Use of Performance Measurement in the Public Sector: the case of the police service

Many public organisations have been under great pressure in recent years to increase the efficiency and transparency of outputs, to rationalise the use of public resources, and to increase the quality of service delivery. In this context, public organisations were encouraged to introduce the New Public Management reforms with the goal of improving the efficiency and effectiveness of the performance organisation through a new public management model. This new public management model is based on measurement by outputs and outcomes, a clear definition of responsibilities, the transparency and accountability of governmental activities, and on a greater value for citizens. What type of performance measurement systems are used in police services? Based on the literature, we see that multidimensional models, such as the Balanced Scorecard, are important in many public organisations, like municipalities, universities, and hospitals. Police services are characterised by complex, diverse objectives and stakeholders. Therefore, performance measurement of these public services calls for a specific analysis. Based on a nationwide survey of all police chiefs of the Portuguese police force, we find that employee performance measurement is the main form of measurement. Also, we propose a strategic map for the Portuguese police service.

Managing through measurement : A framework for successful operative level performance measurement

The research around performance measurement and management has focused mainly on the design, implementation and use of performance measurement systems. However, there is little evidence about the actual impacts of performance measurement on the different levels of business and operations of organisations, as well as the underlying factors that lead to a positive impact of performance measurement. The study thus focuses on this research gap, which can be considered both important and challenging to cover. The first objective of the study was to examine the impacts of performance measurement on different aspects of management, leadership and the quality of working life, after which the factors that facilitate and improve performance and performance measurement at the operative level of an organisation were examined. The second objective was to study how these factors operate in practice. The third objective focused on the construction of a framework for successful operative level performance measurement and the utilisation of the factors in the organisations. The research objectives have been studied through six research papers utilising empirical data from three separate studies, including two sets of interview data and one of quantitative data. The study applies mainly the hermeneutical research approach. As a contribution of the study, a framework for successful operative level performance measurement was formed by matching the findings of the current study and performance measurement theory. The study extents the prior research regarding the impacts of performance measurement and the factors that have a positive effect on operative level performance and performance measurement. The results indicate that under suitable circumstances, performance measurement has positive impacts on different aspects of management, leadership, and the quality of working life. The results reveal that for example the perception of the employees and the management of the impacts of performance measurement on leadership style differ considerably. Furthermore, the fragmented literature has been reorganised into six factors that facilitate and improve the performance of the operations and employees, and the use of performance measurement at the operative level of an organisation. Regarding the managerial implications of the study, managers who operate around performance measurement can utilise the framework for example by putting the different phases of the framework into practice.

Serving the American public : best practices in performance measurement : Benchmarking Study Report /

"June 1997."

Performance measurement of intensive care services in hospitals:The case of Barbados

The Intensive Care Unit (ICU) being one of those vital areas of a hospital providing clinical care, the quality of service rendered must be monitored and measured quantitatively. It is, therefore, essential to know the performance of an ICU, in order to identify any deficits and enable the service providers to improve the quality of service. Although there have been many attempts to do this with the help of illness severity scoring systems, the relative lack of success using these methods has led to the search for a form of measurement, which would encompass all the different aspects of an ICU in a holistic manner. The Analytic Hierarchy Process (AHP), a multiple-attribute, decision-making technique is utilised in this study to evolve a system to measure the performance of ICU services reliably. This tool has been applied to a surgical ICU in Barbados; we recommend AHP as a valuable tool to quantify the performance of an ICU. Copyright © 2004 Inderscience Enterprises Ltd.

Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector

Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

A Performance Measurement System to Manage CEN Operations, Evolution and Innovation

Part 16: Performance Measurement Systems

Performance measurement in child protection

The increasing use of performance measurement by government means that child protection services are under pressure to demonstrate effectiveness in protecting children from harm and efficiency in the use of public funds to help children and families. From a policy perspective, the way performance measurement is conceptualised and implemented can have major consequences for service delivery. This paper examines key issues raised in the literature about performance measurement, the context for its introduction in child protection, how the concepts of effectiveness and efficiency are dealt with, how client outcomes are defined, and assumptions about 'good performance'. An overview of performance measurement in child protection in Australia is provided. The paper argues that a critical approach to performance measurement in child protection can contribute to improved service delivery to clients.

Performance measurement and management in Portuguese law enforcement

Performance measurement of police services is complicated by ambiguous and complex goal- and objectives-setting, and by the difficulties of measuring outputs. This article looks at the organizational and management changes being made in Portuguese police forces. The authors fill a gap in the literature on performance measurement in Portugal by taking a national approach to the study of how law enforcement agencies are introducing new management accounting changes. The article therefore widens the debate on performance measurement and performance improvements in law enforcement.

Designing and implementing a performance measurement system in Auto Ribeiro, Lda.

In any business it is very important to measure the performance and it helps to select key information to make better decisions on time. This research focuses on the design and implementation of a performance measurement system in a Portuguese medium size firm operating in the specialized health care transformation vehicles industry. From the evidence that outputs from Auto Ribeiro’s current information system is misaligned with the company’s objectives and strategy, this research tries to solve this business problem through the development of a Balanced Scorecard analysis, although there are some issues, which deserve further development.

A behavioral perspective on the effects of using performance measurement systems in the companies: Evidence from a case study

The effects of PMSs on the people’s behaviour represent a high degree of relevance in the context of an organization performance and success. Thus, motivational and behavioural consequences of performance measurements are far from being totally understood (Franco-Santos et al., 2012). This work project (WP) purposes going further regarding the consequences/effects on people’s behaviour of using PMSs in organizations. The researcher conducted 11 interviews to managers during a nine-month internship as a controller in a Portuguese multi-national company. The evidence from this WP suggests that the way how managers understand a PMS determines a lot the way how they behave. Data also supports that PMSs influences in several ways motivation, perceptions, participation and job-related stress of managers.

Quantifying Uncertainty in Real Time Performance Measurement for Highway Winter Maintenance Operations – Phase 2, RB03-013, 2014

Winter weather in Iowa is often unpredictable and can have an adverse impact on traffic flow. The Iowa Department of Transportation (Iowa DOT) attempts to lessen the impact of winter weather events on traffic speeds with various proactive maintenance operations. In order to assess the performance of these maintenance operations, it would be beneficial to develop a model for expected speed reduction based on weather variables and normal maintenance schedules. Such a model would allow the Iowa DOT to identify situations in which speed reductions were much greater than or less than would be expected for a given set of storm conditions, and make modifications to improve efficiency and effectiveness. The objective of this work was to predict speed changes relative to baseline speed under normal conditions, based on nominal maintenance schedules and winter weather covariates (snow type, temperature, and wind speed), as measured by roadside weather stations. This allows for an assessment of the impact of winter weather covariates on traffic speed changes, and estimation of the effect of regular maintenance passes. The researchers chose events from Adair County, Iowa and fit a linear model incorporating the covariates mentioned previously. A Bayesian analysis was conducted to estimate the values of the parameters of this model. Specifically, the analysis produces a distribution for the parameter value that represents the impact of maintenance on traffic speeds. The effect of maintenance is not a constant, but rather a value that the researchers have some uncertainty about and this distribution represents what they know about the effects of maintenance. Similarly, examinations of the distributions for the effects of winter weather covariates are possible. Plots of observed and expected traffic speed changes allow a visual assessment of the model fit. Future work involves expanding this model to incorporate many events at multiple locations. This would allow for assessment of the impact of winter weather maintenance across various situations, and eventually identify locations and times in which maintenance could be improved.