Optimizing Bill of Materials Costs With Big Data Analytics

There are many disparate sources that design engineers, commodity managers, platform architects use to compile accurate Bill of Material (BOM) costs. The main barrier for effective cost data management are the excel-spreadsheet based manual processes which rely on a vast array of data sources and prevent a thorough understanding of cost gaps which in turn impacts our ability to drive favorable cost directions for Intel. There have been recent examples where Intel was paying two different prices for the exact same supplier/part which was calculated to have cost Intel $27 million in overpayment, and an additional $29 million potential higher payment that was caught by sheer luck. In this talk, we will share the business transformation via breakthrough solution delivery leveraging latest Big Data and Advanced Analytics technologies to achieve optimum BOM/component cost in outsource. The goal is to reduce platform costing cycle from 2-3 months to <10 days where by virtue of data-science and machine-learning algorithms now we are able to identify cost saving opportunities and highlight variances.