In a competitive environment, the minimization of downtime risk is of the utmost importance for companies. To hedge against high downtime costs and keep their equipment up and running, companies typically make a large investment in stocks of service parts.
However, it is notoriously difficult to manage these parts efficiently, since it is impossible to predict how many spare parts will be needed when with a great degree of accuracy.In practice, the prevalent approach is to control service parts stocks with ERP systems enhanced by inventory management modules. This approach is very reactive and generally results in poor performance, since the predictive power of black-box forecasting methods used in these modules depends on the quality and quantity of historical data, which are typically intermittent and scarce.
The alternative approach is to be proactive by observing the changes in the installed base and integrating this information into the forecasting management system to predict future demand shifts.
This approach is called installed base forecasting. Here, the demand for service parts is correlated to individual equipment units by first forecasting the changes in the number, age, location, etc. of these units, and then relating service parts demand to these changes. In summary, it uses black-box forecasting methods to estimate the individual demand rates for parts and then adjust the estimates to the size of the installed base.
Using more information in forecasting the machine level demand rate and decoupling it from aggregate level demand yields much better estimates in comparison to using black-box forecasting methods alone.
The side benefit of this approach is that it provides feedback on real failure rates per machine to the engineering department. For service providers, the use of installed base information can be particularly instrumental in foreseeing large shifts in the demand rate and initiating proactive measures (e.g., running the stocks down or up before the shift occurs), since this approach requires improved monitoring of the customers and the equipment under service contract.
Interestingly enough, many service companies are already collecting data on their installed base to predict short term parts requirements or for making other operational decisions. However, it seems that they neither direct this information towards service contract expiration predictions nor entirely integrate it in their inventory management systems. Installed base forecasting appears to be a promising method that may lead to improved spare parts forecasting. The effort put into establishing an installed base forecasting system is worthwhile -- especially for small installed bases of expensive equipment or large installed bases of standardized, cheap equipment.Backround Information:
Dr. Çerag Pinçe is Assistant Professor of Operations and Supply Chain Management at the Kuehne Logistics University. He received his PhD in Management from Erasmus University, Rotterdam and MS in Industrial Engineering from Bilkent University, Ankara. Before joining the KLU he worked as a Postdoctoral Research Fellow at the College of Management at Georgia Institute of Technology, Atlanta.
About the KÜHNE LOGISTICS UNIVERSITY (THE KLU)
The Kühne Logistics University – Wissenschaftliche Hochschule für Logistik und Unternehmensführung (KLU) is an independent, state-recognized private university based in the HafenCity district of Hamburg and sponsored by the non-profit Kühne Foundation. The KLU currently offers two Master’s programs in Global Logistics and Management, one part-time Executive Master in Leadership & Logistics and a Ph.D. program. From fall 2013 onwards a Bachelor in Management will be introduced. The programs are characterized by the international make-up of the student body and the faculty, an optimal faculty-student ratio, and a first-class corporate network. The KLU’s executive education provides excellent open enrollment and customized programs like the International Summer Schools for practitioners and managers. With what will in future be over 20 professors, the KLU covers all of the relevant areas of research and teaching in the fields of logistics, supply chain management and business management. By bundling international teaching and research competence in logistics and management, the KLU is the only university of its kind in the world.
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