Data, data everywhere and no, you can’t drink it. The trick is to understand how to monetize it.
There are lots of wild metrics about the phenomenal amount of data now being collected. Statements like “more data was collected last year than in the history of mankind” abound. I have no idea whether any of these enthusiastic pronouncements are true but I (and we all) should accept that the aggregation of data is unprecedented in its scale and ubiquity. However, for a very long time much of this data sat neglected and unused. This is changing and changing rapidly.
Artificial intelligence—a grandiose term for fancy algorithms—is at the heart of this change, as is the recognition of the value of being able to assess huge quantities of data and extract useful information. Let’s examine three examples. Location data from a smartphone will identify whether nights are spent at home, or at the local pub—immediately identifying the work and play habits of the credit applicant. That information is then compared to the trends associated with the credit profiles and history of other borrowers in the data base
Financial services… We have a business partner (from Prague) who owns a consumer lending company in China. The average size of the loans they make is about $750. As you can imagine, such low credit is only feasibly dispensed through online interaction. To introduce any kind of human contact in the credit granting process would render such lending commercially unattractive. That’s why their credit is adjudicated by searching the web and specific data bases for information on the borrower. For instance, location data from the person’s smartphone will quickly identify whether nights are spent at home, or at the local pub— immediately identifying the work and play habits of the applicant. That information is then compared to the trends associated with the credit profiles and history of other borrowers in the data base, those with good history and those with poor performance. It’s a complex process, but in spite of the copious amount of data assessed the applicant gets an answer within three minutes. That’s amazing… especially when you look at the bigger picture, and the impact such assessment processes could have for the insurance business and the pricing of risk.
Personal transportation… Uber is conducting an experiment in Mexico City, a city that suffers (like a lot of others) from huge congestion issues. Uber’s computers gather information from a number of sources: the real time location of the city’s public transportation vehicles; the subway system; and, satellite data of live traffic patterns. The exercise is helping the city’s managers better deploy their assets. At the consumer level, a commuter can walk out of their house or apartment, log their destination address into the system and be instantly advised as to which method will provide them with the fastest commute to their destination, including such supplementary info as to whether the car park at the local subway station is full or where the nearest available spots might be.
Health care… diagnosis, treatment recommendations and prescription writing will all change and change for the better. The work of radiologists in assessing and interpreting x-rays may well become redundant. This is all thanks to the power of algorithms that are designed to compare a patient’s condition or the data points associated with that condition, not to the experience base and technical skills of a single health care practitioner but to the similar data points of tens of thousands of other patients—and the outcomes associated with particular treatment regimes. And it does it in minutes, if not seconds. This doesn’t replace physicians in many of their traditional roles; rather, it makes the healthcare system more efficient and allows physicians to make recommendations more quickly and accurately. This can’t happen fast enough as the system groans under the load of an aging population and ever escalating costs.
So what does all this mean? I’m not sure my crystal ball is any more accurate than yours—and in any case I don’t want to offer up answers. Rather, I want to point out how quickly the explosive growth of computing power, made so easily and affordably available thanks to the cloud, the rapid rise of sensing technology, the internet of things and the ever growing capability of the devices we all carry around with us, from which we have become inseparable, are all leading to changes across society.
This is opportunity on a scale unprecedented in our lifetimes. Think about how you can use data as a tool or an ally to take your business in new directions. Otherwise, it will be used by others as a weapon to take your business and your customers away.