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Cost Regression Analysis (CRA)

Procurement decisions are becoming increasingly complex, requiring supply chain professionals to evaluate many more factors before making important, strategic decisions.  Determining which factors are relevant, untangling interrelationships and understanding causality are essential for helping procurement teams avoid organizational paralysis when confronted with vast amounts of data.

Applied statistics can play an important role in this process.  By using mathematical techniques, savvy procurement practitioners can use statistical techniques to focus attention on the most relevant causal factors underlying today’s tough decision.

Cost Regression Analysis (CRA) is an example of such an applied statistical technique.  Through iterative modeling of various data elements, CRA helps make the relationships between individual variables apparent.  Procurement teams can use these findings to, amongst other things model ‘should costs’, identify savings opportunities not previously known and negotiates pricing variances.

Applications for CRA in Supplier Negotiations

CRA Savings Negotiation Scenarios


A.T. Kearney PA's combination of strategic sourcing expertise and extensive experience with CRA modeling allows us to provide numerous benefits to procurement organizations:
  • Achieve greater visibility into what drives pricing
  • Develop more effective sourcing and negotiation strategies
  • Identify ‘should costs’ to direct individual suppliers to areas of comparative advantage
  • Focus attention on key ‘triggers’ that have causal effects on pricing
  • Better anticipate and forecast future costs
The key challenge in applying CRA and other analytical techniques is to interpret and critique the findings generated by the model.  A.T. Kearney Procurement and Analytic Solutions’ combination of deep category and industry expertise along with analytical capabilities ensure clients benefit from robust analytical models that are both technically rigorous and functionally relevant.  Our consultants continuously check to ensure CRA models hold up against scrutiny from both technical, category, and market level perspectives The result is a market tested analytical model that allow our client to make buying decisions and conduct negotiations with an information advantage.

 
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CRA case study (coming soon)
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