Daily Archives: October 31, 2016

Trade Extensions is Redefining Sourcing, Part IV

In Part I, we not only told you that Trade Extensions unveiled the upcoming version of their optimization-backed sourcing platform at their recent user conference in Stockholm, recently covered by the public defender over on Spend Matters UK, but we also told you that, with it, Trade Extensions are redefining the sourcing platform. But we did not tell you how — instead reviewing the brief history of sourcing platforms, of which we’ve seen only three generations (with the third generation being optimization-backed sourcing platforms, which can be counted on one hand — and this should not be a surprise as there are only six true providers of strategic sourcing decision optimization as it is).

Then, in Part II, we built the suspense even more by taking a step back and describing the key features that are weak or missing in current platforms — namely usability, appropriate workflow, integrated analytics support, repeat event creation, limited visualization, and limited support for different types of users and collaborators. While these are not all of the features a platform might need, they are among the most significant and are certainly necessary for for the full power of advanced sourcing to be realized.

Then, in Part III, we finally discussed how Trade Extensions, realizing the need to not only offer these capabilities, but be best of breed in their offering, decided to tackle the creation of these capabilities head on (even though, unlike many of their competitors, they already had a current generation sourcing platform) in an effort to redefine not only their sourcing platform, but the advanced sourcing process itself.

And with TESS 6’s ability to support as many customized advanced sourcing workflows as the organization requires, where the workflow is not bound to the concept of a traditional sourcing workflow and can instead be defined using any combination of workflow elements in any order the buyer wants, TESS 6 is truly redefining the advanced sourcing process itself. Plus, it is in an elite class of the most usable enterprise software ever (despite supporting extreme complexity in the cost, constraint, and optimization models under the hood), with user management taken to a whole new level. But, as we noted in Part III, it is also coming with a new analytics capability that finally places analytics on the other side of the two-sided advanced sourcing coin, a piece that has, until now been missing. How? We’ll get to that but first, as promised, a brief history of spend analysis.

In the beginning, spend analysis was, depending on who you asked, the set of canned OLAP-based spending reports that came with your sourcing, procurement, or analytics suite or the process of mapping Accounts Payable spend and “drilling for dollars” (because, if you drill deep enough, there is always oil, or value, to be found).

This worked great, until it didn’t. In fact, depending on the skill of the user operating the “drill”, the organization would identify savings for somewhere between six and eighteen months. After that, savings would dwindle off. Why?

Most of the platforms limited the user to variations of Top N reports, which could only be drilled on a pre-defined set of dimensions; scatter plots, that allowed the user to see pricing trends and variances; and year-over-year trend reports. Top N reports are only so useful as most buyers know 7 to 8 of their top 10 suppliers, categories, geographies, departments, etc. Scatter plots are only good for as long as the supplier is still under contract, as you never really recover overspend after the fact. And year-over-year can typically be produced by the AP or ERP system, possibly sans graphics, so how much do they really add in the spend analysis package?

In other words, there was a lasting value problem.

Unfortunately, this wasn’t the only problem. If it was, it might have been partially overcome by switching to a service model where every 18 to 36 months the organization worked with a service organization to identify top categories with top waste. But there was a bigger problem. And we’ll get to that tomorrow in Part V.