How can we learn Exponential Thinking and what can we learn from it?
“[T]he future will be far more surprising than most people realize, because few observers have truly internalized the implications of the fact that the rate of change itself is accelerating.” Ray Kurzweil, The Singularity Is Near
Many leadership programs offer insights and lectures on exponential thinking — how to invent moon shots, when will Singularity overtake us, which unicorns to invest in, how to invent successful start-up business models or how to scale. Yet, SARS COVID-19 taught us some very existential lessons in exponential thinking that no ThinkTank, Start-up incubator or Business School could have done more convincingly: Exponential Thinking is almost completely beyond everyone’s scope.
First challenge: Recognizing exponentiality
In February, I was recruiting new early talents for our SAP Academy for Engineering to join us for a unique learning experience in Silicon Valley planned to start in April. It was late in the process, but an opportunity had opened up, I told them, as the Chinese colleagues we had selected could no longer join due to “their” Corona virus outbreak. 3 weeks later, I felt incredibly stupid for not having foreseen what kind of global turn this virus could take and how it could shut down not only China but also the rest of the world. It’s a small relief that, according to SingularityHub, it’s normal to miss exponential trends early on because they start similar to known linear growth scenarios and then — all of the sudden for most eyes — take off: “Exponential growth is deceptive, then explosive.”
And it’s not only hard to recognize, for most people it’s also hard to acknowledge being in a situation that harbours exponential danger. The Kuebler-Ross grief curve is nowadays increasingly cited along with survey results to show the different stages individuals, populations or countries are in, ranging from denial to acceptance. Comparisons to known dangers with non-exponential growth rates (e.g. people dying from the flue) are not helping as they build up on wrong assumptions. Is it all about math, you may ask? Yes, it is, and much more:
1) Have the data, know your math
First of all, you have to understand what “exponential” means. Linear growth can be easily explained in steps — you take one after the other and add the same amount over and over. Exponential growth is when you double the number of steps or multiply the same amount over and over. If one step equals 1 meter, you would walk 15 meters with 15 linear steps and 16.384 meters with 15 exponential steps (1, 2, 4, 8, 16, 32, 64, 128, …). You see the explosivity coming in deceptively slow; up with step 11, it rises dramatically.
And you only see this coming if you have the “right” data. The NGO www.ourworldindata.org, along with JHU and WHO, have been continuously providing an enormous amount of COVID-19-related data and infographics since January 2020. At the same time, they have not grown tired of emphasizing that they are lacking data: data that are comparable, consistent, based on the same testing paradigms or on known and reliable contexts. It becomes apparent on how easily numbers can be crunched, misinterpreted, and misunderstood outside of any context. Herbert Simon, in 1971, was right in claiming that “A wealth of information creates a poverty of attention.” We are currently flooded with data and do not have sufficient time for analyzing, where they come from, who was sponsoring it, whether it’s been a significantly large study, whether it was a proper scientific study, whether the data are fluid or momentary or constant, whether the data are actually true and not subjected to a political agenda, e.g. “most tests done” — per country, per 1 mio people, with or without reliable results?
2) Multi-dimensional education matters
So, how to cope with the masses of data, influences, graphics? How to analyze it properly and take the right conclusions? It requires different disciplines to understand, evaluate and take the right measures. Looking at it in the binary fashion of right or wrong no longer works. Truth always depends on the context: “Most tests done in US” could be right if meant as “Today was the day in which US has done the most COVID-19 tests in its history.” It’s wrong if meant as “US tests more than any other country in relation to its number of inhabitants.” Each graphic and its underlying data require initial questioning according to the 6 W’s: who, when, what, by whom, why, how? If you wanted an expert opinion on epidemics, would you go to Dr. Phil or to a subject matter expert such as Dr. Fauci?
To make sense of data, you need to understand the background of the data. So the more you understand the political, social, geo-spatial, historical, technological, cultural and economic implications and the dependencies, the likelier you will be able to contextualize the value of the respective data or report. John Snow, one of the founders of modern epidemiology and leader in medical hygiene in the 19th century (with famous namesake in GOT in this century ;-), collected data on a cholera outbreak in London in 1854. He was only able to connect the dots and trace the source of infections by analyzing peoples’ behavior and listening to local experts who knew the local geographics including waste and water systems. The sole number of infections would not have helped to come to that life-saving conclusion. Accordingly, some correlations are simply so farfetched and potentially irrelevant that they have to be questioned, e.g. are you more likely to vote for candidate A if your favorite shower gel brand is X and you had a Croissant for breakfast?
What and how we learn in school often stifles creativity and going beyond out plates. We learn conformity, how to memorize and how to avoid making mistakes instead of creativity, trial and failure or risk taking. We learn how to dive deep into certain subjects, which often leads to self-definitions as experts for certain areas and hence to a behavior that we try to solve a problem with that expertise only, in silos, blind-sided for other, sometimes easier solutions. And while it’s essential to have experts, we should not ask them for decisions outside their area of expertise. Dr. Drosten, German epidemiologist from Charité Berlin, answered to a question about the timeline of opening schools that he is just a virologist, who can give only give the scientific data points to the politicians. They would have to weigh them against other data and make the final decisions.
3) Become creative (again) & fight conformism
Predictions of which technologies will change the future are booming, from augmented reality to quantum computing to personalized medicine, including gene editing and electroceutic cells, AI molecular design or drug-making cell implants. From books, movies or even motorsports and aerospace engineering we get a glimpse at what the future could bring for everyday life. In general, as in the graphics below, even in our wildest dreams, we usually remain way below reality:
The faster we adapt to the changed environment, and the more creative and meaningful the concept, the more successful it will be. I’ve been hearing of restaurants or exhibitors, who want to “wait and hope”, of governments and industry experts who talk about putting the economy into an “artificial coma”. My conviction is: most of those who hesitate or hibernate and don’t adapt to the changed environment now, risk to become redundant. New food truck and food delivery concepts are on the rise, replacing existing restaurants. Fitness and shopping, learning and cooking, music and cinema are reinventing old, such as drive-in cinemas, coming up with new or leveraging known concepts and technologies from other industries, such as fitness streaming channels. Caveat is, people are not willing to pay the same price for online experiences, be it newspaper, movie, sports or educational offers, than for the “real” thing. Reality may change, and online offers may also become more personalized, high touch, higher value assets to justify and trigger a higher price tag.
But how to get there? How can we design our dreams to go wilder? When googling “creativity techniques” you get 194 million results. Creativity workshops teaching techniques such as Brainstorming, Mindmapping, Storyboarding, Role-playing, Visualization, Reverse thinking, User-centric research, Mood boards, Random input, Science-Fiction-Prototyping, etc. are mushrooming. Complete schools of thought such as the HPI School of Design Thinking, have emerged. All there to foster imagination & curiosity, diversity, problem-posting and -solving and challenging existing assumptions. And to come up with creative ideas for future innovations.
My 5-year-old god daughter created her own Pippi Longstockings costume with lots of colors, fabric and glue for carnival and was 150% happy and proud of wearing it. Up until she saw her friends in Kindergarten in 5 identical looking Princess Elsa dresses from a discount store. She immediately looked self-conscious and started hiding behind her mom, wishing for nothing more than to fit in.
How we plan our lives, accordingly, is almost purely linear and adapting to conformism, too — step by step, cause and effect. At age 5, we are using about 80% of our creative potential — think of all the ice-cream flavors 5-year-olds would be coming up with. At age 15, creative output has vanished, almost exponentially, to about 12%. With adults it’s almost gone (2%), according to a 2011 NASA longitudinal study by Dr. George Land and Beth Jarman. We need to teach ourselves again — and most of all tell our kids — that it is okay to be different, that it’s okay to have stupid ideas and fail, that conformism is not the ultimate truth. Otherwise we will never be able to imagine a world after exponential step 11.
Lessons from living in exponential times
Exponential thinking requires a basic understanding of data and making sense of these data. Above all, it needs creativity. Only then we can think ahead and envision a future that is not built on linear progression or learnings from the past. So what can we learn from the current situation? Could we track the “normal” flue in ways we are currently tracking SARS-COVID-19, would vaccination increase? Would investments in medication for tuberculosis or HIV increase if the diseases regained their presence in nice graphics and global death toll rankings? Or will people get sick of rankings as they only portray a tiny glimpse of reality, with many asterisks hiding the complexity of how we got the data in the first place? My take is: we will need easy visualizations and even simplifications for 95% of people to understand the gravity or a problem. If only we could track in a consistent, uniform, globally aligned way the effects of climate change! Infographics like the one from A.T. Kearney are mind-opening to many people:
So let’s invest in education, in creativity, in institutions such as www.ourworldindata.org, who help us in scientifically proven ways understand the complexity of the world we are. Let’s not jump to conclusions or dramatic actions from a single data set that we see, investigate carefully where it is from and what the context is. We need to keep expecting to be surprised — and be prepared to plan accordingly. And to re-plan. And come up with an even better plan right after that.
Don’t just sit and wait for the world to change. It has already changed.
