Performance Assessment of Global Supply Chains and Moving...

International Journal of Recent Advances in Organizational Behaviour and Decision Sciences (IJRAOB)

An Online International Research Journal (ISSN: 2311-3197) 2015 Vol: 1 Issue 3

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www.globalbizresearch.org

Performance Assessment of Global Supply Chains and Moving

Towards Optimization of Efforts and Challenges

Jagadeesh Rajashekharaiah,

SDM Institute for Management Development,

Karnataka, India,

E-mail: [email protected]

___________________________________________________________________________

Abstract

Supply chains are assessed for their performance using various metrics and attributes that

help to compare and benchmark the performance across the globe. Several models have been

developed in the past both for generic applications as well for specific supply chains. This

paper develops a model using both the metrics and the challenges faced by the global supply

chains. This allows the performance assessment against a supply chain’s capabilities to meet

the challenges. The paper uses the results of two independent surveys based on their

applicability and comprehensiveness and develops the model. The paper also describes how

these metrics can be used to optimize and compare using a weighted score model and how the

approach can be extended to a generic linear programming model. The objective is to provide

a better decision making model using well established mathematical models and to move

towards optimization.

___________________________________________________________________________

Key words: supply, chains, performance, metrics, optimization, global, assessment, criteria



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1. Introduction

Supply chains constitute the backbone of business and economy and hence have drawn the

attention of academics and practitioners. In the domain of Operations Management, the

supply chain management along with the logistics function is a key area management. Both in

engineering and management degree courses, the students study supply chain management

(SCM) as a core subject and acquires the necessary skills. The proliferation of the retail trade

enabled the SCM function to bloom and spread across various disciplines along with global

presence. The increased attention on supply chain management focusing on issues like supply

chain competitiveness, risk, networking and collaboration, vendor managed inventory, among

other topics, prompts more and more researchers to examine these issues in greater depth.

The SCM function involves a number of people and organizations who interlink and

exchange information, money or goods, and thus a need is felt to assess the supply chain

performance to ascertain success all along the chain. Two terms namely efficiency and

responsiveness, aare considered as the main parameters of assessment. Efficiency indicates

how well a supply chain meets the demand in terms of availability, volume and variety.

Whereas the responsiveness indicates how quickly the supply chain rises to meet the demand,

and ensures stability in spite of the uncertainty. In terms of these two parameters the supply

chain performance is dependent on several drivers, as illustrated by a simple diagram shown

in Figure 1, (Chopra & Meindl, 2007).

Figure 1: Drivers of supply chain performance

However, it is necessary to properly integrate both the internal and the external supply chains

and be inter supporting to ensure supply chain success, (Bratić, 2011), as given in Figure 2.

Figure 2: External and the internal supply chain elements.



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Today, supply chain management along with logistics management is a major topic

considering the evolution and growth of supply chains. The proliferation of outsourcing has

tremendously increased the scope of operations in a supply chain. It is important to note that

the environmental performance measurement models in the context of a global supply chain

throw open many challenges and the supply chains are expected to be robust, (Genovese,

Lenny Koh, Kumar, & Tripathi, 2014).

2. Supply Chain Priorities - Do they align with Operations’ Performance? Operations managers constantly grapple with meeting multiple objectives and thus seek

optimal utilization of the resources. Considering the evolution of the production systems,

starting from handicraft or job systems to mass and flow systems, the operations priorities

varied to accommodate the changing strategies over time. This also prompted the operations

managers to develop "operations strategies" to successfully meet and beat the competition

offered by the global players. It is understandable that the operations managers focused on

key aspects while manufacturing products and services and focused on 'critical success

factors'. These factors traditionally became the priorities and the challenge was to satisfy them

to the maximum possible extent. This also led to the practice of compromising whenever

required because of the inherent conflicts and constraints, (Boyer and Lewis, 2002). The three

fundamental success factors recognized as priorities are: quality, cost, and delivery, not

necessarily in that order but with equal importance. Later, three more factors namely

flexibility, innovation, and speed were added to expand the basket of success factors, (Ward,

et al. 1998). It is obvious that to realize these success factors a supportive supply chain

should exist and enables to realize the targets in each of the success factors considered.

This further requires the cooperation and coordination of all the supply chain partners

involved in the entire network. However, the strategic alignment between the partners is

difficult to measure and analyze, (Vachon, et al. 2009).

3. Measuring the Supply Chain Performance – Literature Review

Measuring the performance of supply chains is a very popular area of research as observed

by the number of publication in the last two decades. While some researchers have proposed

different measures and performance metrics, some others have developed a framework that

enables performance assessment. Right form the time of developing the supply chain for an

industry or a product line or a manufacturing system, performance assessment of supply

chains became a critical issue. As the supply chains form the backbone for the successful

operations it is imperative that their performance is properly assessed with the help of

appropriate metrics, performance goals are set, and monitored for improvement.

What influences the performance of the supply chains performance is to be understood

first and it is stated that two important factors are driving the supply chain performance.



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These drivers of supply chain performance are: logistical drivers and cross functional drivers.

The logistical drivers include facilities, inventory, and transportation. The cross functional

drivers include information, sourcing, and pricing. Considering the strategic importance of the

supply chains, it is essential that the performance is assessed by comparing it with the better

performances, and an early paper (Stewart, 1995) illustrates the benchmarking of the supply

chain performance. But it is essential to remember that there will be several layers of

operations performed and Tan, et al. (1998) suggest assessment at different levels to enable a

better and comprehensive reporting. Beamon (1999) identified three types of performance

measures as necessary components in any supply chain performance measurement system,

and also recommends new flexibility measures for manufacturing supply chains. Several

researchers have developed frameworks to help better assessment of the supply chain

performance. For example, Gunasekaran, et al. (2001) demonstrate a framework for

measuring the strategic, tactical and operational level performance in a supply chain.

Based on trust, terms like Supply Chain Event Management, Supply Chain Process

Management, and Supply Chain Execution Management are used interchangeably. Supply

chain monitoring must start with tight tracking of the many different processes involved in a

supply chain. As products and information flow through different parts of the supply chain, it

is necessary to capture the information and ensure that the end users’ requirements are

satisfied. Supply chain automation is a major trend in this direction that offers a variety of

tools and techniques to monitor and improve supply chain performance, (Huhns and

Stephens, 2001). A hybrid model that suggests both bottom-up and top-down approaches is

considered more suitable for the point of optimizing and thus can be seen as a new method of

assessing the supply chain performance, (Bullinger, Kühner, & Van Hoof, 2002). Several

researchers have investigated the issue of performance measurement considering various

aspects of supply chain include. Chan (2003) introduces five other performance

measurements like resource utilization; flexibility; visibility; trust; and innovativeness.

Shepherd and Günter, (2006) have attempted a critical review of literature pertaining to

supply chain performance evaluation and have given some directions for further research. In

another survey Gunasekaran and Kobu (2007) have provided an overview of measures

applicable for performance assessment of supply chains. Bhagwat, and Sharma (2007)

developed a balanced scorecard for supply chain management (SCM) that measures and

evaluates day-to-day business operations from following four perspectives namely: finance,

customer, internal business process, and learning and growth. Wong, and Wong (2007)

suggest two DEA (Data Envelopment Analysis) models– the technical efficiency model and

the cost efficiency models that are coupled with scenario analysis to enable improved

resources planning decisions. Wong and Lee (2008) while arguing about the complexities in

performance assessment indicate how difficult the assessment could be because the supply



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chain itself is a new field. A hierarchy based supply chain performance measurement system

using the Analytic Hierarchy Process is reported by Xu, et al. (2007). Models like balanced

scorecard, SCOR, ABC, (Activity Based Costing), and standard costing to ascertain the

performance of various aspects of the supply chain, have been recommended by the

researchers, (Rangaraj, Raghuram, & Srinivasan, 2008).

Further, supply chain performance measurement system implementation (Charan et al.

2008) indicates how the system is implemented in a given situation. It is obvious from the

literature review that the performance measures have attracted the attention of the researchers

and it is a challenging task to develop an exhaustive performance measurement system

considering all the factors suggested or recommended across the world by researchers and

practitioners. Brun, et al. (2009) provide a framework for the selection of the right

Performance Measurement System (PMS) for different supply chain typologies.

Several researchers have commented that supply chain performance needs to be assessed

for several reasons, both for assessment of the status or for control and improvement,

(Yildirim Yilmaz & Umit Bititci, 2006), (Cousins, Lawson, & Squire, 2008), (Chia, Goh, &

Hum, 2009), and (Allesina, Azzi, Battini, & Regattieri, 2010). A literature review of papers

related to supply chain measures is provided by researchers who have looked into three

aspects namely (1) framework development, (2) empirical cross-industry research and (3)

adoption of performance measurement systems, (Arzu Akyuz & Erman Erkan, 2010).

Performance measurement of supply chains started off from logistics assessment and today

encompasses the entire chain, that includes functions like information management, flow of

goods and money, and checking validity, relevance and even costs and benefits, ((Sinha &

Kotzab, 2011). It is further mentioned that the performance assessment can also include

financial as well non-financial measures.

A novel application of neighborhood rough-set theory for the identification and selection

of performance measures related to externally derived outcomes is quite novel and finds

interesting applications, (Bai, Sarkis, Wei, & Koh, 2012). Supply chain mangers today have

plenty of metrics to measure the performance and that may create lot of confusion and

difficulty in application. But using many such metrics can result in better and efficient

assessment of performance of supply chains, (Elrod, Susan Murray, & Bande, 2013).

In an interesting argument the researchers (Chelariu, Asare, & Brashear-Alejandro, 2014)

wonder why only economic and operational measures are used to assess the performance and

relational and strategic measures are given less attention. Based on this approach they have

developed a comprehensive framework that recognizes four major categories

of supply chain performance measures: relational; operational; strategic; and economic, and

the authors call the model as “ROSE”. These additional measures obviously expand the scope

of assessment and makes the process more difficult.



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Using marketing and R & D policy as the base for assessing the performance is claimed as

an innovative method of assessment, (Chan, Nayak, Raj, Chong, & Manoj, 2014). Again the

intangibles involved may create difficulties in proper assessment. Supply chain performance

measurement is also done with the help of ontology and Global Supply Chain Forum (GSCF)

reference model, (Teimoury, Chambar, Gholamian, & Fathian, 2014). It is also possible to

look at the performance measures in terms of the benefits accrued to the buyers or customers,

like reduced lead time, more variety and volume, improved responsiveness, and ability to

meet the uncertainties in supply and demand. Since all these issues result in savings the

performance measurement can be a function of the “shared savings” between the buyers and

sellers, (Chopra & Meindl, 2015). It is important to develop KPI’s (Key Performance

Indicators) for each segment or part of the supply chain and measure both financial and

nonfinancial aspects and carry out benchmarking with better performers.

A performance measurement network was created for the needs of manufacturing industry

based on case research method which involves the key elements for

the measurement framework as time, profitability, order book analysis and managerial

analysis, (Sillanpää, 2015). It is really interesting to note that the supply chain performance

may have to be assessed and what if no data exists. This is the new assumption under which

supply chain is assessed, (Tavassoli, Farzipoor Saen, & Faramarzi, 2015). In a study

conducted in the automobile manufacturing industries located in the National Capital Region

of India, several enables have been identified and the vagueness of field expert's judgments

has been reduced using fuzzy decision making trial and evaluation laboratory (fuzzy

DEMATEL) approach, (Tyagi, Kumar, & Kumar, 2015). A review of papers dealing with

sustainable supply chains’ performance measures based on seven different measures is

recommended by some authors who suggest a comprehensive framework, (Tajbakhsh &

Hassini, 2015). The logistics service supply chain’s performance measurement plays a key

role and based on the overall measures, the indices have been developed, (Gong & Yan,

2015). In spite of all these assessment methods and availability of metrics, it is imperative that

the performance assessment of supply chains could range from a simple calculation of

efficiency to a complex method that tries to capture all the constituent elements.

4. Global Supply Chains - Challenges and Issues

Since the dawn of globalization in the early nineties, researchers across all disciplines have

studied the impact of going global and the associated success factors. The term globalization

is now deeply rooted in everyday business and general talk. Wikipedia (www.wikipedia.com)

defines globalization as “the process by which regional economies, societies, and cultures are

integrated through a global network of communication, transportation, and trade. The term is

used to refer specifically to economic globalization: the integration of national economies into



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the international economy through trade, foreign direct investment, capital flows, migration,

and the spread of technology, (Bhagwati, 2004). Globalization is usually recognized as being

driven by a combination of economic, technological, socio-cultural, political, and biological

factors, (Sheila, 2004).The term can also refer to the transnational circulation of ideas,

languages, or popular culture through acculturation. Alli, et al. (2007) have given a good

interpretation of globalization and its effects. According to them globalization is the

interaction between economies, technologies and politics which creates an environment that

reduces state regulation of the market promoting a more dominant role for large multinational

corporations.

The advent of globalization made the operations mangers to look beyond the local

boundaries and start getting inputs from several places across the world and to look at the

whole world as their markets. Global supply chains with inbound and/or outbound logistics

are quite common today as the suppliers and customers could be located anywhere in the

world. Secondly, it is prudent to look for suppliers and customers far beyond the local

boundaries to realize several distinct advantages in terms of quality, quantity, price, variety,

currency fluctuations, regional policy matters, and to build balanced networks. On the other

hand global supply chains also have their limitations and challenges. A survey conducted by

McKinsey reveals the interesting responses as depicted in Figure 3. This paper proposes to

measure the supply chain performance against these perceptions to construct the supply

chains to meet these challenges. This ensures that the assessment of the supply chains are

with reference to the actual performance parameters taking into mind the challenges and the

realities across the globe.



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Figure 3: Percent respondents agreeing to a given aspect of challenges

(Source: http://www.mckinsey.com/insights/operations/

he_challenges_ahead_for_supply_chains_mckinsey_global_survey_results)

5. Mapping of Global Supply Chain Challenges and Supply Chain

Performance Measures Quality, cost, and delivery are the primary key metrics anytime applicable to assess the

supply chain performance. In addition as already informed, flexibility, innovation and speed,

constitute the expectations from the supply chains. Flexibility and speed refer to several sub-

factors like flexibility in terms of volume, variety, lead times, pricing, batch size, delivery

modes, packaging, distance traveled, shelf life and ability to handle last minute changes, and

several others. Similarly, speed of operations in terms of fast delivery, rapid changes in



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design, ability to introduce new practices quickly, improved responsiveness, faster

turnarounds in inventory, and above all faster communication capabilities, will be helpful for

a comprehensive assessment.

Considering the moderate amount of literature dealing with the performance assessment of

the supply chains, the author proposes to adopt the model suggested by Anvari, et al. (2011)

based on the following considerations:

The proponents of this model have examined the various models of performance

assessment developed by different authors and have given those factors due consideration

Firstly, the affecting factors on SC performance are addressed on the basis of

literature and elites' opinions; and later industrial connoisseurs' ideas were gathered to

identify the factors to be included in the questionnaire

The survey reveals the important factors

The list of factors is modified to reflect the changes in the environment

5.1 Mapping of Factors and the Challenges

The next step involves the mapping of the list of factors given by Anvari, et al. (2011) and

the challenges given by the McKinsey studies by Gorey, Jochim, and Norton. (2015) to reveal

how the assessment can become more relevant to the industry requirements. Further based on

the respondents' perceptions and comments, the lists are ranked from most preferred to least

preferred parameters. Table 1 shows the assessment factors arranged in decreasing order of

importance. (The ranks below27 are not part of the ranks given by the respective authors but

included here for the completeness of the earlier list, and the ranks are just serially given).

Later using the McKinsey's report by Gorey, Jochim, and Norton. (2015), Table 2 shows the

challenges and the corresponding ranks.

Table 1: Assessment factors and corresponding ranks (Anvari, et al. (2011)

Assessment factors Rank

Purchase order cycle time 1

Order entry methods 2

Quality of delivered goods 3

Supplier ability to respond to quality problems 4

Buyer-supplier partnership level 5

Cycle Time 6

Delivery performance 7

Rejection rate 8

Effectiveness of distribution planning schedule 9

Customer satisfaction 10

Range of product and services 11

Order responsiveness 12

Fill rate 13



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Warehouse cost 14

Accuracy of forecasting techniques 15

Lead time 16

Information sharing and availability 17

Frequency of delivery 18

Supplier assistance in solving technical problems 19

Flexibility to meet particular customer needs 20

Total Cash Flow Time 21

Supplier cost saving initiatives 22

Delivery reliability 23

Quality of delivery documentation 24

Inventory flow rate 25

Product development cycle time 26

Delivery lead time 27

Effectiveness of delivery invoice methods 28

Level of customer perceived value of product 29

Level of supplier's defect free deliveries 30

Master Production Scheduling 31

Rate of Return On Investment 32

Rate of unfilled orders 33

Variations against budget 34

Table 2: Global challenges ranked in Gorey, T., Jochim, M. and Norton, S. (2015)

Global Challenges Rank

Increasing volatility of customer demand 1

Increasing consumer expectations about quality 2

Increasing cost pressure in logistics/transportation 3

Increasing pressure from global competition 4

Increasing volatility of commodity prices 5

Increasingly complex patterns of customer demand 6

Increasing financial volatility 7

Increasingly global markets for labor and talent 8

Increasing complexity in supplier landscape 9

Growing exposure to differing regulatory requirements 10

Increasing environmental concerns 11

Geopolitical instability 12

5.2 Observations and remarks

The first challenge in Table 2 pertains to the "Increasing volatility of customer demand"

which refers to the unpredictability of the demand and makes the forecasting difficult. This in

turn demands applying sophisticated methods of forecasting to improve the accuracy. But,



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from Table 1, "Accuracy of forecasting techniques" is ranked at 15 thereby showing a lesser

preference. This is an indication of mismatch between what the customers perceive and the

experts opine. Complex pattern of customer demand is a challenge, ranked at the middle of

the list almost corroborating to the lesser preference to the forecasting accuracy. However,

the conventional factors like quality, cost, and delivery, rank higher in both the customers' list

and list of the challenges. Similarly, factors like flexibility, innovation, and time related

parameters, are ranked almost at the same level of preferences in the two lists. However, the

two lists do not relate in any way in terms of the people surveyed or place of survey or

industries or the profile of the respondents. Hence, the lack coherence between the two lists

need not surprise in general, nevertheless shows some connectivity across the factors.

6. Weighted Score Model using the Multiple Criteria of Performance

Assessment Whenever a certain decision is based on multiple criteria a simple approach would be to

use a weighted score model. In the case of performance assessment of supply chain based on

factors as shown in Table 1, there are 34 factors established and hence a weighted score

model would be appropriate to simplify the decision of comparing the performance of the

same supply chain over a period of time or comparing a set of supply chains using similar

criteria. The first step in using the weighted score model is to convert the ranks to

corresponding weights. The criteria weights are developed by using the approach suggested

by Alfares and Duffuaa (2006), where a linear relationship specifies the average weight for

each rank, assuming a weight of 100% for the first-ranked (most important) factor. For any

set of n ranked factors, the percentage weight of a factor ranked as r is given by:

W(r, n) = 100 – Sn (r – 1)

Where, Sn = 3.19514 + (37.75756/n), 1<= r <= n, and r and n are integers

In the present case n = 34 and using a spreadsheet the weights are calculated and shown in

Table 3 along with their ranks.

Table 3: Rank and weights of the factors

Assessment factors Rank Weight in %

Purchase order cycle time 1 100

Order entry methods 2 95.69434353

Quality of delivered goods 3 91.38868706

Supplier ability to respond to quality problems 4 87.08303059

Buyer-supplier partnership level 5 82.77737412

Cycle Time 6 78.47171765

Delivery performance 7 74.16606118

Rejection rate 8 69.86040471

Effectiveness of distribution planning schedule 9 65.55474824

Customer satisfaction 10 61.24909176

Range of product and services 11 56.94343529



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Order responsiveness 12 52.63777882

Fill rate 13 48.33212235

Warehouse cost 14 44.02646588

Accuracy of forecasting techniques 15 39.72080941

Lead time 16 35.41515294

Information sharing and availability 17 31.10949647

Frequency of delivery 18 26.80384

Supplier assistance in solving technical problems 19 22.49818353

Flexibility to meet particular customer needs 20 18.19252706

Total Cash Flow Time 21 13.88687059

Supplier cost saving initiatives 22 9.581214118

Delivery reliability 23 5.275557647

Quality of delivery documentation 24 0.969901176

Multiplying the regular scores by the weights, the weighted scores can be established and

the composite score is calculated taking up the sum of all the weighted scores. The weights

assigned by the model follow a linear decrement. However, this model starts tapering to lower

values and eventually reaches close to zero when there are 24 factors. Another approach to

assign weights could be to use "learning curve" theory, which starts assigning weights from

100 to the first value and then decrements the values in a negative exponential manner.

However, these models are definitely worth examining further in order to justify the

methodology of assigning weights. For any model chosen variance around mean is to be

established and any model selected should be having a minimum deviation from the central

value. This paper will not delve into the details as it would demand a separate analysis.

Looking at the factors and to simplify the process of optimization, the top three priorities

are considered as shown in Table 4. The second factor is common across both the past and

future priorities.

Table 4: The top three priorities over the past three years and the next five years

Rank Rank over the past three years Rank over the next five years

1 Increasing volatility of customer demand Increasing pressure from global

competition

2 Increasing consumer expectations about

quality

Increasing consumer expectations about

quality

3 Increasing cost pressure in

logistics/transportation

Increasingly complex patterns of

customer demand

7. Moving towards Optimization

The optimization process of the performance measures here is shown as generic model and

proposes the application of linear programming to achieve the objectives. The new challenges



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considered are 12 in number and are considered vital for the sustainability of the supply

chains. Table 5 illustrates the new challenges and their weights.

Table 5: New challenges and the corresponding weights

New Challenges Rank over the

next 5 years Weights

Increasing pressure from global competition 1 W1

Increasing consumer expectations about quality 2 W2

Increasingly complex patterns of customer demand 3 W3

Increasing cost pressure in logistics/transportation 4 W4

Growing exposure to differing regulatory requirements 5 W5

Increasing financial volatility 6 W6

Increasing volatility of commodity prices 7 W7

Increasingly global markets for labor and talent 8 W8

Increasing environmental concerns 9 W9

Increasing volatility of customer demand 10 W10

Increasing complexity in supplier landscape 11 W11

Geopolitical instability 12 W12

Considering only the top three priorities over the next five years, we can say that the

following challenges need to be addressed on top priority. Thus the weights can be assigned

on a scale based on the severity, like for example:

W1:W2:W3 = 0.5:0.3:0.2 or 50, 30, 20% and this can be interpreted as shown in Table 6.

Table 6: Efforts required and expected returns for the challenges

Challenge Required Return

Increasing pressure from global competition At least 50% of the total efforts R1

Increasing consumer expectations about quality At least 30% of the total efforts R2

Increasingly complex patterns of customer demand At least 20% of the total efforts R3

Let E1, E2, and E3 represent the individual efforts or the resources in a generalized way,

and R1, R2 and R3 be the corresponding returns associated with the efforts. The efforts

required or resources to be used can be further expressed in terms of total budget, labor time,

number of persons involved, and other practical considerations.

Here for illustration purpose only three challenges are taken but the model can be extended

to include other challenges. Then the proposed linear programming model is as follows:

Maximize: R1*E1 + R2*E2 + R3*E3

Subject to:

E1 >= 0.5 (E1 + E2 + E3)



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E2 >= O.3 (E1 + E2 + E3)

E3 >= 0.2 (E1 + E2 + E3)

This means any effort represented by E, should not exceed some percent of the total

combined efforts. This automatically ensures that the efforts spent are not channelized in only

one direction rather in all possible directions and forms. The obvious difficulty here is to

express everything in numbers and quantifying the return and the efforts in common terms.

Thus some approximations would be required.

8. Conclusions and Recommendations

Performance assessment of supply chains is considered a vital aspect sine the last two

decades because of the immense importance of the supply chains in the global economy and

also due to the proliferation of the global supply chains. Many researchers and professional

bodies have developed a variety of measures to assess the performance of supply chains and

most of these assessment parameters seems to be agreeing with the conventional measures

that existed right from the days of prioritizing the operations requirements. In this paper the

factors as obtained through a comprehensive survey and the challenges identified by a well-

known research based professional agency, have been mapped to examine how the

assessment can be made with respect to the challenges. This serves the objective of assessing

against the challenges faced and hence tests the ability of the supply chains in meeting those

challenges. However, the model proposed here is limited by the fact that the two lists

containing the factors and the challenges are not based on the survey conducted on common

respondents nor the two lists have any other common factors, and hence not congruent. But

the paper demonstrates the methodology to lead to a better model compared to simply ranking

the factors and converting the values to a single score say using the sum of the weighted

scores. The optimization model is conceptual and needs further refinement. It is also to be

noted that further research on similar lines can be done with a common participating group of

respondents repeated several times which will lead to reliable results.

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