Originally posted on on the e-Sourcing Forum [WayBackMachine] on

Yesterday I pointed out a recent report from Aberdeen in June of last year entitled “Success Strategies in Advanced Sourcing and Negotiations: Optimizing Total Costs and Total Value for the Next Wave of e-Sourcing Savings” where they determined that the application of optimization tools to analyze total costs, and of flexible bidding functionality to uncover creative supplier solutions has enabled early adopters to identify average incremental savings of 12% above those that basic, price-focused auctions alone have generated and discussed the fact that despite this result, optimization still is not used regularly across the board.

I also indicated that the lack of use of optimization across the board is likely the result of a number of factors that have historically combined to downplay the appeal of decision optimization, which has often been viewed as overly complicated unless absolutely necessary.

Specifically, I believe the lack of adoption of decision optimization across the board is the result of four key factors.

1. Early e-Auctions generated amazing returns.
2. Initial optimization offerings were hard to use and harder to understand.
   (In my view, MindFlow fell into this category.)
3. Many solution providers attempted to side-step the complexities by toning down their options.
4. A lack of integrated solutions on the marketplace.

I will now discuss each of these in more detail.

(1) Early e-Auctions generated amazing returns!

Many auctions generated double-digit returns, often in excess of 20%! This caused auction technology to be over-hyped as a technology for cost savings. As a former employee of an early provider of Strategic Sourcing solutions, I saw both the results and the buzz it generated. However, these results cannot be maintained indefinitely! Even if a supplier has a bloated margin of 100%, the most they will be able to give up and maintain viability is typically in the 60% – 80% range. In other words, after 3 events, there are no more margins to trim.

(2) Initial optimization offerings on the e-sourcing marketplace were hard to use and even harder to understand.

By its very nature, optimization, which is based in complex mathematics, is hard. Very hard. And many products had user interfaces to match. The underlying technology may be sophisticated, but this does not imply that the end product should be! Your car is a perfect example. Modern cars have very complex integrated mechanical, electrical, and electronic systems. But the user interface for an automatic is a gear shift (park, neutral, drive), a steering wheel, a gas pedal, and a brake. Decision Optimization should be the same – mind-boggling under the hood but easy as e-mail through the UI. Next generation systems will be. (I believe that this is one of the reasons that decision-optimization (only) companies like MindFlow never caught on beyond a few large CPG and Food Service companies. For example, even though there was a time when MindFlow could not be matched in terms of self-service optimization capability in the sourcing marketplace*, it was also true that it could cause the average user significant consternation. I believe that only sophisticated sourcing professionals with extensive training could take full advantage of the solution. *I’m sure a few individuals at CombineNet would disagree with this statement, but one thing I repeatedly heard from customers and prospects about their early solution offerings was that you needed one of their PhDs to run it for you. However, I should note that for certain areas, this is definately no longer the case with some of their recent releases.)

(3) Many solution providers attempted to side-step the complexities by initially toning down their offerings.

The proclaimed market leaders in the sourcing space provide us with examples. Whereas MindFlow built an extensive model (7+ logical dimensions) with ship-tos, ship-froms, built in lane support, complex cost structures, etc., some of the leaders went with simple point-based bid solutions. Bid 1 from Supplier 1 for Item X, Bid 2 from Supplier 2 for Item X, Bid 1 from Supplier 1 for Item Y, Bid 2 from Supplier 2 for Item Y, etc. with a couple of limit or allocation constraints. Although these products turned out to be much easier to use, they did not provide enough sophistication to model the real world supply chains and constraints of the companies that needed optimization the most! Interestingly enough, I believe that this is one of the reasons MindFlow lasted so long when many other optimization-based start-ups no longer exist (independently). MindFlow’s early market may have been small, but they were one of the pioneers of true decision optimization technologies and one of the few companies to offer the real power multinational CPG and food-service companies needed to accurately model their sourcing scenarios. (In comparison, CombineNet was one of the few companies that could handle their purely logistical models.)

(4) A lack of integrated solutions on the marketplace.

Many of the early providers of decision optimization only offered decision optimization. Furthermore, those companies that did offer other solutions typically weren’t best in class, especially from a usability perspective. However, leading sourcing professionals know that decision optimization is most effective when it is part of an integrated e-enabled strategic sourcing process and relatively ineffective on its own. (At least one of Iasta’s forthcoming solution briefs will elaborate more on this.) Decision optimization needs cost data (that results from auctions, possibly sealed bid), qualified award possibilities (that results from RFx and Supplier Scorecards), and an understanding of the supply chain strategy and appropriate commodity market (that results from spend analysis and proper processes). On its own, its capabilities are limited, integrated into an end-to-end e-sourcing platform, its capabilities are virtually endless.

Fortunately, market conditions are changing and I believe that the industry as a whole will not only be ready for this amazing technology very soon, but be hungry for it, especially when it is properly integrated into an e-Sourcing platform that provides best-of-breed technologies that support the end-to-end e-Sourcing process. The reasons I have for this forthcoming shift, and the reasons why some companies are working hard to build a best-of-breed decision optimization offering that is tightly integrated into an end-to-end e-Sourcing suite, will be illuminated in tomorrow’s post.

For a more in-depth discussion of decision optimization, what it is, what it is not, how it enables decision support, the benefits it provides, and strategies for success, see the “Strategic Sourcing Decision Optimization: The Inefficiency Eliminator” wiki-paper over on the e-Sourcing Wiki [WayBackMachine].