There seems to be a degree of consensus that once a company hits a certain size, when it becomes a “big” business, it stops innovating or thinking in new ways. Of course, there are exceptions to the rule, such as Apple or Patagonia, but they are just that, exceptions. Assuming for a moment that there is some truth in the collective interpretation of how businesses change through time, we have to ask why it should be so. I think it is simply that we forget what it is we actually do – “I make killer Product X” becomes “I do job X.” Customers become data points and thinking is constrained. Innovation becomes stale at best, dies outright at worst. There is a lack of empathy and gut-level understanding of their customers and how their products fit into the big picture. Lacking a gut sense for what keeps ordinary people up at night, individuals within an organization begin to live in a bubble, unable to broaden their view and be genuinely creative. We’ve all heard this argument before and there is a great deal of truth in it, but that’s just part of the problem.
Our companies have spent ages trying to understand the customer, but it has been in the last 100 years that the process has become extremely complex. Particularly since the introduction of the computer. We have spent our time creating systems to handle incredibly complicated problems. Today, if you can ask a good question, our organizations have the power to provide you with a very detailed answer to what ails you. The problem is that don’t always ask good questions. And when we do, the answers are not answers at all – they are the recitation of numbers that address anything but the question asked.
To my mind, “What is the question?” that seems to be the core of the problem. In an increasingly turbulent and interconnected world, the ambiguity that surrounds us is rising to unprecedented levels. And that’s a serious problem that our current statistical models and systems can’t handle. We can no longer assume we know what people are doing or why they are doing it based on the results of a survey, sales data, or traffic patterns, both online and off. Far too often, we simply ask questions that aren’t relevant or lack practical validity. Why should this be the case?
I think it lies in the ambiguity and contextuality I mentioned before. Large companies are phenomenally good at managing complexity, but they’re quite bad at tackling ambiguity. As long as the complexity is constrained by highly logical process, everything is fine, but human beings are far from logical. Or, more accurately, they are logical according to their worldviews; worldviews that increasingly deviate from the uniformity that emerged during the modernist period of the last century. A complicated problem is like playing a game of chess, an ambiguous problem is finding yourself in a new country, trying to find a restaurant and hoping it’s a place you will fall in love. In this situation, the variables can’t be readily accounted for until you’ve done some legwork and learned a thing or two about the people, the place and yourself. In more concrete terms, take something as seemingly simple as shopping for groceries. Are the decisions we make when filling the pantry transportation driven, health driven, calorie driven? Is grocery shopping a political statement, an expression of emotional bonds within a family, a way of coping with emotional stress? The answer is “yes” to all of the above.
That means that you aren’t guaranteed to increase sales just because you know people tend to turn right when you enter a store, that they are more inclined to explore an end cap when it incorporates the color red, or even that mom’s are increasing using smart phones while shopping. All you’ve done in that situation is identify data points. It doesn’t mean you have identified why people do what they do.
How do you get at that sort of thing? The simple answer is fieldwork, but that answer is too limited. So is talking about multidisciplinary teams. It is about having multidisciplinary thinking – the renaissance experience reborn. These are people who are part scientist, part humanist, part artist and part business person. Simply having a range of talents and disciplines working together on a problem isn’t sufficient because it becomes a process of arguing points from a single trajectory or handing of elements a project from one person to another. When multidisciplinary thinking comes together, by contrast, the disciplines themselves start to mutate, allowing for breakthrough thinking. We start to see art and science blend into something unique. We start practicing business like a designer. We shape technology the way we shape a painting, a myth or a story. Rather than seeing data points, we see the linkages between them and start to produce solutions that address real problems.
From the standpoint of designing a research and/or strategy project, it means beginning by getting the client and the team comfortable with letting go of the need to focus on instant solutions. It also means having the client and the team, regardless of training, practice thinking differently. Accountants and engineers need to enter the field and learn through practice to think in terms of complex adaptive systems, rather than complex systems (note the lack of the word “adaptive”). It also means fieldwork researchers spending time think through every insight from the vantage point of “how do we make money on this.” The point is that as different types of thinkers learn to think in more expansive ways, the more likely they are to develop breakthrough ideas.
What’s the payoff? The introduction of the personal computer. The introduction of the automobile. The introduction of inoculation to medicine. We need to think this way more than ever, particularly in an economy defined by prolonged ambiguity and a world where identity drives the purchase decisions as much as necessity.