Measuring Efficiency of a Supply Chain -I

The two part article is based on doctoral research by Prabir Jana at Nottingham Trent University, UK “An Investigation into Indian Apparel and Textile Supply Chain Networks.” In first part we will discuss about efficiency measurement framework in Apparel Supply Chain and in second part we will discuss a case study of practically measuring supply chain efficiency of an apparel manufacturing organization and associated complications and nuances.

What can’t be measured can’t be improved. Even though Supply Chain Management is the most talked about topic today, currently no tool is available to measure any manufacturing organizations’ supply chain efficiency. Unlike productivity and or quality measurement, where the parameter can be measured objectively and expressed in unit or ratio, supply chain measurement is currently more of a qualitative statement. Even though the word ‘performance’ or ‘efficiency’ is often used communicating the same meaning, measuring the performance or efficiency of an ‘enterprise’ or a ‘supply chain’ conveys different meaning altogether.

If we define ‘supply chain’ as an extended enterprise then efficiency measurement of a supply chain will mean efficiency measurement of multiple organizations in synchronization. One of the major strategic objectives of supply chain planning and management is to maximize total profit in the chain rather than maximizing profit of an organization in isolation. The typical adversarial relationship between upstream and downstream players in the apparel supply chain is still prevalent making the job more difficult than saying. Can you imagine if the buying organization you are dealing with, is sharing the profit with you or you have to share your profit and loss with your fabric supplier! Can you blindly trust your fabric supplier that the fabric developed for you will not be shown to another apparel manufacturer? Information that potentially influence the bottomline of an organization is kept so confidential, no trust, or partnership can penetrate that. It is not impossible, but difficult and not yet common in marketplace.

What Are The Measurement Systems Available?
A variety of measurement approaches that have been developed and traditionally used for measuring supply chain performance (Lapide 1999). Apart from the wildly popularized Balanced Scorecard, there are other measurement approaches like Supply Chain Council’s SCOR Model, the Logistics Scoreboard, Activity-Based Costing (ABC) and Economic Value Analysis (EVA).

Balanced Scorecards
Balanced Scorecard (BSC) was developed by Robert S. Kaplan and David P. Norton in 1992 (Kaplan et el 1992). BSC recommends use of executive information systems (EIS) that track a limited number of balanced metrics based on the following four perspectives: financial, customer, internal process, and learning and growth, which are closely aligned to strategic objectives.

While BSC is popular among several industry segments and considered most balanced measurement of possible parameters, application of BSC in contract apparel manufacturing is not suitable because organizations are secretive about financial data, customer perspective is out of bound and innovative and learning perspective is virtually missing in majority. That leaves out only internal business perspective.

The Supply Chain Council’s SCOR Model
The Supply Chain Council (SCC) was set up between 1996 and 1997, with members representing most industries and global geographies, including BASF, Bayer, Colgate-Palmolive, Lucent technologies, Procter & Gamble, Unilever and Siemens, as well as consulting organisations. The SCC designed SCOR model, which is designed and maintained to support supply chains of various complexities and across multiple industries. It spans all customer interactions (order entry through paid invoice), all physical material transactions (supplier’s supplier to customer’s customer, including equipment, supplies, spare parts, bulk product and software) and all market transactions (from understanding of aggregate demand to the fulfillment of each order).

This model is finally adopted to develop the measurement framework, and will be discussed in detail in part II of this article.

The Logistics Scoreboard
Another approach to measure supply chain performance was developed around logistical measures like

This method was developed by Logistics Resources International Inc. (Atlanta, GA), a consulting firm specializing primarily in the logistical (i.e., warehousing and transportation) aspects of a supply chain. The company sells a spreadsheet-based, educational tool called The Logistics Scoreboard that companies can use to pilot their supply chain performance measurement processes. The Logistics Scoreboard is prescriptive and actually recommends the use of a specific set of supply chain performance measures. These measures, however, are skewed toward logistics, having limited focus on measuring the production and procurement activities within a supply chain.

This approach is more suitable for logistics service providers and none of the measures are in direct relevance to contract manufacturing

Activity Based Costing
Activity based costing (ABC) is an accounting methodology that assigns costs to activities rather than products or services. This was developed to overcome some of the shortcomings of traditional accounting methods in tying financial measures to operational performance. The method involves breaking down activities into individual tasks or cost drivers, while estimating the resources (i.e., time and costs) needed for each one. Costs are then allocated based on these cost drivers rather than on traditional cost-accounting methods, such as allocating overhead either equally or based on less-relevant cost drivers. This approach allows one to better assess the true productivity and costs of a supply chain process. From operational perspective ABC method highlights benefits through lower cost, improve quality and reduced manufacturing cycle time (Agarwal and Manjul 2005). For example, use of the ABC method can allow companies to more accurately assess the total cost of servicing a specific customer or the cost of marketing a specific product. ABC analysis does not replace traditional financial accounting, but rather a post mortem on past orders that provides a better understanding of supply chain performance by looking at the same numbers in a different way and helps better aligning the metrics closer to actual labor, material, and equipment usage.

This method can be used for post mortem of cost incurred on different orders that are executed. A case study of a garment manufacturer exporter (Agarwal and Manjul 2005) shows that cost calculated using ABC analysis was 27% to 31% higher compared to cost estimated traditionally using absorption costing. While labour cost is the highest component across all departments namely, sewing, cutting and sampling, it is as high as 90% in sewing and 50-53% in sampling. As this method does not measure any other parameters related to time, quality and output oriented functions, so it is not a holistic approach to supply chain performance measure.

Economic Value Analysis
One of the criticisms of traditional accounting is that it focuses on short-term financial results like profits and revenues, providing little insight into the success of an enterprise towards generating long term value to its shareholders – thus, relatively unrelated to the long-term prosperity of a company. For example, a company can report many profitable quarters, while simultaneously disenfranchising its customer base by not applying adequate resources towards product quality or new product innovation. To correct this deficiency in traditional methods, some financial analysts advocate estimating a company’s return on capital or economic value-added. These are based on the premise that shareholder value is increased when a company earns more than its cost of capital. One such measure, EVA, developed by Stern, Stewart & Co., attempts to quantify value created by an enterprise, basing it on operating profits in excess of capital employed (through debt and equity financing). These types of metrics can be used to measure an enterprise’s value added contributions within a supply chain. However, while useful for assessing higher level executive contributions and long term shareholder value, economic-value added metrics are less useful for measuring detailed supply chain performance. They can be used, however, as the supply chain metrics within an executive-level performance scorecard, and can be included in the measures recommended as part of The Logistics Scoreboard approach.

This measurement method is long term financial health oriented. While majority of the manufacturing organizations are self financed and balance sheets are not public, Economic Value Analysis is not possible for such organizations.

In a platter full of so many options it is obviously difficult for apparel manufacturers to select the right approach. While listing a comprehensive list of supply chain measures Lapide noted (lapide 2000) that most performance measurement systems are functionally focused. For example SCOR model is a typical function based supply chain performance measure, often lead to functional silos and conflicting functional goals. A balanced supply chain measurement system should cover function based, process based, cross enterprise and alignment of executives to management level measures. Measuring performance in a department as though it operates in a vacuum can have a negative effect on other departments—and on the bottom line (Barnard 2000).
We have first highlighted the measurement parameters in the following table from a clothing manufacturer’s perspective. While almost all manufacturing related measures are theoretically measurable by a manufacturer, only selected measures are possible in customer service, logistics and sales related parameters. It is of pertinent importance to understand the secrecy and confidentiality issues perceived by every typical manufacturer working as CMT supplier or fully-factored clothing supplier to any high street retailer in EU or US. An organization of $ 25 million turnover is typically self financed and the operational efficiency horizon for such manufacturer spans between order receipts till goods trucked out of factory. The objective was to develop easy and simple metrics to measure such organization’s supply chain efficiency. After a thorough investigation of all measures SCORE model was selected for final adaptation. Last, but not the least the measurement parameters are chosen based on the functional link between upstream and down stream players in the supply chain and not merely in house functions of an apparel manufacturer.

Table: Lists of Possible Supply Chain Measures

Customer Service Measures	Process, Cross-Functional Measures	Purchasing Related Measures
Order Fill Rate Line Item Fill Rate Quantity Fill Rate Backorders/stockouts Customer satisfaction % Resolution on first customer call Customer returns Order track and trace performance Customer disputes Order entry accuracy Order entry times	Forecast accuracy Percent perfect orders New product time-to-market New product time-to-first make Planning process cycle time Schedule changes	Material inventories Supplier delivery performance Material/component quality Material stockouts Unit purchase costs Material acquisition costs Expediting activities
Extended Enterprise Measures	Manufacturing Related Measures	Logistic Related Measures
Total landed cost Point of consumption product availability Total supply chain inventory Retail shelf display Channel inventories EDI transactions Percent of demand/supply on VMI/CRP Percent of customers sharing forecasts Percent of suppliers getting shared forecast Supplier inventories Internet activity to suppliers/customers Percent automated tendering	Product quality WIP inventories Adherence-to-schedule Yields Cost per unit produced Setups/Changeovers Setup/Changeover costs Unplanned stockroom issues Bill-of-materials accuracy Routing accuracy Plant space utilization Line breakdowns Plant utilization Warranty costs Source-to-make cycle time Percent scrap/rework Material usage variance Overtime usage Production cycle time Manufacturing productivity Master schedule stability	Finished goods inventory turns Finished goods inventory days of supply On-time delivery Lines picked/hour Damaged shipments Inventory accuracy Pick accuracy Logistics cost Shipment accuracy On-time shipment Delivery times Warehouse space utilization End-of-life inventory Obsolete inventory Inventory shrinkage Cost of carrying inventory Documentation accuracy Transportation costs Warehousing costs Container utilization Truck cube utilization In-transit inventories Premium freight charges Warehouse receipts
Administration/Financial Measures	Marketing Related Measures	Other Measures
Cash flow Income Revenues Return on capital employed Cash-to-cash cycle time Return on investment Revenue per employee Invoice errors Return on assets	Market share Percent of sales from new products Time-to-market Percent of products representing 80% of sales Repeat versus new customer sales	APICS trained personnel Patents awarded Employee turnover Number of employee suggestions

Supply chain efficiency measurement framework is developed in terms of efficiency shown by the chain with respect to key functional parameters spanning four different operation domains namely source, plan, make and deliver. There are about five primary key performance indicators (KPI) identified in each operation domain and some primary KPI have multiple secondary KPIs to measure. Each KPI is expressed in percentage. Once all KPI are measured, weighted averages of all KPI would indicate the overall supply chain efficiency of the organization. While a 100 percent supply chain efficiency index would mean perfect organization, there is a possibility of any organization having KPI value more than 100 percent.

Operation domain	KPI’s

Source	1) Inward Material Quality
	2) Quantity and Timely Delivery
	3) Procurement Unit Cost
	4) Material Inventory Level
	5) Vendor Development Capability

Plan	1) Adherence to Production Target
	2) Sample Conversion Rate
	3) Material Utilization
	4) Cost Adherence
	5) Planned T&A v/s Actual T&A

Make	1) Capacity Utilization
	2) Production Cost Efficiency
	3) Quality Capability
	4) Change Over Time
	5) Operator Training Effectiveness

Deliver	1) On Time Shipment
	2) Order Fulfillment
	3) Claims and Discounts
	4) Quality at Delivery
	5) Transit time