Jeffrey Hubbard
04.17.2014
The March issue of the Harvard Business Review had a powerful article called “An Anthropologist walks into a Bar…” and the ensuing 10,000 word punch line is that companies do not really know their customer, but they believe that they do. As you might imagine, this misunderstanding can prove costly. If you have a subscription, you can read it here. If you don’t, the content is worth the price of admission. If you just need the bottom line, keep reading.
Complexity Gap
It is strange to write the following, but we often need to be reminded: we are dealing with real people who have motivations, hopes, and fears. Our customers have families, work, and strong demands on their time. The sum total of these variables is known as the complexity gap. With so many variables, it’s hard to place people in nice and neat boxes in an excel spreadsheet. In more concrete terms, big data cannot cover the complexity gap because we are either asking the wrong questions of a diverse group of people and drawing the wrong conclusions or there are anomalies in our sample of diverse people that are exaggerated on the scale of big data, which leads us to the wrong insight. As Tim Harford notes in the Financial Times this week, when it comes to data, size isn’t everything, as statistical patters do not provide concrete insight into the causation of events. In order to distill the value from big data, we need to go about the sense making process because that mental framework will help close the complexity gap your clients are facing.
Sense Making
The purpose of sense making is to frame the experience of your clients product or service in human terms. The case study used in the article is memorable. The Danish medical technology firm Coloplast is an industry leader for ostomy bags, which are used to capture bodily waste from those who have had their colon removed. I cannot think of a more sensitive product, which is why this example works. Coloplast had market advantage, but they were slipping despite the data and focus groups supporting their R&D pipeline [not my word]. Hence, the “big unknown”: how could Coloplast find new sources of growth? In order to answer this question, we apply the sense making mental model.
Reframe the Problem
The whole function of the sense making mental model is to phrase your questions in terms of human experience. The example provided is to recast the question from “how do we capture new growth?” to “what is it like living with ostomy?” Coloplast had all the big data and consumer metrics, but very few managers knew the world their customers were living in. Put a different way, what kind of social life can you have with an ostomy bag? What is a good day and what is a bad day? Can you make love with your spouse? These types of questions erode the assumption that the Coloplast ostomy bag provided relief for their customers at the time they left the hospital and beyond. The ostomy bag took a diverse group of people and forced them into a lifestyle that accommodated their medical condition. As you think through a challenge your client is facing, find their customers and learn what their product of service means to them in their own daily life. At that point, it becomes possible to ask the right questions and mine the correct data.
Conclusion
When you reframe the problem in light of the sense making mental model, the questions you raise will help you close the complexity gap because your focus will be on how the customer experiences the product or service your client provides. By understanding the experience, you can help guide the product development to capture a broader market because you will no longer be servicing a narrow or assumed need.
