I’ve shared a lot of knowledge with you in this book on how to improve your spend data, but how do you know where you sit now and what needs to be improved? In this chapter, I’ll introduce you to a maturity model that will help you answer those questions. Not one of those fancy consultancy models that has big words and is very technical, but one that is relatable, easy to understand and that you could give to anyone in your organisation and they would have some basic understanding of it. The inspiration for the model came from COAT.

Let me introduce you to …

The dirty data maturity model

Let me share with you how you can move from dirty data to dirt-free data using this model, charting where you are, where you’d like to be and how to get there. We all want dirt-free data, but that could take years to achieve, so let's be realistic about what you have and what you could have in the next 12–24 months.

Dirty data

Dirty data is a pretty bad situation. It's the equivalent of turning your underwear inside out to wear it for another day – you know you have to do something about it, but you can get away with it for a little bit longer. You are delaying the inevitable. What if that one extra day you wear those underpants, you have an accident and get taken to hospital? That's when you get found out.

Data is no different. It is widely known, and I hate to say accepted, within organisations that there are data issues internally, yet no one really wants to address them. Why? Generally, it's not an easy fix, the business might not see data as an investment and the problem could be so big that there's just not the resources internally to fix it and no one wants to pay for a third party to do it. Then the data accident happens and everything gets exposed. At this point, there's no hiding from it. Fingers will be pointed, blame will be apportioned and everyone will be thinking ‘why didn't we just fix this earlier?’