The Importance of Overfitting in Simulations

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A simulation visualizes out this process where sometimes I think as analysts we don't get credit. Sometimes analysts don't fully understand the process themselves and so their analysis focuses on one aspect of it but misses other pieces. And maybe that's the that's where this can become a very powerful tool potentially then. Michael: Is there an idea of overfitting in building a simulation? So they all fit in. You mean having these at two perfects? Yeah, like where it like when you're doing a model, if it perfectly matches the training,. It's like too sensitive and then you put it with your test data and it's going to go kind of crazy.

When it comes to simulation, we're all really asking the same question: are we living in one? Alas! We did not tackle that on this episode. Instead, with Julie Hoyer as a guest co-host while Moe is on leave, we were joined by Frances Sneddon, the CTO of Simul8, to dig into some of the nuts and bolts of simulation as a tool for improving processes. It turns out that effectively putting simulations to use means focusing on some of the same foundational aspects of effectively using analytics, data science, or experimentation: clearly defining the problem, tapping into the domain experts to actually understand the process or scenario of focus, and applying some level of "art" to complement the science of the work! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.