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Workforce modeling

From Wikipedia, the free encyclopedia

Workforce Modeling is the process by which the need for skilled workers at a particular point in time (demand) is matched directly with the availability and preference of skilled workers (supply). The resulting mathematical models may be used to perform sensitivity analysis and generate data output in the form of reports and schedules.

Adoption of a workforce model is usually found in industries that have complex work rules, skilled or certified workers, medium to large teams of workers, and fluctuating demand. Some examples include healthcare, public safety, and retail.

A workforce modeling solution can also refer to software that delivers results of the supposed management.

Definition

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The term can be differentiated from traditional staff scheduling. Staff scheduling is rooted in time management. Besides the aspects of demand orientation, workforce modeling also incorporates the forecast of the workload and the required staff, the integration of workers into the scheduling process through interactivity, as well as analyzing the entire process.

Complexity of model

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Many workforce modeling solution applications use the linear programming approach to create the Workforce Model. Linear methods of achieving a schedule are generally based on assumptions that demand is based on a series of independent events, all of which have a consistent, predictable outcome.[1] Heuristics have also been applied to the problem, and metaheuristics has been identified as the best method for generating complex scheduling solutions.[2][1]

Workforce modeling solutions can be created using a software solution for demand-oriented workforce management.

Notes

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  1. ^ a b Clancy, Thomas R. Managing Organizational Complexity in Healthcare Operations. The Journal of Nursing Administration 38.9 (2008): 367–370. Print.[citation not found]
  2. ^ Burke, Edmund; Causmaecker, Patrick De; Berghe, Greet Vanden; Landeghem, Hendrik Van (2004). "The State of the Art of Nurse Rostering". Journal of Scheduling. 7 (441–499). Archived from the original on March 4, 2016.

Further reading

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  • Sterman JD. Business Dynamics: Systems Thinking and Modeling For a Complex World. Boston, Massachusetts: McGraw-Hill Publishers; 2000.
  • Taleb NN. The Black Swan. New York, New York: Random House; 2007.
  • West B, Griffin L. Biodynamics: Why the Wirewalker Doesn't Fall. Hoboken, New Jersey: John Wiley & Sons Inc; 2004.