Optimal Team Pairing of Elder Office Employees with Machine Learning on Synthetic Data

Abstract

Synchronous office working environments are characterized by a high diversity of expertise and skills requirements during a product or service development. However, without the cooperation and optimal skills pairing among the employees, the success of a project may be negatively impacted. To take full advantage of the potential of each employee, project managers must learn how they can most effectively combine humans skills to benefit from their value. The current research work will assist businesses to make the power of intelligent collaborative matching part of the business core. The elaborated optimal team pairing framework, an integral part of the conceptual architecture of the SmartWork project, aims to combine numerous data sources and novel modelling processes from Machine Learning to provide the employers and project managers with a powerful tool in team pairing of elder office employees concerning a specific work task.

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