The Design Process and the Scientific Method
Every once in a while, there are rumblings about how the design process should be more like the scientific method. Although I profoundly disagree with this (more in a moment), I can understand this impulse. The design process is messy, difficult to explain and sell, and its results are not certain from the beginning. People want more predictability. (We even heard that one of our competitors was selling their services as “a design machine” to a prospective client in order to claim their process was more reliable.)
What is it about the scientific process that people admire? Predictability, certainty, and repeatability. The essence of the scientific method is to test a hypothesis: if I try this, will it work, yes or no? Any time I repeat that process, if done correctly and no other variables are introduced, I should get the same response. The response can be tallied, measured, and recorded.
For observing, analyzing, and understanding natural phenomena and even for some engineering tasks, this process makes sense. But it does not work well for design, because good design is not repeatable. The general design process is certainly repeatable (strategy > research > concepts > refinement), but the outcome, the result of the process, is never repeatable and never guessed at from the outset, for the simple reason that context in design is too important. I can use the exact same process with two similar organizations working in the same field and end up with two widely varying products. Perform the same process with the same group of people a year apart, and you will get different outcomes. Unlike in science, where, when, and, especially, who is performing the design activity matters.
Unlike the scientific method, which attempts to strip humanity out of its practitioners (because you want the results to be able to be repeated (and tested for accuracy) by anyone able to follow the formula/process), the humanity of the participants is enormously important in design. Different designers may, of course, come up with the same solution, but in design, very frequently there is no one correct solution. The solution that would work for one organization might not for another. Someone inside LG or Motorola might have come up with something similar to the iPhone, but even if they had, it wasn’t the right solution for their organizations. It would have been rejected (likely to their later dismay). The solution has to work for the context.
As materials, technologies, styles, cultural attitudes, etc. change, the solution that was correct five years ago, could seem hopelessly dated. Again, this is in opposition to the scientific method, where the search is for solutions that are good for long periods of time (ideally forever, until a new theory or new data challenges it).
Of course, design outcomes (i.e. products) will be imitated. Knock-offs and clones will be made. But they are not outcomes of a design process, but of a manufacturing or development process. The purpose of a design process is invention: to create something new. The purpose of the scientific process is the discovery of something new. It’s a subtle, but important distinction.
This is also not to say that data doesn’t have a place in the design process. You can use research to enhance or inspire your decisions. You can test different solutions and the data can certainly suggest which solution could be the better one, but data can’t make design decisions, only humans can. Jensen Harris has a great story about using data to design Office 2007:
Many people suggest that “you guys should optimize the UI to match the feature usage data.” On the surface, this sounds like a solid idea; you could have a computer determine the organization and prominence of different features depending on what part of the curve they are in. It would be very scientific. The only problem? We’ve already designed that product, and it’s called Office 2003.Put another way: if all we want to do is design a product that matches today’s pattern of feature usage—well, I don’t have to do any work! Office 2003 already matches the curve exactly; we can’t do any better than statistical perfection.
The real equation at work here is data + human = design. We need to take the data, analyze it, understand its shortcomings, and use it to inform a design which meets our goals. But, in itself, the data cannot produce a UI because it has no goals and is a reflection of the DNA of a product you already shipped!
Exactly so. Applying the data as it seemed it should have been used, in a scientific manner, would have re-created Office 2003. And no one—I mean no one—wants that. In any case, you cannot test something (or at least test something well) that hasn’t been created yet. No
And here’s one final, secret reason why the design process should never be more like the scientific method: it’s irrational, in the best way. The best designed products, the ones we admire and, more importantly, cherish are those that are emotional and often idiosyncratic. And, often, so is the design process that creates it. Michael Beirut nails this in his article “This is My Process:”
Sometimes I have one great idea but can’t convince the client it’s great and I have to do more ones. Sometimes this leads to a better idea. Sometimes it leads to a worse idea. Sometimes after I go back and explore other ideas we all come back to the original idea. Sometimes the client accepts an idea, and then produces other people who haven’t been involved up to that point who end up having opinions of their own. One way or another it always seems to get done, but never as originally promised.
This is how the design process works. There’s nothing very scientific about it, nor, I think, would we ever want it to be, lest we lose the very things that make it design—the emotion, the humanity, the decision-making—in the first place.
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9 Comments
Dan,
One of the key drawbacks for me of the scientific method, at least when it’s applied to problem-solving broadly, is that it is inherently single-minded. An hypothesis is formulated, tested, and accepted or rejected. It is iterative, granted, but along a single line of enquiry.
By contrast, the design process attempts to maintain and explore a multiplicity of ideas for as long as possible. Discarding dead-ends along the way, but retaining *all* (or many) good avenues for investigation, design allows for, and actively encourages, divergence and ambiguity to exist.
The scientific research process – particularly as it is practiced in universities and corporate R&D labs – rejects such multiplicity, encouraging researchers to hone in on a single ‘best idea’ and focus. The investigation of that single line of enquiry may become a life’s work for a scientist, which in turn has some fairly negative outcomes.
Scientists are more likely to become heavily invested in their hypothesis, defending it staunchly instead of working to expand, morph and improve it. For the designer, embracing multiple, divergent ideas, this emotional investment is typically much lower and therefore more open to being discarded or changed.
For me, it is this difference that allows design to play a more effective role in solving complex problems where ambiguity is a fact of life.
Steve
I can see your point, and I can see and understand why you would think this. I used to as well. Until I revisited my scientific roots.
First off not every piece of design is ground breaking. Just like not every piece of scientific research is a major discovery. There is a lot of day to day hum-drum scientific research and design.
There is one aspect you seem to be no focusing on is that scientific research can have a creative element to it. Tagging something design, doesn’t mean that it has the exclusivity on the creative mind.
I have personally seen some amazing creative ideas and rethinking during the scientific process. In fact I would say that sterile environment of science sometimes promotes the creative thinking. To even suggest that science doesn’t have that input of creativity (that computers lack) is just a complete misrepresentation.
It is the process of peer review that forces the element of repeatability of scientific research. However sometimes this research just isn’t repeatable eg sometimes due to various environmental and macro biological events. It is this type of field research that is so like the design process. Studies of animal zoology, behaviour and psychology tend to fall into this area.
Now what would happen if you removed the peer review process. The need for strict documentation and experimental rigour… then the basis of scientific methodology is very similar to the design process.
I can see where you are coming from, the “design” element of the design process used to be a lot larger in the process. But now in has been reduced (or rather other elements added on) to a smaller segment. The design element is left to creative spark and iterative process.
In the scientific process this is the creative process of designing the experiment and the hypothesis. Too often the designing of the experiment is an iterative process in its self. Just like with design, things often don’t go to plan. Results get biased, the environment has too much of an influence, the source material is wrong…and so on. Just like in design.
The only difference is in that design is a very sloppy poorly disciplined and documented process by comparison. Mainly because there is no peer review.
Also consider as a side note…on a macro scale that design research is also repeatable, to a degree.
You can’t hide from it the design process has had scientific and engineering based processes added to it. These are based from scientific methodology.
Steve
In design when the budget is tight (most cases) we are also forced to hone in on the single best idea and reject the rest untested.
While I agree that it is inappropriate if not outright silly to try to apply scientific rigour to something like design, I submit there are still useful principles at a greater level of abstraction. I’ve found a great deal of utility in the principles of the mathematical method, which is analogous to the scientific method. It goes like this:
1) Understand the problem,
2) Devise a plan,
3) Execute the plan,
4) Examine the result.
I did a little presentation a few months ago that takes it into account. The book I based the talk on (one of them at least) is called How to Solve It by George Pólya.
Your rant is very timely, I totally agree with your outlook. The call for humanity is urgent and necessary, design can’t be reduced to an algorithm, you can’t reduce it to something less than human.
The desire to “scientise” design appears to be coming around again and again. If we take a look at the past of our discipline, we see that in the sixties the Design Methods movement wanted to develop scientific approaches to design. Although the movement was very important in establishing design as an autonomous discipline, it failed in their aim to develop a set of objective, systematic “rules”.
Even Christopher Alexander one of the fathers of the movement, was soon disenchanted about their practical applicability:
“I’ve disassociated myself from the field.., there is so little in what is called ‘design methods’ that has anything useful to say about how to design buildings that I never even read the literature anymore…I would say forget it, forget the whole thing.”
Design Research and Methods. Vol 7 No 2 (1973) pp 133-135
After that we had 2d and 3rd generation design methods, we’ve learned about the notion of wicked problem, about the reflective practice, about the constructive nature of design…it’s not as simple as data + human = design
I very much like the idea of the design process as being irrational in some degree. It is actually also put forward by John Chris Jones (in the first part of Essays in Design, Wiley, 1984) Jones was another notable member of the design methods movement who became an apostate.
Let me finish with this quote by Mies van der Rohe concerning the Tugendhat House, that somehow complements Bierut’s words very well:
“He (the client) wasn’t very happy at first. But then we smoked some good cigars, … and we drank some glasses of a good Rhein wine, … and then he began to like it very much.”
Quoted in Designerly ways of knowing by Nigel Cross.
I was not, by the way, suggesting that there is no creativity in the sciences or in scientists and researchers. I’m not a scientist, but my conjecture is that the creativity of scientists comes in the creation of hypothesis to test, or in understanding/interpreting the outcome of those tests.
You have a very limited view of the scientific method and scientific knowledge production.
I really like the notion that you cannot repeat the outcome of a design process.
I think this is also why design is more complex than science…
I think design becomes a powerful force when results do become repeatable. Not repeatable in a repetitive redundant sense, but in terms of getting at a more fundamental human nature.
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