Inventory and Supply Chain Management Essay

Tags: forecasting space variable revenue

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Vinod should consider forecasting all SKUs. Less than 3% of the SKUs were normally distributed. Without forecasting, there is no way to correct for the errors leading to Dockomo's current problem. If it helps, Vinod might be able to leave the SKUs with normal distributions alone, like the Cr106, Cr137, and Cr108. Otherwise, forecasting will help create a more effective supply chain distribution to meet the targeted service delivery goals. Exhibit 6 also shows that the percentage of stockouts does not vary overly much between the categories (V, M, S, and VS). This suggests that forecasting is needed for all categories and not just a few. In 2010, the company recorded a forecasting error of 70% for the top 5% of items, the ones contributing to the majority of their revenue and profit (p. 8). Therefore, Vinod might want to consider focusing on these top 5% at first, because of the clear connection to revenue and profit. With a target of customer service improvements, though, and the goal of 95% fill rates, just basing the forecasting on which items are costing the company most will not necessarily be a good idea. Vinod needs to address the inventory and supply chain distribution errors for all products. Basing orders on experience is fine for small companies with less complex supply chains, but not in a situation like this, in which demand is erratic, and supply is also variable.


2. Creating safety stock is a natural reflex to preventing future problemsin enterprise resource planning, and Dockomo should consider reducing its safety stock in accordance with the results of statistical analyses of both supply-side issues and demand forecasting.

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Currently, the company relies on anecdotal evidence and the prior experience of employees, which is barely better than intuition in helping to create a realistic inventory that meets actual customer needs, while also taking into account space limitations. The lack of updated inventory or buying policies, coupled with a mushrooming master parts list, is a recipe for disaster. "The tendency is often to hold too much inventory, and thus to avoid stockouts and the resulting fallout that lands on inventory managers," (Silver & Pyke, 2016, p. 806). A safety stock that is 1.2 to 2 times customer demand is unsustainable (p. 8). The safety stock problem is one of methods. Normal distribution only applies to three items (Cr106, Cr137, and Cr108). The rest of the items, comprising the bulk of Dockomo inventory, needs to reflect a methodology allowing for skewed distributions. In Dockomo's case, the distributions were extremely right tailed, all but the three normal SKUs and the two left-skewed SKUs (Cr108 and Cr1370. Using inventory management software, Vinod can input the data for each SKU, and come up with an appropriate scheme for managing safety stock. Examples of variables that can be input into the algorithm for optimal prevention of stockouts would include order data, shipment data, and existing inventory.
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References


Frankel, R.M. (2014). The Definitive Guide to Supply Chain Best Practices. Pearson.

Glynn, P.W. (n.d.). Inroduction to Stochastic Modeling. Retrieved online: http://web.stanford.edu/class/cme308/Oldwebsite/notes/Probreview.pdf

Silver, E.A. & Pyke, D.F. (2016). Inventory modeling. Encyclopedia of Operations Research and Management Science, p. 806-815.

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