Uncertainty is scary. If you have a problem to solve without a clue how, you’ll probably only get somewhat stressed and anxious. Ordinary solutions for similar problems may have failed or the problem may be like nothing before. Then it is time for innovations and time to get creative and start doing some design.
Design is a working method developed to solve problems that cannot be solved by normal logic. Designers get used to uncertainty and must be confident that a solution will be found. They use creativity and imagination to fill the gaps in order to come up with early ideas which can then be iterated towards refined solutions. This kind of process is an answer to problems that can’t be defined; problems with solutions that can’t be compared by certain set of tests and measurements.
This vagueness of problems leads to the need to define the problem as much as possible before starting to solve it. Otherwise the solving could end up in entirely wrong direction. Thorough research is encouraged in Dash, so participants would have a holistic picture of the base causes behind the problem. A common and not entirely wrong approach to unclear problems is starting from own and relative’s subjective view of what causes the problem. This is a great way to get started but without thinking the variety of different users and their needs, the effectiveness of the solution might remain shallow or completely useless for intended user group.
So, the problems are caused by something. This is called causality. The base causes of problems are not any more defined than the problem itself. They can be seen very differently from different viewpoints. In a universe of causality there are multiple sets of causes that diverge exponentially the further they are tracked. This is why design problems are complex. It is a matter of research to map these causes and concern the right ones for the most effective solutions.
Since that was probably confusing, let’s try an example: Let’s say a turbine falls out of an airplane and we find out that it wasn’t fixed properly by the manufacturer, a human mistake. Some would probably just fire the employee whose fault it was, but because this is an airplane we want to ensure it never ever happens again. But should we train employees more? Put more resources in quality control? Design more idiot proof attachments or ones that won’t fail even with poor installation? Careful research is needed to weight the best option.
The causality works other way around also. There are multiple consequences that follow the existence of the problem. And even though we talk about problems, not every consequence is bad. The deeper you go towards the root of a problem, the wider is the set of consequences in good and bad. This is one point where design work can go wrong. It is important to recognize all the good consequences the problem creates and to make sure the solution won’t ruin them. Mostly it is a matter of compromises, but sometimes we get innovations where almost everybody wins.
So, if we design an attachment for turbine that even a trained monkey could install securely, it would probably be more expensive to manufacture, weight more and be otherwise inferior in many aspects, a compromise. If not, it is good design and true innovation.
It is hard to define what is good design. We don’t know best solutions to any of our problems, so it is just a matter of choosing the least bad option and best compromise for right situations. Possibly making some remarkable innovations during the process. As mentioned earlier, designers must be confident that better solutions can be found. And even though it may seem little pessimistic to see only problems in everything, it still is optimism towards better solutions. It is important to stay open to new ideas. Otherwise we would be stuck with bad ones.
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