Benchmarking Internal Supply Chain Performance: Development of a Framework.
This article develops performance measures that can be computed through publicly available information. The article describes an approach for benchmarking using these performance measures and demonstrates how meaningful results may be derived from this exercise. By following this framework, a firm can identify areas of opportunity for improvement in its internal supply chain. Further, the framework can help to identify specific reasons behind the performance levels in the internal supply chain and stimulate performance improvement. To illustrate the framework, it is applied to the paint industry. The framework provides meaningful results for the firms in the industry.
There has been an increased awareness in recent years regarding the role and potential of supply chain management in supporting corporate goals. Management theorists as well as practitioners have addressed the problem of how to improve supply chain processes. This article is confined to a discussion of the internal supply chain, defined as the flow of materials from the procurement of raw materials to the delivery of finished goods to the customers of an organization (Krajewski 1990).
For an improvement to take place, it is essential that a firm use performance measures appropriate to its business. Subsequently, it may carry out a benchmarking exercise to identify "best-performance" firms and its own relative position. At the next level, the firm may probe further to identify avenues for improvement.
Performance measurement is an essential and powerful management tool, but its power relies on the ability to identify those measures that drive supply chain success. Benchmarking is one way of assessing performance based on these measures (Bogan and English 1994). Smeltzer and Carr (1999) tested the relationships among benchmarking, strategic purchasing, and firms' performance and found that benchmarking is positively related to firms' performance and strategic purchasing. According to this study, firms do obtain valuable comparison information and have the opportunity to learn if they use the benchmarking information. This study also emphasizes that future research should help to identify specific practices that enable better performance.
This article develops performance measures that can be computed through publicly available information and demonstrates how benchmarking these measures may be useful to a firm. The performance measures are based on the material flow and proportionate cost addition at various stages within the internal supply chain. Since only information available in the public domain is used in these measures, some internal cost data, such as ordering costs, are not included. This is a limitation of the study.
This article presents a framework for benchmarking using these performance measures and demonstrates how meaningful results may be derived from this exercise. The results of using performance measures in the paint industry are presented along with selected example cases.
The framework for benchmarking using the techniques developed in this article is shown in Figure 1. The following paragraphs discuss each stage.
Stage 1 -- Performance Measures
The performance measures fall into two categories:
1. Opportunity analysis tool. This tool allows firms to identify avenues for improvement in their internal supply chain processes.
2. Diagnostic tool. This tool helps firms to focus on specific areas of the internal supply chain that require attention.
The performance measures composing these tools serve as the tests to analyze core internal supply chain processes and policies and to identify decision alternatives that could lead to improvements in performance. These tools and the related performance measures are described later in the article.
Given the above considerations, specific industry types are initially identified based on the product homogeneity. This is followed by identifying the firms that fall into each industry type.
Stage 2 -- Computing Performance
In the next stage, the firm should select performance measures depending on its competitive focus and market niche. For instance, a firm competing on cost efficiency would select a measure that would allow it to capture the internal supply chain costs. Likewise, a firm competing on speed of customer responsiveness would select measures related to materials flow. The central concern is that the strategic imperatives of the firm drive the selection of an appropriate performance measure for benchmarking. The benchmarking exercise may be carried out at this stage on the set of firms in the industry using this performance measure. This would enable the identification of firms with "best performance" in terms of the selected measure.
Stage 3 -- Best Practices
At the next stage, one may probe further for identifying the practices and policies of the firms that enable them to perform better. For this purpose, the analysis using the performance measures may be combined with qualitative information on these firms. The qualitative information on the "best-performance" firms is obtainable from business periodicals and other sources in public domain.
Stage 4 -- Performance Improvement
After examining the qualitative information, it can be related to the specific performance measures of the firms. Such an exercise would allow one to discover what bearing the performance measures have on specific practices and policies. In this way, management can identify practices and policies that drive superior performance. This insight itself is quite important since it provides concrete evidence of a practice or a policy enabling higher performance. Efforts may then be made to study such practices further and implement them with appropriate adaptation.
To demonstrate the framework, publicly disclosed financial performance data, compiled and distributed in the PROWESS databases maintained by the Center for Monitoring Indian Economy (CMIE), were analyzed. The advantage of this approach lies in the fact that it allows benchmarking using public information. This information is available in financial statements of annual reports and in business periodicals. Such information is also obtainable from databases like PROWESS (India) and COMPUSTAT (United States) that provide information in compiled form. One can obtain, through these databases, information such as background, share prices, sensitivity index, financials, product profile, raw materials consumed, and accounting policies of the firms. The data used in this study are shown in Figure 2.
The benchmarking approach proposed in this article is applied to one major industry over the three-year period 1998-2000. The section on "Case Study" contains the results of this analysis. Firms with better performance in the industry segment are identified based on the measures selected. Next, information from the business press related to the policies and strategies of these firms is analyzed. This helps to identify the reasons that these firms perform better. The next section provides a detailed description of the diagnostic tools and performance measures.
OPPORTUNITY ANALYSIS TOOL
The opportunity analysis tool is used to ascertain how efficiently firms are managing the internal supply chain processes. Financial measures are used to gauge the firm's operational performance (Chandra 1997). The objective at this stage is to identify the length (in days) of various stages in the internal supply chain and draw a profile of the proportional cost addition during these stages. The opportunity analysis tool is developed as follows:
1. Calculate the length (in days) for which the raw material, work-in-process (WIP), and finished goods remain in the firm.
2. Calculate the cumulative cost addition for the raw material, WIP, and finished goods stages.
3. Calculate the proportionate cost addition at various stages. The information obtained in number 2 above is utilized for this purpose. The cumulative cost at each stage is normalized to obtain the proportionate costs (this is referred to as the normalized costs hereafter).
4. Make a cost profile of the internal supply chain that maps the normalized costs vis-a-vis the time spent in the raw material, WIP, and finished goods stages.
The methodology to develop this profile is explained next.
Calculating the Length of Various Stages of the Chain
The following formulae are used to calculate the length of the various stages in the supply chain:
(1) [DRM.sub.i] = [RM.sub.i] * 365/[CRM.sub.i]
i = index for time period which is taken as a year (i.e., 365 days)
[DRM.sub.i] = days of raw material inventory for time period i
[RM.sub.i] = raw material inventory for time period i
[CRM.sub.i] = cost of raw material for time period i
(2) [DWIP.sub.i] = [SFG.sub.i] * 365/[CP.sub.i]
[DWIP.sub.i] = days of work in process inventory for time period i
[SFG.sub.i] = semifinished goods inventory for time period i
[CP.sub.i] = cost of production for time period i
(3) [DFG.sub.i] = [FG.sub.i] * 365/[CS.sub.i]
[DFG.sub.i] = days of finished goods inventory for time period i
[FG.sub.i] = finished goods inventory for time period i
[CS.sub.i] = cost of sales for time period i
Calculating the Cost Addition at Various Stages
1. Cost at the beginning of the raw material stage. This is the total cost of raw materials consumed during the accounting period. It also includes incidental expenses for procuring raw materials. This value is directly observable from financial statements and is represented by cost of raw materials (CRM).
2. Cost addition in the raw material stage. These are the costs associated with holding raw material inventory and are given by:
(4) [sigma][(RM).sub.t] = [RM.sub.t] * [ICC.sub.t]
[sigma][(RM).sub.t] = cost addition in the raw material stage for time period i
[ICC.sub.t] = inventory carrying cost percentage for time period i
[RM.sub.t] = raw material inventory for time period i
A major part of inventory carrying cost rate comprises the cost of capital for the firm, though other costs (costs of obsolescence, deterioration, warehousing, insurance, stock losses, and so on) may also be included. In this study, the cost of capital for a firm is used as its inventory carrying cost rate for two major reasons. First, a major part of inventory carrying cost rate consists of cost of capital, and second, the cost of capital can be estimated from financial statements and other reports available in public domain. In this article, a standard methodology is used for computing cost of capital that uses the return on equity and debt (Brealey and Myers 1991).
3. Cost at the end of the raw material stage. This represents the expenses up to the end of the raw material stage.
(5) [CRMS.sub.i] [CRM.sub.i] + [delta][(RAV).sub.i]
[CRMS.sub.i] = cost at the end of the raw material stage
In the next stage, the cost at the end of the WIP stage is obtained and then the cost addition in the WIP stage is computed. This is done because that cost at the end of the WIP stage is directly observable from the financial statement. The procedure is explained below.
4. Cost at the end of the WIP stage. This is the cost of production that is inclusive of the total raw material expenses and the cost of transforming raw materials into finished goods. This figure is directly observable from the financial statements and is termed as the cost of production. Therefore,
(6) [CWIPS.sub.i] = [CP.sub.i]
[CWIPS.sub.i] = cost at the end of the WIP stage
5. Cost addition in the finished goods stage. These are the costs associated with holding finished goods inventory and are given by:
(7) [delta][(FG).sub.i] = [FG.sub.i] * [ICC.sub.i]
[delta][(FG).sub.i] = cost addition in the finished goods stage for time period i
6. Cost at the end of the finished goods stage. This represents the expenses up to the end of the finished goods stage.
(8) [CFGS.sub.i] = [CWIPS.sub.i] + [delta][(FG).sub.i]
[CFGS.sub.i] = cost at the end of the finished goods stage
In the next step, the costs are normalized for each company as follows:
(9a) Normalized cost of raw materials = [CRM.sub.i]/[CFGS.sub.i]
(9b) Normalized cost at the end of the raw material stage = [CRMS.sub.i]/[CFGS.sub.i]
(9c) Normalized cost at the end of the WIP stage = [CWIPS.sub.i]/[CFGS.sub.i]
(9d) Normalized cost at the end of the finished goods stage = [CFGS.sub.i]/[CFGS.sub.i]
This normalization ensures that for all of the companies, the normalized cost at the end of the finished goods stage is 1.0. The above process is shown for two companies in Tables I and II.
Making a Cost Profile for the Companies
The calculation of normalized costs for each stage leads to the creation of a cost profile for each company. Company A and Company B are used to illustrate the process. The following shows the length of various stages for Company A and Company B.
Length of Length of raw material Length of finished stage WIP stage goods stage Total length Company A 38 12 38 88 Company B 52 10 30 92
The cumulative lengths are:
Length at Length at Length at the the end of raw the end of end of finished material stage WIP stage goods stage Total length Company A 38 50 88 88 Company B 52 62 92 92
The maximum cycle is 92 days for Company B. This number is used to recalculate the starting times for each stage as follows:
Length at Length at the end of Length at the end of raw material the end of finished goods Start day stage WIP stage stage Company A (42-38) (54-12) (92-38) = 4 = 42 = 54 92 Company B 0 52 62 92
A cost profile can be constructed with the revised duration of the stages as the X-axis and the normalized costs as the Y-axis (see Figure 3). A firm can compare its own profile with that of the competitors and the industry aggregate to ascertain where it stands in terms of normalized costs and length of time the material stays in the internal supply chain.
The diagnostic tool helps firms to identify specific areas of the internal supply chain that require attention. Using the diagnostic tool involves the following:
* Analysis of the internal supply chain management efficiency
* Analysis of the internal supply chain working capital productivity
Analysis of the Internal Supply Chain Management Efficiency
Total inventory carrying costs and distribution costs are considered to be the components of the internal supply chain management costs. The internal supply chain inefficiency ratio is calculated as:
(10) [CI.sub.i] = [I.sub.i] * [ICC.sub.i]
(11) [ISCC.sub.i] = [DC.sub.i] + [CI.sub.i]
(12) [ISCI.sub.i] = [ISCC.sub.i]/[NS.sub.i]
[ISCC.sub.i] = Internal supply chain management costs for time period i
[DC.sub.i] = distribution costs for time period i
[I.sub.i] = inventory for time period i; the aggregate figure for the inventory (raw material, WIP, finished goods) is taken and is not decomposed into the component parts
[CI.sub.i] = cost of holding inventory for time period i
[ISCI.sub.i] = internal supply chain inefficiency ratio for time period i
[NS.sub.i] = net sales for time period
This measure is termed the internal supply chain inefficiency ratio since the internal supply chain management costs would be higher if the operations are not optimal and there is an inefficiency in the system. This ratio provides an insight into the internal supply chain management efficiency of the firm and is based on the following two premises:
1. Firms that manage their internal supply chain processes in an efficient manner will have lower levels of inventory. Lower inventory is achieved by better purchasing, planning, manufacturing, and distribution processes.
2. The distribution costs include the expenses incurred in transportation and material handling. To have an efficient and flexible distribution, firms try to achieve optimization in activities related to transportation, loading, unloading, and warehousing.
Analysis of the Internal Supply Chain Working Capital Productivity
This analysis provides an insight into the partnering activities of the firm with suppliers and distributors. The literature has emphasized the importance of cooperative relationships with suppliers and distributors. One such study examined the development of suppliers using a process-oriented approach (Hartley and Jones 1997). Another study in this area investigated the linkage of sourcing strategies with specific business units (Narasimhan and Carter 1998). These studies have suggested that the firms need to objectively determine avenues for improvement in the transactions processes with their suppliers and distributors.
Consider the following components of internal supply chain working capital:
1. Accounts receivable. Termed as sundry creditors in the public databases. These are essentially the distributors and the dealers who buy the products and owe payment to the firm.
2. Inventories. A composite of raw materials, semifinished goods, and finished goods inventories.
3. Accounts payable. Termed as sundry debtors in the public databases. These are essentially the suppliers of raw materials to whom the firm owes payment.
These asset and liability forms are short-lived and are swiftly transformed into other forms. In addition, their life span depends upon the extent to which the basic activities -- procurement, production, distribution, and collection -- are synchronized and effectively carried Out. For instance, if the procurement, production, and distribution were totally synchronized, the need for inventories would be almost eliminated. By the same logic, if all customers paid cash, then accounts receivable would be eliminated.
In a business setting, most transactions are carried out on credit. The tool discussed in this section captures the performance affected by inventories, accounts receivable, and accounts payable. In a competitive economy, firms have to allow credit to attract sufficient business. This, in turn, forces them to delay their payments in order to finance their operations. Consider the case when the products are sold on credit. This depletes inventories and increases accounts receivable. To replenish the inventories, the firm commences production, for which it buys raw materials. If the raw materials are bought on credit, accounts payable increase. Under these circumstances, the working capital components affect the procurement, production, and collection activities and are, in turn, affected by them (Mehta 1974). For the purpose of analysis, the interaction of accounts receivable, inventories, and accounts payable should be considered simultaneously.
Large firms need to consider that their suppliers and distributors incur different costs of capital. Normally, small firms incur high costs of capital. Long credit periods for them are very costly and these costs are ultimately passed on to the customers, Therefore, it is mutually beneficial for the suppliers, producers, and distributors to ensure better integration and increase cost efficiency (Jensen and Meckling 1976). For instance, a firm that delays paying invoices for an extended period of time is receiving an interest-free loan from the supplier. In such cases, quicker payments must be negotiated (Lewellen and Johnson 1972; Smolen 1997). A conceptual base for this analysis is provided in Table III.
The policies regarding credit allowed to the dealers and distributors are also affected by lost sales, experience with bad debts, and aging of accounts. Stringent policies for accounts receivable may reduce the volume of receivables but result in lost sales. Conversely, indiscriminate credit extensions and high finished goods inventory would result in decreased lost sales but a larger investment in receivables and an increase in bad debt. This discussion points to the need for arriving at a trade-off between different components of working capital. Table IV lists a few critical scenarios that may exist in a given business setting and the related repercussions that may emanate from having different combinations of working capital components. Using this approach, it would be necessary to analyze the components of the working capital and their interactions with each other as well as with the lost sales for the all of the partners, i.e., the suppliers, the firm, and the distributors.
At this stage, the objective is to analyze the impact of inventory, accounts receivable, and accounts payable on the performance of the firm. The analysis needs to simultaneously consider the components of internal supply chain working capital as well as its productivity. The internal supply chain working capital is calculated as follows:
(13) [ISWC.sub.i] = [I.sub.i] + [AR.sub.i] - [AP.sub.i]
[ISWC.sub.i] = internal supply chain working capital for time period i
AR = accounts receivable from the dealers/distributors for time period i
[AP.sub.i] = deferral of payments to the suppliers for time period i
Subsequently, the internal supply chain working capital productivity is measured as:
(14) [ISWCP.sub.i] = [NS.sub.i]/[ISWC.sub.i]
[ISWCP.sub.i] = internal supply chain working capital productivity for time period i
These tools provide the following set of performance measures:
* Total length of the stages (days of raw material inventory + days of work-in-process inventory + days of finished goods inventory). The "best-performance" firm would have the minimum total length of the stages.
* Internal supply chain inefficiency ratio. This ratio would be low for the firms with better performance.
* Internal supply chain working capital productivity. The analysis of firms on this metric would be based on the levels of inventory, accounts receivable, and accounts payable.
This framework has evolved over a period of time through studies done in the paint, automobile, fertilizer, and cement industries. In this article, the paint industry is used to describe the framework and validate the performance measures. The following discusses the results of using the performance measures in the paint industry and presents explanations for the case examples of firms in this industry.
In the paint industry, cost efficiency is an important consideration for success; therefore, the internal supply chain management costs are an appropriate basis for selection of the "best-performance" firms. This measure was computed for all 28 companies in the paint industry, and the three firms that have the lowest internal supply chain management inefficiency ratio were identified. The range of performance for the firms in the industry is presented in Table V.
The selected firms are called "best-performance" firms in terms of internal supply chain management inefficiency ratio. However, a firm using this framework would choose an appropriate measure based on its strategy. Identification of a good benchmark target (performance measure) would require consideration of the firm's market niche and competitive focus. In this sense, there is a need to consider specific strategies followed by the firm while identifying appropriate measures. In the next stage, all of the other performance measures may be computed for this subset of firms for a number of years to allow comparison over time. As outlined in the framework, analysis of the industry aggregate as well as three "best-performance" companies was done for the years 1997-1999. Again, the weighted average cost of capital for each company was calculated from publicly available information (Brealey and Myers 1991). In the next section, the results of the case studies are reported.
Table VI shows the inventory holding periods for the three firms and Figure 3 presents the cost profiles for the three firms and the industry aggregate for the year 1999. The following conclusions can be drawn from Figure 3 and Table VI:
1. Company A has the least days of raw material inventory. Also, this company has the lowest aggregate length, i.e., the composite figure including days of raw material, WIP, and finished goods.
2. Company B has the least days of finished goods inventory. However, the product stays as raw material for the longest time in Company B.
3. Company C has the longest days of finished goods inventory but the least days as WIP.
4. The aggregate industry profile shows that for the industry as a whole, the product stays in finished goods inventory for a long time and the companies bear significant cost in keeping the product as raw material.
The results suggest that the companies strive to bring down the level of raw material and finished goods since there is no value added in these stages and the company has to bear the inventory carrying cost. Company A seems to be successful in this objective. However, the product stays in the WIP stage for the longest time for this company. This suggests that the company attempts to delay the product differentiation to the last stage of the production process.
Analysis of Internal Supply Chain Efficiency
Table VII shows the working capital productivity for the three firms.
Note that Company A has been successful in bringing down the internal supply chain inefficiency ratio from 0.07573 in 1997 to 0.07435 in 1999. For Company C, this ratio has decreased from 0.08153 in 1997 to 0.07939 in 1999. Likewise, the ratio has decreased for Company B from 0.7049 to 0.06961. The industry aggregate ratio has also decreased. This suggests that the industry in general and Company C in particular seem to be following an integrated logistic strategy, thereby achieving cost efficiency and optimization in the internal supply chain processes. Company B has managed to achieve the highest increase in sales while, at the same time, reducing the internal supply chain inefficiency ratio. It may be further observed that the duration for which the product stays in the finished goods stage was the least for Company B.
Internal Supply Chain Working Capital Productivity Analysis
Table VIII shows the breakdown of working capital for each of the three companies.
The following conclusions can be drawn from Tables VII and VIII:
1. Company A's working capital productivity has increased steadily over the years, but its accounts payable also have increased substantially from 55.61 in 1997 to 101.9 in 1999. One can infer from this result that the internal supply chain working capital productivity increase is attributable to the deferral of payments to the suppliers.
2. For Company B, the internal supply chain working capital productivity has decreased substantially from 1997 to 1999. Sales have gone down for this firm, but the inventory and accounts receivable have gone up instead of coming down proportionately during the same period. This phenomenon has driven internal working capital productivity down.
3. Company C has allowed its internal supply chain working capital productivity to decrease from 11.14 in 1997 to 10.79 in 1999. This is explained by a significant increase in its accounts receivable from 91.57 in 1997 to 159.56 in 1999.
These results point to the fact that looking only at internal supply chain working capital productivity per se would be myopic and would not capture the total performance of the firm. Total performance needs to take into account the partnering approaches of the firm, which is possible in this case by examining the components of the internal supply chain working capital. A firm can hope to be competitive only if it keeps in mind the interests of its suppliers and distributors. It can be seen by examining Table VIII that all three firms have higher accounts payable compared to accounts receivable. Under such circumstances, the suppliers have to finance their operations at a very high cost since their capital is locked up with the buying firms for an extended period of time. Ultimately, this cost is passed on to the firm as an add-on to the services and physical goods provided by the supplier. Therefore, a high working capital productivity may not always be optimal in terms of cost efficiency. This performance measure needs to be evaluated along with the components of internal supply chain working capital.
Note that Company C also carries high accounts receivable compared to the other two firms. The distributors seem to be financing their operations at the cost of Company C. This is counterproductive because the distributors may lose their cost-competitiveness since they are able to delay their accounts payable. Under these circumstances, the cost of inefficiency and the additional interest rate cost would be added to the cost of the product.
If a firm is very large in comparison to its suppliers, then it should be more concerned about keeping its accounts payable at lower levels since the cost of capital faced by a small player is much higher. In this case, the firm may be able to defer its payments owing to its bargaining power, but, ultimately, the higher cost of capital is borne by the firm itself when the supplier adds this on to the price.
On the sell side, a firm may be prone to offer extensions of credit and sell more on credit to generate sales. However, these policies may prove to be detrimental since it results in an increase in working capital that must be financed.
It is necessary to mention that the firms in a specific industry segment follow specific strategies that are aligned to their business objectives. Under such circumstances, it would not be appropriate to evaluate the firms based on general performance criteria. It would be worthwhile to measure the performance of these firms in the context of the situation in which they operate and the business environment. At this stage, it becomes important that the analysis probe deeper to ascertain why the firms have different performance levels. This would facilitate the identification of the practices, policies, and processes that lead to an improvement in the internal supply chain performance. For the purpose of illustration, Company B has been analyzed using information obtained from business periodicals and other secondary sources. This information has identified how Company B is trying to improve its internal supply chain performance.
PRACTICES FOLLOWED BY "BESTPERFORMANCE" FIRM
The paint industry faces a very competitive environment, and the companies operating in this segment struggle to provide high product variety while maintaining cost efficiency at the same time. Also, they have to manage frequent changes in production volume because of large and abrupt changes in demand. Company B has the shortest days in finished goods and comparatively longer days in WIP. Industry information reveals that Company B employs point-of-sale manufacturing to provide a high level of product variety while maintaining cost efficiency. This is achieved by enabling retailers to make the desired shade by using tinting machines at the retail level. Innovative packing techniques are also utilized that allow the retailers to store pigments, thinners, base oil, and so forth so that these chemicals do not deteriorate in quality. This strategy, termed postponement, allows Company B to achieve flexibility and cost efficiency in a competitive environment (Balram and Shah 1999).
There is another benefit attributable to the postponement strategy. This benefit is manifested in less product waste. Frequently, firms dealing with high product variety face the risk of products not getting sold. Company B seems to be averting this risk by delaying the production process and giving the product a final shape only when the orders are more or less confirmed.
An examination of Company B reveals that it has one of the largest distribution systems in the industry and follows policies to reduce distribution-related costs and to improve the responsiveness of the chain. This company also holds less inventory, and thus spends less on inventory carrying costs, even though it has a larger sales turnover. These are the reasons that it has a low internal supply chain inefficiency ratio.
Using the diagnostic tool, a firm would be able to know where it stands in terms of inventory management and distribution. Also, this analysis would allow firms to identify the magnitude of improvement they need in these processes.
Industrial information also reveals that Company B has combined the policies of co-located suppliers and shipping to point-of-use. This policy has been successful in controlling its accounts payable and accounts receivable. The company is also managing its inventory levels at a much better level than the industry average.
This discussion brings forward several implications for other firms in the paint industry:
1. Firms need to focus on the production processes and find ways and means of improving operational effectiveness and efficiency. This can cut down the costs at the WIP stage. This is very important since the firms aim to maintain higher WIP rather than to overstock raw materials and finished goods.
2. The distribution networks should be strengthened to achieve a wider customer base.
3. Better coordination between the production and logistics interface can lower the inventory at the stocking points and the factories.
4. Firms should develop new and innovative ways of postponing production so that the product gets its final shape once an order is received.
This article developed performance measures that can be computed through publicly available information. A framework for benchmarking using these performance measures was presented and applied to the paint industry. By following this framework, firms can identify areas of opportunity for improvement in their internal supply chain. The framework was one of the main benefits of this exercise in that it highlights performance shortcomings in specific areas. Such an exercise encourages firms to look outward and gain an external perspective on performance improvement opportunities.
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COMPUTING COSTS AT DIFFERENT STAGES Company A Company B Cost of raw materials [*] 412 237 Cost addition in the raw material stage [a] 34 14 Cost at the end of the raw material stage [b] 412 + 34 = 446 237 + 14 = 251 Cost at the end of the WIP stage [c] 687 482 Cost addition in the finished goods stage [d] 21 13 Cost at the end of the finished goods stage [e] 687 + 21 = 708 482 + 13 = 495
(*.)Source: PROWESS, Center for Monitoring Indian Economy, Bombay, India
(a.)Use of equation (4) for computing this value
(b.)Use of equation (5) for computing this value
(c.)Use of equation (6) for computing this value
(d.)Use of equation (7) for computing this value
(e.)Use of equation (8) for computing this value
NORMALIZATION OF COSTS Company A Company B Normalized cost of raw materials [a] 412/708 = 0.57 237/495 = 0.47 Normalized cost at the end of the raw material stage [b] 446/708 = 0.61 251/495 = 0.50 Normalized cost at the end of the WIP stage [c] 687/708 = 0.97 482/495 = 0.97 Normalized cost at the end of the finished goods stage [d] 708/708 = 1 495/495 = 1
(a.)Use of equation (9a) for computing this value
(b.)Use of equation (9b) for computing this value
(c.)Use of equation (9c) for computing this value
(d.)Use of equation (9d) for computing this value
INTERNAL SUPPLY CHAIN WORKING CAPITAL ANALYSIS [a] Impact on internal supply Accounts Accounts chain working capital Scenarios receivable payable productivity Scenario 1 Low High Increases Scenario 2 High Low Decreases Scenario 3 High High Remains same Scenario 4 Low Low Remains same Scenarios Remarks Scenario 1 The increase in working capital productivity is attributable to shifting of the costs to the suppliers and the distributors. Scenario 2 The working capital productivity decreases because the funds of the firm are totally locked up. It keeps its credit period low but is not successful in getting the receivables fast. Scenario 3 In this case, one needs to look into the components of the internal supply chain working capital [b]. Scenario 4 In this case, one needs to look into the components of the internal supply chain working capital [b]. (a.)Assuming the same levels of inventory in all of the scenarios. (b.)Refer to Table IV for further exposition. INTERACTION OF THE WORKING CAPITAL COMPONENTS AND LOST SALES Aging Accounts accounts/ Scenario receivable Inventory Lost sales bad debts 1 High Low Low High 2 High High Low High 3 Low High Low Low 4 Low Low High Low 5 Low Low Low Low Scenario Repercussions 1 The firm pushes the product on to the dealer with the effect that collection becomes problematic and the risk of aging of accounts increases. 2 Same as (1) above but the inventory levels remain the same, indicating that the inventory management policies need to be streamlined. 3 A strict credit policy leads to an increase in inventory at the firm. 4 The firm is too stringent on credit policy and is not getting sufficient business. 5 An ideal case in which the firm is able to manage the inventory as well as the credit policy. SUPPLY CHAIN INEFFICIENCY RATIO [a] SCM Costs/Net Sales 1997 1998 1999 Company A 0.07573 0.07868 0.07435 Company B 0.07049 0.06707 0.06961 Company C 0.08153 0.07676 0.07939 Minimum 0.07049 0.06707 0.06961 Mean 0.09178 0.09096 0.08656 Maximum 0.11023 0.10879 0.12690 (a.)Source: PROWESS, an electronic database maintained by Center for Monitoring Indian Economy, Bombay, India HOLDING PERIOD FOR THE FIRMS [a] Holding period (No. of days) Company A Company B 1997 1998 1999 1997 1998 1999 Raw materials 40 38 38 53 55 52 Semifinished goods (WIP) 14 13 12 10 11 10 Finished goods 42 39 38 33 29 30 Holding period (No. of days) Company C 1997 1998 1999 Raw materials 62 58 43 Semifinished goods (WIP) 4 4 4 Finished goods 43 48 42 (a.)Source: PROWESS, an electro- nic database maintained by Center for Monitoring Indian Economy, Bombay, India WORKING CAPITAL PRODUCTIVITY [a] 1997 1998 1999 Company A 6.88 7.22 7.25 Company B 9.53 7.88 6.82 Company C 11.14 12.68 10.79 (a.)Source: PROWESS, an electro- nic database maintained by Center for Monitoring Indian Economy, Bombay, India INVENTORY, ACCOUNTS RECEIVABLE, AND ACCOUNTS PAYABLE [a] Company A Company B 1997 1998 1999 1997 1998 1999 Inventory 146 140.25 166 64.92 63.41 68.72 Accounts Receivable 60 67 80.74 45.59 60.3 56.94 Accounts Payable 55.61 70.9 101.9 61.74 75.45 63.61 Company C 1997 1998 1999 Inventory 101.15 118.45 118.47 Accounts Receivable 91.57 126.72 159.56 Accounts Payable 198.51 181.7 217.97 Source: PROWESS, an electronic database maintained by Center for Monitoring Indian Economy, Bombay, India
STEPS DELINEATING THE BENCHMARKING FRAMEWORK
Selection of performance measures among the ones presented in this study by the firm depending on its competitive focus, market niche, and strategy.
Benchmarking exercise on the firms in the industry using the selected performance measure. This would enable the identification of firms with "best performance" in terms of the selected measure. Other performance measures developed in this article may then be computed for the selected firms.
The information about specific strategies of the "best-performance" firms to be obtained from business periodicals and other sources in public domain. This information can be extracted and be related to the specific performance measures of the firms.
Leveraging this knowledge to find what bearing the firms' performance measures have on their specific practices and policies. At this stage, management's objective is to identify practices and policies that drive superior performance.
DATA DIRECTLY OBTAINED FROM THE FINANCIAL STATEMENTS [*] Terms Expressed as Cost of raw materials [CRM.sub.I] Cost of production [CP.sub.I] Cost of distribution [DC.sub.I] Cost of sales [CS.sub.I] Net sales [NS.sub.I] Inventories (inclusive of raw materials, semifinished goods, and finished goods) [I.sub.I] Raw materials inventory [RM.sub.I] Semifinished goods inventory [SFG.sub.I] Finished goods inventory [FG.sub.I] Accounts receivable (excluding loans and advances) [AR.sub.I] Accounts payable (current liabilities) [AP.sub.I] (*.)Expressions for industry aggregate are taken out from the industry research through similar financial statements.
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|Author:||Shah, Janat; Singh, Nitin|
|Publication:||Journal of Supply Chain Management|
|Article Type:||Statistical Data Included|
|Date:||Jan 1, 2001|
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