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How to succeed at failure

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Two hikers encounter a hungry bear in the woods, the old joke goes. The bear clearly means business, which prompts one hiker to turn to run away. The other hiker, drawing upon conventional wisdom, reminds his departing companion that running is futile. No one can outrun a bear. Without pausing a step, the fleeing hiker responds, “I don’t need to outrun the bear, I just need to outrun you.”

The joke works on a lot of levels besides providing a few yuks. It illustrates, for example, that data is only valuable when applied in the proper context.

Invoking the predatory response in an animal that clocks 35 miles per hour is indeed ill-advised unless, perhaps, you are accompanied by a second — and slower-running — data point. Conversely, you don’t wish to fall prey to survivorship bias. Fleeing permitted the first hiker to survive. But blindly applying his “model for success” without regard for its original context is also a losing strategy.

The point is that focusing only on past successes offers an incomplete roadmap to future achievement. Errors and failures also provide vital context, and industries that apply a systematic and open methodology for self-criticism tend to achieve more predictable wins.

Contrast the fatal error rates between health care and aviation. A 2013 analysis published in the Journal of Patient Safety estimated that medical errors contribute to the deaths of at least 210,000 patients per year. Our culture has come to accept this ratio of fatal errors in a practice dealing daily with sickness and death. But that number equates to ten 747 jets crashing every week — an error rate that would decimate air travel.

How does the aviation industry minimize error? Through routine, comprehensive, and objective self-analysis of every accident and failure. Even the data from near misses is scrutinized and shared transparently across the industry in a standardized process. Contrast this to health care’s closed system, which lacks a comprehensive methodology for gathering or sharing data on errors.

The photonics industry spans these two industry models. While new technologies emerge from the lab in a peer-review process that invites challenges and criticism, the business of photonics operates on keeping data proprietary and competitive. Trial and error is implicit at either end of the industry. But only one end leverages error to build future success.

Many of the articles pitched to Photonics Spectra highlight a commercial technology as though it were the natural and exclusive solution to a host of problems. Limitations of the technology are rarely mentioned, nor are the trials and errors that went into its development. I don’t expect contributors to dwell on the failures they learned from. But I do encourage them to share where their challenges remain. What is the limit of their knowledge? What barriers bar further advancements? How could their success be extended, “if only…”?

Everybody loves sharing their success stories. But this is an industry of problem-solvers. Contributors with the courage and finesse to talk about the limits of their successes might find a sympathetic and helpful audience. Readers might even offer solutions that would lead to new successes.

Photonics Spectra
Sep 2021

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