Прогнозирование затрат времени на выполнение работ в системах управления рабочей силой

Abstract

The Workforce Management (WFM) systems, which allow organizations to manage workforce efficiency and related factors such as expected workloads, ideal staff numbers, and technical capabilities of staff are considered. WFM software ensures that an organization is functioning with an optimally productive team. The solution for forecasting problem of time costs for jobs performance provides the job’s number assessment in future and the quantity of necessary stuff. The analysis of time costs of job's performance shows that the time series designed using this data are homogeneous so the standard classic methods cannot be applied to forecast such data. The method of time series data forecasting using singular value decomposition and presenting it in the several phase spaces is proposed to solve this problem. The provided technique is very flexible and adaptive to forecast the data of different job types for different areas of business since it doesn’t restrict the statistical characteristics of original data.