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.

In our last four posts, we dove deep, really deep, into the basic requirements for any modern e-Negotiation platform (which we defined as e-RFX and/or e-Auction) and then dove deeper into the additional requirements for any e-Auction platform that claims to be a modern, best-in-class, e-Auction platform in the year 2017 (not 2007, where some seem to be stuck — but we won’t talk about them). [See Best-in-Class e-Sourcing Part I, Best-in-Class e-Sourcing Part II, Best-in-Class e-Auctions Part I, and Best-in-Class e-Auctions Part II.] But we excluded optimization for a reason, because the requirements for optimization go beyond — way beyond — the requirements for even the most intense set of requirements for the most advanced e-Auction platform (which can support bills of materials and constraints).

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) (that’s right, 4-part series), where we begin our deep dive into what best-in-class sourcing optimization looks like and how form follows function from a design perspective.

First of all, optimization is 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. Why do you think Coupa spent a healthy chunk of its IPO proceeds to purchase Trade Extensions. (They might not understand what they bought, or how to use it, 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.)

Secondly, it’s the only advanced sourcing solution that has been demonstrated, when properly applied, to generate year-over-year returns over 10% (and an average of 12% according to two of the first back-to-back studies conducted by Aberdeen last decade). 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.

Third, and most important, optimization identifies opportunities for both savings and value generation that no other platform can. Opportunities and supply chain designs no human, even with thousands of spreadsheets, will ever identify. It’s the foundation for a new sourcing age, but one that will only happen if optimization gets adopted, which will only happen if it provides a great user experience (as that’s the only thing that will overcome the math-based fear that surrounds it).

So what does such a platform need? Many, many things (as we dive into in What To Expect from Best-in-Class Sourcing Optimization Technology and User Design (Part 1) [membership required], but one thing it requires is powerful cost modelling.

You see, true calculation, and optimization, of the cost 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. For example, there are fixed costs to set up and start a production line, and then variable costs for each production level depending on raw resources, energy and manpower required to produce the product. And that’s just the beginning. You also have to worry about import / export tariffs, taxes, logistics costs, utilization costs, warranty, return, and disposal costs and a host of other category specific costs. If the costs aren’t modelled accurately, they can’t be optimized accurately. A great optimization platform thus supports flexible and powerful user defined cost models that break down costs as needed and to levels where individual elements can be optimized when possible.

And this is just the beginning.

Stay tuned for Part II in our series.