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

As per our last post, in this series we are diving into spend analysis. Deep into spend analysis. So deep that we’re taking a vertical torpedo to the bottom of the abyss. And if you think this series has been insightful so far, wait until we take you to the bottom. By the end of it, there will be more than a handful of vendors shaking and quaking in their boots when they realize just how far they have to go if they want to deliver on each and every promise of next generation opportunity identification they’ve been selling you on for years.

We’re giving you this series so that you can use it to make sure they deliver. Because, as we have repeatedly pointed out, you only have two technologies at your disposal to achieve year-over-year savings of 10% or more. Optimization (covered in our last four-part series, see Part I, Part II, Part III, and Part IV), which can capture the value, and spend analytics, which can identify the value.

But, as we will keep repeating, it has to be true spend analytics that goes well beyond the standard Top N 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 means that, in organizations without highly trained analysts, the first generation tools would sit on the shelf, unused. And that is not how value is found.

However, creating the right UX is not easy. That’s why it takes a five part series just to outline the core requirements (and when we say core, we mean core — there are a lot more requirements to master to deliver the whole enchilada). But it’s needed because we are 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 when, in fact, they are not.

In each part of the series to date (What To Expect from Best-in-Class Spend Analysis Technology and User Design Part I, Part II, and Part III), over on Spend Matters Pro [membership required], the doctor and the prophet have explored three to four key requirements of a best-in-class spend analytics system that are essential for a good user experience. Here on SI, we’ve covered three of these to whet your appetite for the knowledge that is being kept from you.

In The UX One Should Expect from Best-in-Class Spend Analysis … Part I we discussed the need for real, true, 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.

In The UX One Should Expect from Best-in-Class Spend Analysis, Part II, we pointed out that one cube will NEVER be enough. NEVER, NEVER, NEVER! And 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 required cubes, cubes, and more cubes with views, views, and more views. But this is just the foundation.

Then, in The UX One Should Expect from Best-in-Class Spend Analysis, Part III, we indicated that success requires appropriately classified and categorized data. But good data categorization is not always easy, especially for the average user. That’s why the third key requirement is real-time idiot-proof data categorization, which, while a mouthful, is a lot easier to say than it is done. (For details, check out the articles.)

But, as you’ve probably guessed by now, more is required. Much more. In What To Expect from Best-in-Class Spend Analysis Technology and User Design (Part IV) over on Spend Matters Pro [membership required], the doctor and the prophet dive deep into a couple of additional key requirements for a best-in-class spend analytics solution. And, like the previous requirements, these are intensive. Quite intensive.

The one we are focussing on today is support for descriptive, predictive, and predictive analytics. First generation solutions stopped at descriptive. They simply reported on what happened in the past, and stopped there. And usually the description of the past was so far behind that the reports were not always that useful. So next generation moved onto predictive, and computed trends, taking into account historical sales data and current market data to describe opportunities so that, even if the data was a bit outdated, at least the analyst had a good idea of direction.

And as platforms got faster, and more powerful, and more real-time, the predictive power got better, and more useful. And organizations realized more value … but not nearly what they should realize. Because it’s not always enough to know that there may be an opportunity, to realize that opportunity, one needs an idea on how to capture it. And if one’s not a category or market expert, one can be completely lost. But if the system supports prescriptive analytics, then the analyst has an idea where to start. And that is key to a great user experience.

But is that everything the system needs for a great user experience. Nope. And we’ll continue our overview in the next, and final, part of this initial series. (We’ve written the first few chapters, but believe us when we say the book has not been written yet.)

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