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Management of change: Lessons learned from staff reductions in the chemical process industry

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Author: Zwetsloot, G.I.J.M. · Gort, J. · Steijger, N. · Moonen, C.
Institution: TNO Kwaliteit van Leven
Source:Safety Science, 7, 45, 769-789
Identifier: 240106
doi: doi:10.1016/j.ssci.2006.08.028
Keywords: Workplace · Veilig en Gezond Werken · Downsizing · Management of change · Productivity · Safety management · Staffing arrangements · Unintended consequences · Chemical industry · Chemical plants · Competition · Decision making · Productivity · Safety management · Staffing arrangements · Unintended consequences · Safety engineering · Change management · Competence · Conceptual framework · Electrolysis · Engineering · Industrial worker · Occupational safety · Organizational structure · Personnel management · Time


Increasing global competition and shareholder pressure are causing major changes in the chemical industry. Over the last decade companies have been continuously improving staff efficiency. As a result, most modern chemical plants can be regarded as lean. Plans to further reduce the number of staff have come under increasing criticism by personnel for safety reasons, and there is strong resistance to further staff reductions. It is clear that management and workers often have conflicting viewpoints for more than just safety reasons; technologists and safety engineers also have different points of view. This results in complex decision-making processes and makes it difficult to realize changes. What can the chemical industries learn from their experiences of decision-making and management with regard to staff reductions? In our exploratory research that used four case studies, we were able to identify and analyse three distinct patterns, with some variations:•Fragmented and incomplete decision-making.•Unintended and undesirable side effects generated by the decision-making and management of change.•Development of difficult dilemmas and ambiguous issues. In this paper, we present a conceptual model that includes factors important for optimizing shifts. This model can serve as a common frame of reference for all agents involved in the decision-making and management process with regard to staffing. The present study was based on four cases, which means our findings serve to form rather than test hypotheses. At this early stage it is not yet possible to generalize from or validate the results, but we plan to go beyond these preliminary results in future research. © 2006 Elsevier Ltd. All rights reserved.