Everyone today knows data has a lot of value. Ten years ago, we developed a market slogan for our then data analytics company - “data is the black gold of the 21st century.” Nowadays, almost all companies share that sentiment. But it is not so simple. Oil became the black gold because it enabled freedom. The data business must achieve the same.
“We try to collect all possible data, and then we find a model to monetize it, maybe sell to advertisers,” is a common sentence in many business plans. “We help companies monetize their data,” is another typical value promise. “Let’s offer our solutions for free, if we can get the data,” is a ‘sales strategy’.
Is it so simple that you offer software, apps, and services to consumers and companies, utilize their data and create a big business? It really isn’t that simple anymore, because 1) so many parties want that data, 2) most users are becoming smarter with their data and asking more questions about their data, 3) data doesn’t have uniform value, 4) authorities create rules about the use of data, and especially 5) most data utilization is marginal optimization, not real value to customers.
Let’s think about some examples. Media companies and their analytics partners seem to be very keen to utilize all data they have from their subscribers and online visitors. Then they use this data to target their own marketing activities, but especially offer better targeting to advertisers. This is mainly outside the consumer’s control, and media companies possibly try to claim that the value the consumer gets is more relevant advertising. But I wonder how many consumers really feel they are provided value by getting more targeted boring banners or an ad video. No wonder consumers hate it when these media companies talk about monetizing their data.
Retail loyalty program analytics became popular globally particularly based on Tesco’s success story in the UK. Tesco doesn’t do so well anymore, and its competitive advantage based on loyalty program analytics has disappeared, when many others do the same and when competitors offer lower prices always to everyone; why would you follow personalized discounts?
Finance institutions and credit scoring companies collect data specifically to manage risks, for example, to decide, if a customer is allowed to get a loan. There are several new credit scoring companies, especially in the emerging market, but also in developed countries, that collect much richer data, e.g. social media, mobile and finance apps data. Typically, consumers don’t even exactly know what data is collected and how it is used. Or the consumer learns about the data when hackers steal it, like from credit rating agency Equifax. One could also say that the use of this data is very one-sided. Finance institutions use this to make decisions about customers and product offering for them, but it doesn’t really help customers to find the best deals.
All these above examples are about cases involving companies collecting customer data and wanting to utilize it make better business by optimizing some of their operations like marketing, risk management or product offerings. But the real value for those customers is often very limited. This means those companies can improve their business a few percent, but it is not disruptive or game changing. Google changed the game, it collects a lot of data, but its services have been also much more direct value to users than analytics from many other companies.
Regulators, authorities and law makers have become more interested in the use of data. One example is EU’s General Data Protection Regulation, GDPR, that gives more power to consumers to know his/her data and control the use of them. Generally, authorities and consumers see it as more acceptable to collect and use data if the consumer can see and control the data, and if consumers also get real value from it.
Many companies still see that the way to utilize data is to optimize their own operations to generate more revenue or cut costs. They don’t want to empower customers properly to utilize that data in the services that customers could get direct value. For example, finance data should not be used only by a lender to make a loan decision and adjust interest rates, but it should enable a customer to have a better user experience and find the best loan and interest rate.
Data is the black gold, but to get the full value, it cannot only be a one-sided marginal optimization. All parties must be able to utilize it and build totally fresh solutions. If oil companies had used oil only internally to offer transportation services, it wouldn’t have changed the world, created free mobility and huge businesses. Oil became the black gold when people got cars and other vehicles and got freedom to move based on their own needs. The data business must learn to be an enabler, not just a one-sided optimization tool.