Guest blog by Jonas Vandenbruaene, business-engineering student at the University of Antwerp.
Athens. April 10th 1896. Five athletes prepare themselves for the 100m final of the first modern Olympic games. Their hearts are racing as they walk up to the starting line. Thomas Burke is one of them. Instead of standing up straight like his competitors he crouches as he concentrates and waits for the sound of the starting pistol. Thomas is going to win the race easily. His crouch start is far more efficient; the standing start goes into the history books.
Mexico. October 20th 1968. Dick Fosbury gets ready to jump over 2.24m. In the next moments he is going to break the Olympic record, astonish the audience and revolutionize high jumping with his new, weird looking technique. From then on, the ‘Fosbury Flop’ becomes the standard for professional high jumpers.
Gold medals and quantum leaps
Continuous but small improvements are inherent to all sport disciplines. Every now and then an athlete sharpens the world record by a millisecond or a centimeter because of tremendous effort and a huge portion of luck. But from time to time, there is a quantum leap like the crouch start or the Fosbury Flop. A new technique comes along that completely outpaces the old one and shatters all previous records by a large margin.
Data analytics is such a quantum leap in business. By using advanced algorithms and smart strategies companies can easily outrun their competitors in the same way crouching Thomas Burke defeats his standing opponents any day of the week.
As high jumpers started practicing the ‘Flop’ the day after they saw Dick Fosbury win the Olympic gold medal, businesses too are keen on rapidly adopting superior techniques from their competitors.
However, completely changing the way of doing business is very difficult. It requires a lot of money and persistence plus it is super risky. Therefore, it makes a lot of sense to analyze the effect of data investments on profitability in depth before taking serious action.
How much faster will I run if I use the crouch start? How much higher will I jump when I ‘Flop’ over the bar? Does the benefit of the new technique really outweigh its costs? Is there evidence proving data analytics makes companies more profitable?
Show me the money!
Ironically, data analytics promises managers more data-driven decisions but the decision to invest in these data capacities are often quite intuitive.
Of course there are a lot of breath taking examples of the great opportunities of data analytics: self-driving cars, catching terrorists or even online dating. But how does this translate to the profitability of a company?
“Asking digital natives about the effect of analytics on the profitability of their companies is as meaningless as asking headmasters about the effect of teachers on the success of their schools.“
According to McKinsey, big data analytics can increase US GDP up to 1.7% ($325 billion) by 2020. This figure is a good start in the empirical assessment of the profitability of data analytics, but it will not make the investment decision of a CEO easier.
On a micro level, we, data fanboys, often praise the so-called digital natives. Companies like Google, Facebook or Uber that established enormous business empires within just a few years by using advanced algorithms and smart strategies. The stories of these companies are inspiring lighthouse examples of how any company should deal with digitalization and data analytics. They are great to give a sense of direction to any transformation plan. However, they will not pave the road for the complete digital metamorphosis of cumbersome, obsolete businesses. These examples do not show how to bridge the gap between an outdated, analogue way of doing business and its updated, digital equivalent. They do not answer the question of how to achieve data maturity, nor provide insight in the expected profitability of data related investments. Asking digital natives about the effect of analytics on the profitability of their companies is as meaningless as asking headmasters about the effect of teachers on the success of their schools.
For CEOs struggling with data strategies, it makes more sense to figure out how other big and old companies are tackling the problem. IBM, Caterpillar but especially GE are good examples of thoughtful but profound innovation in enormous companies.
The profitability of data investments in those cases is usually very clear. A SAS study for example shows great savings in fuel costs for UPS after the implementation of an integrated analytics solution for route optimization (ORION). More generally, McKinsey estimates the increase in profits from big data related investments at 6% on average, but there are major profitability differences between data projects across different companies and industries. Bernard Marr estimates that half of these investments fail to reach the expectations.
- Dick Fosbury showed us what to do, but it is up to us, our peers and our coaches to figure out how to get there. Google is a great example, but CEOs better study the transformation of old companies when they devise their own digital strategy.
- Data investments have enormous potential, but the difference in profitability is enormous as well. Some companies manage to reap the full benefits of data analytics while others fail.
Guest blog by Jonas Vandenbruaene, business-engineering student at the University of Antwerp. Passionate about data analytics, art and traveling the world. Currently writing his master’s thesis on data maturity in organizations and the role of the CDO. Blogging to fuel interesting discussions!