We often refer to business data as an asset. Data is essential for every function in an organization, so it’s easy to see why it’s so valuable and vital. On our blog, we’ve discussed ways that clean data can make an organization more efficient and profitable. And we know that clean data cuts waste.
But data is not just an internal asset. Some businesses deal in data. They trade it, sell it and market it to other firms. This type of activity requires pristine data quality and a continuous commitment to maintain that quality.
Profiting from data is not simple, though, and businesses are learning that there are boundaries. Before advancing plans to turn data into riches, some basics must be considered first.
Selling and accumulating data
Organizations that sell data have had some bad press recently. Perhaps the biggest scandal can be accredited to the NHS, which has sold private patient data unlawfully to insurance companies and researchers. The NHS still sells patient data, but it now has to be clear about its motives, selling data only when patients are sure to benefit from the activity.
There are less controversial reasons for buying and selling data. Some businesses buy in marketing lists containing prospective customers. There are various reasons for this; their own database may have suffered data quality problems, or they may have struggled to build a list at all. While buying lists is a valid tactic for new and established organizations, care must be taken to be selective about their provider, and realistic about the returns and pitfalls.
From these two examples, you’d be forgiven for thinking that bigger is better: more data means a better chance of getting a sale. But that isn’t the case. The more data you have, the bigger the potential risk, and the higher the cost of management will be. This is why turning a profit is so tricky, and why data quality comes into play.
Big Data has been hailed as a way to improve business efficiency and react more effectively to the world around us. It has ushered in the Internet of Things, a technology where every part in a machine, or in a factory, can potentially generate data. We have the option of storing all of that data and using it for analysis or profit.
The cost of managing this data has to be offset against the potential money that is made. Look at Facebook’s data centers; the social network has them dotted all around the globe, and one of it’s biggest challenges is to cool its tens of thousands of servers naturally, to avoid spending millions on power. Facebook and Google are leading the way in eco-friendly cooling technology, using icy air and electricity generated by the movement of water. They do everything they can to manage cost so that their main business remains profitable.
There’s also an element of financial risk from compliance problems or hacking, particularly where personal data is concerned. In the EU, every business that holds data on an individual must be prepared to reveal it, and they must handle it in a responsible way.
Businesses are keen to find new ways to make money from data. Every day, they have more of it. There’s certainly potential there. Every business needs a business plan and a clear destination, cleared by the right legal backing. They need to make sure their efforts do not detract from their main business activity or risk placing their business in an uncomfortable position if data is misused or distrusted.
Small businesses sometimes look to rent out their own marketing databases or look to sell them, but this is a potential minefield when it comes to data quality and data protection law. Not only is there an obligation to the customer to treat their data with care, but there’s also an obligation to the purchaser of the list to ensure it still contains up to date records.
This leads us to an inevitable conclusion. Whenever we talk about monetizing something, accuracy comes into stark focus. Data cannot be monetized if it is not accurate, complete and free of duplicates. It is worthless if it cannot be relied upon; we see that in our own businesses, just as we see it in our interactions as consumers. Care needs to be taken to sell only the right data, at the right time, and for the right reason.
Risks and returns
Regardless of the potential risk of data monetization, we can be sure that data has value, and its value increases as its quality improve. Even if a business chooses not to market its data, there will always be a benefit to its own ROI if the data is well maintained.
Investing in data management may seem like a cost, but for most organizations, it will pay dividends. As we collect more data about more people, and we store and share that data in different ways, the onus is on the business to look for safe ways to monetize, without exploiting data or using data that is unsuitable for sale.
With data quality tools as part of their arsenal, there are more and more opportunities for businesses to sell, rent and recycle in an evolving data landscape.
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