Program design is about creating a program that includes the best-known motivation triggers based on science. The design most likely to get you results. The program design you would bet on if given that opportunity.

I did a webinar with two guys who run the Behavioral Grooves podcast and one of their past guests was Annie Duke – one of the winningest women poker players of all time and author the great book “Thinking in Bets.” That webinar experience made me revisit some of their podcasts and the one with Annie stuck with me. Again.

In the podcast Annie talks about decision quality and how we link decision quality to results. Meaning if you get a good result we therefore made a good decision. She called that “resulting”. While some decisions probably had some effect on the outcome, the results are probably because of a mélange of inputs – not just the few decisions you made. You can’t assume that because the results were good the decisions you made were good. Just like you can’t say that a program was designed correctly because it provided good results. That is resulting.

And I see that every day in my conversations with clients who want to run a program “just like the one that got great results.” Sure, it got great results. But how much to you believe (or know) the results were the direct outcome of the design decisions? Would you bet on it?

Annie explains how you can help your decision making by focusing on “accepting” – knowing not every result is the basis of your decision making and accepting it’s not a given. This is from an interview she did on the Nautilus website:

“That’s what accepting outcomes is like. Accepting that you don’t know if the coin will land heads or tails on the next flip. That means that if you offer me a $2-to-$1 gambling proposition on this coin, I should be willing to do that. Even if I lose the next 10 flips, that doesn’t mean that I made a bad decision. And I should strive to be happy that I made a good decision and not focus on the result. It’s a mindset thing.”

Design programs using the best data-driven information – not just the old “It worked last time so let’s reuse, recycle, rehash.”

Accept there is some luck in the system.

But bet on good, proven design elements not just the outcomes from previous programs. Review your decisions and see if they REALLY were the cause or just a happy accident.