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Science-led innovation: the fast and the furious

By Chris Rosser - Last updated: Wednesday, May 10, 2017

Ford muscle car

“Science is a way of life. Science is a perspective. Science is the process that takes us from confusion to understanding in a manner that’s precise, predictive and reliable” – Brian Greene

It can often be difficult to resolve the contradiction between the rigour and discipline of an engineering design process and the boundless creativity required to innovate. Often the key breakthrough in design is made through an intuitive leap by the designer to the solution. This can produce some fantastic technologies but it is not without its drawbacks. I’ve lost count of the number of times that I’ve been asked to evaluate a design and explain what makes it so good, what makes it tick? Inevitably the next question is how can we further improve it or modify it to work in a different situation or under different conditions.

I have found that a science-led innovation process is the best way to answer these questions. By applying a rigorous approach grounded in experiment to create solutions to difficult problems you can have the best of both worlds. The weird, wacky and often inspired solutions you never would have thought of and the security of methodology and process. I will use the Fast and Furious movie franchise by way of example. If you squint a little, Vin Diesel really does embody the concept of science-led innovation.

First you have to carefully define your problem. It must have requirements that can be tested and have objective and quantitative pass/fail criteria. In Fast and Furious the requirement is building a faster car than the opposition. There are sub requirements around cornering, top speed and acceleration. The tests are the parts of a race course and the pass/fail criterion is the finish line and whoever crosses it first.

Once you have the problem, the test and the target you need a team of creative engineers and designers to make it happen (Vin has his petrol head mates of course!). They must use their understanding of the physics that govern the system to produce a range of possible solutions (or improvements if there is some existing design). Some of the solutions will be quite conventional (stripping out weight and fitting better tyres etc). Others less so – like stealing a year’s supply of Nitrous Oxide from the local dental surgery.

Each of these solutions must then be framed as a number of individual hypotheses addressing each of the requirements directly. Do the new tyres improve the cornering speed? Does increasing the engine power affect top speed? Does a scuba tank full of nitrous reduce the 0-100km/h time?

Each hypothesis can then be the focus of a single experiment which will either confirm or disprove the hypothesis. Careful observation and processing of the results will inform the design as well as future experimentation until a solution is reached. The advantage of taking such a sure-footed approach is that the whole team can have the utmost confidence that the solution arrived at is the right one. In Vin’s world every race is an opportunity to test his latest modification, to find what works and what doesn’t. And in the end his car ends up the fastest, and the franchise gets another 7 movies!

The key to implementing this process is streamlining the documentation and data capture. Unlike Vin we can’t keep all the knowledge to ourselves. Without robust templates and procedures that can be transferred from one problem to another implementing this methodology is laborious and slow. But once you have invested the time and fine-tuned the process over several projects the return on investment is deeper understanding and faster problem solving. In my experience it’s a trade worth making.


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AuthorChris Rosser


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