Spend Analysis I: “It’s The Analysis, Stupid.”

Today’s post is from Eric Strovink of BIQ.

James Carville is not my favorite person, but he’s a funny man. And the above bastardization of his (in)famous Clinton campaign quote seems quite apropos, given the current frenetic level of marketing activity around “spend analysis” (I’m always amused by vendors using this term, because… excuse me for asking… where’s the “analysis?”)

So why is there so much spend analysis marketing activity, all of a sudden? I suspect it’s Oracle Terror. For the last nine years, I’ve watched spend analysis vendors promote their “product” — typically a service masquerading as a product — using the same tired strategy: “We classify data better than [those other guys].” Problem is, when you spend so much time and effort dumbing down spend analysis to a simple-minded premise, you open the door for almost anyone, even a sleepy ERP vendor, to steal your lunch. And that’s exactly what has happened. Oracle has neatly synthesized all of the “classification” messages together, packaging them up with some Silicon Valley marketing magic, and the legacy spend analysis vendors are in a panic. You’re absolutely right, folks, Oracle’s messaging is better than yours. Smarter, more sophisticated, priced innovatively — it’s both ironic and funny. The only surprise is that this didn’t happen years ago.

But here’s the point: real spend analysis is so much more than classification, that the whole classification discussion is absurd. It has always been absurd. Classification-centrism is the Titanic of spend analysis, aiming squarely at a snowball on the top of the iceberg, while completely ignoring the massive value beneath. Nevertheless, relentless classification-oriented marketing over many years has warped end-user perceptions, and carried analysts right along with it. Current analyst firm surveys are spending over 90% of their time on classification questions, Pandit’s hopelessly off-target book (previously dissected and dismissed by Sourcing Innovation) is garnering new attention, and so on.

My iconoclastic point of view has been outlined in these (and other) pages before, but put very simply, it’s this: Classification is easy. Armed with appropriate tools, any intelligent person (your admin, for example) can be trained to do it effectively, in about an hour; and the rules they generate can be applied automatically to new transactions, forever after. When you stop to consider that sourcing consultants have been performing effective spend analysis for years, using nothing more than pencil and paper, it’s obvious that the classification Emperor really doesn’t have any clothes.1

In fact, true value lies in the analysis that you perform. Value is about results, and results come from analysis, not from a data classification process that is just a baby step toward value realization, and one that may not even be relevant. For example, consider that spend classification is really only useful for A/P data. There are many higher-value sources of data lying around, and many datasets can be built from them. In most of those datasets, classification has no place at all. By the way, how many spend datasets do you plan on building? One? Just on A/P data? Then you are missing out on value, by a wide margin.

In this series, I’ll discuss the requirements for ad hoc data analysis, and the very real value that results from it. Spend analysis, at the end of the day, is just data analysis; so it’s critical that your data analysis tools provide the necessary power and flexibility to make you successful.

Next installment: Why Data Analysis Is Avoided

1Ironically, based on the datasets we’ve seen from customers who have walked away from their classification-centric vendors, talking a great game on classification doesn’t necessarily mean delivering great classification.

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