Michael Lamoureux on the Future of Sourcing Optimization (Part 2)

In the first post in this series, I provided a high level overview of some of the suggestions that Michael Lamouruex makes in terms of future enhancements to sourcing optimization (click here to access the full research brief). In the second installment, I'll offer up what I believe are two other critical observations he makes in the paper about optimization, including the ability for suppliers to provide different offers for different products through "embedded substitution." Here Michael writes, "most strategic sourcing decision optimization platforms assume that one item requirement matches one product from a supplier. A couple of platforms allow multiple products from a supplier to match one item."

In the future, we'll see capabilities that enable more flexible and complete substitution. When this capability is available, a sourcing team member will be able to source, for example, at the bill of material (BOM) level for "a complex piece of machinery or electronics where engineering can permit substitutions at multiple levels" but "not necessarily any substitution as not all parts will be compatible with all other parts." Simply put, as optimization becomes more powerful, we'll see the ability for suppliers to further expand the "embedded" options within a broader set of parts, components, services, etc. based on their ability to deliver a complete, working solution. This will enable procurement organizations to get far more creative when it comes to evaluating make/buy options as well as expanding potential supply bases by allowing even greater potential substitution.

The future of optimization will also be prescriptive, as solutions "will recommend constraints," in Michael's words. These might take the form of "entire models" based on recommendations that the system recognizes for like parts, components, supply markets, etc. I'd also toss out that we'll see not only similar suggestive capabilities when it comes to actual constraints, scenarios and modeling, but also the underlying workflow in optimization capabilities as well (e.g., the ability for a certain offer or constraint to automatically acquire the approval of stakeholder in the organization).

All in all, for true sourcing geeks, Michael has done a bang up job painting what the future of optimization might hold. Even though the subject matter is very specific and by nature, somewhat technical, anyone who has an interest in sourcing optimization or has applied it in the past -- or is thinking of using it in the future -- should download a copy. But one prediction I'll toss out and highlight that I think is more important than all the technical advances that Michael proposes is that optimization will only gain wider adoption not only when it is even more powerful, but when it is easier to use and masks unnecessary and increasing complexity based on role, category, etc.

The best analogy I can think of in this area is to compare the future of optimization to piloting an inherently unstable aircraft that constantly corrects itself to stay in the air (e.g., the stealth fighter, F-22, etc.). These planes are too complicated to fly as one would another aircraft. Instead, they put the pilot in control, but make constant adjustments to keep the plane in the sky behind the scenes, presenting only the most relevant information and feedback along the way.

Jason Busch

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