Spend data classification is one of those terms you’ll hear thrown around a lot in the world of data. But exactly what is spend data classification? And why is it so important? 

To answer this question, we must first take a step back. This is the age of data. From the way we spend our money to healthcare information, data is everywhere. And it’s easy for this data to get somewhat tangled. 

What is spend data classification?

Spend data classification – also known as data categorisation – is when you categorise or classify your data into a bucket from a taxonomy or a category tree. Doing this sorts your data into organised piles of information. 

So, let’s look at an example. Travel expenses are a common spend for many companies. One of those spends will be hotel stays. However, when people log their expenses, they’ll use a range of labels to do this. They might call it ‘accommodation’, ‘travel’ or ‘hotel’.  

Why is spend data classification important?

At first glance, this might not seem like a problem. However, it means that although all hotel spend will fall into the ‘travel expenses’ bucket, it could be under various levels of detail. This means you can’t get a full picture of accommodation spend and that could alter the decisions you make.  

Admittedly, this might not be such a big problem for your travel costs. But what if this happened with your professional services costs or other high-cost areas such as building maintenance? 

Digging deeper…

Topline labelling is only the tip of the data classification iceberg. Once you dig into the data, things get even murkier. You’ll find multiple descriptions for hotel stays within one set of data. It can be described as a ‘hotel’, a ‘room’, ‘single for three nights’, ‘SNGL’, ‘RM’ or just simply ‘2 nights’. Without classifying your data, it’s difficult to capture this spend accurately. And this means you won’t get an accurate overview of how you’re spending your budget.

Invoices are the backbone of spend data, yet invoice descriptions can be scarily vague. Without accurate classification, you’ll miss more spend. For example, a taxi invoice might just say ‘from hotel to restaurant’. A human eye can pick up on this and interpret the description. Automated methods might be less accurate – it might only pick up on the ‘hotel’ or the ‘restaurant’ part. The tech wouldn’t necessarily know that this was a taxi between two locations, especially if the word ‘taxi’ isn’t in the vendor’s name. 

Understanding spend data classification is only part of the story 

What should you do with your data once it’s been classified?

You can use it to unlock a lot of potential for your business. Well-classified spend data will show you the specifics of where you’re spending your money. For example:

• Should you be negotiating better rates with your suppliers?
• Are you spending more than you thought on a product or service?
• Are you being overcharged by a supplier?

You can look at your classified data by supplier, by category, by category by month, by year, and year on year. You can also look at invoices per supplier. (You get the picture, I’m sure.) 

You can do a huge amount of analysis depending on how much data you’ve got, but you won’t be able to do much without some level of categorisation. 

Your data classification project may also highlight potential changes to the way you capture data and log spend. What could you do to ensure consistency in the future? 

What is spend data classification good for? 

Ultimately, data classification or categorisation is about saving you money – and who doesn’t want a bit of that? Even with the upfront cost of getting a professional data classification specialist on the case, you will save money in the long run and be able to operate more efficiently. 

If you found this post useful, read this post next – Should I maintain my data? 

Want to see some real-life examples? Still have questions? I’d be happy to help. Just get in touch with me at susan@theclassificationguru.com.