Daily Archives: February 15, 2017

Do You Need a Spend Cube to Identify Top Underperforming Products?

No, you don’t. But that doesn’t mean you shouldn’t have one!

Let’s face it, if you have an n-step process that can theoretically be done in a spreadsheet, then it can be done in a spreadsheet — but how long will it take to do it in a spreadsheet vs. doing it in a modern spend analysis solution?

If sub-steps of the process consist of:

  1. researching and accumulating industry specific data
  2. comparing your data to industry averages
  3. repeating the comparisons with selected competitors, putting your place in their shoes
  4. looking for anomalies
  5. selecting top categories outside industry average
  6. selecting top underperforming products within those categories

How long is it going to take without a proper spend analysis product?

Industry data is going to come in many different forms, in many different tables, and will initially need to be stored in many different sheets. It will take a lot of manual effort and data formatting to get the data into a consistent format that will allow it all to be compared apples to apples. In contrast, a good spend analysis platform with ETL will allow for data to be automatically mapped to the right format will easily save hours or days of manual effort, as most good data tables will be detailed and large.

Comparisons in spreadsheets require lots of formulas and calculations, which can be tedious and error-prone to implement. Modern spend analysis packages come with lots of standard reports and templates that will allow for comparisons with industry averages and available competitor data out of the box. Again you will be saving hours, if not days, with a good package.

Anomalies are really easy to see in appropriate scatter plots, but very, very hard to spot in rows of data. If you have thousands of rows, how do you detect outliers with a manual scan? Sure you can pivot on volume or distance from average and so on, but is it really an outlier? Careful inspection and analysis is required on each potential row — but a visual glance at an appropriate scatter plot gives you results in seconds.

So no, you don’t need a modern spend analysis product or a spend cube to identify good potential opportunities, if you don’t mind dedicating a back room full of people for days or weeks to do an analysis that can be done by a good spend analysis product in a few hours.

And that’s why modern spend analysis solutions can deliver an ROI of more than 10% year over year as the expected value of analysis is typically above water, vs. under it, as it is when you do it manually. (See this classic post on .)

So while you don’t need a spend analysis solution, it’s akin to saying you don’t need modern technology for sourcing either. There’s nothing you can’t do with pen, paper, and telephone, but do you really want to remain in the dark ages?

As far as SI is concerned, there are only three reasons someone trying to sell you a sourcing suite would tell you that you don’t need a modern spend analysis solution (based on proper spend cubes):

  • they don’t have it and they don’t want you to use another vendor in case that vendor also has, or implements, a comparable sourcing solution (and they fear competition);
  • they want the services revenue (there’s a lot of billable hours to doing it manually); or
  • they truly don’t understand what modern spend analysis can do

And none of these reasons are good reasons. In fact, they are all reasons to be wary of the provider! There are only two cornerstone technologies that set leading sourcing organizations apart, and analytics is one. (The other is optimization.)