In our last post on The UX One Should Expect from Best-In-Class Optimization we began our foray into the world of optimization and how the requirements for a good user experience goes well beyond the requirements for e-RFX and even best-in-class e-Auction. (As for the basic requirements of any e-RFX or e-Auction platform, see our two-part series on Best-in-Class e-Sourcing Part I and Part II and our deeper dive into Best-in-Class e-Auctions Part I and Part II.)
In our post, where we noted that last Thursday over on Spend Matters Pro [membership required] the doctor and the prophet posted the first article in our four part series on “What to Expect from Best-in-Class Sourcing Optimization Technology and User Design (Part 1)”, we indicated that optimization is important, very important, and about to become even more important as savings go up in smoke due to inflation, protectionist policies, and insufficient supply of raw materials. (And, as we noted, that’s why Coupa spent a lot of its IPO proceeds to buy Trade Extensions. They might not understand what they bought, or how to use it, or where it fits in, but they saw the future and wanted to get in the game early enough to have some time to — hopefully — figure it out before their competition.)
Plus, as we noted, it’s the only advanced sourcing solution that has been demonstrated, repeatedly, by analysts and providers alike, to provide year-over-year returns over 10% when properly applied. Plus, unlike spend analysis, which only identifies the high-level savings opportunities (which can only be captured if appropriate events are undertaken, possibly based on optimization), optimization produces the exact award scenario required to generate the savings. And, often, this will be a scenario that will never, ever be identified by any human, even if given enough time to generate dozens, or even hundreds, of spreadsheets.
In our last post, we noted that one of the core requirements of such a platform was powerful cost modelling as true calculation, and optimization, of the costs of goods sold requires complex breakdowns and formulas because, in practice, with even the most “vanilla” or simplest of products, there are fixed costs and variable costs and that these change at different production levels. And in addition to fixed and variable costs associated with the product creation, there’s also import / export tariffs, taxes, logistics costs, utilization costs, warranty, return, and disposal costs and a host of other category specific costs.
But that’s just one core component of the platform. Another, as explained in the doctor and the prophet‘s second piece on “What To Expect from Best-in-Class Sourcing Optimization Technology and User Design (Part 2)” [membership required] is guided sourcing by way of system-assisted “what-if” support.
Cost modelling is indeed a powerful tool, especially when compared to a system that doesn’t have it, but arguably the real power of a strategic sourcing decision optimization tool lies in the ability to generate, analyze, and compare what are called “what if?” scenarios. This statement holds true both when analyzing cost and when analyzing risk, as well as the broader resilience components of sourcing award/allocation decisions.
As the co-authors note, even expert sourcing optimization users commonly look to collect data and apply constraints centred on near-term thinking — and award decisions. But when viewed in true context (i.e. an awarded supplier’s performance over the term of the contract), it is rarely the lowest cost and resulting business allocation scenario that brings the greatest value to the organization. Rather, it is the scenario that is the most resilient in the face of unpredictability.
Moreover, even minor variations resulting from different initial or future award considerations can have drastic impacts on costs. And it is only through such scenario analysis that a slightly higher cost award decision today (or in the future) could end up delivering far greater organizational value. Users can now think through all such potential scenarios, so it should be common practice to use the capability to test hunches and/or quantify potential risks … which can only be done with the right sourcing optimization platform with a modern, appropriate, user experience.
But this is just another piece of the puzzle. Stay tuned for Part III.