The weather is unpredictable and can have a large impact on the profitability of seasonal businesses, particularly if staffing requirements are highly temperature-dependent. In this paper we describe our efforts in developing a what-if analysis tool to assist affected Small and Medium Enterprises in determining the best case scenario for timing hiring new staff and deciding the optimum length of temporary employment contracts. Together with a boiler maintenance company we have developed a prototype simulation tool that can be employed by users with minimal statistical and modelling knowledge. Our usability tests with the boiler maintenance company confirmed the usefulness of the developed tool as a decision support aid for managers. In this paper we focus on describing the tool development and testing process.
There has been a lot of work carried out in the area of Contact Centers (CC) and hospitals to determine the optimum number of staff needed based on the service requirements of the business. One of the biggest challenges contect centers faces each year is to estimate the required CC's staffing levels over the winter period, when it cannot be known in advance how severe the winter will be. Our aim is to develop a novel simulation tool that helps managers to make better informed decisions about their CC recruitment needs. For this purpose we want to integrate the ideas of "degree-days" consumption forecasting into a stochastic simulation model. The tool is also intended to support managers to estimate effective lengths of contracts for temporary staff.
