University of Twente Student Theses


Strategic workforce planning model in business intelligence

Petersen, T.G. (2022) Strategic workforce planning model in business intelligence.

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Abstract:In recent years, more employees are changing profession. This causes new challenges for organizations to manage their workforce. The acquisition of essential knowledge is crucial for organizations and threatened if the competition has a better analysis of the market, better management of job preferences or is more resilient to the dynamics of supply and demand. Strategic workforce planning implies governing that “the right people with the right competencies are in the jobs at the right time” (Willis et al., 2018, p. 3). The difficulty of workforce management should be captured in strategic workforce planning research, along with the creation and application of models to advise strategies for workforce management. is a data start-up, specialized in realizing Business Intelligence and Artificial Intelligence solutions. They developed a mathematical model that provides parameters for workforce transitions through the organization which could predict future workforce occupation. This model builds on the Markov chain theory and offers a theoretical framework for strategic workforce planning. The research field of the Markov model lacks publications on the possibilities and the application of Markov in business intelligence, its integration into mainstream analytics tools, or how it could enable strategic workforce planning. The goal of the research is to assess how the integration of Markov chains in Business Intelligence can enable strategic workforce planning. It is important to understand what strategic workforce planning consists of, how Markov chains can integrate into a mathematical model and how the mathematical model can be used for analysis, strategic decision making and strategic workforce planning. According to the Creative Technology Design Process that consists of an Ideation, Specification, Realization and Evaluation phase, a Business Intelligence solution with an integration of a mathematical model based on Markov theory was developed in the Microsoft Power BI application. This solution visualizes the current workforce occupation, personnel change, predicted future workforce occupation and the onboarding targets to reach the desired workforce occupation. The evaluation through semi-structured interviews with potential users shows that the solution enables innovation, automation, standardization, customization, and development in relation to strategic workforce planning. The model contributes to innovation by accelerating digitalization and modernisation. The model contributes to automation by automatising data processing, limiting manual work and increasing efficiency by using a structured dataflow, reliable solution and unlocking capacity. It contributes to standardization by using centralized definitions, methodologies, and data processing. The model contributes to customization by offering room for changes in parameters, variables, definitions, formulas, and goals while offering organizationspecific insights. The research contributes to the academic discussion by making a first attempt at integrating Markov into business intelligence, a mainstream analytics tool, exploring its contribution to workforce analytics and realizing a strategic workforce planning model that enables analysis, strategic decision making and strategic workforce planning while incorporating different needs and applications in an effective approach. The interviewees endorse that the model alone cannot replace the entire process of strategic workforce planning. There are many aspects that are often nuanced or require more in-depth research in addition to quantitative analysis. The interviewees indicate that the model can contribute to the further development of strategic workforce planning and enable organizations to gain insight into anticipated workforce gaps and gain opportunities for the correct solutions to be implemented.
Item Type:Essay (Master)
Faculty:BMS: Behavioural, Management and Social Sciences
Programme:Business Administration MSc (60644)
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