Telcos must be transparent on data

Big data has been hot for some time, and data privacy has recently become really hot. Everyone must have a big data plan and projects.

 

But how many organizations and people really know how to improve their business with big data, what they want and how they can respect their client’s and user’s privacy?

 

We also see many 'small data' applications that produce things based on a few data points such as current location, current speed or latest status update.  A problem of data analytics is that it gives a lot of wonderful visions, but it requires a lot of work, planning and a long-term systematic approach to get real results.

 

Telecom operators have for years developed exciting plans, how to utilize all their data and really turn data to revenue. But in real life we have increasingly seen simple mobile applications that maybe track a few data points and then produce something useful or fun to their users.

 

For carriers privacy is extremely important. Most countries have very strict policies and laws governing how telecom data can be used. And the topical issues - how security agencies want to use data - just make the situation more complex. People share a lot of data in Facebook, Foursquare, Twitter and many other services. They are ready to share data in retail, airline, hotels and many other loyalty programs.

 

People expect to get something back. Sometimes, it is loyalty points or better prices, but it can be also a kind of social benefit; you might get noticed by other people or receive better security. One question is also, which one is worse for human beings, that someone knows too much about you or everyone ignores you. It can also be that many people haven’t realized, how data can be utilized and is collected until now. And now they want to understand more.

 

 

There are probably two main ways to utilize mobile data: 1) big data based on general results, technical data and profiling, not individual user level activities, and 2) small data based on the current activities and sharing. The first one must be totally anonymous, e.g., market research location data that shows people typically spend time in certain areas in evenings and weekends, and use certain routes. But it must not have information available on individual people. The second one must be shared based on user’s own decisions and actions, and then the person expects to get some value from it - monetary, social or something else. And people want to know how the data is used and why it brings value to them.

 

Companies must now become very transparent on how they collect and use data. But companies must also themselves understand how they really get some business value from data and offer value to people whose data is used. Too many big data plans have been too ambiguous. It might be better to collect less data with a clear purpose than a lot of data based on unclear plans. They must categorize, what data is used and for which purposes, when it is anonymous, and when personal level data is required. This is now a good time to review and really clarify data and analytics business plans.