In their introduction to Arc 2.1: Exit Strategies, “Escaping reality,” editors Simon Ings and Sumit Paul-Choudhury tell us that “ninety-six percent of the cosmos is ineffable” — incapable of being expressed or described in words. In addition to reminding us of the widely accepted scientific fact that 96% of our universe is made up by yet-to-be-explained dark matter and dark energy, their point — I think — is that it is in our imagination (our ability to make stuff up) that the future lies.
I like imagination as much as the next guy. I also think imagination is an important executive competence that can be mastered and must be managed. Ings and Paul-Choudhury seem to be telling us that we should resign ourselves to not knowing — to the impossibility of knowing, at least at this time, with the information currently available. I believe, like Socrates, that “wisdom begins by knowing that you don’t know.” But I also believe that significant effort should be expended toward knowing what can be known. Analytics exponentially expands the zone of what can be known. For-profit executives and hard-working public servants no longer need to make stuff up as they try to achieve organizational objectives. Nowhere is this truer than in the world of product development, especially with respect to bringing insights about customers to that process.
In the middle of the last century, during the era on Madison Avenue of Mad Men, the focus group was the cutting-edge method of doing this. Consumers would be brought in to spend a few hours in a conference room at a company’s marketing department or ad agency, and they would be asked things like how they used a product and what they wanted from a category of products. Sounds simple, but as Bob LeBoeuf, the chief digital officer at Dispatch Printing Co., explains, pop songs sound simple too, but it isn’t really so simple to figure out just what it is that sets the most successful ones apart from the duds.
Focus groups can go wrong. The classic example of this is the design and launch of the Pontiac Aztec. Jonathan Wiseman told the story in June 2005 in The Washington Post:
In the mid-1990s, then-General Motors Corp. Chairman John G. Smale decided to bring the world's biggest automaker a dose of the give-the-people-what-they-want ethic that had animated Smale's old company, Procter & Gamble Co. And what the people wanted was sexy, edgy and a bit off-key; in short, a head-turner.
General Motors' culture took over from there. Design would be by committee, the focus groups extensive. And production would have to stick to a tight budget, with all that sex appeal packed onto an existing minivan platform. The result rolled off the assembly line in 2000: the Pontiac Aztek, considered by many to be one of the ugliest cars produced in decades and a flop from Day One.
As LeBoeuf notes, what people say and what people actually do are not always the same thing. “Suppose,” he says, “someone came up and asked you, ‘How do you spend your free time?’ You would probably say something like, ‘Well, I stay fit. I spend time with my children. I do a little gardening. I always like to make something a special for my wife on Sunday night.’ Now if we actually followed you around and saw what you did, would it reflect what you said you did?” LeBoeuf is skeptical, and not wanting to turn his company’s Columbus Dispatch into the Pontiac Aztek of newspapers, he sought something more reliable than focus groups as a means of determining what potential readers really want as the company set out to totally redesign the Ohio daily. Yes, the company conducted extensive focus groups to gather insight into how people would perceive the product when it came to market. But focus groups were not the only and certainly not the most efficient way the design team at the Dispatch went about understanding customer wants and needs. And thanks to the digital realm that LeBoeuf oversees, the Dispatch could use analytics to identify authentic customer wants by observing actual customer behavior.
Of course, product design isn’t the only area where analytics can help you know what you don’t know. Asset management is another discipline that will see a completely new approach because of analytics.
The aviation industry has led the way on rule-based equipment maintenance analysis. If the oil pressure is low, a light in the cockpit lets the crew know, and maintenance will then check the oil when the plane lands. Analytics takes this a step further.
A tremendous amount of data is collected during flights. The sensors on the various subsystems — the engines, the landing gear, the flight controls, the air conditioning, the entertainment system — all collect data. This data can be collected and analyzed.
It is now possible to compare the data from one flight against the data from the entire fleet. If an airline flies scores of Airbus 320s, for example, it can look at the data collected from all the various subsystems on all of its 320s and see if there are there any outliers. This kind of analysis makes it possible to identify and prevent maintenance events before they happen.
In these and myriad other ways, analytics is changing how we work. What is it doing for you?
Futurist Thornton A. May is a speaker, educator and adviser and the author of The New Know: Innovation Powered by Analytics. Visit his website at thorntonamay.com, and contact him at firstname.lastname@example.org.
This story, "With data analytics, no more Pontiac Azteks" was originally published by Computerworld.