Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
The 11:30 Rule for Data Science
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"The show doesn't go on because it's ready; it goes on because it's 11:30." - Lorne Michaels, creator of Saturday Night Live. Data scientists can learn a lot from Saturday Night Live. SNL has a rule: The show goes on at 11:30. Not when it’s perfect. Many years ago, I was responsible for performing the annual workcover premium rate calculation for the whole of Victoria. It was a calculation of the utmost importance - $2b in revenue depended on it and once the results were published, they couldn’t be changed. No pressure there at all. The biggest problem? A key input to the calculation was employer remuneration for the coming 12 months, as estimated by the employers themselves, with updated estimates flowing in each day while the calculation was taking place. If we performed the calculation too early, we could miss out on a vital update with significant implications for accuracy. If we waited too long, we would miss the premium rate publication cut-off date and our calculations would be worth nothing. Our solution? We set a deadline and stuck to it. We did the best we could with what we had up to that point. Once we reached the deadline, that was it. Our best would have to be good enough (something our stakeholders agreed to in advance). We used this approach year after year. And sometimes data did come in after our deadline that would have changed our results. We had to live with that. But the alternative - missing publication deadlines and jeopardising $2b in revenue - would have been far, far worse. Here’s the thing… It’s easy to fall into the trap of chasing perfection - constantly pursuing that extra 1% accuracy gain or fixing edge cases that affect 0.1% of your data. But if you start down that path, you soon discover it’s a path with no end. There’s always another improvement to make - meanwhile, your stakeholders can’t make the decisions they need to make. A decision made with good enough data beats a perfect analysis that arrives too late. Set your deadline first, then plan your work backwards from there. Keep stakeholders informed, but don’t let perfect become the enemy of good. To paraphrase Lorne Michaels, creator of SNL: “Your analysis isn’t done when it’s flawless; it’s done when the deadline hits.” Set your “11:30” and stick to it. Your stakeholders are waiting. Talk again soon, Dr Genevieve Hayes |
Data Science Impact Algorithm
Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
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