Packaging the solution
We now have a model in place that gives us relatively good accuracy. As a ballpark figure, we can say that we achieved an overall 75% accuracy with a TPR of 70% and TNR of 75% (scope exists to improve this further).
How does it add up to the use case's revenue story? With our model in place, we can say that we will correctly predict a power outage 7 out of 10 times. So we have saved the losses that happen because of power outages by 70%. Now, we also incorrectly predicted a power outage when it wasn't, that is, approximately 2.5 out of 10 times. Let's say that there was a cost associated with stocking diesel when it was predicted that the next day will be having power outages; this cost will tax the losses saved from the ...
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