Operational Assessment
A system for logistics performance assessment first requires a functional perspective. In addition to basic functional performance, improved methods for measurement of customer accommodation are receiving increased attention in many organizations. Measurement of integrated supply chain performance poses a major challenge for contemporary management. Benchmarking is a fourth concern in logistics assessment.
Functional Perspectives
While many different classifications of logistics functional measures exist, research over a period of years suggests five categories: (1) cost, (2) customer service, (3) quality, (4) productivity, and (5) asset management.2 Table 15.1 provides examples of common metrics related to each of these five areas of concern. Of course, numerous other examples exist as well.
Table 15.1 Typical Performance Metrics
Cost
The most direct reflection of logistics performance is the actual cost incurred to accomplish specific operations. As shown in Table 15.1, cost performance is typically measured in terms of total dollars spent. Early in the text, the work of integrated logistics was identified as incorporating five interrelated areas: order processing, inventory, transportation, warehousing and materials handling, and facility network.3 Total logistics cost, sometimes referred to as total landed cost, is the sum of costs related to performance and administration of each of these areas of work. Unfortunately, recent research suggests that few organizations have the ability to actually capture the information required to measure total cost. This occurs because different organizations may have different orientations toward which of the areas identified above actually constitute integrated logistics, or because of the lack of readily available data.4 Nevertheless, at senior management levels of responsibility this total cost should be monitored closely. It is also important to monitor cost data for each of the individual functions so that appropriate diagnosis and control can take place. The functional cost data may be further fine-tuned and measured for individual activities such as order picking and order loading in the warehouse function.
It is also common to monitor and report cost data as a percentage of sales or as a cost per unit of volume. For example, transportation cost is frequently expensed as a percentage of dollar sales volume and as the number of dollars spent per order delivered. Warehouse cost may also be reported as a percentage of sales and cost of individual activities reported such as the picking cost per item or loading cost per order. Such measures, when compared to historical levels or performance standards, provide critical information regarding the potential need to take corrective action. When considering the number of different specific logistics activities, ranging from entering an order to picking an item to unloading a delivery vehicle, and the number of different ways in which volume can be measured, ranging from sales dollars to number of orders to pounds of product, a rather lengthy list of possible cost metrics could be generated. The key is for logistics executives to identify the most appropriate metrics for their organization and consistently apply them over time to control and direct the activities.
Table 15.1 also shows other measures that require measurement of logistics cost, such as direct product profitability, customer profitability, and cost of service failures. In fact, most firms recognize the importance of these measures but currently lack the information necessary to accurately assess these costs. Accurate measurement in these critical dimensions requires a level of sophistication in accounting data that has just recently become available. Activity-based costing is discussed later in this chapter as a means to more accurately assess the cost related directly to customers and products.
Customer Service
In Chapter 3, the elements of basic customer service were identified as availability, operational performance, and service reliability. An effective basic service platform requires specific metrics for assessing performance in each dimension.
Availability is typically reflected by an organization’s fill rate. It is critical to note, however, that fill rate may be measured in a variety of ways:
equation
Clearly, the order fill rate, also known as orders shipped complete, is the most stringent measure of a firm’s performance relative to product availability. In this metric, an order that is missing only one item on one line is considered to be incomplete. It is also common for companies to track specifically the number of stockouts encountered and number of back orders generated during a time period as indicators of availability.
Operational performance deals with time and is typically measured by average order cycle time, consistency of order cycle time, and/or on-time deliveries. Average order cycle time is typically computed as the average number of days, or other units of time, elapsed between order receipt and delivery to customers. Order cycle consistency is measured over a large number of order cycles and compares actual with planned performance. For example, suppose average order cycle time is five days. If 20 percent were completed in two days and 30 percent in eight days, there is great inconsistency around the average. In situations where delivery dates or times are specified by customers, the most stringent measure of order cycle capability is on-time delivery, the percentage of times the customer’s delivery requirements are actually met.
Quality
Performance relative to service reliability is generally reflected in an organization’s measurement of logistics quality. As Table 15.1 shows, many of the quality metrics are designed to monitor the effectiveness of individual activities, while others are focused on the overall logistics function. Accuracy of work performance in such activities as order entry, warehouse picking, and document preparation is typically tracked by computing the ratio of the total number of times the activity is performed correctly to the total number of times it is performed. For example, picking accuracy of 99.5 percent indicates that 99.5 out of every 100 times, the correct items were picked in the warehouse.
Overall quality performance can also be measured in a variety of ways. Typical measures include damage frequency, which is computed as the ratio of the number of damaged units to the total number of units. While damage frequency can be measured at several points in the logistics process, such as warehouse damage, loading damage, and transportation damage, it frequently is not detected until customers receive shipments or even some point in time after receipt. Therefore, many organizations also monitor the number of customer returns of damaged or defective goods. It is also common to measure customer claims and refunds on adjustments.
Other important indicators of quality performance relate to information. Many organizations specifically measure their ability to provide information by noting those instances when information is not available on request. It is also common to track instances when inaccurate information is discovered. For example, when physical counts of merchandise inventory differ from the inventory status as reported in the database, the information system must be updated to reflect actual operating status. Additionally, the occurrence of information inaccuracy should be recorded for future action.
Productivity
The relationship between output of goods, work completed, and/or services produced and quantities of inputs or resources utilized to produce the output is productivity. If a system has clearly measurable outputs and identifiable, measurable inputs that can be matched to the appropriate outputs, productivity measurement is quite routine.
Generally, as Table 15.1 shows, logistics executives are very concerned with measuring the productivity of labor. While the labor input can be quantified in many ways, the most typical manner is by labor expense, labor hours, or number of individual employees. Thus, typical labor productivity measures in transportation include units shipped or delivered per employee, labor dollar, and labor hour. Warehouse labor productivity may be measured by units received, picked, and/or stored per employee, dollar, or hour. Similar measures can be developed for other activities, such as order entry and order processing. It is also common for managers to set goals for productivity improvement and compare actual performance to goal, or at the very least to prior year performance.
Asset Management
Utilization of capital investments in facilities and equipment as well as working capital invested in inventory is the concern of asset management. Logistics facilities, equipment, and inventory can represent a substantial segment of a firm’s assets. For example, in the case of wholesalers, inventory frequently exceeds 80 percent of total capital. Asset management metrics focus on how well logistics managers utilize the capital invested in operations.
Facilities and equipment are frequently measured in terms of capacity utilization, or the percentage of total capacity used. For example, if a warehouse is capable of shipping 10,000 cases per day, but ships only 8,000, capacity utilization is only 80 percent. It is also common to measure equipment utilization in terms of time. Logistics managers are typically concerned with the number or percentage of hours that equipment is not utilized, which is measured as equipment downtime. Downtime can be applied to transportation, warehouse, and materials handling equipment. These measures indicate the effective or ineffective utilization of capital asset investment.
Asset management measurement also focuses on inventory. Inventory turnover rate is the most common measure of performance. Throughout the text, impr
Operational Assessment
A system for logistics performance assessment first requires a functional perspective. In addition to basic functional performance, improved methods for measurement of customer accommodation are receiving increased attention in many organizations. Measurement of integrated supply chain performance poses a major challenge for contemporary management. Benchmarking is a fourth concern in logistics assessment.
Functional Perspectives
While many different classifications of logistics functional measures exist, research over a period of years suggests five categories: (1) cost, (2) customer service, (3) quality, (4) productivity, and (5) asset management.2 Table 15.1 provides examples of common metrics related to each of these five areas of concern. Of course, numerous other examples exist as well.
Table 15.1 Typical Performance Metrics
Cost
The most direct reflection of logistics performance is the actual cost incurred to accomplish specific operations. As shown in Table 15.1, cost performance is typically measured in terms of total dollars spent. Early in the text, the work of integrated logistics was identified as incorporating five interrelated areas: order processing, inventory, transportation, warehousing and materials handling, and facility network.3 Total logistics cost, sometimes referred to as total landed cost, is the sum of costs related to performance and administration of each of these areas of work. Unfortunately, recent research suggests that few organizations have the ability to actually capture the information required to measure total cost. This occurs because different organizations may have different orientations toward which of the areas identified above actually constitute integrated logistics, or because of the lack of readily available data.4 Nevertheless, at senior management levels of responsibility this total cost should be monitored closely. It is also important to monitor cost data for each of the individual functions so that appropriate diagnosis and control can take place. The functional cost data may be further fine-tuned and measured for individual activities such as order picking and order loading in the warehouse function.
It is also common to monitor and report cost data as a percentage of sales or as a cost per unit of volume. For example, transportation cost is frequently expensed as a percentage of dollar sales volume and as the number of dollars spent per order delivered. Warehouse cost may also be reported as a percentage of sales and cost of individual activities reported such as the picking cost per item or loading cost per order. Such measures, when compared to historical levels or performance standards, provide critical information regarding the potential need to take corrective action. When considering the number of different specific logistics activities, ranging from entering an order to picking an item to unloading a delivery vehicle, and the number of different ways in which volume can be measured, ranging from sales dollars to number of orders to pounds of product, a rather lengthy list of possible cost metrics could be generated. The key is for logistics executives to identify the most appropriate metrics for their organization and consistently apply them over time to control and direct the activities.
Table 15.1 also shows other measures that require measurement of logistics cost, such as direct product profitability, customer profitability, and cost of service failures. In fact, most firms recognize the importance of these measures but currently lack the information necessary to accurately assess these costs. Accurate measurement in these critical dimensions requires a level of sophistication in accounting data that has just recently become available. Activity-based costing is discussed later in this chapter as a means to more accurately assess the cost related directly to customers and products.
Customer Service
In Chapter 3, the elements of basic customer service were identified as availability, operational performance, and service reliability. An effective basic service platform requires specific metrics for assessing performance in each dimension.
Availability is typically reflected by an organization’s fill rate. It is critical to note, however, that fill rate may be measured in a variety of ways:
equation
Clearly, the order fill rate, also known as orders shipped complete, is the most stringent measure of a firm’s performance relative to product availability. In this metric, an order that is missing only one item on one line is considered to be incomplete. It is also common for companies to track specifically the number of stockouts encountered and number of back orders generated during a time period as indicators of availability.
Operational performance deals with time and is typically measured by average order cycle time, consistency of order cycle time, and/or on-time deliveries. Average order cycle time is typically computed as the average number of days, or other units of time, elapsed between order receipt and delivery to customers. Order cycle consistency is measured over a large number of order cycles and compares actual with planned performance. For example, suppose average order cycle time is five days. If 20 percent were completed in two days and 30 percent in eight days, there is great inconsistency around the average. In situations where delivery dates or times are specified by customers, the most stringent measure of order cycle capability is on-time delivery, the percentage of times the customer’s delivery requirements are actually met.
Quality
Performance relative to service reliability is generally reflected in an organization’s measurement of logistics quality. As Table 15.1 shows, many of the quality metrics are designed to monitor the effectiveness of individual activities, while others are focused on the overall logistics function. Accuracy of work performance in such activities as order entry, warehouse picking, and document preparation is typically tracked by computing the ratio of the total number of times the activity is performed correctly to the total number of times it is performed. For example, picking accuracy of 99.5 percent indicates that 99.5 out of every 100 times, the correct items were picked in the warehouse.
Overall quality performance can also be measured in a variety of ways. Typical measures include damage frequency, which is computed as the ratio of the number of damaged units to the total number of units. While damage frequency can be measured at several points in the logistics process, such as warehouse damage, loading damage, and transportation damage, it frequently is not detected until customers receive shipments or even some point in time after receipt. Therefore, many organizations also monitor the number of customer returns of damaged or defective goods. It is also common to measure customer claims and refunds on adjustments.
Other important indicators of quality performance relate to information. Many organizations specifically measure their ability to provide information by noting those instances when information is not available on request. It is also common to track instances when inaccurate information is discovered. For example, when physical counts of merchandise inventory differ from the inventory status as reported in the database, the information system must be updated to reflect actual operating status. Additionally, the occurrence of information inaccuracy should be recorded for future action.
Productivity
The relationship between output of goods, work completed, and/or services produced and quantities of inputs or resources utilized to produce the output is productivity. If a system has clearly measurable outputs and identifiable, measurable inputs that can be matched to the appropriate outputs, productivity measurement is quite routine.
Generally, as Table 15.1 shows, logistics executives are very concerned with measuring the productivity of labor. While the labor input can be quantified in many ways, the most typical manner is by labor expense, labor hours, or number of individual employees. Thus, typical labor productivity measures in transportation include units shipped or delivered per employee, labor dollar, and labor hour. Warehouse labor productivity may be measured by units received, picked, and/or stored per employee, dollar, or hour. Similar measures can be developed for other activities, such as order entry and order processing. It is also common for managers to set goals for productivity improvement and compare actual performance to goal, or at the very least to prior year performance.
Asset Management
Utilization of capital investments in facilities and equipment as well as working capital invested in inventory is the concern of asset management. Logistics facilities, equipment, and inventory can represent a substantial segment of a firm’s assets. For example, in the case of wholesalers, inventory frequently exceeds 80 percent of total capital. Asset management metrics focus on how well logistics managers utilize the capital invested in operations.
Facilities and equipment are frequently measured in terms of capacity utilization, or the percentage of total capacity used. For example, if a warehouse is capable of shipping 10,000 cases per day, but ships only 8,000, capacity utilization is only 80 percent. It is also common to measure equipment utilization in terms of time. Logistics managers are typically concerned with the number or percentage of hours that equipment is not utilized, which is measured as equipment downtime. Downtime can be applied to transportation, warehouse, and materials handling equipment. These measures indicate the effective or ineffective utilization of capital asset investment.
Asset management measurement also focuses on inventory. Inventory turnover rate is the most common measure of performance. Throughout the text, impr
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