In early 2013, I wrote this article on the applicability of predictive analytics in the world of sourcing and procurement.  In the article I point out that many other industries are well ahead of sourcing and procurement when it comes to data modeling and predictive analytics.  Sales and Marketing groups certainly have taken advantage on using data to anticipate what buyers want.  The healthcare industry is using predictive analytics to increase the accuracy of diagnosis and hospital readmission rates.  The government even uses it to identify cases of tax fraud.  The applications suited for predictive analytics and appear to be limitless.

But two years later, not much has changed for sourcing and procurement professionals.  The existing tools and service providers still haven’t come up with any solutions that properly address the need organizations have to pro-actively ensure that they are buying on contract, anticipate how changes in raw material prices will impact final costs, or classify spend in an ongoing and meaningful way for sourcing and finance to make decisions based on datasets without a lot of manual rework.

Yet these needs do exist – so why aren’t more solutions available?  I believe one primary reason they have yet to come to fruition for our industry is because we are still focused (and measured, by the way) on taking cost out of an existing expenditure (most widely known as savings) versus anticipating costs and driving it out of future spend (what Finance unfortunately calls cost avoidance).  In other words, if it didn’t happen, it can’t be called savings.

Think about it.  Over the last five years, sourcing groups focused our procurement transformation projects on developing category management teams, implementing supplier relationship management programs (kind of) and creating procurement “Centers of Excellence” to assist with tools, process and reporting to support our sourcing managers.  Yet to some extent, these are all reactions to existing needs within our organizations.  Yes they allow sourcing to become more efficient and effective.  They allow us to obtain savings.  But they don’t allow us to predict costs – and pro-actively remove them from the system.   And I believe the primary reason is because we won’t get credit under the antiquated definition of savings.

Still, the industry continues to evolve and at Source One, we are evolving with it.  Most recently we hired our first data scientist – a position I hope we will begin to see in many Procurement COE’s across the industry.  In three years, I believe Procurement Data Scientist should be as common an occupation as Sourcing Analyst.                                                                                                                
Our goal in hiring a data scientist?  Our humble objective is simple - to change the future of spend management.  For years at Source One, we’ve helped client’s increase spend under management, optimize compliance and utilize index based pricing to pare out costs.  But even for us, the process has been manual and reactive.  We understand that simple business rules and access to the right data can easily change the way sourcing professionals do their work.  And we are embarking on a journey to develop that solution.
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Joe Payne

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