Forecasting sales in industrial services: Modeling business potential with installed base information. (27th November 2017)

• Record Type: Journal Article
• Authors: Stormi, Kati; Laine, Teemu; Suomala, Petri; Elomaa, Tapio
• Is Part Of: Journal of service management. Volume 29:Number 2(2018)
• Page Start: 277
• Page End: 300
• Publication Date: 2017-11-27
• Subjects: Profitability -- Servitization -- Customer lifetime value -- Industrial services -- Sales forecast -- Installed base; Service industries -- Management -- Periodicals; 658.005
• DOI: 10.1108/JOSM-09-2016-0250
• Languages: English
• ISSNs: 1757-5818

Abstract

Abstract : Purpose: The purpose of this paper is to examine how installed base information could help servitizing original equipment manufacturers (OEMs) forecast and support their industrial service sales, and thus increase OEMs' understanding regarding the dynamics of their customers lifetime values (CLVs). Design/methodology/approach: This work constitutes a constructive research aiming to arrive at a practically relevant, yet scientific model. It involves a case study that employs statistical methods to analyze real-life quantitative data about sales and the global installed base. Findings: The study introduces a forecasting model for industrial service sales, which considers the characteristics of the installed base and predicts the number of active customers and their yearly volume. The forecasting model performs well compared to other approaches (Croston's method) suitable for similar data. However, reliable results require comprehensive, up-to-date information about the installed base. Research limitations/implications: The study contributes to the servitization literature by introducing a new method for utilizing installed base information and, thus, a novel approach for improving business profitability. Practical implications: OEMs can use the forecasting model to predict the demand for – and measure the performance of – their industrial services. To-the-point predictions can help OEMs organize field services and service production effectively and identify potential customers, thus managing their CLV accordingly. At the same time, the findings imply new requirements for managing the installed base information among the OEMs, to understand and realize the industrial service business potential. However, the results have their limitations concerning the design and use of the statistical model in comparison with alternative approaches. Originality/value: The study presents a unique method for employing installed base information to manage the CLV and supplement the servitization literature.