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External influences on metrics - regulation and industry benchmarks

External influences on metrics - regulation and industry benchmarks

Warren, Liz ORCID: 0000-0002-1441-9369 and Brickman, Karen (2017) External influences on metrics - regulation and industry benchmarks. In: Harris, Elaine, (ed.) The Routledge companion to Performance Management and Control. Routledge. ISBN 978-1138913547 (In Press)

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Abstract

The design of a Performance Management (PM) control system is a complex process. As argued by Franco-Santos et al. (2014), performance is both multi-dimensional and ambiguous, resulting in challenges for the designer. PM control system design involves establishing operational processes to be linked directly to the organisation’s intended strategy. Designing a PM control system involves utilisation of Performance Measurement Systems (PMS), including benchmarking. However, there must be systems within the PM system to ensure targets/metrics within the PMS or benchmarking process are sufficiently flexible to accommodate change. To manage the complex processes within a PM system, the criticality of appropriate performance measurements for control systems, such as Total Quality Management (TQM), six-sigma and Just-In-Time (JIT), has long been recognised (Meybodi, 2015). In addition to appropriate measurements, it is noted that benchmarking can be used in many ways to achieve competitiveness, either to maintain continuous improvements, or for process reengineering (Meybodi, 2015). Within the benchmarking literature, focus on the nature of the metrics has evolved over the three decades since research in this area emerged. Whilst short-term targets were originally the common subjects of discussion when analysing financial and technical problems, these targets were frequently misaligned with the strategies of the organisation (Meybodi, 2015).

Companies invariably have strategies that provide two types of metrics/targets; the first being those intended to help manage the internal operations of the organisation and the second those set to help achieve externally imposed targets. Arguably there is a third type, i.e. intermediate cases, whereby companies design metrics to meet externally set targets, by measuring actions anticipated to achieve operational goals also. The combined approach to designing a good PM systems reflects the complexity of the process involved.

The preceding chapters, seven and eight, examined target setting in general and the manner in which multi-dimensional complexity can be analysed using composite measures. Whereas, this chapter presents a review of how the design of PM systems can be shaped through regulation and benchmarking. It will also consider the industry benchmarks commonly adopted by organisations as components in their own PM systems, within the target setting process, and will explore some of the mandatory targets imposed via regulation. Additionally, this chapter will assess the theoretical impact of external data sources, whilst providing the reader with a variety of examples, in the form of case studies as illustrative examples ; table 1 provides a summary of the cases presented herein:

Case Industry Contextual factors impacting on the design of the PMS Outcome
1 Financial services: banking Regulatory remuneration code changes and culture An example of good practice that demonstrates how regulatory changes can be aimed at reducing excessive risk taking in settings where significant cultural changes have occurred, explaining the shaping of PMS in the form of a Balanced Scorecard.

2 Utilities: Retail electricity Regulation on clear information An example of how industry can comply with regulation without adjusting outcomes. Regulation shapes the design of metrics used within the PMS without achieving the behaviour sought.
3 Financial services: banking Industry benchmarking An illustrative example that explains how companies can use data from other companies within the same industry to improve strategic outcomes.

4 Utilities: electricity generation Health and safety regulation and benchmarking An example of good practice, providing evidence of how regulators can provide extremely useful information that the industry can use to create their own benchmarking systems.

5 Utilities: electricity Distribution Network Operators Regulatory data on reliability and availability An illustrative example of how regulatory data can be used as a marketing tool in annual reports by industry reporting the same information to regulators and shareholders.

Table 1 – Summary of case studies presented in this chapter

Although the problems and unintended consequences of mis-designing metrics are not the main subject of this current chapter, they will appear toward the end of the chapter, and therefore, we will also touch on some of the general problems that arise.

Item Type: Book Section
Additional Information: Chapter 6.
Uncontrolled Keywords: Performance management, Performance management system, Metrics, Regulation and benchmarks
Subjects: H Social Sciences > HF Commerce > HF5601 Accounting
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of Accounting & Finance
Last Modified: 22 Jun 2017 10:48
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/16436

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