An Introduction to Sourcing Business Intelligence (Part 2): The Leap from Sourcing Analytics to Supply Intelligence [PRO]

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In Part 1 of this Spend Matters PRO research series, we defined and explored the concept of sourcing business intelligence (BI), an emerging focus area for an increasing number of procurement organizations. Sourcing BI is not a “tool” like a spend analysis application module or a general purpose BI tool — like the visualization tools Qlik, Tableau or Sisense. Rather it is an enabling approach to sourcing, supplier management, total cost modeling/should cost analysis and related initiatives like clean sheeting that focus on the ability to incorporate increasingly rich external market, commodity, category and supplier intelligence with existing internal data sets, process flows and activities to enhance savings, compliance and organizational resilience.

Much of this activity is occurring within category management where managers are trying to move from historical descriptive analytics to “outside-in” predictive/prescriptive analytics that yield true intelligence rather than just subscribing to tribal best-practices sharing and generic data-as-a-service (DaaS) offerings in the marketplace.

In Part 2 of exploring sourcing business intelligence, we first will set some context about how to make the leap from sourcing analytics to broader supply intelligence. “Supply management” is bigger than “sourcing management” — and similarly — “intelligence” is bigger than “analytics.” By understanding this evolution, it helps us set up a deeper discussion into how artificial intelligence relates to analytics — with an immediate focus on sourcing, but a longer-term focus on broader spend/supply.

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