Integral Logistics Management — Operations Management and Supply Chain Management Within and Across Companies

1.4 Performance Indicators and Performance Measurement

Intended learning outcomes: Present the basics of the measurement, meaning, and practical applicability of logistics performance indicators. Describe performance indicators in the target areas of quality, costs, delivery, and flexibility. Produce an overview on performance indicators of the primary entrepreneurial objective.


A performance indicator or performance criterion is the specific characteristic to be measured for estimating performance. 
A performance measurement system collects, measures, and compares a measure to a standard for a specific performance indicator. 
A performance measure, or performance measurement, is the actual value measured for the indicator ([APIC16]).

Appropriate performance indicators are meant to show the degree to which entrepreneurial objectives (see Figure 1.3.1.1) are fulfilled or not fulfilled.

Logistics performance indicators analyze the effect of logistics on entre­preneurial objectives in the four target areas of quality, costs, delivery, and flexibility.

Descriptions of logistics performance indicators can be found in [OdLa93] or [Foga09], Chapter 5, and in the following. Whenever possible, a logistics performance indicator will give direct indication of fulfillment of one of the individual objectives within a target area. A performance indicator relates to a logistics object and thus becomes an attribute of that object — and sometimes it becomes a logistics object in its own right.

Global measures measure the overall performance of a company or supply chain (such as cash flow, throughput, utilization, inventory). 
Local measures relate to a single resource or process and usually have a small influence on global measures (i.e., volume discount on an item, lead time for stock entries, utilization of a storage location).

In the following, we introduce a balanced set of global measures from a logistics perspective. This balance is one of the requirements of the balanced scorecard, an approach that pointed out the one-sidedness of performance indicators in the financial sector, which (too) often only refer to the company’s primary entrepreneurial objective of return (see [KaNo92] and Section 1.3.2). A systematical derivation of the balanced set of performance indicators from the company’s strategy can be found in [Schn07]. Together with indicators from other areas of the firm, such as finance, marketing, and R&D, the logistics indicators form a complete set of measurements of performance, and thus a basis for improving company performance.


1.4.1 The Basics of the Measurement, Meaning, and Practical Applicability of Logistics Performance Indicators

In actual practice, the measuring of logistics performance varies in difficulty and usually requires that certain aspects be counted. With the exception of local measures, it is generally not possible to assess these aspects without expending a lot of time and energy. In addition, integrating and compressing the local measures into global measures, covering several levels, for example, can be very problematic.

The following sums up central problems in terms of the meaning and practical applicability of performance indicators in the form of practical methods. The problems are typical of any quality measurement system and, in part, costing systems as well.

  • General performance indicators: Simple, measurable performance indicators are often so general and qualitative in meaning that no practical steps can be derived from them without making additional, nonquantitative, and implicit assumptions. An example of such a performance indicator is customer satisfaction.
  • Lack of comprehensive measurement methods: Simple, applicable performance indicators often cannot be measured directly. They require various, at times complica­ted or inexact measurements that are combined with nonmeasured, implicit methods to yield the desired indicator. A good example is flexibility potential.
  • Distortion of the processes: Each measurement affects the process being measured. The disturbance can be so great that the process would behave differently under nonmeasurement conditions.
  • Meaning of the performance indicators: The absolute value of a performance indicator has little meaning as such. Only repeated comparison of measurements of the same performance indicator over time can make the performance indicator an instrument of continual process improvement (CPI).
  • Comparability of performance indicators: Benchmarking with other companies, in the same supply chain, has meaning only if the competitor has used the same bases of measurement. In practice, it is common to find that companies use different reference objects, the objects to which certain performance indicators refer. An example is fill rate or customer service ratio (see Section 1.4.4). Fill rate can refer to either order positions or items; its measurement can be based on quantity units or value units. Before making comparisons, therefore, it is essential to know how another enterprise defines the performance indicator.

It makes sense to weigh the value of the potential application of the measurement against the time and effort required by the measurement. In practice, a few simply measured perform­ance indicators have proven worthwhile. Employees must then apply the measure­ment using a multitude of means that cannot be directly derived from the measurement.


1.4.2 Performance Indicators in the Target Area of Quality

Performance of logistics, operations, and supply chain management can have an impact, although a rather low impact, on indicators in the target area of quality; for example, on scrap factors and complaint rates of all kinds. The causes can be many and difficult to pinpoint. They may even be insufficient in quality of information.

Complaint rate and scrap factor in Figures 1.4.2.1 and 1.4.2.2 are related. The source of a complaint may turn out to be a cause that, if discovered sooner, would have entailed scrap. Scrap can lead to supplier com­plaints. The yield factor is complementary to the scrap factor. Hence, for a given reference object, the scrap factor plus the yield factor is equal to 1.

Fig. 1.4.2.1        The indicators scrap factor and yield factor.

Fig. 1.4.2.2        The indicator complaint rate.


Video (not yet available)

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1.4.3 Performance Indicators in the Target Area of Costs

The influence of logistics, operations, and supply chain management in the target area of costs is significant. The performance indicators in Figure 1.4.3.1, Figure 1.4.3.2, Figure 1.4.3.3,  and Figure 1.4.3.4 are direct measures of the target objectives involved. For terms, definitions, and arguments, see Sections 1.2.1, 1.2.3, and 1.2.4.

Fig. 1.4.3.1        The performance indicator stock-inventory turnover.

Fig. 1.4.3.2        The performance indicator work-in-process-inventory turnover.

Fig. 1.4.3.3        The performance indicator work center efficiency.

Fig. 1.4.3.4        The performance indicator capacity utilization.

Further performance indicators relate to administration costs for purchase, sales, work preparation, and so on. They are all of the type in Figure 1.4.3.5.

Fig. 1.4.3.5        The performance indicator administration cost rate.


1.4.4 Performance Indicators in the Target Area of Delivery

Logistics, operations, and supply chain management have a direct effect on the target area of delivery. The performance indicators in Figure 1.4.4.1 and Figure 1.4.4.2 are direct measures of objectives.

Fig. 1.4.4.1        The performance indicator fill rate, customer service ratio, or OTIF (on-time and in-full)

Fig. 1.4.4.2        The performance indicator delivery reliability rate.

The next performance indicators are connected with lead time. For terms, definitions, and arguments, see Sections 1.2.1, 1.2.3, and 1.2.4.

Fig. 1.4.4.3        The performance indicator batch size or lot size.

Fig. 1.4.4.4        The performance indicator capacity utilization.

Fig. 1.4.4.5        The performance indicator value-added rate of lead time.

Fig. 1.4.4.6        The performance indicator variance in work content.

And, finally, there are two performance indicators in Figure 1.4.4.7 and Figure 1.4.4.8 for data and control flow.

Fig. 1.4.4.7        The performance indicator response time.

Fig. 1.4.4.8        The performance indicator order confirmation time.

Additional performance indicators may reflect the time required for product design or maintenance time of the production infrastructure.

The SCOR model contains the following performance indicators in the area of delivery. The first concerns the goal of high fill rate, the second the goal of short lead times.

  • Perfect order fulfillment: The percentage of orders meeting delive­ry performance with complete and accurate documentation and no delivery damage. This includes all items and quantities on-(customer’s)-time, and documentation.
  • Order fulfillment cycle time: The average actual cycle time consistently achieved to fulfill customer orders. For each individual order, this cycle time starts from the order receipt and ends with customer acceptance of the order.

1.4.5 Performance Indicators in the Target Area of Flexibility

Examples of performance indicators in the target area of flexibility are the success rates in Figure 1.4.5.1 and Figure 1.4.5.2:

Fig. 1.4.5.1        The performance indicator bid proposal success rate.

Fig. 1.4.5.2        The performance indicator order success rate.

The performance indicators in Figure 1.4.5.3 and Figure 1.4.5.4 rather measure the past. In order to determine potentials, additional assumptions are required.

Fig. 1.4.5.3        The performance indicator breadth of qualifications.

Fig. 1.4.5.4        The performance indicator temporal flexibility.

The SCOR model contains the following performance indicators in the area of flexibility:

  • Upside supply chain flexibility: The number of days required to achieve an unplanned sustainable 20% increase in quantities delivered. The new operating level needs to be achieved without a significant increase of unit costs.
  • Upside supply chain adaptability: The maximum sustainable percentage increase in quantity delivered that can be achieved in 30 days. The new operating level needs to be achieved without a significant increase of unit costs.
  • Downside supply chain adaptability: The reduction in quantities ordered sustainable at 30 days prior to delivery with no inventory or cost penalties.
  • Overall value at risk (VaR): The sum of the probability of risk events times the monetary impact of the events for all the supply chain functions.

As performance indicators of the flexibility to enter as a partner in supply chains, the following are possible (see [HuMe97], p. 100):

  • Reduction of the company’s part in value-adding in the various supply chains.
  • The number of partners in a supply chain community and the turnover achieved by the supply community.

Additional performance indicators measure what has been achieved by the enabler objectives that were introduced in Figure 1.3.1.2. But as those are qualitative goals, it is generally not possible to calculate the degree achieved. Usually, a value is determined ranging from “insufficient” to “perfect.” See here [Hieb02].


1.4.6 Performance Indicators of the Primary Entrepreneurial Objective

We noted above (see Section 1.3.2) that the primary entrepreneurial objective is the return on net assets (RONA). To measure performance, the indicators in Figure 1.4.6.1 and Figure 1.4.6.2 are used:

Fig. 1.4.6.1        The performance indicator cash-to-cash cycle time.

Fig. 1.4.6.2        The performance indicator return on net assets (RONA).


Recap

The animations on the following pages show the Performance Indicators in the different Target Areas.
Click on the names of the indicators to get the accordant details.



Course sections and their intended learning outcomes

  • Course 1 – Logistics, Operations, and Supply Chain Management

    Intended learning outcomes: Describe basic definitions, issues, and challenges. Identify business partners and business objects. Explain strategies in the entrepreneurial context. Disclose how performance is measured.

  • 1.1 Basic Definitions, Issues, and Challenges

    Intended learning outcomes: Produce an overview on terms of the working environment and of business life. Explain service orientation in the classical industry, product orientation in the service industry, and the industrial product-service system. Disclose the product life cycle, the synchronization of supply and demand, and the role of inventories. Produce an overview on supply chain management, the role of planning and control as well as the SCOR model.

  • 1.2 Business Objects

    Intended learning outcomes: Present business-partner, and order-related business objects in detail. Explain product-related, process-related, and resource-related business objects. Produce an overview on rough-cut business objects.

  • 1.3 Strategies in the Entrepreneurial Context

    Intended learning outcomes: Differentiate between various entrepreneurial objectives in a company and in a supply chain. Explain resolving conflicting entrepreneurial objectives. Describe the customer order penetration point (OPP) and the coordination with product and process design. Produce an overview on the target area flexibility: investments in enabling organizations, processes, basic technologies, and technologies toward personalized production.

  • 1.4 Performance Indicators and Performance Measurement

    Intended learning outcomes: Present the basics of the measurement, meaning, and practical applicability of logistics performance indicators. Describe performance indicators in the target areas of quality, costs, delivery, and flexibility. Produce an overview on performance indicators of the primary entrepreneurial objective.

  • 1.5 Summary

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  • 1.6 Keywords

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  • 1.7 Scenarios and Exercises

    Intended learning outcomes: Describe improvements in meeting entrepreneurial objectives. Differentiate between entrepreneurial objectives and the ROI. Assessing the Economic Value Added (EVA) of Supply Chain Initiatives. Derive rough-cut business objects from detailed business objects.


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