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Chapter – 4
SUPPLY CHAIN PERFORMANCE MEASUREMENT USING ANALYTIC HIERARCHY PROCESS
METHODOLOGY
This chapter highlights on supply chain performance measurement using one of the renowned modelling technique i.e. Analytic Hierarchy process or AHP. The chapter starts with different supply chain scenarios and identifies eight prime factors that are vital for any of the supply chains. Under each factor, the sub criteria are identified.
Weights are assigned to each sub criterion and an AHP model is developed.
4.1 Performance measurement and supply chain strategy
In today’s scenario, performance measurement of the supply chain is the prime research focus on supply chain management. It is a severe challenge for supply chain enterprises to set up a scientific and comprehensive performance measurement system of the supply chain. This is important as measuring supply chain performance can facilitate a greater understanding of the supply chain, positively influence supply chain players’ behavior, and improve its overall performance [106]. In order to achieve supply chain goal of fulfilling customer orders faster and more efficiently than competitors, a supply chain requires continuous improvements [85]. It demands that effective performance measurements be established, and as such, performance measurement system is required. Many researchers [85, 86, 54 and 37] have proposed measurement systems with performance metrics established from different perspectives. Due to the fact that some measurements are in qualitative format, while others are in quantitative format, it remains a challenge to integrate both types of measurements into one cohesive performance measurement system [54]. Furthermore, there is also a lack of linkage between supply chain strategy and performance measurement. All these challenges will hinder management from making good decisions regarding supply chain, to align with its overall business strategies. AHP is a relatively popular tool for modelling strategic decisions.
2 Studies has suggested link between product characteristics and type of supply chain or strategy such as efficient, quick or lean supply chains and also a model that can be considered as a prescription for choosing the right supply chain i.e. efficient supply chain or a market responsive supply chain, for a certain product. The following is the findings from literature [106]:
Mature and simple products require an efficient supply chain
Mature and complex products require a lean supply chain
Complex products in the growth phase require a lean supply chain
Simple products in the introduction/decline phase require a quick supply chain An efficient supply chain brings products to the market that can broadly be considered as commodities and are often sold in high volumes. Because of the stability of their product flows, such organizations can invest in large and financial- intensive facilities, and improvement initiatives are focussed on operations rather than product innovation.
A quick supply chain can be defined as “products whose demand is difficult to forecast”. These types of organizations invest in manufacturing systems with a high variable vs. fixed cost ratio due to the fact that manufacturing flexibility is very important.
A lean supply chain, deals with a functional product, the demand for which can be forecast (e.g. automobiles). Lean supply chains also have intermediate characteristics:
firms do not only compete on product price or novelty, but simultaneously on price, novelty, quality and customer service. A lean supply chains employs continuous improvement processes in order to eliminate waste or non-value stops across the chain. It employs both lean production and time compression to ensure economical, flexible and responsive operation.
Innovative products focus on capturing new markets and are designed to be acceptable to changing customer demands. This type of product usually has uncertain demand and its design may be unstable. In such cases an agile supply chain can be used, which means using market knowledge and a virtual corporation to exploit profitable opportunities in a volatile marketplace [37]
3 In order to form an effective strategy, a company must understand its core competencies and market requirements. No matter what supply chain strategies are adopted, the performance metrics will help to translate and to enforce the strategy execution.
4.2 Framework for supply chain performance measurement
In our research, we have identified eight commonly used supply chain performance measurement attributes such as cost, time, innovation, quality, flexibility, resource utilization, trust and visibility and linked for different supply chains. A framework for supply chain performance measurement is proposed and as shown in Figure 4.1
Fig. 4.1: Framework for Supply chain performance measurement
For each supply chain, performance measure priority is different and it is as shown in table 4.1.
Table 4.1 Priority of various performance measures by different supply chains.
Sl. No. Type of Supply chain Performance measures priority
1 Responsive supply chain Delivery, quality, Information, flexibility, Innovation and cost
2. Lean supply chain Quality, Cost, delivery, Information sharing and customer service
3. Efficient supply chain Cost, Information, quality
Supply chain strategies
Cost
Time
Innovation
Quality Flexibilit
y Resource
utilizatio n Trust
Visibility
4 4. Agile supply chain Trust, Innovation, flexibility, Information
As seen in the above table, an efficient supply chain will be focussing on cost where as a lean supply chain will be placing more weightage on quality or waste elimination.
With many metrics to be measured, it so happens that the company loses focus on which metrics to measure. They may not be able to identify the more important metrics which will help them to be more competitive. Even though they know some are more important to their overall business strategy and survival, it is hard to know how much degree that the importance is. In order to ensure a company’s measurement system aligned with its strategy, it is critical for us to have an approach to help companies to understand their supply chain strategy.
4.3 Steps for developing AHP model
The AHP model for evaluating firm's long-term overall performance is depicted in Figure 4.2. As an initial or first step managerial objectives are defined. Once the objectives are defined, all relevant and important performance criteria are identified.
These criteria are then structured into a hierarchy descending from an overall objective to various criteria and sub criteria in successive levels. Important guidelines for selecting criteria and constructing the hierarchy structure have been suggested in literature:
The hierarchy structure should represent the problem as thoroughly as possible, but not so thoroughly as to lose sensitivity to change in the elements,
Consider the environment surrounding the problem,
Identify the issues or attributes that contribute to the solution, and
Clarify the necessary participants associated with the problem.
The priority weights of structured criteria are then determined through pair wise comparison to reflect the judgments and relative preferences of different decision makers When there are several levels of criteria and sub criteria, the weight vectors of higher-level criteria are first computed. The weight of the corresponding higher-level criterion is then used to weigh the criteria at the lower level in the hierarchy (composite weight). The procedure is repeated by moving downward along the hierarchy, computing the weight of each criterion at a particular level and using these
5 to determine composite weights for succeeding levels. When multiple decision makers are involved in developing priority weights, achieving consensus may be difficult. Weight analysis can then be used to assess the extent of differences and the potential impact on final decision. In the final step, the criteria, which have the relative higher overall priority scores, will be identified as the firm’s most important long-term overall performance measures and to be analyzed and incorporated in the firm’s long-term strategic planning process.
Fig. 4.2: Steps for developing AHP model
Two sets of specific data: (1) the ranks of each criterion, and (2) the scores for each criterion, are used for the AHP model. Quantitative factors are measured by their corresponding values while the qualitative factors will be measured by the rating scale instrument. The criteria are first compared and prioritized based on the rates of the lowest level in the hierarchy. Qualitative analysis is conducted based on the pair wise comparison relative to each criterion and sub criterion. The numerical rating values of each criterion are normalized considering all other ratings of the criteria at the same level of the hierarchy. The ratings of qualitative criteria are the Eigen values of the pairwise comparison matrix. The results of both quantitative and qualitative analysis will be combined for each criterion at the lowest possible level in the hierarchy. The
Step-7 : Incorporate key performance criteria into firms long term strategic planning process
Step-6 : Analyse and evaluate the impact of all criteria Step -5 : Compute priority weights and ratings of criteria
Step-4: Collect experts opinion comparison and judgement
Step 3: Construct all criteria into a hierarchy structure Step -2 : Identify all relevant and important Performance
criteria
Step - 1 : Establish Objectives (Firm's Long - term Strategy)
6 priority weights of each criterion are the eigen values in the corresponding eigenvector of each matrix. This eigenvector is weighted with the weight of the higher-level element, which is used as the criterion in making the pair wise comparison. If the criteria at a particular level do not have any sub criteria, their priorities remain unchanged in the next level of the hierarchy. The overall priority scores for each criterion are the sum of individual products of rating scores by the corresponding priority weight for each subcriterion from the lowest level in the hierarchy. The consistency of the data may also be investigated during the analysis.
The AHP provides a method to assign numerical values to subjective judgments on the relative importance of each element and then to synthesize the judgments to determine which elements have the highest priority.
4.4 AHP model
For developing the model, eight factors were identified as mentioned previously.
Various criteria’s and sub-criteria’s were identified for each factor. The complete description of all these criteria’s are shown in table 4.2
A high quality computer system/software-Super Decision was used to develop the model and also to conduct a sensitivity analysis of the final ranking list. Figure 4.3 shows the screen shot of the AHP model developed using Super Decision software.
As can been seen from the table 4.2, cost criteria had 8 criteria and each of these criterion had 5 sub-sub criteria. Similarly all of the other seven criteria has sub- criterion as well as sub-sub criteria.
7 Fig. 4.3: Screen shot of the AHP model
8 Table 4.2: Supply chain performance attributes and measurement metrics
Criteria Sub criteria level 1 Sub criteria level 2 Performance measurements
Cost
Distribution
High cost Low cost Medium cost Very high cost
Very low cost
Transportation and handling cost
Manufacturing Labour, rework and maintenance costs, purchased materials, equipment and supplier’s margin
Inventory The work in process and finished goods inventories
Warehouse Associated with allocation from one tier to another
Incentives Incentives and Taxes
Intangible Quality costs, product adaptation or performance costs & coordination.
Overhead Total current landed costs
Sensitivity to long term cost
Productivity and wage charges, exchange rate charges, product design and core competence.
Resource utilization
Labor, m/c, energy and capacity
<30%, 30–50%, 50-70%, 70-90%, 90-100%
Investigate the % of excess or lack of that particular resource within a period.
Time
Lead time Too long, Long, short, medium, very short
The time required once the product began production until the time it is completely processed
Customer response High, low, medium The amount of time between an order and its corresponding delivery Cycle time Too long, long, short,
reasonably short
The time required to begin one complete process Fill rate High, Reasonably- high,
low
The proportion of orders that can be filled immediately.
Flexibility
Labour
Very high, high, low, very low
The number of tasks a worker can perform
Machine The efficiency (time and cost) by using a more flexible machine to the
traditional switching over machine.
Material handling The number of existing paths between processing centers and the variety of material which can be transported along these paths
Operation The number of products which have alternative sequencing plans without
incurring high costs or large changes in performance outcome.
9 Criteria Sub criteria level 1 Sub criteria level 2 Performance measurements
Flexibility
Modification
Very high, high, low, very low
The number and variety of product modification which are accomplished without high transition penalties or large changes in performance outcome.
Volume The extent of change and degree of fluctuation in aggregate output level which the system can accommodate without incurring high costs or large changes in performance outcome.
Mix The time required to produce a new product mix OR
The number and variety of products which can be produced without incurring high costs or large changes in performance outcome.
Delivery The percentage of slack time by which the delivery time can be reduced
Quality
Complain Too many, many,
reasonable, quite low
The number of customer complains registered for a particular time period Defects Very less, less, reasonably
less, more, too many
The number of defects produced from the entire process during a time period
Wastes elimination Few, medium, more The use of various techniques such as 5S to eliminate wastes
Visibility
Time Acceptably- long, short,
too long, reasonably- long,
Time required from when the designer changes his idea to when the product starts being processed in a new way.
Accuracy Low, unexpectedly low, satisfactorily high, very
high
The % waste of wrong products made after the new design is launched
Trust
Consistency Good, reasonably good, very good, inconsistent, no consistency
The % of late or wrong delivery to the next tier which led to an
inconsistent supply. For late delivery, it is the % of time delayed whereas for wrong delivery, it is the % of returned goods.
Innovativeness
Launch of a New product
<20%, 20 – 40%, 40-60%, 60-80%, 80-100%
Compare the number of products launched by a particular company within a period.
New use of technology
T<20%, T20 – 40%, T40- 60%, T60-80%, T80- 100%
The % decrease in time necessary for producing the same product.
10 4.4.1 Pair wise comparison of the parameters
Pair wise comparison is a key step in an AHP model to determine priority weights of factors and provide a rating for alternatives based on qualitative factors. The procedure focuses on two factors at a time and their relation to each other. The relative importance of each factor is rated by a measurement scale to provide numerical judgments corresponding to verbal judgments. The instrument used in this research is a discrete scale, from 1 to 9 with 1 representing the equal importance of two factors and 9 being the highest possible importance of one factor over another, as shown in Table 4.3.
For the model developed relative importance between any two of attributes is assigned by placing a number between the two attributes to represent the relative importance. Questions are designed to ask the supply chain managers or decision makers on the relative importance between any pair of attributes and the number is assigned Questions are asked as “which is more important”, “equally important” or
“less important” between two attributes and by how much. As per the model developed, 28 questions were asked to find out the importance among all the criteria.
Similar questions were asked to find out the relative importance of sub criteria as well as sub-sub criteria.
The relative importance of each of the criteria, sub-criteria and sub-sub criteria are obtained with the discussion with an expert from the automobile industry. The answer given by the expert is further used to calculate the weights or priority
Table 4.3 Pair wise comparison scale
Intensity Definition Explanation
1 Equal importance Two factors contribute equally to the objective
3 Moderate importance of one over another
Experience and judgment favor one factor over another
5 Essential or strong importance
Experience and judgment strongly favor one factor over another
7 Very strong importance An factor is strongly favored and its dominance demonstrated in practice 9 Extreme importance The evidence of favoring one factor over
another is of the highest possible order of affirmation
2, 4, 6, 8 Intermediate values when compromise is needed
11 With the relative importance scale, the companies understand which direction they should head. However, how to measure each attribute still remained a problem not solved. We can use the same AHP approach to analyze all factors related to an attribute. But we need to be able to measure them effectively first.
4.4.2 Calculation of weightages
Once the pair wise comparison is done, the next step is to calculate the weights or priority. The priority of the attributes determines the strategy of the supply chain.
Following are the steps for the calculation of weights:
Step 1: To form a complete pair wise comparison matrix. For each pair of attributes, the relative importance number is placed.
Step 2: To sum up the column values, - The total value of each column is added together to be the denominator.
Step 3: To divide each value by the column total values. This is the important factor for each attribute relative to the corresponding attribute.
Step 4: To average across each row to get weights. After going through the processes, the final weightages of attributes are calculated.
For the model developed, the various weights calculated based on the relative importance of the attributes is as shown in Figure 4.4. It can be seen that ‘time’ has more weightage compared to other attributes. It means that the expert believes that lowering time or being more responsive is very critical in their company and will try their best to shape their supply chain to improve the performance on time. Similarly the various weights calculated for different sub-criteria and sub-sub criteria is shown in the Figure 4.5
The different weights calculated for different sub-criteria and sub-sub criteria are as shown in the Figure 4.4 As the value of consistency ratio (CR=0.04) is less than 0.1, the judgments are acceptable. Consistency ratio (CR) is used to verify the credibility and reasonability of evaluation, and to check whether there is inconsistent causality or conflicts in subjective judgments. If consistency ratio is greater than 0.1, the judgement matrix is inconsistent. To obtain a consistent matrix, judgments should be reviewed and improved by repeating the process. In this case, the process were repeated twice to obtain a consistency ratio less than 0.1
12 Figure 4.4 Normalized weights for attributes
4.5 Results
Based on the weights of different criteria, sub-criteria and sub-sub criteria, the best supply chain is determined as shown in Figure 4.6. It is observed that the best alternative is responsive supply chain.
Figure 4.6 Priorities of the alternatives
0 0.05 0.1 0.15 0.2 0.25
13
0 0.1 0.2 0.3
0.4 Cost subcriterias
0 0.1 0.2 0.3
high low medium Very
high very
low cost sub sub criterias
0 0.05 0.1 0.15
0.2 Flexibility sub criteria
0 0.1 0.2 0.3 0.4 0.5
high low very high
very low Flexibility sub sub criteria
0 0.1 0.2 0.3
Innovativeness sub sub criteria
0 0.1 0.2 0.3 0.4
complain defects wastes elimination
Quality sub criteria
0 0.2 0.4 0.6
Complain sub criteria
0
0.5 Defects sub criteria
0 0.5
few actions
medium actions
more actions
Waste elimination sub criteria
14 Figure 4.5: Priorities of criteria and sub-criteria for AHP model
0 0.1 0.2 0.3 0.4
Plant Energy Machine Man power
Resources utilization sub criteria
0 0.1 0.2 0.3 0.4
Resources sub sub criteria
0 0.1 0.2 0.3 0.4
customer response time
cycle time fill rate Lead time
Time subcriteria
0 0.2 0.4 0.6
high low medium
Response time subcriteria
0 0.1 0.2 0.3 0.4
long r. short short too long
Cycle time sub criteria
0 0.2 0.4 0.6
high low r.high r. low Fill rate sub criteria
0 0.1 0.2 0.3 0.4
a. long long r. long r.short short too long
Lead time sub criteria
0 0.1 0.2 0.3 0.4
Trust - consistency sub criterias
0 0.5
Accuracy sub criteria
15
4.6 Sensitivity analysis
The purpose of performing the sensitivity analysis is to study the effect of the different factors on deciding the best decision option. The final selection of the design concept is highly dependent on the priority vectors attached to the main criteria. The minor changes in the priority vectors might contribute to the major changes in the final ranking. The stability of the ranking under varying criteria weights has to be tested as these priority vectors are usually based on highly subjective judgements. The sensitivity analysis is performed by increasing or decreasing the priority vector of individual criterion, the resulting changes of the priorities and the ranking of the decision can be observed. Therefore, sensitivity analysis provides information on the stability of the ranking. Figure 4.7 shows the sensitivity analysis of the model
Figure 4.7 Sensitivity analysis of the AHP model Summary
In this chapter, the various performance measurement systems of the supply chain are analyzed to identify and highlight some important performance metrics. An AHP (Analytic Hierarchy Process) based methodology is proposed to link a company’s performance measurement to its supply chain strategy. This is to help the company to understand which measurement metrics really matter to their business strategy and goals, and ensure measurement is aligned with their strategy.
