Daily Archives: July 25, 2017

The UX One Should Expect from Best-in-Class Spend Analysis … Part III

In previous posts, we took a deep dive into e-Sourcing (Part I and Part II), e-Auctions (Part I and Part II), and Optimization (Part I, Part II, Part III, and Part IV). But in this series we are diving into spend analysis. And this time we’re taking the vertical torpedo to the bottom of the deep. If you thought our last series was insightful, wait until you finish plowing through this one. By the end of it, there will be more than a handful of vendors shaking in their boots when they realize just how far they have to go if they want to deliver on all those promises of next generation opportunity identification they’ve been selling you on for years! But we digress …

We’ve said it multiple times, but we are going to repeat it again. The key point to remember here is that there are only two advanced sourcing technologies that can identify value (savings, additional revenue opportunity, overhead cost reductions, etc.) in excess of 10% year-over-year-over-year. One of these is optimization (provided it’s done right, useable, and capable of supporting — and solving — the right models; see our last series). The other is spend analytics. True spend analytics that goes well beyond the standard Top N and report templates to allow a user to cube, slice, dice, and re-cube quickly and efficiently in meaningful ways and then visualize that data in a manner that allows the potential opportunities, or lack thereof, to be almost instantly identified.

But, as per our last two posts, this requires truly extreme usability. Since not everyone has an advanced computer science or quantitative analysis degree, not everyone can use the first generation tools. This limits these users to the built-in Top N reports. And as we have indicated many times, once all of the categories in the Top N have been sourced and all of the Top N suppliers have been put under contract, there is no more value to be found from a fixed set of Top N reports. At this point, the first generation tools would sit on the shelf, unused. And that’s not how value is found.

However, creating the right UX is not easy. It’s not just a set of fancy reports (as static reports have been proven to be useless for over a decade), but a powerful set of capabilities that allow users to cube, slice, dice, and re-cube seven ways from Sunday quickly, easily, and repeatedly until they find the hidden value. It’s innovative new reporting and display techniques that makes outlier identification and opportunity analysis quicker and easier and simpler than its ever bin. It’s real-time data validation and verification tools that insure that a user doesn’t spend a week building a business case around data where one of the import files was shifted by a factor of 100 because of missing decimal points, destroying the entire business case in 4 clicks. And so on. And that’s why the doctor and the prophet are bringing you a very in-depth look at what makes a good User eXperience for spend analysis that goes far, far deeper than anyone has done before.

In a time where there seems to be a near universal playbook for spend analysis solution providers when it comes to positioning the capability they deliver and when many vendors sound interchangeable, and when many vendors are fungible in a way that is not necessarily negative, this insight is needed more than ever. And if a few dozen vendors quake in their books when this series is over, so be it.

In the first part of our series, we explored a few key capabilities that must be present from the get go, including, as we dove into here on SI in our first post on The UX One Should Expect from Best-in-Class Spend Analysis … Part I, dynamic dashboards. Unlike the first generation dashboards that were dangerous, dysfunctional, and sometimes even deadly to the business, true next generation dynamic dashboards are actually useful and even beneficial. Their ability to provide quick entry points through integrated drill down to key, potentially problematic, data sets can make sharing and exploring data faster, and the customization capabilities that allow buyers to continually eliminate those green lights that lull one into a false sense of security is one of the keys to true analytics success. (For more details, see the doctor and the prophet‘s first deep dive on What To Expect from Best-in-Class Spend Analysis Technology and User Design (Part I) over on Spend Matters Pro [membership required]).

In the second part of our series we explored a few more key capabilities, four to be precise, that include dynamic cube and view creation “on the fly”. Given that:


  • A cube will never have all available (current and future) data dimensions
  • Not all data dimensions are important;
  • Some of the essential data (referenced in the previous point) will be third-party data updated at different time intervals
  • A user never needs to analyze all data at once when doing a detailed analysis.
  • We have not (yet) encountered a system that will have enough memory to fit enough of a true “mega cube” in memory for real-time analysis.


One cube will NEVER be enough. NEVER, NEVER, NEVER! That’s why procurement users need the ability to create as many cubes as necessary, on the fly, in real time. This is required to test any and every hypothesis until the user gets to the one that yields the value generation gold mine. Unless every hypothesis can be tested, it is likely that the best opportunity will never be identified. If we knew where the biggest opportunity was, we’d source it. But the best opportunities are, by definition, hidden, and we don’t know where. Success requires cubes, cubes, and more cubes with views, views, and more views. (For more detail, or information on the other capabilities we didn’t cover in our post on The UX One Should Expect from Best-in-Class Spend Analysis … Part II, see the doctor and the prophet‘s second deep dive on What To Expect from Best-in-Class Spend Analysis Technology and User Design (Part II) over on Spend Matters Pro [membership required].)

But much, much more is required. That’s why the doctor and the prophet recently published their third deep dive on What To Expect from Best-in-Class Spend Analysis Technology and User Design over on Spend Matters Pro [membership required] on the breadth of requirements for a good Spend Analysis User Experience. In this piece, we dive deep into three more absolute requirements (which, like the previous requirements, are so critical the absence of any should delete a vendor from your list) including real-time idiot-proof data categorization.

Just about every solution has categorization, most allow end users to at least over-ride categorization, but, in our view few, relatively few solutions can claim (to approach) idiot-proofness.

So what is an idiot proof solution? Before we define this, let us note that the approach a provider takes to classification is secondary. It doesn’t matter whether the methodology provided is fully automated (and based on leading machine learning techniques), hybrid (where the machine learning can be overridden by the analyst with simple rules), or fully manual (where the user can classify data using free-form rules created in any order they want on any fields they want).

This means that the system must provide a simple and effective methodology for classifying, and re-classifying, data in an almost idiot-proof manner. So, if the engine uses AI, it should be easy for the user to view, and alter, the domain knowledge models used by the algorithms. If it uses rules-based approaches, it should be easy to review, visualize, and modify rules using a language and visual techniques wherever possible. And if the solution uses a hybrid approach, the user should be able to quickly analyze the AI, determine the reason for a mis-map, and then define appropriate over-ride rules that will correct any errors the user discovers so the error never materializes again in the future.

In other words, success requires cubes, cubes and more cubes on correctly mapped and classified data that can be accessed through views, views, and more views. With any data the user requires, from any location, in any format. But more on this in upcoming posts. In the interim, for additional insight on a few more key requirements of a spend analytics product for a good user experience, check out the doctor and the prophet‘s second deep dive on What To Expect from Best-in-Class Spend Analysis Technology and User Design (Part III) over on Spend Matters Pro [membership required].) As per the past two parts of the series, it’s worth the read. And stay tuned for the next two parts of the series. That’s right! Two more parts. We told you this one was a doozy!