The era of unknown unknowns
Turbulence in business is changing the rules of the game
While the concepts of known knowns, known unknowns and unknown unknowns have been used in the intelligence community for a while, they surged to the radar screen of the general public, during the infamous press conference on the missing WMD in Iraq, on Feb 12 2002, in which the US Secretary of Defense stated:
“Reports that say that something hasn’t happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we don’t know. And if one looks throughout the history of our country and other free countries, it is the latter category that tend to be the difficult ones.”
Unknown unknowns are becoming business as usual, because of the turbulence characterizing – even the most traditionally stable and mature – markets. Turbulence is caused by new boundary conditions, at economic, social and technological levels:
- Globalization: which has created links that we did not expect, nor we did see. The sub-prime crises in the US financial system, spilled over Banks overseas, which did not own any of the sub-prime securities, but had placed bets on Credit Default Swaps and credit derivatives. Chinese investors own a large portion of the American debt, while Italian and Greek borrowers, basically owe their money to French banks and French communities.
- Pseudo-innovation, the “better and improved” line-extension craziness, has reduced the product-life cycle, by stretching the ability to contribute to the bottom line of new products. It is easier than ever to copy-cat launches, and while many companies strive to be first in the market-place, first mover advantage has not existed for nearly 30 years.
- Digital Transformation/ Business Model Innovation, is challenging the pillars of our economic models, but also stretching the boundaries of our social welfare and labor and contractual law (e.g., Uber, AirBnB, Upwork)
- All innovation is influenced by digital: the digital dimension is putting pressure on traditional innovation funnels. Products connected to an IoT environment are struggling to keep the pace of the change of the IoT ecosystems and verticals (e.g., if you bought a connected light bulb two years ago, it is probably not compatible with the current version of the ecosystem). For example automotive companies are struggling to balance their innovation time-frames – traditionally encompassing multiple years -with the electronics and software innovation time-frames, measured in weeks and months.
While known unknowns belong to the field of risk management, unknown unknowns stem from the domain of uncertainty, and cannot be treated through traditional business methods. The vote in the UK, in which the electorate to choose to leave the EU, and the election of Trump to the US Presidency, are both great examples of why traditional methods are weak in turbulent conditions. In both examples traditional statistical models, predicted the opposite result. And this is due to the fact that the predictive model is based on historical conditions, which were true 20-30 years ago. Conditions, which are almost never true nowadays, in an era, in which we are hyper-connected, always a digital keystroke away from a kindred spirit group on a social network. In an era, in which we can express our dissident opinion or our alternative facts and reach millions of people around the world. In this era we have no reliable statistical model to predict the results of an election, especially when populist candidates are on the rise.
How can businesses and managers adapt to the new turbulent era of unknown unknowns?
- Fail Fast, Learn Faster: in his IESE Insight Article, “Speaking the Lingua Franca of Innovation”, Prof. Jay Rao of Babson University posits that when the conditions are chaotic and unpredictable, the risks are complex and ambiguous, the only sensible business logic is “action before analysis”. In other words, we need to use our intuition to try new approaches, and learn from our mistakes. The logic is defined as creative, and the strategy is emergent, by using the principles of Agile management: the focus should be on intrapreneurial leadership, small tiger teams, customer-centric solutions focused on simplicity.
- Learn to detect the symptoms: before your organization has had time to collect and analyze the data, it might be too late to develop an emergent strategy. You should use your creative intuition, by validating it through the only metric which really makes sense in this situation: consumer relevancy. Learning to detect the symptoms means assuming that the Swan which is not white enough, is effectively Black, unless and until proved otherwise. The true north of the process consist in doing what is right for the consumer and the customer, putting politics aside.
- Challenge the data modeling: understand what question you are asking and whether the answer provided by the data fits or not the situation. Each market research methodology is a model. Models tend to simplify reality, by focusing on certain dimensions which are critical, and in the case of statistical model, they assume a certain behavior is normally captured through a specific distribution. In our previous example, electoral polls model reality starting from the likely voters, the ones who are often going to vote. But what happens to the model when the unlikely voters have a reason to show up and vote? Predictions go terribly wrong.
- Sensing is the new thinking: sensing is perceiving reality directly through the senses, dealing with the practical elements of reality and facts. It is focused on what is actual, in the present or past (During, D., 1999. Intuition in Design: A perspective on designers’ creativity. In Asia Design Conference (pp. 2-3).). Sensing is about establishing an emphatic approach with your consumers, is about observing as much as co-developing; also it is about being focused on the future and in the right type of leadership. Sensing is about generating early consensus internally, like prototyping at Pepsi, while keeping an eye on consumers’ experiences, as suggested by Jon Kolko on the HBR.
- “Know thyself”, learn to deal with your cognitive biases. More importantly beware of personal and group behaviors when information is scarce and pressure to deliver is high. Build a litmus test around consumer needs and relevance of solution. Also beware that people tend to be risk-adverse when winning, and more prone to taking risks when losing. Cognitive biases are what make fake news and alternative facts possible.
- Pivot: albeit a typical start-up jargon, and quite abused nowadays, it’s still a powerful concept. When market conditions are turbulent, pivoting is about changing the strategy to strengthen the link between the right customer, the value proposition and the positioning. Pivoting is about being ready to challenge your main assumptions, but also to challenge your business model for that specific instance.
In conclusion: tackling the unknown unknowns
When conditions are challenging, strategy is not a game of chess any longer. You can’t plan several moves ahead, based on the expected moves of your opponent. Big data set only provide one side of the picture, and in-depth analysis might put an end to your venture. Agile management, Sensing, Design Thinking, and Creative Intuition are better tools to ensure you can deliver relevant experiences to your consumers.