Performance Measurement and Performance Measures

In this section, we will provide a definition and criteria for a good performance measure and elements of the performance metrics to be able to execute Step 6 of the benchmarking process. Performance measurement is the process of quantifying an action; (Neely et al., 1995). To do so we need to set certain performance measures, which can be defined as “as a metric used to quantify the efficiency and/or effectiveness of an action” (Neely et al., 1995, p. 1229).

There are various performance measures. One characteristic which can differ is the level of detail: More detailed performance measures, like order lead time, have a high diagnostic power. They enable a more descriptive and complete view that clarifies the gap between planning and realisation. However, detailed measurements require a close monitoring and a highly frequent measuring. Generic operations performance measures, in contrast, like cost, quality, or speed, enable a broad view on the performance and show more the strategic relevance (Slack, Chambers, & Johnston, 2010). For benchmarking a combination of both would be suitable: first a more generic operational performance measure to illustrate their overall performance and then zooming in on it by using detailed performance measures of that field to identify performance gaps or best practices.

Not only can the level of measurement vary, but also the scope. Performance measures were used originally in the financial area; however, this encourages short termism and does not consider the external environment. Later on the focus shifted towards quality and consumer satisfaction. But as the environment is getting more dynamic, companies should also consider performance measures on long-term value creation, thus on innovation and knowledge management (Anderson & McAdam, 2004).

To define the scope of performance measurement different performance measuring frameworks are presented. There are several frameworks within the academic literature to categorise performance measures (Bourne & Neely, 2003). Some focus on the different levels of performance measures (e.g. performance pyramid by Lunch & Cross (1991)), others on the different organisational perspectives (e.g. balanced score card by Kaplan & Norton (1992), performance measurement matrix by Keegan, Eiler & Jones (1989)) and some on the horizontal (information or material) flow within an organisation (e.g. Inputs, processes, outputs, outcomes by Brown (1996)). Our aim is not to select performance measures that reflect the whole organisational performance, but to focus solely on the mail delivery process from a process manager perspective. Frameworks like the balanced score card presented by Kaplan & Norton (1992) or the business excellence framework are helping to translate the overall corporate strategy into a balanced set of performance measures, however those frameworks are too broad for our purpose. In contrast, the framework of Brown (1996) is very specific and focusses on processes. He emphasizes the difference between input, processing system, outputs, outcome and goal by suggesting that each step had its own specific performance measures (Neely et al., 2000). By applying this framework to the mail delivery process, we can gain clarity on internal factors; however this neglects external factors like customer satisfaction which are quite relevant for the process managers.

Slack et al. suggest a framework which incorporates different perspectives, but still keeps a focus on the operational level (see Figure 4.2). Using this model enables us to combine all three procedures suggested by Bourne and Neely (2003) for developing performance measures, the needs led procedure which considers the requirements of customers, business and stakeholders which we can see within the top-down and market requirement perspective, and the audit led procedure which follows the bottom-up perspective. Finally, within each perspective we can apply theoretical models which would be the model led procedure. For instance, to analyse the day-to-day experience we can apply the framework for processes of Brown (1996).

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FIGURE 4.2:THE FOUR PERSPECTIVES ON OPERATIONS STRATE GY (SLACK ET AL.,2010)

Overall, we use the four perspectives on operations strategy framework as a guideline to derive performance measures. However, before being able to define performance measures we have to clarify some criteria for a good performance measure as well as the elements of the metric, which we do in the following section.

Criteria

To ensure effective performance measures we use the 22 recommendation given by Neely et al. (1997). They selected based on the extensive academic literature review on performance measurement of Neely, Gregory and Platts (Neely et al., 1995) ten different papers and books to develop those recommendations. We summarised the most distinctive recommendations below and categorised them into five different areas: the development, aim, calculation, presentation and implementation of performance measures.

Performance measures should … 1. Development:

a. …be derived from strategy and reflect the business process – i.e. both the supplier and customer should be involved in the definition of the measure.

2. Aim:

a. …have an explicit purpose and relate to specific goals (targets) b. …focus on improvement

c. … provide information 3. Calculation

a. …be clearly defined and be based on an explicitly defined formula and source of data b. …employ ratios rather than absolute numbers and be based on trends rather than

snapshots

c. …be based on quantities that can be influenced, or controlled, by the user alone or in co-operation with others

d. …use data which are automatically collected as part of a process whenever possible 4. Presentation:

a. … be simple to understand and should be reported in a simple consistent format 5. Implementation:

a. …be part of a closed management loop

b. …provide timely and accurate feedback and should be objective – not based on opinion

c. ..be consistent (Neely et al., 1997, p. 1337)

32 The aim of Neely et al. (1997) is that the recommendations can be applied universally, however for our project we need to make some specifications and adaption of the Recommendation 1a, 2a, 5a, 3b and 3d:

Recommendation 1a: Performance measures should be derived from strategy, but as we do not define performance measures for the corporate level, we should focus on the strategy for the mail delivery process. This strategy is defined by the logistic strategy department based on the corporate strategy and the requirements of the mail delivery process.

Recommendation 1a: Scope of our research is to define performance measures for the mail delivery process which starts at the HUB or depot and ends at the customer. Thus including suppliers would be out of our scope. However, we consider the customers as for service provider, which the mail delivery department is, customer satisfaction is critical (Chan et al., 2009; Grönroos & Ojasalo, 2004).

Recommendation 2a: Benchmarking is more focused on learning and exchanging (Dattakumar & Jagadeesh, 2003; Voss et al., 1997; Yasin, 2002) than on fulfilling specific targets. Achieving certain targets is rather important in MJ dashboards at PostNL, which compares budgets to the realisation. To motivate process managers, we should provide a certain goal. In benchmarking the goal is to adapt best practices from others. Thus each goal of a performance measure is based on the best score within the benchmarking and given per cluster.

Recommendation 5a, 3d: Those recommendations are highly important and we do consider them, however as we are not implementing the benchmarking model, but only design a prototype, designing an information system that could automatically retrieve the information is out of our scope. Furthermore, we do make recommendations for the management of the benchmarking, but do not design and implement a specific management loop.

Recommendation 3b: Evaluating trends rather than snapshots gives the advantage to assess and to compare performance improvements between the different benchmarking partners, however snapshots can give insights into one moment and enable to zoom in and determine the root of the problem. By combing snapshots of different moments, we are still able to show the performance trends.

Elements of the Performance Metrics

Based on the comparison of the two benchmarking processes, we should define as part of the benchmarking process a metric for each performance measure to ensure that it is sufficiently specified. Binder et al. uses four elements for the performance metrics: related CSF, title, unit of measurement and formula of the performance measure. Anand and Kodali (2008) add one more element: the interval of measuring the performance. Still, those elements are not sufficient as the recommendation by specifying only those elements are not fully satisfied. For instance, those elements do not clarify the relevance (Recommendation 2a) of the performance measure.

Neely et al. (1997) developed a performance measure record sheet, which incorporates ten elements derived based on the 22 recommendations. This framework (see Table 4.2) incorporates not only those recommendations, but also covers the elements named by Binder et al. (2006) and Anand and Kodali (2008). Using this framework for our performance metrics ensures that performance measures are sufficiently specified, which is a critical part of Step 6 in our benchmarking process.

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TABLE 4.2:PERFORMANCE MEASURE R ECORD SHEET (NEELY ET AL.,1997) Element Related

recommendation

Description

Title 3a, 4a The title should not only specify what has to be measured but also why. It should be easy to understand and self-explaining.

Purpose 2a To clarify the relevance of the performance

measure one should briefly state the rational reasoning behind it.

Relates to 1a, 2a, 2b The performance measure is related to the business (or in our case the mail delivery department) objective to show the value and the connection with the overall context.

Target 2a, 2b, 2c, 3c, 5a The performance measure should provide a certain target, which we base on the best performance within the benchmarking.

Formula 1a, 3a, 3b, 3c, 4a, 5b The formula enables to calculate the performance measure but also determines the unit of measurement.

Frequency 2c, 4a, 5b, 5c Includes the frequency of measure and of review

Who measures? 3c, 3d Specifies the person that collects and reports data

Source of data 3a, 3b, 3d, 4a Clarifies the source of the raw data to ensure consistency in the measurement over time

Who acts on the data?

2a, 2c, 3c Names the person who is responsible for acting on the measure

What do they do? 2a, 2c, 3c Specifies actions that could influence the outcome of the performance measure

Notes and comments