Statistical analysis of Hungarian public service processes for key performance indicator measurement

Buics, László and Süle, Edit (2020) Statistical analysis of Hungarian public service processes for key performance indicator measurement. Hungarian Statistical Review, 3 (2). pp. 71-98. ISSN 2630 9130

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Abstract

The sophisticated and extensive toolkit for designing, managing, and measuring industrial processes is constantly expanding and forced to meet the new standards that are set by the limitless amount of data offered by the digitalisation of the industrial environment. However, services are managed under cumbersome conditions, in terms of expectations, measurability, and the modelling techniques used. Key performance indicators (KPIs) have been used for a long time in the private sector and industry compared with the public sector. Companies often use KPIs to measure the performance of individual processes to determine whether they meet or fail the expectations of customers and themselves. While public sector service providers are often monopolistic, the performance measurement also becomes a hot debate in the public sector as the citizens’ demand for quality services increases. This study aims to identify objective KPIs and demonstrate how they can be measured in a public service context, regardless of the type and complexity of the given service. As an example, the authors discuss the front office operations of government windows and the contact affair procedures of guardianship offices. They apply business process modelling in order to map the service processes and perform a statistical analysis to extract waiting, processing and lead times from the available dataset to comprehensively overlook these services. Their goal is to offer an analogy of industrial service process management by presenting how the methods and measures can be used to review processes in an industrial, manufacturing or public service, using a holistic management approach.

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