“If a tree falls in a forest and no one is around to hear it, does it make a sound?” We’ve all heard this question, but may not recognize it for its practical value. It does, in fact, have practical applicability – I’m here to tell you how it applies to thinking about spend analysis. To that end, let’s posit the question a bit more specifically:

“If you perform a spend analysis and it isn’t being used properly, does it even matter?”

Data analysis, spend analysis included, is becoming more and more important to business operations. It is also a lot more prevalent than decades gone by. For Procurement pros to do their job most effectively, they need data analytics – no question there. What is questionable is the way we convey and ultimately the analysis.

Data vs. Information vs. Knowledge vs. Wisdom
Too often, analysts get too caught up in “data.” We spend our time collecting it, cleansing it, centralizing it… But then what? This data obsession is a mistake – we need to shift this preoccupation towards an obsession with developing “information” and transforming it into “knowledge.” Only then can we help our organizations create “wisdom.”

That was a lot of quotation marks and many people aren’t clear on the difference between these terms, so let’s break this down a bit:
  • Data is raw fact. Clean, simple, single-minded facts. By itself, a data point is useless.
  • Information is the organization of data into a collective whole. Information can be useful in terms of understanding a bigger picture.
  • Knowledge is the application of our subject matter expertise to information. Knowledge takes our information and applies it to our organization, specifically.
  • Wisdom is applying our knowledge to real problems to generate action. Wisdom allows us to improve upon our processes and practices.

This is vague summation of the DIKW pyramid, so let’s review in terms of spend analysis and sourcing in general.

An invoice lands on our desk. It’s for this month’s office supplies shipment. We see line items for pens: it has a SKU number related to a specific box of pens, 60 pens per box, and see we bought 10 boxes for $5.99 each. All of the things are data points. So far, so good.

As the months go by, we see several types of pens being purchased, all at different price points from a handful of different suppliers. We can compare costs and watch as they fluctuate over time. These differences are important bits of information for sourcing purposes.

Spend starts getting out of control on these pens – If the cheapest pen from the cheapest supplier suffices, then why are we buying all these expensive pens? Plus, if we consolidate pen purchases to a single supplier, ordering would be easier and we may be able to drive cost savings via consolidation among suppliers. This is knowledge.

We’ve reached our breaking point. Based on the number of suppliers and SKUs in play, we need to go to market to find the best price on the best product, and work harder to enforce on-contract office supply purchases. This is actionable wisdom.

This all Sounds Good – So Where are we Going Wrong?
Following a path from data inputs to insights to action, as we’ve done in our pen example, is exactly where we want to be. The problem is that we all too often don’t move all the way through. Too many of us as analysts get stuck hovering somewhere between point A (data) and point B (information), never closing in on the level of actionable wisdom to truly make an impact.

You can have the best spend analysis in the world, but it won’t matter one bit if upper management comes to you for proactive wisdom and all you can do is hand them a stack of facts and figures (with a few pie charts thrown in for good measure).

Where do we go from Here?
We need to get better in two ways:
  • We need to understand the value of data and where that value ends. Data will always be the crucial foundation of our analysis. However, the only time raw data needs to be presented should be as an addendum to this analysis, to be viewed only if our audience wants to look under the hood – A clear understanding of your data should never be a requirement to understand our analysis.
  • We need to move beyond providing a story and start providing action. Our CEO in the aforementioned pen saga isn’t interested in whether this supplier or that supplier charges more or less. He wants to know what we’re going to cut costs and maximize value – our analysis needs to end with a call to action and specific strategy for success.

Only once we learn to do these things are we going to make a true impact.
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Brian Seipel

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