Exploring knowledge work waste in public emergency services using the AHP algorithm

Abstract

Purpose

This paper aims to explore knowledge work waste and defines the priorities for enhancing performance and productivity in policing and prosecution services (PPS), especially in the crime investigation process (CIP).

Design/methodology/approach

Using the analytic hierarchy process (AHP), a case study of a Norwegian police district is examined to identify and prioritize the most performance-vulnerable crime investigation unit, using the adapted knowledge work waste as the performance metric.

Findings

Nine waste categories and 15 subcategories are identified and understood within a two-dimensional network of managerial and operational waste adapted for the PPS. The AHP helps classify levels of priority for each knowledge work waste and orderly prioritization of crime investigation units.

Research limitations/implications

The findings have limited generalizability, as they are based on a single Norwegian police district. This warrants research on the wider applicability of the adapted waste categories and approach.

Practical implications

This study can support public managers in implementing lean thinking and identifying the most prominent wastes in a complex system. In this context, processes and operations are among the factors dominated by knowledge work and are dependent on multiple stakeholders, cross-functional activities and interdisciplinary collaboration, which is more challenging to measure systematically and quantitatively than in a manufacturing environment.

Originality/value

This study contributes to the gap in lean thinking literature by advancing the knowledge on the adaptation and application of the foundational principles of lean thinking in the PPS and CIP.

Citation

Santhiapillai, F.P. and Ratnayake, R.M.C. (2023), "Exploring knowledge work waste in public emergency services using the AHP algorithm", International Journal of Lean Six Sigma, Vol. 14 No. 7, pp. 1431-1455. https://doi.org/10.1108/IJLSS-08-2022-0172