You might think better if you were less of a scientist

It took me some decades to appreciate how my education has shaped not only my knowledge but my thinking. As a chemist, I had absorbed the idea of reductionism, that phenomena could be condensed into a simple ‘x plus y causes z’ explanation. Even later, as a management scientist, I tried to force much more complex organisational issues into the same simplistic approach, despite finding that it rarely worked. It wasn’t until I discovered complexity theory and Generalised Darwinism that I managed to break out of the intellectual prison into which my early education had confined me. I was reminded of this recently during a strategy workshop with a firm that was clearly still incarcerated in a reductionist prison. As ever, let me make a small diversion into the science before coming back to the practical implication.

I remember the day of my release. I was sitting in my garden, looking at some research data and having one of those moments that every scientist will recognise. The data was clear but it didn’t fit my mental model, so my mind was contorting itself trying to make the data fit my model. Scientists are taught from a young age not to do this, but I think we all do before we eventually concede and follow the data.

My ‘x plus y causes z’ mental model, shaped by a physical sciences education, was that some factors, like the genomic revolution and globalisation, would lead to a new business model for the life sciences industry. My research data was supposed to identify both that model and the mechanism of its formation. Chemists in my audience will see the paradigmatic link with organic synthesis. At one point I think I even labelled my hypotheses SN1 and SN2. But the data didn’t show the cause and effect my mental model predicted. Instead, it showed an explosion of many business models and, while some partial mechanisms of formation were visible, my reductionist mental model was in tatters.

Then the lightbulb came on. I’d recently read a lot of evolutionary and complexity science and its salient point was emergence, the idea that a system can have properties that its parts do not have. Or, in other words, ‘x plus y plus a lot of other things can lead to something completely unexpected’. In that moment, I realised that while my old model worked for a handful of chemicals in a flask, it was the wrong paradigm for thinking about complex adaptive systems like our industry.

Back to the strategy workshop. The clients, on a verge of a huge investment in CNS, wanted to anticipate the market but, still in a reductionist prison, was focused on the impact of the current therapy pipeline on market size. That approach wasn’t wrong but it was insufficient. It gave a keyhole view of their future when they wanted a panoramic view from a helicopter. Eventually, I used my ‘external expert’ authority and mock outrage to say ‘Stop that!’ and move them to an emergent properties perspective. That allowed them a wider market view, including substitute therapies like neural stimulation devices, but also a wider habitat view, such as the economic impact of new ‘budget buster’ therapies in areas like Alzheimer’s disease. To be clear, this complex system’s view of their market was less comfortable than their reductionist view but it was a much more authentic one. And, armed with this view, they were still able to apply reductionist analyses to the smaller, better-defined sub-questions on their agenda.

Forgive me if this little morality tale sounds a bit smug but I have the zeal of a convert. As a reductionist-turned-complexity-thinker, I want everyone to share in my enlightenment. Everywhere in our industry, I see thinking that works well for molecules failing horribly in markets. Every day, I’m asked questions like ‘how will factor x impact on situation y’, which reveal the same reductionist mindset. Which isn’t to say that reductionist thinking and simple answers don’t have their place, of course. Rather, it is to say that reductionism is a thinking tool that works very well in relatively simple situations or ones where confounding factors can be isolated and controlled for. But, like using a hammer on a screw, we sometimes need a different kind of tool. Complex systems thinking, even if it can’t be quantified, can be harnessed in tools like Emergent Properties Analysis to provide better answers to bigger questions. Like any convert, I look at those still imprisoned in reductionist paradigms with a mixture of pity and quasi-religious zeal. Only because I was and am a trained scientist, with years at the bench, do I feel able to say that sometimes you might think better if you were less of a scientist.