Sunday, July 28, 2013

Insight: How To Tackle Big Data Like Sherlock Holmes?

By Marsha Lindsay (Guest Writer)

Big data is just a bunch of numbers if those interpreting it don’t know how to have big "ahas." And bigger ahas can get a jumpstart by changing one’s self-concept. To what? To be more like Sherlock Holmes.

Of course, Holmes was a fictional character famous for his ability to think deductively, inductively, and abductively (from a platform of information, making logical but big creative leaps to what could be true). But any marketer faced with lots of information and wanting to nail what’s really going on with consumers (and why) would be wise to cultivate the wisdom of great detectives like Holmes.
Here are seven lessons to learn from Holmes:

1. Know how to parse--from small and large amounts of data--commonalities, contradictions, coincidences, and causality relevant to your consumer, brand, category, and competition.

2. Know that with more data comes the appearance of more correlations, but most are totally irrelevant.

3. Know that some of the most important things to figure out may have no hard data associated with them at all--but require the wisdom of your gut. This should not be discounted because one’s gut is your subconscious reading the data of your experience--your implicit learning.

4. Know the first step in all detective work is defining the mystery to be solved.The famous sleuth of the universe, Albert Einstein, said that if he had but one hour to save the world, he would spend 55 minutes defining the problem and only five minutes conceiving of the solution. Holmes would agree, explaining that a clue is only distinguishable from noise when viewed through the frame of the one mystery that matters most. Is it low awareness? Low trial? People dropping off the path to purchase at a certain point? When a problem is well-defined, you can work faster by knowing what data to focus on and what to ignore.

Marketers who don’t begin by clearly articulating what they’re trying to solve gather tons of data to the wrong question. Or they gather tons of irrelevant data to the right question. But when you’ve defined the mystery and obsessively searched for clues, the next step in solving the case is. . .

5. Ask “so what?” of each of the clues.This separates ordinary detectives from those with Holmesian potential: The latter know what to do with the clues they’ve found. Unfortunately, many marketers today do the wrong things with clues, using rules of thumb no longer true or now proved to never have been true. For example, in the face of clues revealing low market penetration, it would be wrong to assume the case could be solved by using price promotions. Robust analysis of performance data, as well as considerable new data, now proves price promotions don’t boost penetration. First and foremost, solving mysteries means first and foremost knowing what is real and true about marketing and human nature.

6. Know what data is in service to “where to play” versus what data is in service to “how to win.” Where to play is a brand’s reason for being, the meaningful role it plays in people’s lives. Its fuel is strategic intelligence--data, insights, and clues that are less time-sensitive than those informing how to win in the space you’ve chosen to play. In contrast, how to win requires tactical intelligence--insights on how to quickly optimize the products, services, systems, and marketing that deliver and make profitable the meaningful role you play.

It’s important to understand that different kinds of clues inform where to play versus how to win. For example, envisioning a disruptive new category, meaning platform or business model--that is, where to play--almost always starts with a dream or an intuitive hunch. These are subconscious reads on observational and implicit data--the source of which is impossible to reverse engineer because they’re embedded in our memory and DNA. Complementing this is real-world data often qualitative in nature, the kind used for taking your product or service platform and branding it.

In contrast, data that perfects how to win is more quantitative. Its focus is to quickly optimize how you deliver on your brand promise. And given today’s rapidly changing market conditions, winning requires embracing not just faster ways of getting clues, but also accepting that not all the evidence can be known before drawing conclusions. Holmes would approve of this effort to get just enough insight to frame the next logical hypothesis and then quickly focus on searching for clues in service to its validity.

7. Know how to compensate for the human brain’s inherent weaknesses when dealing with clues and evidence. Did you know that later in the day, data presented to you will likely result in a decision different than the one you’d make with the same data earlier that morning? Decision-making fatigue is real. What’s more, we’re prone to mistake correlation for causality where it doesn’t exist--quick to jump to erroneous conclusions.

Take the statistic that the Android operating system has been outselling Apple’s new iOS system by 5 to 1. From this, a rookie detective could conclude that Androids are the best choice for app developers. However, Holmes would dig deeper, uncovering stats that reveal iPhone users are consistently and dramatically more engaged than Android users in browsing, apps, and e-commerce. Holmes would thus conclude that while Android sells disproportionally more devices, they are used disproportionately less than the iPhone, making Apple still the best for app developers.

Another human weakness preventing even great marketers from bigger ahas is the tendency to see what we want to see even in the face of data that disagrees. Called confirmation bias, it’s a prejudicial way of thinking that is the basis of not just of misreading research, but also stereotyping people.

In a world where we’ll all be suffering more decision-making fatigue from increased amounts of data that we’ll be expected to act on more quickly despite our brain’s inherent weaknesses in information processing, Holmes would advise us to build safeguards into our thinking. One way is to have a candid and trusted foil like John Watson. Another way is to have a hypothesis on what you’ll eventually conclude from evidence you gather, and then design your research not to prove yourself right, but specifically to try and prove yourself wrong.

We’re moving from a time when great amounts of information were demanded in order to have a high degree of confidence for decision-making, to a marketplace where information’s purpose is to quickly size up and react to the mystery of what’s working and what’s not.

This means success will come only to those companies where everyone--from the CEO on down to the rank and file--develops thinking as acute as Holmes. It’s a conclusion so obviously true that even Holmes himself would call it “elementary.”

(About the Writer: Marsha Lindsay is CEO of Lindsay, Stone & Briggs, an ad agency specializing in the launch of new products and brands for marketers from the Fortune 100 to VC-infused startups.)

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