Data is extremely valuable. This should come as no surprise to anyone in business, and neither should the fact that many organisations entertain the thought of selling their data to bring in some easy cash. After all, if data is so valuable and you’re automatically producing it for free, why not get someone to pay you the big bucks for access to it?
It’s a great idea, and businesses who think ‘big picture’ about their data are on the right track - but commercialisation is more multifaceted and complex than it’s often made out to be. Let’s take a look at what commercialising your data really means and outline how to determine whether or not it’ll bring value to your business.
What is data commercialisation really?
The term 'data commercialisation' has different significance for different people, but what it boils down to is getting some sort of value from your data. There are three primary ways to do this
In this article, we’ll be focusing on the first iteration – selling your data externally for profit.
Data commercialisation isn’t as easy as it sounds.
There’s a misconception that external data commercialisation is simple - you just clean up your data, put it out there and someone will buy it, right? Unfortunately, a lot of companies have discovered the hard way that selling your data is rarely this straightforward. Firstly, just because you have data doesn’t mean others will want to buy it - there needs to be a quantifiable value exchange in order for data commercialisation to be viable. Secondly, it’s difficult to actually know how (or even if) someone else can use your information to create value in their business. Yes, data is valuable - but only if it’s clean, structured and usable. Many businesses don't have their data adequately cleaned for internal use, let alone in a state that’s good enough to sell to others.
On the other hand, you might have a dataset that’s actually worth 10x what you think it is to a certain buyer - but how do you determine this from the inside? It’s imperative to understand the value chain and how far down that chain you’re going to capture, otherwise someone who does understand it could capture much more of the value than they should.
As you can see, it’s very easy to either over or undervalue a given set of data. In order to get commercialisation right, you need to have a thorough understanding of your data and what it can actually offer someone else.
Should I sell my data?
Before jumping in and investing people time and resources into external commercialisation, be sure to ask yourself these questions to determine how suitable your situation is:
1. How unique is your data? Getting customers onboard works best when you’ve got an uncommon and valuable dataset that isn’t already on the market (if not a monopoly, then close to a monopoly). In short, the value of your data is only as high as its difference from the alternatives.
Your answers to the five questions above will be a good place to start if you’re thinking about commercialising your data. The next step is seeking advice from someone who has done it many times before and can assess your situation individually to recommend a course of action. Datamine has been helping organisations across all manner of industries (banking, energy, FMCG, telco etc.) commercialise their data for over 10 years - check out our Retailwatch reports to see one example of how we’ve taken one business’ data and turned it into a valuable asset for a host of others.
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