Analysis of equipment demand for rental services

Abstract

The article examines the features of automated equipment demand analysis for companies providing rental services. The relevance of improving equipment inventory management in order to reduce the costs of its acquisition, storage, maintenance and repair is substantiated. The main problems of equipment rental companies are analyzed, in particular, asset downtime, mismatch of the demand range, the complexity of accounting for technical condition and the need to forecast future demand. An information representation of equipment is proposed, which takes into account its type, quantity, characteristics, rental cost, physical units, contracts and maintenance costs. Based on the proposed information representation, a set of indicators was formed for analyzing and forecasting equipment demand, in particular, the number of orders, the number of rental days, the seasonality coefficient and the load coefficient. A demand forecasting method was developed, which involves the integrated use of the specified indicators and the multiple linear regression model to determine the forecasted demand. To verify the proposed method, an experimental sample was formed based on a three-year history of data on equipment, orders, rental, availability, maintenance and repair. A comparison of forecasting using the Moving Average, Seasonal Naive and linear regression methods was carried out using the forecast error assessment metric. The results of the experiment determined the possibility of using the proposed approach for quantitative demand forecasting and forming recommendations for increasing, maintaining or optimizing the amount of equipment. The functional capabilities of the software for equipment accounting, management of rental contracts, analysis of use, generation of reports and recommendations for replenishment of stocks are determined. The proposed approach is aimed at supporting decision-making regarding equipment procurement.