What Is the Real Value of Data? The Answer Is Not So Simple!
Companies have been collecting data for years. Useful data can give companies competitive advantages and form the basis for better services and better customer experience. Many companies have also become data aggregators, collecting and selling data. However, success in big data has not come from selling data — sometimes data can even be a toxic asset. What can we learn from the successes and failures of data monetization and utilization? We are entering a new personal data economy, and many parties appear as if they want to repeat the same old mistakes.
Fifteen years ago, in one of my earlier startups, we developed a marketing slogan: Data — the black gold of the 21st century. It was and is a relevant comparison, but the data business differs significantly from the oil business in a few major ways. In the oil business, there are separate business lines for drilling oil, refining oil, and selling the refined products. There are similar structures in the data business, but making big money in the value chain is very different.
Google, Facebook, and Amazon are the superpowers of the data market. They primarily collect data and build services that utilize that data. They might buy some third-party data, but it is not their primary method of getting data and they don’t actually sell data. The reputation of companies that focus on trading data is nowadays quite shaky. As a person who runs data operations for a Silicon Valley giant once said to me, they are becoming more and more skeptical about buying data when they don’t know its sources, how accurate it is, how companies that are selling it got hold of it, and how such companies conduct their businesses.
Don’t get me wrong, some companies make significant revenue by selling data and some companies spend hundreds of millions buying data. But it hasn’t been a practice that has produced unicorns or companies that shape the world, contrary to expectations held 10 or 15 years ago. At that time, there were a lot of expectations surrounding data exchanges and other creative data trading business models.
Today data is traded more like a commodity than a unique source of value. Companies buy outside data to enrich their data and help their solutions utilize data better. The real value is achieved when companies build solutions that use data in marketing, sales, and operations. One could even claim that the winner doesn’t have the most data but the best tools to utilize data. Of course, the Internet giants have heaps of data. Still, banks, telecom carriers, and retailers have lots as well (and the opportunity to collect more) but they have generally been slow to utilize it. Successful companies also use their data to create value for users — think of Google Search, Google Maps and other services, and Amazon’s better customer experience.
We are now in the early days of a personal data economy, in which tools that allow people to utilize their own data will be a valuable commodity. Some initiatives and companies want to build solutions based on ideological views — people have moral rights to own and control their data. Those haven’t done too well; only a small set of people are interested in these ideological projects.
Then there are companies that want to help people collect their data and sell it. This has many practical challenges, including getting enough demand and supply to make a data market work. Pricing is also a complex challenge, as are associated terms and conditions, such as tracking data to determine if it’s actually being used for the reasons stipulated in its sale. It is not easy to get this kind of personal data market working correctly. The user value promise is often disappointing, like being paid a few dollars monthly to watch ads.
The most obvious option that has consistently led big data businesses to success for over ten years has been largely forgotten — offering people better tools to collect and utilize their data. When companies offer to help people to control and use their data by selling it, it is similar to recommending that Google, Amazon and Facebook sell all the data they collect. Those companies have achieved their current position and power by creating top tools to utilize the data they get, not by turning around and selling that data. It is the same with individuals. If you want to empower them with their data, you need to offer the best tools to utilize that data personally.
Utilizing personal data will require overcoming many challenges, and we don’t yet know them all. We need an open market to innovate and develop tools that will help us utilize personal data. These tools could include tools that plan better personal finance, find best prices, promote better health and wellbeing, and provide assistance with all kinds of daily needs and activities. The longer-term vision is to build personal AI that offers a dashboard to guide all daily activities.
As with data businesses, personal data could also be enriched with external data sources. For example, public data like price comparisons, traffic, and public health and map data could be combined with personal data to make it more powerful. Data model training for Machine Learning and AI improves significantly when it can use data from multiple sources.
In many ways, the best way to utilize personal data is similar to what the leading data companies have done for years. But it seems that when presented with this new business opportunity, many parties first go to very complex models, like justifying data with ideological thoughts or wanting to build a blockchain-based data exchange with digital rights management systems. Often the simplest and best solution is to copy one that has worked earlier elsewhere.
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The article first appeared on Disruptive Asia.
