Determination of Drivers of Stock-Out Performance of Retail Stores using Data Mining Techniques

Khalid Usman

Research Fest 2008

This project utilizes data mining techniques to determine the drivers of stock-out performance. Best performing and worst performing clusters of stores were identified using data clustering techniques. Furthermore, Logistic regression and multiple ordinary-least-squares regression were used to gain further insights and quantify the drivers of stock-outs.

22-May-08, Session 1 (8:30-9:30)

Comments (2)

i want to know the stock ou form

Posted over 3 years by Anonymous User

At TCLogic, we often describe this process as determining the drivers of inventory performance. For some organizations it may be the variance in lead time, or it may be the variance in demand. For others, it could be something entirely different. The underlying issue is discovering the drivers. Without the use of an advanced inventory optimization tool, it can be a daunting task. While this process is very data intensive, it can provide an organization with advanced inventory planning techniques that reduce inventory, improve service levels and add significant value to the bottom line. Visit http://www.tclogic.com for more information.

Posted 3 years by tclogic

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MIT CTL

Category: Education | Updated 2 months ago

Created: June 20, 2008 09:53
Category: General
Tags: trasportation, techniques, mining, research, center, retail, performance, drivers, fest, logistics, determination, stock-out, ctl, stores, supply, chain, data
Formats: H.264 Video (mp4)
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Determination of Drivers of Stock-Out Performance of Retail Stores using Data Mining Techniques

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