This continues on from an Innovation Excellence blog I wrote last month about how personality types can influence innovation capability. https://innovationexcellence.com/blog/2019/10/03/5-psychological-traits-of-highly-innovative-organizations/ While many of the ideas in that article could also be applied to personal development, the primary focus was on how we behave, develop and recruit innovation capability in a team context. But personality and thinking styles are obviously interconnected, and so almost inevitably, as I explored personality, I also strayed into individual cognitive as well as behavioral styles. I believe both are important, so in this article I’ll dive deeper into that space, look ‘under the hood’ and explore what kinds of thinking and intelligence may help us to innovate more effectively. Perhaps more usefully, I’ll also explore which of these we can, or cannot protect, cultivate and improve over time.
Some of the cognitive styles I previously discussed included analogical thinking, need for cognition (deep causal understanding) and the role of curiosity in innovation teams. These got me thinking deeply more generally about what kind of individual cognitive styles, or intelligence we need to be effective innovators, and how they interact with behavior and personality? For example, personality types like openness and conscientiousness help us to explore and understand new conceptual spaces, but this desire or willingness alone is not enough. How we process, categorize and understand different types of information and different problems or opportunities is also a critical part of the ‘innovation equation’.
And the importance of behavior and thinking applies not just to ideation at the front end of innovation and idea generation. An effective innovator needs to be able to take an idea, and turn it into a product or service that people understand, desire, can use and in most cases, buy, either directly or indirectly. This requires a broader set of mental skills that go beyond those that simply facilitate coming up with ideas. But if we want to ‘peel back the onion’, and explore how different types of ‘intelligence’ or thinking styles can enable innovation, first we need to dig a little deeper into what ‘intelligence’ actually is.
What is intelligence? When I was growing up, this seemed a pretty simple question. It was a somewhat innate property that could be measured quantitatively by IQ, or inferred from standardized tests or exams. But by the 1980s more complex models started to emerge that challenged and expanded this rather linear view. Steinberg’s triarchic theory argued that intelligent tests were wrong to ignore creativity, and that creativity, planning, performance and decision making also contributed to ‘useful’ intelligence. Gardener’s multiple intelligence model broke intelligence down into a number of different components, including musical, visual (perceptual), linguistic and embodied (kinesthetic). And over the last ten years or so, people like Dan Goleman and others have further developed these ideas via concepts such as emotional, social and ecological intelligence that account for our interpersonal and communication skills, and start to factor in goals and biases. Furthermore, a number of other cognitive scientists have been developing insights that I believe are also crucial to understanding ‘intelligence’, or the thinking styles and capabilities that make us effective innovators. For example, Moshe Barr has been exploring how the brain is a predictive and proactive organ that constantly, and often unconsciously leverages memory to generate a future simulations and predictions. Similarly, Cognitive linguists and scientists such as George Lakoff, Art Markman, Dedre Gentner and Gilles Fauconnier have been exploring analogy, metaphor, and how concepts and knowledge can be transferred from one domain to another, and blended to create emergent new ideas. In short, the intelligence we need as innovators is not one dimensional, but instead comprises a range of thinking skills, styles and processes that combine to help us both come up with ideas, but also collaboratively turn those ideas into useful innovations.
Why is this important? Thinking is the engine of innovation, and so tuning it can be a springboard for self-improvement. And understanding how we think can also help us to understand our limitations and opportunities; as with any engine, some parts are tunable, other parts are relatively fixed. The better we understand this, the better decisions we can make around, for example, seeking out partnerships with complimentary thinkers who have strengths where we may be weaker, or to make investments in self improvement.
Intelligence Models. This is not physics, so there is no absolute right or wrong model. Instead there are many valid ways to slice and dice the intelligence pie. Below I share my personal model, one that I find most useful in the context of innovation capability. It borrows heavily from, and reapplies the work described earlier, but frames it in a way that I believe is particularly salient for innovation, breaking intelligence into 4 interconnected parts. We can evaluate ourselves against these, and use this analysis to understand what we can and cannot improve as we grow as innovators over time.
Intelligence Quotient -IQ. I have to start with IQ, the classic measure of intelligence. It comes with several benefits. It is familiar, easy to measure, and easy to compare. It is also important, in that it correlates at least to some degree with life success, and certainly has attributes that are relevant to innovation. We probably need a reasonably high IQ if we want to be successful and consistent innovators. But reducing the wonderful, complex organ we call the brain down to a single number also comes with limitations. IQ primarily measures reasoning, problem solving, pattern recognition and arguably motivation. But while a high IQ correlates with success in all sorts of careers, it doesn’t guarantee it, and people with very high IQ’s can struggle. On it’s own it ‘s too one dimensional, and innovators (and most professions) also need other, complimentary types of intelligence if they are to thrive. And the good news is that some of these others are easier to nurture and train than IQ. IQ can change over time, especially in children and adolescents, but it tends to stabilize as we get older. It maybe even drops a little as we age (this is debatable, as it is also tied into the Flynn Effect, that shows IQ of the population is slowly increasing over time, making it difficult to separate out any aging effects from a more general increase in younger generations). But beyond doing what we can to maintain our health and biochemistry, and keep our mind active, when it comes to IQ, we are largely stuck with what we have. So the bigger opportunities for self-improvement lie with other components of our intelligence.
ESI (EQ and SQ);If innovation was just about ideas, we debatably could have stopped at IQ. But innovation is a team sport. We need to be able to understand both ourselves and others if we are to discover and invent things that people will want, understand and find useful. We need to be able to communicate our ideas to potential consumers, but also to the people who fund and resource innovation, and to the partners we need to turn ideas into useful realities. We also need to be able to manage ourselves and others as we navigate the inevitable challenges and frustrations associated with creating meaningful change. Some of us are innately more emotionally and socially adept than others, and there are tests we can take to evaluate our basic social and emotional intelligence. But more importantly, unlike IQ, we can cultivate and grow ESI. We can practice empathic listening and synchrony. We can engage in self-assessment, and learn how to better recognize and control our own emotional responses. And we can work to habitualize our conscious, thoughtful responses to situations, so that our unconscious, knee jerk reactions more closely follow out more considered, thoughtful ones. It’s not easy, but possible, and if our IQ really does drop as we age, one option is to counter it by actively increasing our ESI.
AQ – Agile intelligence.The lifespan of an expert is contracting as the pace of change increases. Lifetime learning is no longer a luxury, but an essential component of any modern career. The chances that the factual knowledge we bring from education at the beginning of our career will still be relevant when we retire is increasingly small. Fortunately adapting to change is another trainable skill. We can practice switching gears, either directly by exploring different jobs, or indirectly by embracing hobbies or interests that stretch us in different directions. And we can consciously focus on learning transferable skills, such as communication, analysis, the scientific method. And one of my favorite topics, which I also covered in my personality blog, is that we can push ourselves to become expert generalists and analogical thinkers. Analogy is to some extent a trainable skill. The more analogies we experience, the easier it becomes to intuitively see the underlying patterns that underpin analogical thinking. This can not only help us to reapply ideas from one domain to another, but also to see how our skills and experience can transfer from one job to another. And seeing this need to be adaptable as a cognitive skill, or type of intelligence is becoming increasingly mainstream, as evidenced by this recent BBC article https://www.bbc.com/worklife/article/20191106-is-aq-more-important-than-intelligence
CQ – Creative intelligence. This is one of Sternberg’s three elements of intelligence, sometimes also called experiential intelligence. But I am going to take some liberties with his definition and expand it a little. He refers to the ability to deal with an unfamiliar problem or situation by coming up with a novel solution. Nothing at all wrong with that, but how do we do it? One mechanism is our ability to see patterns, and to have sufficiently agile intelligence to make analogies. These intelligence models clearly overlap, as pattern recognition is also measured, at least to some degree in the IQ test, and agile intelligence was described above. But I’ve broken CQ out separately because I believe the ability to turn mental agility and pattern recognition into new, emergent concepts goes beyond these attributes, and is worth considering and nurturing in it’s own right. For example, it’s also tied to an ability to define problems at an optimum level of abstraction. It is nurtured by an expert generalists’ ability to know a lot of stuff about a lot of things, and also by a strong need for cognition, that leads us to understand things at a causal, rather than superficial level. All mental skills and resources that facilitate useful analogy, and that can to some extent be trained and nurtured. We can become more deliberate about problem definition, and consciously seek causal understanding of a variety of things. Another way to measure our ability to see patterns and make analogies, and possibly hone these skills is via CRAP (compound remote association problems). Underpinning all of this is the question “Why?”, a common trait of infants and innovators, and hence one of the keys to lifelong learning. If nothing else, we can develop the habit of habitually asking ‘why?’, at least as much as we can get away with in polite company.
Another aspect of my broader definition of Creative Intelligence is the ability to create the cognitive context that facilitates creativity. There is a reason so many big ideas come to us when we are not thinking about the problem, but are instead taking a shower, a nap, or are out for dinner. Our brain tends to make big creative connections when it isn’t focused on the problem at hand. This has been explored via neuroscience, and it appears alpha waves in the brain may play a key role in this ‘distanced creativity’. Research by Caroline Di Bernardi Luftat Queen Mary’s in London showed high alpha brain wave activity, associated with resting and relaxation states, correlates with people’s ability to come up with less obvious or well-known ideas. So an important trait for an innovator may simply be to carve out time. If we are spending every waking hour trying to solve a problem, we may actually be blocking ourselves from coming up with the biggest ideas. And as a bonus, creating thinking space may also help us with creative vision, as predictive capability in the brain, a topic studied extensively by Moshe Barr, may also be connected to down time.
In summary, some things we can control, some things we cannot. Our IQ is largely fixed, at least by the time we are practicing innovation. But other important elements of our innovation intelligence, such as emotional and social intelligence, how we define problems, and the breadth of experience we draw on are all to some degree open to improvement. And if downtime and distance from a problem are import for finding creative solutions to problems, that is context we can to some degree control, by trying to ensure we, and anyone in our organizations has sufficient downtime. Work life balance is not a perk, it is an essential for a productive innovator. Sleep and health are also critical innovation tools, and exercise and diet are important parts of maintaining our brain. At extremes, a urinary infection, or Ca imbalance can very seriously impact our IQ, but lack of sleep, minor infections or illness all have the potential to take the edge off of out thinking, and that edge may be the difference between breakthrough and mediocrity. In summary, even if we cannot train ourselves to a significantly higher IQ, we can protect it, at least parts of our innovation intelligence are things we can control and improve.
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A twenty-five year Procter & Gamble veteran, Pete Foley has spent the last 8+ years applying insights from psychology and behavioral science to innovation, product design, and brand communication. He spent 17 years as a serial innovator, creating novel products, perfume delivery systems, cleaning technologies, devices and many other consumer-centric innovations, resulting in well over 100 granted or published patents. Follow him @foley_pete