Aligning Fulfillment Metrics to Customer Segment Requirements

Understanding and filling customer needs collaboratively adds more value than designing processes and systems to beat the competition. Here's an example of how one company did it.

Understanding and filling customer needs collaboratively adds more value than designing processes and systems to beat the competition. Here's an example of how one company did it.

A common saying when it comes to performance measurement is, "You can't manage what you don't measure." But more importantly, the real challenge comes in determining what to measure and how to measure it.

Often manufacturers fail to adopt the right metrics for their businesses to track. However, the proper metrics can accurately reflect performance improvements or services provided across segments, and reinforce appropriate practices for continuous improvement. One such metric that measures the effectiveness of the supply chain is order fulfillment, which takes into account the cross-functional performance of an enterprise.

Manufacturers often design or adopt fulfillment metrics and targets that are neither indicative of their customer requirements, nor take into account the realistic capabilities of their processes and systems. For instance, while the sales group likes to promise the world to their customers, the supply chain group can't afford to give up the farm in trying to keep up with those promises. To avoid such problems it is critical, then, to understand and target what matters most to the customer, which is an important step toward understanding the end consumer.

Measuring Fulfillment Performance

In consumer packaged goods (CPG) manufacturing, the following are some of the ways order fulfillment is measured:

  • Line Fill Rate  percentage of lines on an order filled in full

  • Order Fill Rate  percentage of orders filled in full

  • Perfect Order  orders delivered on time, in full and in good condition

CPG companies also measure the duration of back order fill, order picking and assembly times, on-time deliveries, and quality of the delivery  metrics that are often used locally for corrective actions across functions in a supply chain. One of the widely used methods to set fill targets is based on historical performances, as it can be quickly implemented. As an example, a Southern packaged food products manufacturing company with a perfect order record of 77 percent decided to push the performance by 2 percentage points the following year, as this jump was in line with the past improvements in fill rates.

The goal of CPG companies is to build lasting relationships with valuable customer segments by supporting them on events like in-store promotions in addition to filling regular orders on time and sustaining their brand fame. The targets for the line fill, order fill and perfect order are usually set internally by the manufacturer and do not take into account the customer preferences. Major retailers see value in proper positioning of premium brands, which require uninterrupted supply. Additionally, as retailers also have the option to source private brands, it becomes critical for traditional brand manufacturers to perform timely deliveries. Developing the right set of metrics and enabling supply chains to achieve superior fulfillment performance from the customer's perspective is key to meeting both the brand and sales expectations.

In addition to the above, CPG companies are striving to move toward "fill to demand" practice and cut inventory levels, while also investing in research and development to achieve product differentiation and increase market share. Thus, measuring actual fulfillment, as opposed to the perception of it, helps companies to properly understand customer satisfaction and get a real picture of how the company is delivering on brand expectations across segments.

For several years, a major CPG manufacturer based in the Southern United States was consistently falling short of the perfect order target. The company offered a huge mix of stock-keeping units (SKUs) of various sizes, colors and shapes of products, and sold them through four market segments that included wholesalers, retailers, independent dealers and franchisees. The sales group had set one perfect order target for the supply chain to hit for all customer segments, and the idea was to push the demand fulfillment performance ahead of the competition. Segment-specific order requirements included custom labeling on packages, shipping on different size pallets and random customer pickups from company-owned warehouses. The order assembly and shipping process lacked information on stock allocation priorities, which caused, for example, low priority segment's, like franchisee, orders to be shipped ahead of a retailer's order. These complexities, along with setting the perfect order target in line with the competition, caused:

  • The shop floor to often take expensive changeovers just to fill a few units for fulfillment, which did not add any more value to the customer.

  • Increased investment in inventories to hit a pre-determined service target.

  • Delays in launching new products, as filling for service got first priority.

The target was elusive during the peak selling season every year, in spite of increased operational cost. The problem was that the target was not validated by inputs from the different departments internally, and the company did not seek feedback from different customer segments on their fulfillment requirements. Slow moving and near obsolete brands got the same fill priority as high-performing brands. Additional labor and material expediting costs were incurred several times to deliver big wholesaler orders which could have been delivered in parts, as these were for ongoing projects.

In another case, out of a retailer's order of 45 SKUs, 44 were delivered perfect by the company, and one SKU was short by 15 units, and thus did not meet the requirements of a perfect order. But the system had no means to credit the 44 SKUs in the current measurement system. The customer got most of the order filled, and there were no complaints on a number of orders delivered that close. The actual fulfillment performance, as it applies to the customer, was understated and misleading.

In summary, by adopting metrics and targets to get ahead of the competition, the company incurred additional costs for delivering what sometimes was not important to the customer.

Developing Alternate Measurement Methods

The company therefore formed a cross-functional manufacturing/sales team to get customer inputs and develop alternate order fulfillment metrics to correctly reflect requirements of different segments. The method adopted was to set fill targets across brands, and across customer segments of wholesalers, retailers, franchisees and independent dealers.

The brands were classified as power, regular and tail brands for each customer segment. Power brands were the popular and the consistently high-performing products, as well as some low-volume, crucial, "gotta have it" products. Regular brands included the fairly steady performing products with some demand volatility, and the tail brands consisted of low-volume and near obsolete products.

Feedback from the scheduled requirements gathering from customers provided their views of value add, like cutting delivery lead times and response times to brand promotion events, which were then integrated into the measurement system. Additional factors considered for segment service differentiation included customer value, strategic business tie-ups and driving fulfillment performance of certain specialty brands.

As a strategy for growth, the perfect order target for power brands was set at 100 percent for all segments. For the regular and tail brands, the perfect order targets were set in line with historical performance, as customers were comfortable at these levels. The following table shows sample targets for the new metrics.

Benefits Derived From the New Measurement System

Calculating targeted inventory levels by brand to meet planned fill requirements stabilized production runs and cut unnecessary stock build up. The year-on-year investment in inventories dropped by $0.8 million.

System output modification allowed the capture of order fill data daily by brands and by segment, and this was used as a diagnostic tool to drive performance in the areas of manufacturing and distribution.

Focusing on segment fill requirements helped develop credible relations with customers and in obtaining demand and replenishment plans in advance.


Understanding and filling customer needs collaboratively adds more value than designing processes and systems to beat the competition. Wrong business decisions are inevitable if measurement systems are focused on metrics as opposed to customer satisfaction. In maintaining that fine balance between cost and service, manufacturing organizations should not hesitate to find out what is important and acceptable to the customers and design appropriate metrics to help drive performance across the enterprise.


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About the Author: Subramanyam Venkataraman is a senior consultant in the Supply Chain Management domain at Infosys, an end-to-end business solutions provider.