My wife and I have been watching a number of old television series via DVD and video streaming services. We have both noticed (in a distressing way) a common theme among the shows that purport to have a major character who happens to be a scientist – the scientist(s) know more than any reasonable person would, they accomplish tasks quicker than anyone (or a team of a thousand people) reasonably could, and they make the proper leaps of logic in one or two iterations. While these may be useful mechanisms to keep a 20 to 40 minute story moving along, it in no way reflects our experience in the real engineering world.
Tim Harford’s recent TED talk addresses the successful mechanism of trial and error to create successful complex systems and how it differs from systems that are built around systems built based on a God complex. The talk resonates with my experience and poses a statement I have floated around a few times over the years in a different manner. The few times I have suggested that engineering is a discipline of best guesses has generated some vigorous dissent. Those people offering the most dissent claim that given a complete set of requirements, they can provide an optimum engineering design to meet those requirements. But my statement refers not just to the process of choosing how to solve a requirement specification, but also in making the specifications in the first place. Most systems that must operate in the real world are just too complex for a specification to completely describe the requirements in a single iteration – there is a need for some trial and error to discover what is more or less important for the specification.
In the talk, Tim provides an industrial example regarding the manufacturing of powdered detergent. The process of making the powder involves pumping a fluid, under high pressure, through a nozzle, that distributes the fluid in such a way that as the water evaporates from the sprayed fluid, a powder with specific properties lands in a pile to be boxed up and shipped to stores for end users to purchase. The company in this example originally tried an explicit design approach that reflects a God complex mode of design. The company hired an expert to design the nozzle. Apparently the results were unsatisfactory; however, the company was eventually able to come up with a satisfactory nozzle by using a trial and error method. The designers created ten random nozzles designs and tested them all. They chose the nozzle that performed the best and created ten new variations based on that “winning” nozzle. The company performed this iterative process 45 times and was able to create a nozzle that performed its function well. The nozzle performs well, but the process that produced the nozzle did not require any understanding of why it works.
Over the years, I have heard many stories about how using a similar process yielded a superior solution to a problem than an explicit design approach. Do you use a trial and error approach in your designs? Do you introduce variations in a design, down select the variations based on measured performance, and repeat this process until the level of improvement suggests you are close enough to an optimum configuration? I suspect more people do use a variation and select process of trial and error; however, I am not aware of many tools that facilitate this type of approach. What are your thoughts and experiences on this?