Each month, “Lochhead on Different” episodes will explore the need to differentiate people, products, and services in a world that encourages a lot of imitation. A best-selling author, top podcaster, and former tech-industry CMO, Christopher Lochhead is a student of not only business and technology and marketing but also human nature, human folly, human genius, and very human joy.

Episode 8

In this episode, Chris agrees with me that “Data is the new oil” is stupid. He says data is more valuable than cash. Data can be converted into value in more and powerful ways than cash. He goes on to say that cyberbullying is an epidemic, and that people of all ages are committing suicide as a result.

According to IDC, Chris says, there’s going to be a 10X increase in the amount of data on planet earth –163 zettabytes. And according to Statistica, the average person – adults and children – will interact with a connected device nearly 4,800 times a day! Also according to Statistica, the Internet of Things will have 75.5 billion connected devices by 2025.

Chris says there’s a company called DribbleUp, and they have created a “smart basketball," which tracks things and gives data back to your phone – and presents you with different and more effective ways of training and using the ball.

Chris says there’s a term going around called, the “data flywheel.” Simply stated, the company that has the most data around who their customers are and what customers are purchasing. Chris and his partner Eddie Yoon co-authored a Harvard Business Review article that said the company with the fastest growing data flywheel is most likely the one who is going to be able to dominate that category, because their lead will soon be insurmountable.

He says many concert tickets get sold on the secondary market – and are essentially digitally scalped. So Adele said on her recent tour, ”If we don’t solve this problem, somehow only the people who are in the audience are a bunch of rich people. I want to perform for my most enthusiastic fans – some might be rich, but others aren’t. So how do I allocate the tickets?” The solution was an algorithm. It was effective in getting tickets into the hands of fans who actually wanted to come – and that is an example of a data flywheel.

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