What Do Bid Optimization and Corporate Strategy Have in Common? Everything.

I am a bit of a technology geek not just when it comes to procurement, but also supply chain and optimization. Twenty-five years ago, I did my university senior thesis project on redesigning the school’s mail delivery route using network optimization software (yes, they actually had optimization software back then). Since then, I have studied and implemented optimization tools from the shop floor to supply network design tools. A decade ago, I wrote in a report on “strategic transportation sourcing”:

“Win-win sourcing is mission-critical to all strategic spending categories. It’s important to realize that these [sourcing optimization] techniques and tools are applicable to all strategic spending categories. Unfortunately, there’s been a zone of lost savings opportunity between sourcing and the supply chain. Some firms use reductionist, price-centric competitive bidding techniques that clearly don’t capture the full value that suppliers have to offer. The sweet spot for strategic spending categories is the use of such expressive bidding techniques to create and capture this full win-win opportunity upstream at the source.”

Based on the 35-40 implementations that I studied in transportation procurement optimization, it was pretty clear that an optimization-based approach was delivering superior financial and operational performance outcomes, as opposed to the traditional competitive sourcing approach. However, although the technology needed to manage such large-scale combinatorial sourcing problems is impressive, it is obviously not only the tool that matters. The tool is a means by which a more sophisticated set of techniques are used within a broader methodology / framework and philosophy. That said, it irritates me when people say, “Oh, sourcing optimization is too complex and a niche area barely used and needed by most sourcing folks – it’s a niche tool.” My problem with this statement is that it throws out the philosophy, methodology, and techniques that are behind the tool. And what is that overarching methodology? It is called corporate strategy. Let me explain.

Corporate strategy is a fact-based process of developing strategic scenarios and then determining how to best allocate finite resources (i.e., financial and operational constraints) to support various business objectives and a balanced scorecard. The chosen strategies should hopefully be “optimal” in the sense that they minimize trade-offs and are doable by the various stakeholders (i.e., working within the truly hard constraints that cannot be changed).

Now, we can apply the same approach to a category strategy. Again, resources are limited, stakeholder requirements are diverse, and trade-offs and constraints are plentiful. Scenarios are developed with stakeholders during the planning process, and they are then used to improve the quality and robustness of the category strategy (while identifying additional opportunities that may be cross-category in nature). More generally, they improve how procurement will tap supply market power to help the stakeholders meet their objectives (i.e., a “balanced scorecard of supply” that I’ve written about here and here).

Makes sense, right?  So, why is it that when we take this approach to a specific market basket and sourcing project, it somehow becomes an obtuse technology thing rather than just doing good strategy work? The power of “collaborative sourcing” or “market informed sourcing” is not the tool, but rather the philosophy of cross-functional teams doing scenario planning, defining what they really want as an objective, reducing or eliminating unneeded constraints, and fully tapping supply market power. The optimization tool is just an enabler, albeit a critical one. My colleague Jason Busch has written about the scenario planning aspects here and here, and I’ve also talked about the use of various tools here.

So, my basic point is don’t pooh-pooh sourcing optimization as a niche piece of software functionality while you implement a reductionist “winner take all” process where non-price requirements are fixed and we bid out based on price. Rather, if you do strategy (corporate, category, bid event, etc.) the right way, you may end up using sourcing optimization a lot more than you had in the past. Sourcing optimization is about optimizing the sourcing process strategically, not the combinatorial optimization of supplier bids. Don’t throw out the best practice based philosophy, methodology, and techniques because of an advanced technology tool.

Can I get an amen please?

Thanks for listening.

Voices (5)

  1. Pierre Mitchell:

    Thanks Alan, you are indeed right. If it’s really about “supply chain versus supply chain”, then the supply chain should be optimally sourced from the onset, and that means letting suppliers put their best foot forward so that the best options are available and the best trade-offs can then be made. Crude heuristics like “winner take all” will go the way of the dodo as more sophisticated analytics become commonplace in the marketplace.

  2. Jennifer S:

    Amen!!

  3. Alan Gleeson:

    Excellent post Pierre. Another important point is that it is not ‘zero sum’. All parties can be happier with the outcome rather than the more adversarial ‘winner and loser’ approach that often occurs in procurement. Alan

  4. Pierre:

    Edith, I’m preaching to the choir with you and your husband David regarding supply chain optimization! MIT has been on the forefront here. Chris Caplice, the current executive director of MIT’s Center for Trucking and Logistics, wrote what I think was THE seminal piece on applying combinatorial optimization to truckload transportation sourcing – way back in 1996! Those techniques that made their way into niche sourcing tools have slowly crossed over into cross-category sourcing applications, but adoption still lags unfortunately.
    Keep innovating!

  5. Edith Simchi-Levi:

    Totally agree! My impression is that this is about to change and procurement will be pushed to take more of an end to end optimization approach to various decisions. Therefore its practitioners will require more analytic and supply chain knowledge to do their jobs.

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