There’s No Such Thing as Spend Intelligence

For the last six weeks, I have been exploring problem solving methodologies you could use to help you with your sourcing problems. At a later date, I’m most likely going to take up six sigma and lean, but today I’m going to rant.

There’s no such thing as a Spend Intelligence Solution!

And before you start huffing and puffing about how wrong I am, please read this post in its entirety. Thank you.

A few weeks ago, Aberdeen released its study The Spend Intelligence Benchmark Report: Turning Data into Action. This study by Sudy Bharadwaj, Aberdeen’s new Vice President and Research Director of Global Supply Management, and Rick Saia, an Aberdeen Research Analyst, found that companies employing spend intelligence have reduced sourcing cycles by 19 to 25%, reduced the overall number of items they need to purchase by 10 to 15%, and reported contract compliance rates of 31 to 35%, depending on how long the program has been in place. These are some significant results, so there must be something to it.

Shortly after its release, this report sparked a considerable amount of coverage on the blogs. Jason Busch of Spend Matters challenged the thinking behind Aberdeen’s use of the phrase spend intelligence. The main points of his post were as follows:

Consider how in a recent study, Aberdeen adopted the term “spend intelligence” to describe the broader spend visibility and analytics market. The purpose of my post today is not to rip into the findings — the study itself is highly useful — but to challenge the thinking behind Aberdeen’s use and definition of the phrase, “spend intelligence,” which at this point feels dangerous to me, just as overly political language feels dangerous to Orwell. Why? As an attempt to shoot some Botox into a segment of the Spend Management market that can be challenging to explain and position, Aberdeen’s choice of language shortchanges and over simplifies a concept, potentially corrupting how the market will look at a key Spend Management business process. …

The problem is that spend visibility and analytics is much more complex, requiring data cleansing, rationalization, classification and other efforts which go far beyond what is needed to gain insight into basic HR, financials, IT and other internal information, which fall cleanly in to the BI camp. …

Fundamentally, “spend intelligence” should exist both inside and outside the organization, but Aberdeen’s usage might lead companies to think that everything they need lies within. The problem with this thinking is that supply market information changes all the time …

… by focusing too much on the final insight itself, “spend intelligence” conjures up images of the end-result, rather than the journey or path to get there (which can be as insightful as the data crunching itself). For example, in data gathering efforts, procurement can learn just as much about spend categories by talking with design engineers and operations team members as reading the SAP tea-leaves where dirty data resides.

Not long after, Tim Minahan, who used to occupy Sudy’s position at Aberdeen, of Procuri came to the defense of Aberdeen’s Spend Intelligence Moniker on his blog Supply Excellence. The main posts of his post were as follows:

As an analyst, every software vendor — … — touted their spending analysis capabilities. The caveat: you just needed to give them the data in a cleansed, classified, and structured format. … In short, most vendors pitched building a data cube or data warehouse from which you could run analyses and reports as spending analysis. They were wrong. And they confused the marketplace (possibly intentionally).

It is the automated and repeatable classification of spending information to a structured schema (e.g., UNSPSC, eClass, proprietary schema, etc.) and then the enrichment of this data with related business information (e.g., parent-child relationships, financial risk scores, contracts, performance information) that turns spend information from “dumb” data into true spend intelligence that a company can use to make fact-based sourcing and supply decisions rather than gut-based or hunch-based decisions.

The distinction between spend data and spend intelligence is an important one. Bravo Aberdeen for calling out the difference between dumb data and actionable intelligence.

And just a few days ago, Purchasing Magazine sponsored a webinar on the report where Sudy presented the main findings of the report and Brett Mauser of NCR, a corporation that recently implemented Zycus‘ spend management solution, discussed how spend intelligence has kicked NCR’s spend management program into overdrive. (Note that Zycus was one of the sponsors of the Spend Intelligence Benchmark Report.) The webcast has been archived for your review.

According to the study, and reinforced in the webinar, companies with best-in-class spend intelligence solutions have a process maturity that is twice that of their counterparts, and those processes are almost twice as likely to be aligned company wide. In addition, those processes are twice as likely to be automated. And mature, automated, processes get results. So why am I insisting that there is no such thing as a spend intelligence solution, when it appears that these solutions not only exist, but get great results?

Let’s start with the definition of intelligence.

Intelligence is a most complex practical property of mind, integrating numerous mental abilities, such as the capacities to reason, plan, solve problems, think abstractly, comprehend ideas and language, and learn.

And since spend management solutions are software, let’s review a definition for software.

Software is the (collection of) program(s) that enable a computer to perform a specific task, as opposed to the physical components of the system (hardware), where a program is the collection of source code and libraries which have been compiled into an executable or otherwise interpreted to “run” in (active) computer memory, where it can perform both automatic and interactive tasks with data.

Simply put, intelligence is a property of mind and software is a property of machine. And despite the efforts of the artificial intelligence community, I do not expect the property to cross the chasm anytime soon. Artificial intelligence is simply a collection of very sophisticated algorithms processing large data stores, instruction sets, and probabilities very quickly to come up with reasonable responses to queries – it is not thought, although it might appear to be thought since today’s computers can perform billions of calculations in a second. And that’s where my beef with the term spend intelligence lies.

Furthermore, as Jason Busch of Spend Matters points out, the term is very misleading and overlooks the fact that results from enhanced spend visibility and analytic efforts require data cleansing, rationalization, classification and other efforts which go far beyond what is needed to gain insight into basic HR, financials, IT and other internal information, which fall cleanly in to the BI camp.

So if you want to call it spend visibility, actionable spend, or maybe even spend knowledge, I’m all for it. But since the real intelligence lies in the user of the tool who takes the actionable data and uses it to get results, there is no spend intelligence software, only spend intelligence enablement software. And when you get right down to it, that’s what you really need as an expert power procurement user – software that helps you make the right decisions, not software that purports to make those decisions for you.

However, regardless of what you call it, check out the The Spend Intelligence Benchmark Report: Turning Data into Action while you have the chance. Just like the On Demand Supply Management report, it is top notch research, whatever you want to call it.  After all, as Tim Minahan pointed out, the distinction between spend data and spend intelligence is an important one, and the Aberdeen report is one of the first reports to call it out, even if I may take issue with the impreciseness of the terminology used.