Overstock of aftermarket parts in Africa at Sandvik Stationary Crushing and Screening

Abstract: Title: Overstock of aftermarket parts in Africa at Sandvik Stationary Crushing and Screening Author: Mattias Johannesson Supervisor: Fredrik Olsson, Division of Production Management Background: An increase of customer expectations such as demand for more customizable options, shorter lead times and availability puts more and more pressure on a company's logistical processes. With fluctuating demand, inconsistent lead times and uncertainty around the world, variability is present and adds complexity to the logistical processes and needs to be handled appropriately to lower costs and match supply and demand. Purpose: Find major root causes of the overstock situation in the region of Africa and suggest solutions to these identified causes. Furthermore, investigate the possibilities of redistribution and scrapping of current obsolete inventory. Research questions: 1. What are the major root causes to the overstock situation in Africa? 2. How can these issues/root causes be mitigated and thereby reduce future overstock? 3. How can the current obsolete inventory be handled in terms of redistribution and scrapping? Methodology: The methodology presented and used is based on Höst et. al. (2006) and the project procedure presented by Hillier & Liebermann (2010). The initial step was to define and investigate the severity of the overstock situation, to then analyze and find the root causes of this phenomenon, based on the literature study and input from company representatives. From these root causes, different solutions are presented to ideally avoid or mitigate the severity of these causes in the future. To reduce the current inventory obsolescence, a framework based on quantitative historic data is presented, which explores the possibilities of redistribution and scrapping. Conclusion: Based on the analyzed data it was found that the two major root causes of overstock were the lag of the demand forecast for items that have lost demand and a manual forecast increase with no realized demand. It is concluded that there are operational possibilities of identifying potential loss of demand by studying the forecast accuracy on an item level, instead of on an aggregated level. Furthermore, it was found that there are possibilities of redistribution, mainly from Africa SA to SMCL to clear out obsolete and slow-moving inventory. Lastly, it was found that there is a significant non-zero probability of an item going from obsolete or slow-moving to moving again in the SMCL network, which dismisses the option of scrapping based on quantitative data and strengthens the argument of returning obsolete inventory from SA to SMCL.