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Analysis of Enterprise Material Procurement Leadtime using Techniques of Data Mining

Author(s): S. Hanumanth Sastry | Prof. M. S. Prasada Babu

Journal: International Journal of Advanced Research in Computer Science
ISSN 0976-5697

Volume: 04;
Issue: 04;
Start page: 288;
Date: 2013;
Original page

Keywords: Regression | Classification | APD | ARM | Purchase | Order | Purchase | Request | Prediction | BIW

Material procurement in a large enterprise depends on typical factors like Type of Material, the Departmental Hierarchy, the locationwhere material is used, dealing officer, material group etc. Minimizing the material procurement Leadtime at different stages is a business requirement. The influencing factors on Leadtime can be grouped according to business criteria and same can be analyzed for specific trends & patterns. This paper examines the Data Mining techniques applied to uncover natural groupings among leading attributes of Leadtime like Material groups, Purchase groups and Dealing officers. Performance criteria of Data Mining algorithms are measured by accuracy, comprehensibility and interestingness. The analysis is carried out with an objective to improve predictive accuracy of different categories of Leadtime. Our study confirms that regression modeling gives better predictive accuracy when outliers in data are less significant and scales up well to match new dimensional attributes on model.
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