Supply Chain and Risk Management: “3Ps” – Predictive, Proactive, Prescriptive

The fifth concept that I introduced as part of the ten items in my “what’s next” presentation at ISM’s Risk Conference in Chicago this summer was to appreciate the “3Ps” of risk management: Predictive, Proactive, Prescriptive. I noted in my talk that predicative tools, which take behavior patterns and make suggestions, have become commonplace in the consumer world— including applications with infinitely large datasets (e.g., Apple Genius and Pandora for music). Moreover, think about friend or colleague recommendations on Facebook or LinkedIn. But these approaches are only just starting to surface in the B2B sector.

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From a risk management perspective, what is important to pay attention to is the concept of decision guidance: to leverage the intent of the user (e.g., to place an order with one supplier or an alternative) to provide recommendations based on the outcomes they want to achieve within the context of the application itself outside of a different analytics layer or dashboard; and to surface information on either a “critical” or “need to know” basis.

Such approaches can focus on the basics (e.g., providing guidance based on general risk compliance). Or it can be more advanced, such as delivering predictive risk and performance analytics. In other procurement areas, the type of decision guidance that Beeline, for example, has built into their vendor management system (VMS) platform around rate recommendations and next steps in a requisitioning/sourcing process is already helping procurement teams make better decisions. Moreover, spend classification tools today rely on the same predictive building blocks.

Putting all of this together from a risk perspective is something few providers have even tried to tackle except within stand-alone tools (e.g., outside of primary procurement tools and systems themselves). But we believe that buying decisions for procurement suites in the next five years could very well hinge on their predictive and proscriptive recommendations to users based on intelligence and patterns within their organization as well as within a broader network.

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