A Framework for Strategic Performance Management for the Public Sector Using the Analytic Hierarchy Process
Toward Strategic Performance Management
Performance management systems are designed to obtain information from the environment through consultation with the public, stakeholders, public representatives, and analyses of the external environment in the strategic planning phase. This process produces a series of information categories such as strategic goals, objectives, performance measures, and targets (Moynihan 2008:6). The process of planning and implementing performance management mechanisms resembles the core idea ofstrategic management (Behn 2001, 2003; Bouckaert and Halligan 2008; Moynihan 2009). Based on the organization’s vision and overall strategy, the desired outcomes are set, and in a process of backward planning the outputs that can lead to these outcomes are planned. Then, the inputs and activities that may lead to these outputs are determined. In each stage of this process, we create goals, targets, and measures. Therefore, performance management can be viewed as strategic management, and the planning of such mechanisms is strategic planning.
However, many studies show that managers in public organizations adopt narrow views of strategic management such as key performance indicators, balanced scorecards, benchmarking, and lean management that overemphasize performance measurement rather than performance management (Arnaboldi et al. 2015; Broadbent and Laughlin 2009). These initiatives resonate with the classic phenomenon of following the latest managerial fads and fashions (Abrahamson 1996). Existing performance management © The Author(s) 2017
S. Mizrahi, Public Policy and Performance Management in Democratic Systems, DOI 10.1007/978-3-319-52350-7_5
systems focus on measurement and incentives, top-down mechanisms that exclude stakeholders and workers, and lack reference to the complex environment in which public organizations operate (Arnaboldi et al. 2015; Broadbent and Laughlin 2009; Moynihan 2008). As a result, performance management systems in public service organizations often have negative side effects that undermine the motivation, morale, and behavior of employees (Arnaboldi et al. 2015; Diefenbach 2009). The framework detailed in this chapter attempts to overcome these pitfalls.
Indeed, as explained in previous chapters, the performance management approach has faced serious criticism and objections (Behn 2003; Hood 2006; Moynihan 2008, 2009). Critics highlight the difficulties in setting goals, measuring performance in public organizations, and using the collected data effectively. Recent studies have paid special attention to the strategies of gaming adopted by the players involved in performance management systems and to the extent of, and the factors influencing, the use of information about performance (Bevan and Hood 2006; Courty and Marschke 2004; Heinrich 2007; Hood 2006; Mizrahi and Minchuk 2015, 2016; Radnor 2008). This malfunctioning of performance management systems is often exacerbated by the fact that managers in the public sector rarely use performance information to actually improve performance (Moynihan 2008). A series of studies attempting to explain the factors influencing the use of performance information demonstrate the importance of the commitment of transformational leadership to results, learning routines led by supervisors, the motivational nature of the task, the ability to link measures to actions, the availability of performance information, and flexibility in the organizational culture and its administration (Ammons and Rivenbark 2008; Moynihan 2008; Moynihan and Lavertu 2011; Moynihan and Pandey 2010; Moynihan et al. 2011b).
This chapter presents a decision-making tool for planning a performance management system that addresses these malfunctions in existing systems. This framework is based on two main principles. First, we describe a method through which managers can decide on goals, performance indicators, and technical performance measures in a way that minimizes the ability and motivation to game the system. This method is based on the application of the analytic hierarchy process (AHP) methodology that is usually used for grading multi-criteria alternatives where a subjective (expert) comparison between alternatives is required (Saaty 1990). In our context, this methodology helps rank the relative importance of each component in the organization’s activity by assigning weights to each one.
This method integrates various control measures that make it difficult to manipulate subjective goal setting and performance evaluations.
Second, the framework suggests integrating organizational workers into the performance management system by treating them as role experts who participate in setting goals, assigning performance indicators and measures, and evaluating the effectiveness of their roles. In accordance with the research mentioned earlier, we argue that such participation mechanisms help minimize the motivation to use gaming strategies and increase the likelihood of using performance information to improve performance. Hence, the framework described in this chapter presents a decision-making tool for planning performance management systems that minimize gaming strategies, encourage the use of performance information, and promote an organizational culture that encourages cooperative learning.
More specifically, the suggested framework produces a tri-level decision-making procedure. On the first level, we map the organization’s activities and evaluate the relative importance of each activity within a given dimension of the organization’s activity. On the second level, we calculate the relative importance of each dimension in the organization’s activities. Based on these two stages, managers can plan the performance management system, meaning they can decide which activities should be evaluated and the relative weights that should be given to each activity in the organization. To a certain extent, through this process the organization’s goals are also scanned and reevaluated. On the third level, we evaluate the measurement techniques through which activities are evaluated by assigning weights to their importance. This method also allows us to aggregate all of the performance components to produce a strategic performance management approach. Furthermore, given that the first stage is based on the workers’ evaluations of their role definition and assigned resources, the framework developed here can also help reform the organization’s structure.
To demonstrate the general framework and its empirical applicability, we develop decision-making tools for evaluating the performance of internal auditing in local government. In this case, performance is important, because it indicates how political and bureaucratic players view and treat public policy and decision-making processes. In our context, the first stage requires the identification of the main components of each function. We then use the AHP methodology to rank the relative importance of each component in the auditing report by assigning weights to each one. Finally, we apply this method to functions in local governments to illustrate the applicability of the framework to public organizations.