Daily Archives: October 19, 2016

How Do We Accelerate the Adoption of Optimization and Analytics? Part I

Every organization that adopts Strategic Sourcing saves time, money, and reputation (that would result from poor sourcing that typically results from tactical buying), but any organization that adopts Advanced Sourcing processes and platforms saves more. A lot more. Only advanced sourcing, based on analytics and optimization, saves an organization an average of 10%+ year after year after year, even when traditional sourcing methods fail.

But despite this, the adoption of modern analytics platforms and optimization-backed sourcing platforms is still minimal, and considering second generation platforms have been in existence for about ten years, and third generation platforms have been hitting the scene for the last couple of years (which can do more than first generation systems ever imagined) that can now be used by even the most junior buyer. There’s no reason that these systems are not in every leading Supply Management organization and every organization that wants to be a leading Supply Management organization.

Why aren’t these systems, which can deliver an ROI not only many times their cost but many times that of every other system, not being adopted?

Well, there are still the rampant myths that they are hard to use, require a PhD, and are only applicable for complex strategic categories, but anyone who does even a bit of research will realize that these myths only had (a shred of) validity with respect to first generation systems. There is also the belief that they are unaffordable (as first generation systems required high six figures, if not seven figures), but again research will illustrate that powerful systems are available in the five figure range and best in class systems, which support the organization end to end, can be obtained on an enterprise basis in the low six figures (and often deliver eight figures of value year after year, a 100X return). But what’s the real reason, and how do we overcome it?

If we want to really accelerate adoption, we have to figure out the critical roadblock. Last year, the prophet, in his post on brainstorming how to accelerate the adoption of sourcing optimization suggested the answer resided in:

  • simplifying the non-power user experience,
  • providing dynamic global/geo analysis from a visibility and risk perspective,
  • including greater API-based connectivity to back-end systems,
  • providing decision guidance as to the best models to use and scenarios to run, and
  • allowing for the sharing of models, scenarios, and best practice guidance between users

suggesting that the real reasons were

  • perceived complexity,
  • lack of visualization beyond cost tables,
  • lack of integration,
  • lack of guidance, and
  • lack of collaboration.

But, just like the myths, these reasons don’t apply to modern optimization-backed platforms, which make it easy to import and export data (for file-based integration, which is all that is needed); visualize data on a map and against constraints and identified risks; share models and scenarios; use pre-packaged cost and constraint templates (which is guidance); and walk a user through the advanced sourcing process using a wizard.

So what’s the problem? Why isn’t the adoption being accelerated? We’ll address this in Part II.