Theoretical background

This section addresses the concepts of performance measurement models and performance indicators separately in order to be able to differentiate them further in the study.


Performance measurement models

According to overviews in the performance literature, some of the most cited performance measurement models are the Balanced Scorecard, self-assessment excellence models such as the EFQM, and the models by Cross and Lynch, Kueng and Neely et al. A distinction should, however, be made between models focusing on the entire business and models focusing on a single business process.


Organizational performance measurement models

Organizational performance measurement models typically intend to provide a holistic view of an organization's performance by considering different performance perspectives. As mentioned earlier, the BSC provides four perspectives for which objectives and performance indicators ensure alignment between strategies and operations (Fig. 1). Other organizational performance measurement models provide similar perspectives. For instance, Cross and Lynch offer a four-level performance pyramid: (1) a top level with a vision, (2) a second level with objectives per business unit in market and financial terms, (3) a third level with objectives per business operating system in terms of customer satisfaction, flexibility and productivity, and (4) a bottom level with operational objectives for quality, delivery, process time and costs. Another alternative view on organizational performance measurement is given in business excellence models, which focus on an evaluation through self-assessment rather than on strategic alignment, albeit by also offering performance perspectives. For instance, the EFQM distinguishes enablers [i.e., (1) leadership, (2) people, (3) strategy, (4) partnerships and resources, and (5) processes, products and services] from results [i.e., (1) people results, (2) customer results, (3) society results, and (4) key results], and a feedback loop for learning, creativity and innovation.

Fig. 1

An overview of the performance perspectives in Kaplan and Norton (1996, 2001)


An overview of the performance perspectives in Kaplan and Norton (1996, 2001)

Since the BSC is the most used performance measurement model, we have chosen it as a reference model to illustrate the function of an organizational performance measurement model. The BSC is designed to find a balance between financial and non-financial performance indicators, between the interests of internal and external stakeholders, and between presenting past performance and predicting future performance. The BSC encourages organizations to directly derive (strategic) long-term objectives from the overall strategy and to link them to (operational) short-term targets. Concrete performance measures or indicators should be defined to periodically measure the objectives. These indicators are located on one of the four performance perspectives in Fig. 1 (i.e., ideally with a maximum of five indicators per perspective).

Table 1 illustrates how an organizational strategy can be translated into operational terms using the BSC.

Table 1 An example of translating an organizational strategy into operational terms using the BSC

Perspective

Strategy

Objective

Indicator, measure or metric

Target

Initiative

Year 1 (%)

Year 2 (%)

Year 3 (%)

Customer

Operational excellence

Industry-leading customer loyalty

Customer satisfaction rating

80

85

90

Mystery shopper program

Customer loyalty program

During periodical measurements using the BSC, managers can assign color-coded labels according to actual performance on short-term targets: (1) a green label if the organization has achieved the target, (2) an orange label if it is almost achieved, or (3) a red label if it is not achieved. Orange and red labels thus indicate areas for improvement.

Furthermore, the BSC assumes a causal or logical relationship between the four performance perspectives. An increase in the competences of employees (i.e., performance related to "learning and growth") is expected to positively affect the quality of products and services (i.e., internal business process performance), which in turn will lead to improved customer perceptions (i.e., customer performance). The results for the previous perspectives will then contribute to financial performance to ultimately realize the organization's strategy, mission and vision. Hence, indicators belonging to the financial and customer perspectives are assumed to measure performance outcomes, whereas indicators from the perspectives of internal business processes and "learning and growth" are considered as typical performance drivers.

Despite its widespread use and acceptance, the BSC is also criticized for appearing too general by managers who are challenged to adapt it to the culture of their organization or find suitable indicators to capture the various aspects of their organization's strategy. Additionally, researchers question the choice of four distinct performance perspectives (i.e., which do not include perspectives related to inter-organizational performance or sustainability issues). Further, the causal relationship among the BSC perspectives has been questioned. To some degree, Kaplan and Norton responded to this criticism by introducing strategy maps that focus more on the causal relationships and the alignment of intangible assets.

Business process performance measurement models

In addition to organizational models, performance measurement can also focus on a single business process, such as statistical process control, workflow-based monitoring or process performance measurement systems. The approach taken in business process performance measurement is generally less holistic than the BSC. For instance, in an established BPM handbook, Dumas et al. position time, cost, quality and flexibility as the typical performance perspectives of business process performance measurement (Fig. 2). Similar to organizational performance measurement, concrete performance measures or indicators should be defined for each process performance perspective. In this sense, the established perspectives of Dumas et al. seem to further refine the internal business process performance perspective of the BSC.

Fig. 2
An overview of the performance perspectives in Dumas et al. (2013)

An overview of the performance perspectives in Dumas et al. (2013)

Neely et al., on the other hand, present ten steps to develop or define process performance indicators. The process performance measurement system of Kueng is also of high importance, which is visualized as a "goal and performance indicator tree" with five process performance perspectives: (1) financial view, (2) customer view, (3) employee view, (4) societal view, and (5) innovation view. Kueng thus suggests a more holistic approach towards process performance, similar to organizational performance, given the central role of business processes in an organization. He does so by focusing more on the different stakeholders involved in certain business processes.

Performance indicators

Section "Performance measurement models" explained that performance measurement models typically distinguish different performance perspectives for which performance indicators should be further defined. We must, however, note that we consider performance measures, performance metrics and (key) performance indicators as synonyms. For reasons of conciseness, this work will mainly refer to performance indicators without mentioning the synonyms. In addition to a name, each performance indicator should also have a concretization or operationalization that describes exactly how it is measured and that can result in a value to be compared against a target. For instance, regarding the example in Table 1, the qualitative statements to measure customer satisfaction constitute an operationalization. Nonetheless, different ways of operationalization can be applied to measure the same performance indicator. Since organizations can profit from reusing existing performance indicators and the related operationalization instead of inventing new ones (i.e., to facilitate benchmarking and save time), this work investigates which performance indicators are used or mentioned in the literature on business process performance and how they are operationalized.

Neely et al. and Richard et al. both present evaluation criteria for performance indicators (i.e., in the sense of desirable characteristics or review implications), which summarize the general consensus in the performance literature. First, the literature strongly agrees that performance indicators are organization-dependent and should be derived from an organization's objectives, strategy, mission and vision. Secondly, consensus in the literature also exists regarding the need to combine financial and non-financial performance indicators. Nonetheless, disagreement still seems to exist in terms of whether objective and subjective indicators need to be combined, with objective indicators preferred by most advocates. Although subjective (or quasi-objective) indicators face challenges from bias, their use has some advantages; for instance, to include stakeholders in an assessment, to address latent constructs or to facilitate benchmarking when a fixed reference point is missing. Moreover, empirical research has shown that subjective (or quasi-objective) indicators are more or less correlated with objective indicators, depending on the level of detail of the subjective question. For instance, a subjective question can be made more objective by using clear definitions or by selecting only well-informed respondents to reduce bias.