Just continuing on the theme of how different industries can learn from each other, I used to work for NCR. NCR had several major industries they served: retailers, airlines, telcos and banks. The common thread across all of these industries was high frequency customer contact, and the challenge for all of these industries was how to leverage that contact.
The highest frequency contact was in banking and telecommunications. Sure, retailers and airlines see customers often, but banks and telecommunications firms touch customers every day. Back in the 1990s, when I was at NCR, I made a prediction as a result. The prediction was that one day banks would become telecoms firms and telecoms firms would become banks.
Today, that prediction is part-true. In some countries, banks are running mobile networks and, in other countries, mobile networks are running banks. But what happens longer term, if that prediction plays out?
Well, today, many banks claim to be technology companies. The thing is that I didn’t predict banks would be technology companies. I predicted they would be telecoms. The difference between a technology company and a telecoms firm is that the former makes and deploys systems; the latter enables connections.
This is the critical difference for me, and I think banks do need to be enabling connections. Connecting my financial lifestyle with my social lifestyle. Connecting my spending and savings habits. Connecting me better with my money.
Twenty years later, I still believe this. And the very heart of this idea is that the company connecting me as intimacy with my data. In fact, the company is so good with my data that they can predict what I’m going to do next.
Leveraging data about lifestyles is the core differentiation of today. Amazon, Google, Alibaba and Tencent all do this really well, and it is companies born on the internet that get data leverage. This is why we admire them. It’s also why we fear them, as they really understand how to mine data.
In fact, going back twenty years ago, NCR had a sister company called Teradata (still going) where we talked about a single view of the customer by mining terabytes of data using predictive analytics. Only the biggest firms could afford our solutions, as mining a terabyte of data cost gazillions.
Today, 60 terabytes of data is being uploaded to the network every second. Today, we are drowning in data, and only those who are fit to swim will survive. Being fit to swim is really about having a clear data architecture; being clear about how to mine that data; being clear about how to structure that data; being clear about how to tag that data; and so on.
In fact, data is the key to survival as, in a decade from now when all companies are using artificial intelligence for customer marketing and service, the question will be who is using their data the best? We know that Amazon, Alibaba and their brethren born on the internet use data well. We know that we want to be as good as Amazon, Alibaba and company at using our data. But the question is: have we done the right thing with our data?
As banks become telecoms and technology companies, and telecoms and technology companies become banks, it is only going to be the companies that have the most intimacy with our data, and who then use that data the most intelligently, who will win. In other words, it is not really about banks becoming technology companies or vice versa, it is purely about data intimacy and data leverage.