Failing by Design

Failing by Design
Rita Gunther McGrath
Harvard Business Review, April 2011

Whether you're launching a new business, creating a new product, or developing a new technology, one of the best tools for learning is failure. This isn't to suggest that failure is a good thing. Failure can waste money, destroy morale, infuriate customers, damage reputations, harm careers, and sometimes lead to tragedy.

Failure is inevitable in uncertain environments, and, if managed well, it can be a very useful thing. In fact, organizations can't take the risks necessary for innovation and growth if they're not comfortable with the idea of failing.

As Columbia Business School professor Rita Gunther McGrath explains in "Failing by Design," in the April 2011 Harvard Business Review, the smart alternative to ignoring failure is to foster "intelligent failure." If your organization can adopt the concept of intelligent failure, it will become more agile, better at risk taking, and more adept at organizational learning.

Here are seven principles that can help your organization leverage learning from failure.

Principle 1: Decide what success and failure would look like before you launch an initiative.

People working on the same project often have entirely different views of what would constitute success. In one case, an organization that made environmental remediation equipment was hoping to introduce a new product line.

The marketing group thought the equipment's selling point was that it met a tough new regulatory standard. The engineering group thought the point was cost-effectiveness — and to keep costs down, it was designing out the very features the marketing group wanted to sell.

This gap in understanding could easily have led to a failure of the unintelligent variety. But the company found out about it in time to get everyone on the same page and prevent what could have been a marketplace disaster.

Principle 2: Convert assumptions into knowledge.

When you're tackling a fundamentally uncertain task, your initial assumptions are almost certain to be incorrect. Often the only way to arrive at better ones is to try things out.

You shouldn't start experimenting until you've made your assumptions explicit. W...