Think big helper, not big brother
Data analytics brings customer service into focus
CONSIDER the trail of information left behind every time you scan a website, natter on social media, click a TV channel, buy a ticket, make a call, swipe a card, draw cash, pay an account, write a text message. As the stop orders tick off on your bond, car and insurance policy, somebody somewhere is recording those transactions. They are watching you. The trouble is, all that information sits in isolated boxes — mainframe computers that do not know how to talk to each other.
Now, if only that “big data” could be illuminated and cross-referenced, it would tell companies what their customers’ habits are, what they need, what they are likely to do next. But how?
In a world of too much information, it is no surprise that the sexiest job is data analytics. That is why so many companies fling money at IT consultants and strategic planners to decipher the arcane code sitting under their noses — and they are making an almighty hash of it.
Glenda Wheeler, a qualified engineer, was told by the group financial director of a major bank that the failure rate for IT projects in South Africa is 90%, as much an indictment of technology skills as of managers who have no clue how to adapt to the new environment.
“Compare an IT project to civil engineering,” she said. ‘You don’t build a bridge that has a 30% chance of success. It’s 100%.”
Wheeler and her partner, Carn Iverson, run a firm called Tharollo Consulting. Most of its work in the past 17 years has been to rescue multibillion-rand IT projects that were ill-conceived and executed, bleeding companies and their shareholders dry.
Now the pair have a new idea — to shine a light into those datapacked boxes, giving bosses a proper idea about how their customers behave and what they want.
We are all customers, and few of us are happy. Are you delighted with the products and services you get from your bank, medical aid, cellphone company or insurer? I doubt it. Yet we all need those facilities. So why are the providers messing up so badly?
Because they do not have a clue what you want. Corporations lumber forward simply because of their size and momentum. Managers fly by the seat of their pants. Hence we get rubbish products and service.
They may use antiquated demographic profiling, such as age or living-standards measures, to fit you into a likely group. Nobody has bothered to challenge those notions because they lack the analytical tools — or the processing power — to properly examine how and why the likes of you or me decide to buy, remain or bail out.
Companies are losing piles of money and many customers because of bad strategic decisions. They are very good at billing you, but that is where their efficiency ends.
Wheeler spent 13 years at IBM in the 1980s and 1990s, cutting her teeth on steam-driven Cobol pointof-sale and marketing solutions for Checkers, Woolworths, Hyperama and Southern Sun. All she could see was useful customer data piling up and being wasted.
Then, you could perhaps sample a tiny sliver of your information and analyse it. It was like eating soup with a fork: it could be done,
Why are providers messing up? Because they don’t have a clue what you want
but it was not very satisfying and took an awful long time.
Big-data analytics has changed that. High-speed processing power now lets you slice and dice information on 200 million customers at a time, work out their worth, predict what they are likely to do next and prescribe what you should do about it.
Managers like the idea because the insights let them develop products then market, sell and service them much more effectively. Customers ought to be happier, too.
This is where it gets scary: the data we spray about our daily lives — buying, browsing and chatting — lives on and on and on. So the analytics boffins can dig around not only one big-data box (such as a cellphone invoice list or ream of banking transactions), but drag in other records you may have left lying around in the ether (such as your Facebook, Google or Twitter activity). Everything is for sale.
Wheeler and Iverson tell scary stories about how the business world can wobble if it ignores big data, like the cellphone company that assumed its best customers wanted retail outlets in shopping centres and built an expensive marketing campaign around it.
Big-data analytics told them their most profitable customers did not want or need cellphone stores. Based on a presumption, they were about to open 15 shops to service clients who would actually drain the company’s money. Return on investment: less than zero.
Managers love to talk about customer focus, but most of it is just lip service, says Iverson, who worked with IBM in the ’90s to develop a logistics management product for the Royal Air Force.
“What I learnt from the military is mission focus,” he said. “In the commercial world they talk about mission, but it’s usually airy-fairy statements that are clear in the executive’s head. But the translation of those mission statements, such as customer-centricity, into actionable stuff is woeful.”
We live in a sometimes terrifying surveillance society. Sure, we are being watched, but if the upshot of advanced data analytics is better products and service, bring it on.