Practices vs Metrics

This section demonstrates both metrics and practices being considered important in performing benchmarking process. The section will point how important it is to remember that metrics without practices do not necessarily lead to better performance because knowing “how much” is not enough, one should also know “how” to achieve improvement. In practice this means that performing the benchmarking process an organization needs to do measurement and description of activity concerned. It may feel a little complicated especially in small and medium sized companies in which there are not so much resources for the process. This section will address the demand for versatile and easy tools for collecting measurement information, analyzing it and combining it to qualitative descriptions. Also some advice for selecting the object to benchmark will be indicated as necessary.

Benchmarking represents a versatile process management method that helps organizations identify and understand what constitutes best operating practices. There are at least two ways according to which the differences in practices can be analyzed and their impact assessed. The ways are illustrated by Camp (1989) in Figure 5.1 and Bogan et al. (1994) in Figure 5.2. There are metrics that are presented as quantitative benchmarks and the information is usually data in number format defining the achievement level of any given practice or system. Another form of information is qualitative describing practices in text format.

Managers understand the meaning of short-term financial results. Consequently, companies are learning to manage systems and processes that reach across traditional departmental or functional boundaries measuring both financial and no financial measures, which are quantitative benchmarks. This new generation of process managers creates a balanced scorecard of operating metrics that enable them to carefully monitor, maintain, and improve the health of the systems and work flows. Typical among the growing scorecard of no financial benchmarks are measures of work process speed, quality, first-pass yields, employee turnover, reliability, productivity, innovation, training, employee involvement, and learning (cf. Bogan et al., 1994; Reider, 2000).

Zairi (1994) divides metrics as financial performance indicators (business performance), technical performance indicators (productivity measurement), and efficiency indicator (human contribution measurement), which have to be continually calculated and reviewed. The basic idea should be that the quantification of the benchmark metrics could be accomplished by

87 modifying existing metrics to reflect different practices in order to be able to notice what the operation would look like after the best practices are adopted.

The meaning of qualitative word description of the practice and statement of opportunity analysis is not only the answer to the question “what”. There are also answers to questions “why” and “how”. The gap i.e. difference between the performance levels in the organizations must be broken down and the process must be described to the lowest significant component. The meaning of benchmarks requires to be interpreted. To be able to make a qualitative analysis for an operation it has to be presented as a step-by-step process or as a flowchart, for example (cf. Camp, 1989; Reider, 2000). For each process there is an input, a process between and an output. For each step in the process there is a supplier and a customer. Reider (2000) calls these descriptions as performance drivers as an exception to the typical terminology. He defines a driver as an underlying characteristic or factor of the company or its environment that determines the amount and type of activities performed to meet stakeholders’ demands.

Again Zairi (1994) gives a definition to practices being characteristics, which describes internal and external business behaviors, which tend to lead to the creation of a performance gap. Practices could be related to:

− the processes themselves − organizational structures − management systems − human factors

− strategic approaches.

According to figures of Camp (1989) and Bogan et al. (1994), combining these two analyzes; metrics and practices, is the way to find the best practices. Benchmarking investigations should concentrate on the understanding of practices before attempting to measure the results. For this reason the qualitative will be stressed first (Camp, 1989). Comparing numbers will not help one to compete; it is necessary to compare the practices that have given rise to the numbers (Bendell et al., 1993).

88 Fig. 5.2 Benchmarking for best practices (Bogan et al., 1994, p.5)

What gets measured is what gets managed and improved. It is the truth that many managers know and follow. Also in benchmarking process there is a tendency to stress the quantitative before the qualitative analysis. Fortunately, the rising tide interest in total quality management and the Malcolm Baldrige National Quality Award have highlighted the importance of performance indicators in achieving quality excellence (Bogan et al., 1994). Clearly, some form of quantitative measurement is essential in order to monitor progress towards the stated aims. However, often in the past, measurement has been carried out for its own sake. In general, what is required is a unified measurement system, which can be used for planning, for monitoring and for driving improvement. In benchmarking process there are some other important aspects like comparability of indicators in the form of units and the way that the information is gathered. There is a tendency to accept data and information that are believed to be comparable, especially from external visits (Camp, 1989). This could lead to acceptance of a cost per desired metric (cost per order for instance) as a correct statement of the benchmark although the orders are not comparable in the organizations because the order units are different. Another example of misleading comparison may be as simple as measuring the total delivery costs per product unit when the transportation distances and so also the freight costs are totally different. Normalizing data is one way to ensure that the information used is really comparable across companies. This is accomplished by mathematically deriving common denominators for all performance indicators. For instance, if the partner measures billing productivity per week and the

Metrics Benchmarks Operating Statistics Practices Benchmarking Processes

Best Practices

89 benchmarking team’s company measures productivity per month, the measures are normalized to daily, weekly, monthly, or some other common denominator (Bogan et al., 1994).

Ideally, the measurements used should indicate clearly how the organization is progressing towards its mission, and should avoid the failures of the past in which most measurement was financial and/or historic and so unfocused as to be confusing. The key to any successful measurement system is simplicity, both in the nature of individual measures and in the means by which it is unified into a coherent, focused whole (Bendell et al., 1993).

Camp (1989) also mentions the psychological effect of metrics; while most operations are quantitatively goal driven and targets are a way of operational life, if benchmarking external firms produces performance gaps beyond what may be considered normal and reasonable the shock can be considerable. Still he emphasizes that what is wanted is an understanding of practices first, then quantification of the effect of the practices to reveal the size of the opportunity. He also reminds that what is wanted when quantifying an operation is the level, not the precise number. (Camp, 1989) The practice offers examples of primary information found from the benchmarking activities being flow charts and process descriptions. The more important is to find best practices than numerical performance data. (Andersen et al., 1999)

In Jackson’s (2001) theories benchmarking results in three different products, which seem to cover metrics and practices as well as cooperative research environment:

1. Improved networking, collaborative relationships and mutual understanding between participants.

2. Benchmarking information – in the form of text, numerical or graphical information about the area of study (e.g. evaluative reports, guidelines, specifications, how to do it workbooks, specifications and codes of best practice, exemplars of good/different practice, statistics)

3. A better understanding of practice, process or performance, and insights into how improvements might be made. This understanding can be retained among the participants e.g. in order to gain or maintain competitive advantage, or it can be disseminated more widely through conferences, workshops, publications etc.

According to Boxwell (1994), not all benchmarking is created equal. Some collaborative efforts, although called benchmarking, are typical just data-sharing exercises that address the question “How much?” but fall short answering the question “How?” In that sense, these studies are not benchmarking as it is strictly defined, inwhich the benchmarking team learns not just how much improvement can be made but also how to make it.

90 As a conclusion of this section both metrics and practices can be considered important in performing benchmarking process. Important is to remember that metrics without practices do not necessarily lead to better performance because knowing “how much” is not enough, one should also know “how” to achieve improvement. In practice this means that performing the benchmarking process an organization needs to do measurement and description of activity concerned. It may feel a little complicated especially in small and medium sized companies in which there are not so much resources for the process. Versatile and easy tools for collecting measurement information, analyzing it and combining it to qualitative descriptions are needed. Also some advice for selecting the object to benchmark is necessary. In Section 5.3 these subjects will be explored.