Twenty years ago, we wrote a post that said, so you want to do spend analysis?

And in that post, we noted that you want to get on with it, but you’re not sure where, or how, to start. So we provided you with a step-by-step process you can use to get your spend analysis effort under way and keep more of those corporate dollars in the corporate coffers, where they belong. And, after 20 years, the steps remain, more or less, the same. Because the song hasn’t changed. Only the noise by those trying to sell you fancy tools (that don’t work) has gotten louder in their attempts to drown the song out.

1. Locate Your Data

You need to identify where all of the source data is. Not the data warehouse or data lake you’re pointed at or someone’s random, monthly data dump, but the source data. That’s because it’s not likely that all of the data you need will be in the warehouse, lake, or dump because that likely consists just of the ERP or AP system, and we know that no single system contains all the data you need. Spend will be split between the ERP, AP, and T&E. Supplier information in the ERP, SXM, and Risk Management Systems. Contracts, and key data, in the CLM and Legal Systems. And so on.

Make sure you know where all the source data you need is, what warehouses and lakes it is pushed to, on what schedule, and which of these you can use. If you can work with system owners to get the missing data pushed to central locations, or if you will need to retrieve it directly.

2. Create a starting taxonomy

You can’t integrate the data otherwise. As long as the taxonomy integrates and federates all of the data, it will be sufficient. Remember that a modern spend analysis system supports multiple cubes, with inheritance, that each cube can have its own hierarchy, and that cubes and sub-cubes can be created on the fly.

3. Centralized the Data

Centralize the data into a single (virtual) starting cube that everything can work off of. Do this by defining the master transaction records, absorb all of the related information, and build the initial (virtual) cube(s) that every (derived) cube will work off of. (By virtual, we mean that the system can pull data on demand as needed with predefined definitions, it doesn’t have to be stored in a single cube in a single warehouse or lake.)

4. Family the Data

In just about any ERP or enterprise system, there are multiple entries for every supplier, product, or other entity. Make sure these are familied into one instance in the master data set.

5. Map the Data

As the data gets pulled in, map to the starting taxonomy so that the data is ready for use.

6. Pick the Low Hanging Fruit

Always start with the easy opportunities — today those might be the highest ranked opportunities spit out by the AI, the ones from the “start here” guide (supplier rationalization, bypass spend identification, growing, off-contract, categories, etc.). A few quick wins will build up support for a real, manual, spend analysis effort — which is where the real results will come from.

7. Make sure you get the right tool!

Remember, the tool, which should have all of the features defined in our previous entry in this series, must be one that gives you the agility, speed, and power you need to apply your intelligence to the problem at hand.

8. Get a good consulting mentor

You want someone to teach you not only how to do spend analysis, but how to approach and even think about spend analysis so that you can translate your instincts into analysis with quick, pinpoint, accuracy and answer your queries faster and better than any AI ever could. That’s not your run of the mill consultant who just executes the standard slate of analysis and applies the AI tools in their stables, that’s a real analyst who understands what analysis truly is and is willing to teach you. They are few and far between, and may not come cheap due to high demand, but once you learn, you won’t need them anymore. And what you spend up front will be insignificant with respect to the opportunities real analysis can uncover.