Reading @Leading Blog: Why Design Thinking Is the Next Competitive Advantage

Leading Blog: A Leadership Blog: Why Design Thinking Is the Next Competitive Advantage.

Why Design Thinking Is the Next Competitive Advantage

We live in a reliability-oriented world. And understandably so. We want predictable outcomes. We want things to keep working as they have always been—perfectly.

Success. Repeat. Success. Repeat.

But that thinking ultimately limits our growth and quite possibly harbors the seeds of our own destruction. It can be (very) valuable to a point, but it isn’t adaptable because by its very nature it has to leave something out of the equation. While reliable outcomes “reduce the risk of small variations in your business, they increase the risk of cataclysmic events that occur when the future no longer resembles the past” and the reliable is no longer relevant or useful.

To remain relevant—to foster innovation—you need to incorporate into your thinking outcomes that are valid. That is, outcomes that produce a desired result even if the solution employed can’t produce a consistent, predictable outcome. A perfectly valid solution is one that produces a result that is shown, through the passage of time, to have been correct. It is best to have a system that incorporates both—validity and reliability—into their approach. Balancing and managing the two approaches—analytical and intuitive—is what design thinking is all about.

In The Design of Business, Roger Martin presents the knowledge funnel to show how knowledge moves. Each stage represents a simplification and ordering of knowledge. At the beginning is a mystery; a question. It is the observation of phenomena. Things we see but don’t yet understand. 

The next stage is a heuristic, “a rule of thumb that helps to narrow the field of inquiry and work the mystery down to a manageable size.” Heuristics don’t guarantee success but do increase the probability of success.

The last stage is the development of an algorithm. “An algorithm is an explicit, step-by-step procedure for solving a problem. Algorithms take the loose, unregimented heuristics—which take considerable thought and nuance to employ—and simplify, structuralize, and codify them to the degree that anyone wi

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