confidence level of 0.05, therefore
a t-critical value of 1.68 will be used(by looking in the t table at d.f = 58 and α = 0.05). That means that
the null hypothesis will be rejected if we obtain a t value > 1.68
Figure 13 - t distribution curve (shaded area represent the rejection area)
The four outcome (Y) indicators for the three projects are in Appendix xx
5.1 Testing Y1p1 : % of pallet staged in Project 1.
The first Y indicator to be tested is Y1p1, the % of full pallet staged in project 1. For recall, a drop of this
indicator indicates an improvement in performance; therefore we draw the null and alternate
hypothesis as below.
Ho: μ1 = μ2
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Ha: μ1 > μ2
μ1 = 95% d1= 14%
μ2 = 57% d2= 10%
t 58 = (95-57) / √(142/30-10
2/30)
t = 21.3
Therefore the null hypothesis can be rejected as t = 21.3 is greater than the critical value of 1.68.
This means that the Y1p1 has significantly improved.
5.2 Testing Y1p2 : Picking rate in Project 2.
For recall, an increase in this indicator indicates an improvement in performance; therefore we draw the
null and alternate hypothesis as below.
Ho: μ1 = μ2
Ha: μ2 > μ1
μ1 = 303 d1= 30
μ2 = 305 d2= 26
t 58 = (305-303) / √(302/30-262/30)
t = 0.73
Therefore the null hypothesis cannot be rejected as t = 0.73 is not greater than the critical value of 1.68.
This means that the Y1p2 has not significantly improved.
5.3 Testing Y2p2 : % loads outside in Project 2.
For recall, a drop of this indicator indicates an improvement in performance; therefore we draw the null
and alternate hypothesis as below.
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Ho: μ2 = μ1
Ha: μ2 > μ1
μ1 = 32% d1= 10%
μ2 = 0% d2= 0%
t 58 = (32-0) / √(102/30-0
2/30)
t = 17.58
Therefore the null hypothesis can be rejected as t = 17.58 is greater than the critical value of 1.68.
This means that the Y2p2 has significantly improved.
5.4 Testing Y1p3 : sorting rate in Project 1.
For recall, an increase in this indicator indicates an improvement in performance; therefore we draw the
null and alternate hypothesis as below.
Ho: μ2 = μ1
Ha: μ2 > μ1
μ1 = 82.5 d1= 13.6
μ2 = 65.7 d2= 9.3
As μ1 is greater than μ2, we have to accept the null hypothesis meaning that the Y indicator Y1p3 has
not improved.
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6. Survey findings- OE implementation at PBL
The purpose of the survey part of the research is to find out how much the key ingredients to the
success implementation of the OE program were present at PBL. The questionnaire was developed from
a literature review on the key success factors necessary for such operational improvement programs
and a set of variables were taken out to form questions. The questionnaire was sent to all participants of
the program, a total of 37 PBL managers and staff, from which 27 responses were obtained, thus a
positive response rate of 73%. Due to confidentiality and to stay completely anonymous, the answers to
this survey were not linked to any specific project. The questionnaire was divided into 6 sections, each
of the first 5 sections containing a series of questions specific to one of the variables and the last section
dedicated to key learning and general comments about the program.
For the close-ended questions, a score was developed for each question according to the answers. This
score ranges from 1 to 5 and the bigger the value, the more the respondents agree about the respective
statement asked. Finally a score is calculated for each of the first five sections the questionnaire, each
question carrying equal weight in the calculation of this average.
The answers to these closed ended questions and the calculated scores are represented in table 1 below
whereas the answers to the open ended questions are to be found in appendix 5. The results of both
these set of questions are analyzed in the different sections below.
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Table 1 - Survey results source OE survey PBL 2009
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6.1 Section A: Leadership, Management support and commitment:
This section scored 3.8 over a maximum of 5 points. Each question carries more or less an equal score
but with some minor differences with the access to information and resources pulling down the
average, whereas management support and commitment and leadership pulling it up. The answers from
the open ended question were various and confirmed the results of the close ended questions. While
the respondents in general liked the commitment and presence of management, there are some
complaints about the limited access to information and resources, especially from the finance
department.
6.2 Section B: Communication:
This section scored an average of 4 points, once again very balanced among the various questions with a
preference on the communication among the team members and between the teams and the OE
coordinator. It is to be noted here that PBL employed a full time OE coordinator for the program and
that was a strong signal from management in showing its dedication to the program. Lagging somehow
behind in that section is the communication between the teams and management. Another question
that was asked in that section was to see if the OE program helped in creating a better communication
in the company. 54% strongly agreed and 12% agreed with the statement that the program did
effectively helped in increasing communication in the company, 7% were neutral and 2% disagreed. The
answer to this specific question was not part of the score of the section as it is outside the scope of the
survey but the researcher was interested to get the perception of respondents on this point. The
answers to the open ended question once again confirm the results obtained and the difference in the
score of the closed ended questions. Several respondents requested more communication meeting,
especially between the staff level and management while recognizing in general that the OE program
was a very good opportunity for them to voice out what they always thought that was not working well
in the company, thing they never had the opportunity to do before.
6.3 Section C: Group / Team Problem solving:
This section got the highest score of 4.1 among all other sections. This is not very surprising knowing
that the OE program was a great first formal opportunity for people to work in teams and that generally
this is not very common in the company. The question that really pulled down the average in this
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section was about the number of people in the team; only 3 respondents strongly agreed that there
were enough team members in their teams. It is important to point out once more that there was a total
of 19 projects being run simultaneously at PBL and that the teams were relatively limited in terms of
team members due to the unavailability of resources. A very high score of 4.4 for the first question of
this section shows that most respondents enjoyed working in their teams. The answers to the open
ended question revealed that the respondents had an enriching experience working in teams but
requested some better balance of the teams according to the different competencies and backgrounds
of the employees.
6.4 Section D: Worker empowerment and involvement:
A score of 3.8 was obtained in this section with an equal weight for each question except for the one
asking if the employees participated actively in the brainstorming sessions which pulled up the average
with a score of 4. This shows that the OE program was a great opportunity to get all employees
throughout the hierarchy of the company to participate and get together in solving the daily operational
problems faced at PBL. The main comment emerging from the open ended part of this section was
about the fact that the employees were not well aware of the OE program and thus could not
participate effectively in brainstorming sessions. The fact that this practice was new at PBL, more effort
could have been made to sellthe program to employees at all levels of the hierarchy. Probably some fear
about loss of jobs also played an effect in the willingness of employees to participate in the program.
Nothing was clearly communicated on this particularly sensitive subject even if it was informally agreed
that any saving of manpower would be reallocated to other more productive tasks and that the OE
program would not cause any lay-offs in the company. On the other hand, it was clear that any gain in
productivity would affect the amount of working hours needed and consequently the overtime
remuneration of employees which forms an important section of employees package at PBL.
6.5 Section E: Training, Tool and Time:
This section obtained the lowest score (3.5) among all others due to the very low score obtained in the
last two questions, the one about if the participants felt they had enough time for the projects (2.9) and
the one on the period of implementation of the program (3.0). The open part confirmed that the
respondents required more time for the projects.Somecomplained about the complexity of some of the
tools and the limited time they had to digest these and use for their project. For information, the project
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ran for a total of three months, each month starting with two day training on one or two of the DMAIC
steps and being followed by a review of the update of the projects’ previous steps. The teams would
then have the rest of the month to work and complete the one or two steps required. While most
appreciated the appropriateness of the tools and training given, some found them bulky and requested
translation in French (all training and tools were in English). Nothing was said about the timing of the
program in the open ended question, I personally felt that this had been perfect for the first phase of
that project as it was during the winter (lowest) season and the operations were relatively not on strain,
even if it made things more difficult to effectively obtain substantiate savings during these low periods
(e.g. reducing overtime in a period where structurally there is no much need for overtime anyway).
6.6 Section F: Key learning points, what went well and what went wrong:
This section contained four open ended questions and the purpose was to capture the key learning
points and also the general appreciation of the OE program participants.
When asked about the key learning points, the learning experience came up in several of the answers,
learning the new tools and problem solving methodologies. Several answers also mentioned the value
creation, reduction of waste and working more productively and efficiently. These results are very
encouraging as these key learning points form the essence of Six Sigma and lean, problem solving
methodology and value creation respectively.
Team spirit was the highlight in the answers of the second question of this section. The mention of
correct team work was in 6 of the 19 answers received for this question. Also was well appreciated the
management commitment and involvement in the project, which was very beneficial for participants,
“Management had time to hear us” says it all. Looking at things differently, challenging the way to do
things were also mentioned in the answers to this question
On the ‘What went wrong’ question, several respondents mentioned time issues like in the section E.
Lack of available resources also came up in that section. Some respondents also mentioned the lack of
communication issues among management and employees and the difficulties of getting through the
entire set of tool effectively, mainly the language barrier issue as discussed previously.
Lastly the respondents were asked for tips that would be useful for the future implementation stages of
the OE program. Following the previous answers from the previous sections, it was not surprising to see
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in that one a request for more time for implementing the project. Also other things that were lacking
were in the list of requests for future implementation, such as have better access to financial
information, improve communication challenge and better awareness of the OE program for all the
employees in the organization.
7. Discussion of Results
7.1 Results of quantitative part
Two of the four Y indicators showed a significant improvement in the operations and a third one showed
improvements but these were not significant enough. The forth Y indicator did not show any increase in
the process performance and that could be explained by the different reasons as discussed previously. It
can safely be said that the implementation of the Operations Excellence program has been successful at
the warehouse operations at PBL. These improvements in the processes will definitely with time be
transformed into real resource and cost savings for the company.
Also, the program provided a unique opportunity for employees and management to work together in
cross departmental teams, armed with solid lean principles and a structured Six-Sigma DMAIC problem
solving methodology. As the researcher and an active participant within the projects, I experienced a
real opportunity in challenging ourselves in the way we operate and using the tools provided during the
projects to really identify the root causes of the problems and to apply appropriate and sustainable
solutions to our problems.
I also realised that several of the problems we solved during the projects were not new or newly
identified problems. Most of these problems already existed but we were used to living with them. The
program was a unique opportunity for us to tackle these problems at their roots and apply long term,
sustainable solutions to them.
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7.2 Results of Survey
The results of the survey shed light on several benefits and threats of the program at PBL. Employees
and managers appreciated solving problems within teams and recognized the benefits of applying a
structured problem solving methodology to process improvement within their work environment. These
results will serve as a constructive and objective feedback for the future stages of implementation of the
OE program at PBL or at other Coca-Cola bottlers.
7.3 Contribution to the literature
Operations management literature does not contain a lot on process improvement in warehousing
operations and this research paper aimed at contributing to close that gap of the literature. The
research had a big focus on certain specific processes within PBL warehouse operations and
demonstrated how these processes could be improved using lean principles and Six-Sigma problem
solving methodology. The findings of this research are based on hard figures from the quantitative
section of the research rather than just an analysis of the perception of participants through surveys.
This brings value and credibility to the study and could provide certain guidelines for replication on
other warehousing sites. These Y indicators will serve as Key Performance Indicators for their respective
process at PBL warehouse.
7.4 Implication for managers
This paper gives managers some simple but concrete examples of how using lean principles and the
DMAIC methodology can help in bringing significant and sustainable improvement in processes. It
proposes examples showing how these tools are applied in a warehousing context and how these
contribute to achieving real process improvement. Managers at various levels of the hierarchy can draw
from this study some very practical tips that could be helpful for them when starting any process
improvement initiative. The survey part of the research could also be useful and provide some
guidelines to planning when one is to enter into a process improvement initiative. DMAIC could seem
heavy and lengthy but is definitely a very efficient structured problem solving methodology.
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8. Conclusion
The central question of the research paper was:
Can the lean and Six Sigma tools and methodology used in the Operational Excellence Program (OE) at
PBL bring a significant improvement in its warehouse operations?
And the hypothesis to be tested was:
The use of lean and Six Sigma tools and methodology can significantly improve PBL’s warehouse
operations.
With the results obtained from the research and the analysis of the Y indicators in chapter 6, we can
with confidence accept the hypothesis that the use of lean and Six Sigma tool and methodology brought
significant improvement in PBL’s warehouse operations. Among the three projects under study, two
showed real improvement achieved, whereas good reasons explain the non-improvement of the third
one.
The survey part of the research was a good opportunity for the participants in the first phase of the OE
program to give their feedback about their experience. The compiled results will be helpful in the future
phases of implementation at PBL or in other companies.
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9. Future research
One of the important limitations of that study is that it was not possible it, due to the time limit, to test
for the sustainability of the solutions applied over time. Also, as specified in the research, PBL’s activities
are highly seasonal and the Y indicators have been measured over only four months. There is a scope for
a follow up of these processes and to test the sustainability of the solutions through a future study of
the Y indicators over time and particularly over the peak period of November / December. A follow up of
the sorting project will also be interesting once the ‘Light weighting’ transition stage is over.
The same survey questionnaire could also be applied to the second population of participants, those
involved in the second phase of the OE program which started in October 2009 and is due to end in
February 2010.
Finally, a long run study about the real sustainable changes the OE program brought to the way PBL
operates will be interesting in a few years. It would be interesting to see if the program was for PBL just
another one bringing some short term benefits or, like it claims to be, one bringing “continuous
improvement through a structured and systematic approach, which improves operating margins of a
business by focusing on the elimination of waste and the reduction in variation through standardized
work.” (OE presentation, 2009, slide 2)
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Appendix 1: Value Stream Maps (Full Products and Empties)
C/T:
1 shift
C/T:
2 shift for trucks
C/T: 18 sec
2 shifts
C/T: 86 sec
1 shift
C/T: 638 sec
Mixed pallets : 69%Full pallets: 31%Picking rate 229 cases / hrD/Time electric transpallets > 80%
1 shift 8hrs
C/T: 170 sec
1 shift
C/T:
1 shift
Warehouse ControlWMS
Value Stream Mapping – Full products
Production Distribution120 trips a day (960 pallets)
1 or 2 trips per lorry( 3 in peak)
ASN generated
Load docs
Weekly forecast W1-4
Full picks orders
Pick ticketsASN completed
Daily request
Load manifest
Daily: Limo: 500 PalletsBrewery: 400 pallets
8%92%
Loading Trailer
3
Driving
Limo: 4 Trailers + 1 truckBrewery: 3 Trailers + 1 truck
Receiving
2
unloading
3-5
Picking
18-20
Loading
3-5
Check out
2-6
2.76 days
I
Production warehouse
18 sec 56 sec 638 sec 170 sec
8.75 days 0.5 days 0.3 days
I I I I I I
Lead time: 12.36 days
Processing time: 1010 sec (17 mins)
23 mins34 mins 10 mins
55 sec58 sec 15 sec
D/T: 14%D/T: 14%
D/T: 14%
Takt time = (27,000 / 960=) 28 sec
Time available (from 7:00 to 14:30)= 27,000 sec
HR: 15 mins break system
Staging lanes
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II
Check In Double check In Unloading sorting
3-6 1 4 12-16
C/T: 30 sec C/T: 30 sec C/T: 38 sec C/T: 654 sec
Sorting time for 1 pallet65cl: approx 5 minsChop: approx 12 minsMixed: approx 20 mins
C/T: 37 sec
Warehouse ControlWMS
Value Stream Mapping – Empties
ProductionDistribution
120 trips a day (450 pallets)
Load in ASN Generated
ASN Completed
Weekly / daily empties request
Loading on trailers
2
Lead time: 2.77 days
Processing time:789 seconds
6 mins
30 sec 30 sec
10 mins 14 mins
38 sec 654 sec 37 sec
.75 day 2 days
Total: 450 pallets per day
Total time available: 7:00 to 19:00 (43,200 sec)
Takt time = (43,200 / 450=) 96 sec
I I I I
HR: Piece Rate system - weather conditions
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Appendix 2: Action research Journal
Date Place Purpose Participants Outcome Insights gained 29-Jan PBL
boardroom OE introduction meeting by mr. Gerald Glancey ( Technical Operations Manager Coca-Cola East and Central Africa Business Unit
All senior Managers
Commitment for OE implementation at PBL
Introduction to OE
Antis Treebobhun designated project manager
Basic training on OE history and methodology
Project plan, timing, deliverables
PBL to employ OE manager
30-Jan PBL training room
OE introduction to key staff-
Senior Manager + key staff
Basic introduction to OE, tools and methodology
Basic knowledge of OE program by Key staff
30-Jan PBL Pre-Diagnostic data pack
All senior managers
Templates of data to be filled for diagnostic phase remitted to all senior managers.
Data that will be needed for diagnostic phase
List of staff that would for part in OE teams
24-Apr PBL, 3rd floor meeting room
OE general presentation and how schedule of diagnostic phase
All OE team leaders / Members- into 4 different groups
Timing, load of work, deliverables of diagnostic and future OE phases
Basic understanding of what is the OE project.
4th May
PBL training room
OE kick off meeting, start of diagnostic phase.
All team leaders, team members, core team, senior management, CEO
Presentation of program, welcome speech, break in teams, agenda for next two weeks, deliverables, templates etc.
Overview of program and deliverables
PBL training room
8 waste training OE teams Training on the 8 types of waste, examples, tips for identification.
What is defined as waste, where to look for waste
My office 1st team meeting Team 8 Introduction and presentation of team members, agreement on deliverables, planning 2 days ahead
Start of group bonding, agreement on way forward, definition on scope of work, overview of processes in the scope of operations.
On site- LIMO factory
8 waste identification on the site
Team 8 Identified several type of waste in different areas of operation
Waste present in all operations, scope for improvement
5th May
My office Team working sessions
Team 8 Continue site visit for waste identification.
Several areas of waste detected
Brewery site / Commercial unit warehouse
Entering waste observed on data record sheet
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6th May
My office Compilation of Waste detection report
Team 8 Record of 69 different observation of waste on the 3 sites we visited during the last 2 days
There is much more waste that we thought there was.
Identification of certain areas where operations could be significantly improved.
Training room
Presentation of waste findings to OE core team
Team 8 / Core team
Presentation of list of waste priorities by score (mixture of impact and resource needed to eliminate) + series of photos to show these waste.
Feedback on work performed, to categories the list of waste into 4/5 broad categories to be tackled together
7th May
PBL training room
Feedback of all group on waste observation
All teams
PBL training room
Value added / non value added analysis, VSM and process mapping training
All teams Introduction to techniques for mapping processes and separate value added to non value added activities in our system
My office Planning and draft VSM layout for our operations (Logistics and reverse logistics)- split of tasks
Team 8 Have our plan of action validated by core team member before proceeding
Can do a single VSM for the entire operation, initially wanted to perform two separate.
Production and warehouse site
Time keeping exercise in order to get data for our VSM
Team 8 Data for the different processes
Lot of variability in process depending on several factors, challenge to work out averages. Not enough data captured due to lack of time, to have more data during the course of the project
My office Start the VSM with data obtained
Team 8 Draft VSM Not so easy to draw VSM, after time keeping exercise, several parts of the map had to be changed.
8th May
Production and warehouse site
Additional time keeping to compile data set.
Team 8 Data for the different processes
Finalize VSM
My office Finalize VSM and analysis with team
Team 8 Final VSM drawing, brainstorming and identification of key problem areas.
Identification of key areas we would focus on namely receiving, picking and sorting
My office In-depth study of processes that will be investigated
Team 8 Draw functional process maps for the key areas of study following value stream map done
Lot of dependent parameters to take into consideration when drawing process map for one process, must consider support functions
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My office Presentation of VSM and findings to core team
Team 8 / core team
Validation of key areas of research + agree on other parameters to consider (like glass breakages, damages products on trade etc)
What are the important parameters to consider in our process, effect these can have on other parts of our business
11th May
3rd floor meeting room
Briefing with core team on way forward
All team leaders Inter team communication, each team to meet supplier team(s) and client team(s)- our team to meet production and distribution
Final objective of the OE diagnostic phase
Template for final presentation- key findings and projects
New member in team for end of the week- Francine from Madagascar
Examples of other OE implementation for idea generation
Production site
Meet with ‘ Supplier’
Production team, part team 8
Talk about initiative of inventory reduction and improvement of T/Around time for trailers
Inventory reduction may not be applicable to them running longer batches to improve productivity and yields- T/around welcomed, less driving for them also (fork lift drivers)
Commercial unit
Meet with ‘ Client’ Distribution team, part team 8
Obtain client’s demand from us their suppliers
To Improve lorry turnaround, load preparation, damaged products, avoid errors in loads.
My office Team meeting- briefing, brainstorming on action points to present- plan ahead- review of past OE initiatives
Team 8 Start working on draft presentation- share tasks among members
Initiatives are very much interlinked
12 – 14 May
My office / Site
Finalise list of opportunities and quantify financial impact these can have on operations
Team 8 / OE core team
Presentation, 6 identified opportunities with potential saving of Rs 3.2 m
Clear definition of projects that will be held during first phase of OE implementation
Overview of projects in Warehouse & Transfer operating area
15th May
Sofitel hotel – conference room
Presentation by teams of key opportunities identified that will be dealt with during first phase of OE implementation
All teams / all PBL management / OE core team
Presentation of each team’s findings and opportunities selected to be focused on during OE first phase of implementation
Overview of all the teams identified opportunities and financial impact in terms of cast saving
Our team got special price for ‘Best use of tools’
19Th May
PBL”s Board room
Steering committee selected opportunities for
OE steering committee
List of 21 opportunities from the total list to be implemented in first wave starting 1st June
Priority given to opportunities according to their impact and resources needed.
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first wave implementation process
2009
(3 OE projects for the warehouse area)
26th May
PBL’s Warehouse
Introduction meeting with project teams
Project teams for the three identified OE projects for warehouse section
Brief on the different projects, explain to team members the general purpose of OE program
Buy in of team members, very motivated to make things happen. Confident that the projects can be implemented
27th
May PBL board room
OE Steering committee
OE steering committee
Finalized projects that would be implemented and teams
30th May
My office Informal meeting with my brother Jean Marc- Six Sigma green belt and some experience in lean implementation
Jean Marc Rivet + me
Validation of project and some new ideas about framing the project
Lean initiative must have clear customer oriented purpose, else drive towards a corporate global strategy.
Importance of human aspect in the implementation process
1st June
PBL training room
Six Sigma Green Belt training
Team leaders and team champions
Classification of selected projects into track 1 projects (Quick gains) and track 3 projects (DMAIC)
Methodology for problem solving, new tools for the define stage in DMAIC.
Introduction to DMAIC methodology Tool kit for the define stage
Taking a structured approach is the long route but will produce sustainable results
Overview of lean and Six Sigma tools Time table for project implementation.
Detailed training on ‘Define’ phase of DMAIC
2nd June
PBL training room
Six Sigma Green belt training.
Team leaders and team champions
Toolkit for the measure stage.
Methodology and tools to be used.
Detailed training on ‘Measure’ stage of DMAIC
Finalization of OE projects team.
Importance of data, what to measure
Quick wins project format
Quick changeover module and exercise
3rd June
Warehouse Meeting with teams for the two main OE projects
Teams Picking and Sorting
Basic overview of OE program and specific project.
Lot of insight for team members embarking on OE project just now.
Explanation of the different implementation stages (DMAIC)
Detail explanation of Define stage and requirement for next meeting
4th June
My office Meeting with Mark Sinnick (Master black belt) and Barlen to validate projects
Team leader / champion + MS / BA
Validation of warehouse projects, teams and Outcome indicators (Y)
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5th June
PBL’s boardroom
OE Steering Committee
OE steering committee / MS
Brief overview of DMAIC methodology, recap of all projects phase one, key responsibilities and deliverables
Clear project timelines and deliverables.
11th June
Warehouse Meeting with OE groups for picking and sorting projects
OE team Finalization of Define stage and agree on measures to be taken for next meeting.
Importance of define stage to go down to the root cause of the problem
Sorting project
18th June
Warehouse Meeting with OE groups for picking and sorting projects
OE team Validation by team of storyboard of projects. Discuss measures taken and agree on pilot test for projects. Communication plan set up for pre-sorting and finalise / validate communiqué for sales attendants
Start seeing a progress even at preliminary stage.
Teams motivated for projects- forecasting on the potential benefits.
My office Meeting with OE coordinator
OE coordinator + Me
Update of project progress and planning for future stage
30th June
Training room
Six Sigma green belt training analyze
Team leader / champion + MS / BA
Analyze stage of DMAIC- training on tools and methods to be used in the Analyze Stage
1st July
Training room
Six Sigma green belt training Improve stage
Team leader / champion + MS / BA
Improve stage Risk analysis, pilot testing
3rd July
Training room
Presentation to Master Black belt on Define and Measure stage for projects
OE team + MS / FH / BA
Define and Measure stage storyboard review
Black belt very happy with storyboards
7th - 10th July
My office Analyze stage with team
OE team Brainstorming - C&effect diagram - identification of root causes
Lot of ideas coming from supervisor / coordinator - to organize a session tomorrow with some sorters and Boodhun who was abs today
14th July
My office review Analyze stage with Sarind
Sarind and Me review presentation and modified where needed
14th July
warehouse yard
organized for repairs of crates conveyors
supervisors / garage mechanics
plan for repair and installation of conveyors in yard to help sorting
14th July
My office Review Analyze stage with team and start with improve
OE team Sorting start 'improve' stage create solution Matrix - lot of small solutions ranked by importance
15th July
My office Improve stage- risk analysis
OE team Sorting FMEA tool Tool over killed for the project. Useful to see the risks that we could be experiencing when implementing solutions but the tool itself is not very
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appropriate
16th July
My office Complete improve stage
OE team sorting Action plan the action plan of piloting and implementation will be done simultaneously. We have a pretty good idea how things will work out, in terms of principles and framework but trial and error will be necessary to implement these changes.
24th August
My office Review project- Y indicator, improvement solutions, review of what works and not
OE Sorting team Pre-sorting works more or less okay- see with distribution for reinforcement. Fast track working fine. Train employees for conveyor- sell the system
Decide on strategy to sell in the conveyor system with employees.
25th august
Warehouse yard
Sorting on conveyors
Sorters / supervisor
Talk to employees – see them in action. Explain to employees the ideas behind and principles in using conveyor
Conveyor system can work correctly, some minor modifications on conveyor necessary
28th August
My office Review of project Sarind / Myself Very different solutions than those initially thought of during diagnostic
Ideas have to mature, DMAIC process has been useful to get to the roots of the problems and identified the correct long term sustainable solutions to the problems.
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Appendix 3: Online Survey Questionnaire
Operational Excellence (OE) implementation at PBL
Page 1 of 1
Dear Colleague, In the context of my studies, I am conducting a survey on the implementation of the OE program at PBL. The objective of the survey is to determine the factors that contributed to the success or failure of the projects being implemented in the OE program. Your opinion and experience will be of great interest for this survey and ultimately for the improvement of the OE process at PBL. Thank you for taking a few minutes to answer the questions below. All answers and opinions in that survey will be kept strictly confidential. Thank you very much in advance, Hugues Rivet - Supply Chain Manager, Phoenix Beverages Limited
Section A. Leadership, Management support and Commitment
1. During the implementation of the OE project, there was good*
Strongly Agree Agree Neutral Disagree Strongly
Disagree Leadership Management Support and Commitment Availability of resources Access to information
2. Any other comments on leadership, Management Support and Commitment?
Section B. Communication
3. During the implementation of the OE project, there was good communication between*
Strongly
Agree Agree Neutral Disagree Strongly Disagree
OE coordinator and teams
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Management and teams OE teams and the workforce Communication among team members
4. The OE programme has increased the communication in the company Strongly Agree Agree Neutral Disagree Strongly Disagree
5. Any other comment on communication?
Section C. Group / Team problem solving
6. What do you think of the following statements?*
Strongly Agree Agree Neutral Disagree Strongly
Disagree I enjoyed working in my team There was enough members in my team There was a good team spirit in my team There was good leadership in my team
7. Any other comment on the work in teams?
Section D. Worker empowerment and involvement
8. How much do you agree with the folowing statements?*
Strongly Agree Agree Neutral Disagree Strongly
Disagree Employees in the process are aware of the OE project Employees were well involved about the OE projects Employees participated in Brainstorming sessions Employees were empowered to implement changes
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9. Do you have any other comment on employee involvement and empowerment?
Section E. Training. Tools and Time
10. What do you think of the following statements*
Strongly Agree Agree Neutral Disagree Strongly
Disagree The training given was very satisfactory The tools were appropriate for the OE projects The tools were correctly explained by the team leader / trainer We received good feedback and support from trainer and OE coordinator We had enough time to work on our projects The period of implementation of the projects was appropriate
11. Any other comment on training and tools used in the OE project implementation?
Section F. Key learnings, what went well and what went wrong
12. tell me more about....
Your key learnings in the OE project implementation: What do you think worked well in the OE project implementation: What do you think went wrong in the OE project implementation: How do you think the future implementation of OE projects could be improved:
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Appendix 4: Y indicators
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Appendix 5: Answers to open ended questions
Section A: Leadership, Management support and Commitment 1 N.B: All answers in this questionnaire are related to the diagnostic phase only. 2 Top management leadership and support weren't visible and tangible. Management level staff who
weren't involved in OE showed no interest probably because there had been no formal presentation to them
3 Very good, done in interest of company but constraints regarding time and involvement 4 management support was total 5 Oe project has been implemented to show that savings can be done in various departments. However
for propoer support and better output, someone must have been made available to guide the team as Mark
6 management suppoirt and commitment must be well attended 7 TIME LIMIT TOO SHORT 8 There was very much involvement/push of management to implementation OE, employees had to be
involved and priority was given to access information 9 There was little access to information, we had issues to contact people from finance to get
information 10 This was the first time that I could see the Management around me and I felt very good
Section B: Communication
1 More regular meetings would have been beneficial 2 In many cases communication has stopped at a certain point, mainly high level. The latter should have
been brought even to the down level too as mainly all processes which we evaluated were their's. 3 More to do on communication 4 The big problem in the company is lack of communication and this problem has never been resolved. 5 Communication within a team was fine but no communication in between teams probably because of
limited time and huge amount of work. Need to rethink well choice of team members and subjects. 6 This was very good and had opportunity to know more about other team members 7 constant communication with OE coordinator has kept all OE team on track regarding their specific
field 8 OE has been a very good tool for communication among employees from different departments. 9 Through OE, we team members of OE witnessed the fact that much things can be done through
communication. 10 Some frustrations could be communicated to management 11 I could voice out things that were not going on smoothly in the company which I wanted to say much
before
Section C: Group / Team problem solving 1 In order for this to be a success, each and everyone in the team should work on the same level sharing
their ideas, feelings, etc... 2 Need to balance teams in terms of number of members, competences and from different backgrounds
- other department views might prove most useful 3 Particulaer attention should be given to profile of team member before forming a team
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4 Their was agood listening to each other in the team 5 brilliant experience 6 the purpose of OE is team oriented approach to solutions and better ways of doing things. However
groups working seperately took this challenge and critisise in the wrong way the other members. 7 Everybody in the team got the opportunity to share and discuss at ease 8 perhaps it will be more effective if all team members were in the same dept 9 Traits of team members should be clearly reviewed before team is setup.
10 Unfortunately everyone had to spare time from daily works to be able to involve in team and time to match all team members was difficult
11 I have most of the time worked in team, we should respect opinions of other team members
Section D: Worker empowerment and involvement 1 Owner of the process should be more involved so as to help in the improvement, but also in order to
make his task more easy and more efficient. 2 Worker involvement was very limited - formal awareness sessions prior to projects would be welcome
and certainly tools to be provided to them for execution of changes would be most beneficial for OE
3 No 4 a small explanation session / overview on OE would have triggered better involvement of employees 5 employee very keen in participating in brainstorming sessions 6 make group session for employee after OE project 7 Empowerment of employees to implement projects is a need in today's business, people feel a sense
of belonging to the company and are more cost-oriented when decisions are taken 8 There was lack of communication to other employees not in OE, and so they were not that incolved
and had fears in brainstorming session 9 Employees in general were not aware of this programme, we had to explain before we brainstorm,
employees had fear to tell their opinion at time in the braistorm
Section E: Training, Tools and Time 1 Training not yet performed 2 May be more on Time management 3 Define and measure phases too short 4 Training and tools can be used in our day to day activities - both at work and at home 5 need more training 6 tools very appropriate in implementing the project 7 need more time to perform well in the OE project 8 Some tools are very bulky for the OE project, time has beenn very limited, however the time limit
factor has indirectly push us to complete projects 9 Training was too much in one days- should have been done off site for three days instead of two
consecutive days 10 The training was quite hard for me, this should have also been translated in french
Key learnings
1 It is really valu added when we measure and target improvement based on reliable figures. 2 Fail safe device and Control
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3 Quick, organised way of looking at problems and taking corrective action 4 How to make the work more productive and effective with reduced costs. 5 New Tools 6 New methodology of work were shown. 7 DMAIC and benefits 8 DMAIC tools, time management 9 To challenge my ways of doing things
10 concious and focus on waste 11 8 waste survey improved my views towards processes 12 more used of statistical tools 13 savings for the company 14 usefull tools to identify & solve problems 15 The different tools/graphs used. 16 Usage of new tools to identify and eliminate waste 17 I developed a new mindset in doing and leading projects (Define your problem first/know the root
cause/ tackle the root cause) 18 learnt a lot 19 Problems should be solved through models given
Went well
1 The support of the champion and the willingness to improve. 2 Good spirit / team building 3 Team spirit and having clear and well defined measurable targets 4 Good team spirit. 5 Served as eye opener to Senior Mgt Team on a lot of wastage /non conformances that had long been
communicated but not addressed 6 New way of doing sorting (Type 1 & Type 2) Fast-Track project. 7 better comunications and able to deal with sensitive issues 8 The team spirit 9 all team members were involved in the project
10 Quick response from management, new tools bought 11 involvement of team members and sharing views with other team members concerning projects 12 well attended 13 Brainstorming sessions 14 The fact of implementing the project rapidly i. e just after the diagnosis phase 15 define and control 16 Everybody were involved any different level. 17 Motivation/Communication/Pleasure in doing it/It was a pride in doing it 18 management had time to hear us 19 We had time limits to complete projects
Went wrong
1 The time available to balance usual tasks and tasks specific to project areas.
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2 Commitment of all team members 3 Low cost investments or investments or finace availability 4 Communication issues. 5 The implementation plan was disrupted by bad weather conditions and lack of sorters. 6 fight with time 7 Had to cope with routine workload & OE 8 lack of information to employees, not concious of big waste 9 lack of follow up and conselling during the project
10 too many details 11 Time period 12 We cannot expect the results now. I think we have to give some "adaptataion time" to be able to get
the real results. 13 measurement 14 There were like a competition between some teams 15 The OE coordinator lacked experience in OE model projects. 16 time restraints 17 I had difficulties to understand english
Suggestions for future
1 Giving more time for the improve step as some needed investment (even minor ) but the administrative and implementation takes time like ordering , and installation.
2 Time management and Finance ( investments)related to improvement 3 By giving more appropriate equipment and good information among the company. 4 Improve communication, choice of subjects and teams but mostly keep track over time +
accountability 5 Advanced training should be provided. 6 To have a better OE facilitator full time on site 7 Training sessions, time lapse for implementation of each phase of DMAIC 8 by providing an overview training to employees - awareness of OE 9 support, counselling& Guidance throughout the project
10 reorganise the teams 11 more time to implement OE 12 To concentrate on one dept at a time 13 New people should get involved 14 OE coordinator to coordinate/set on track/monitor/advise/guide on project
develepment/implementation 15 to be allocated only OE projects during its implementation 16 to have a simpler training version of the oe in french or creole
