The idea of thinking like designers to solve problems is a hot topic.
Now you may be thinking, that this is just another fad. Maybe you’ve even tried applying this type of thinking to help solve a problem and it didn’t work. We’ll call you Person A.
Or maybe you’re just the opposite and are thinking that this is just the type of thinking you need to apply to problem solving and are gearing up to use it for every problem you need to solve. We’ll call you Person B.
But wait. That goes for both you, Person A, and you, Person B.
Design thinking is not appropriate for every type of problem, just like linear analytic methods aren’t always the best way to go. That’s why some of you may have tried it without success and other just shouldn’t rush out and try to apply it.
I found the best explanation I’ve seen thus far concerning when to use each problem-solving method when I took a course called Design Thinking for Business Innovation. At the start, we were given some questions to ask to determine when it would be best to use design thinking to solve a problem and when it would best to use linear analytic methods. I’m going to share them with you now.
Is the problem human-centered?
Design thinking is appropriate if deep understanding of the actual people (users) involved is both possible and important.
Linear analytic methods may be better if there are few human being involved in the problem or the solution.
How clearly do you understand the problem itself?
Design thinking is appropriate if we have a hunch about the problem and/or opportunity, but we need to explore to get agreement.
Linear analytic method may be better if we understand the problem clearly and are sure we’re solving the right one.
What’s the level of uncertainty?
Design thinking is appropriate if there are many unknown (large and small), and past data is unlikely to help us.
Linear analytic methods may be better if the past is a good predictor of the future.
What is the degree of complexity?
Design thinking is appropriate if there are many connecting and interdependent facets of the problem; it’s hard to know where to start.
Linear analytic methods may be better if the path to solving the problem is clear, and analytic methods have succeeded in solving similar problems in the past.
What data is already available to you?
Design thinking is appropriate if there is very little existing data to analyze.
Linear analytic methods may be better if there are several clear sources of analogous data.
What’s you level of curiosity and influence?
Design thinking is appropriate if you say, “I’m excited to explore more and can get a group of people willing to help me.
Linear analytic methods may be better if the problem feels routine to you and you have to follow existing processes and systems.
Source: Designing for Growth Field Book: a step-by-step project guide, Jeanne Liedtka, Tim Ogilvie, and Rachel Brozenske
What do you think of using this as a guide to decide which problem-solving method is best? What examples of using different methods do you have to share?