Evaluating the Impact of Strategic Personnel Policies Using a MILP Model: The Public University Case

• Published in: Journal of industrial engineering and management Vol. 9; no. 5; pp. 1078 - 1089
• Main Authors: Torre Martínez, María del Rocío de la, Lusa García, Amaia, Mateo Doll, Manuel
• Format: Journal Article Publication
• Language: English
• Published: Barcelona Universitat Politècnica de Catalunya 01.01.2016; OmniaScience; Vicenc Fernandez; Universitat Politècnica de Catalunya. Departament d'Organització d'Empreses (OE)
• Subjects: Administració; Case studies; Colleges & universities; Condicions laborals; Economia i organització d'empreses; Gestió; Industrial engineering; Linear programming; Mathematical models; MILP; Optimization; Personal; Personnel management; Personnel policies; Public universities and colleges; Strategic planning; strategic staff decisions; Strategic staff decisions, university, MILP; Technology transfer; Treball; Universitats públiques; university; Workers; Workforce; Workforce planning; Àrees temàtiques de la UPC
• ISSN: 2013-8423; 2013-0953; 2013-0953
• DOI: 10.3926/jiem.2085

Purpose: The main purpose of the paper is to evaluate the impact of diverse personnel policies around personnel promotion in the design of the strategic staff plan for a public university. The strategic staff planning consists in the determination of the size and composition of the workforce for an organization. Design/methodology/approach: The staff planning is solved using a Mixed Integer Linear Programming (MILP) model. The MILP model represents the organizational structure of the university, the personnel categories and capacity decisions, the demand requirements, the required service level and budget restrictions. All these aspects are translated into a set of data, as well as the parameters and constraints building up the mathematical model for optimization. The required data for the model is adopted from a Spanish public university. Findings: The development of appropriate policies for personnel promotion can effectively reduce the number of dismissals while proposing a transition towards different preferable workforce structures in the university. Research limitations/implications: The long term staff plan for the university is solved by the MILP model considering a time horizon of 8 years. For this time horizon, the required input data is derived from current data of the university. Different scenarios are proposed considering different temporal trends for input data, such as in demand and admissible promotional ratios for workers. Originality/value: The literature review reports a lack of formalized procedures for staff planning in universities taking into account, at the same time, the regulations on hiring, dismissals, promotions and the workforce heterogeneity, all considered to optimize workforce size and composition addressing not only an economic criteria, but also the required workforce expertise and the quality in the service offered. This paper adopts a formalized procedure developed by the authors in previous works, and exploits it to assess the impact of various personnel policies in the staff planning for a particular university case, and this is the principal contribution of the paper.