How can data science teams inside businesses measure costs and efficiency of their technical work?
I don't know what you mean by &quot;measure and improve costs of their technical work&quot; - but I'll answer in response to the question &quot;how do you know how much value your insights are bringing the business&quot;:
To structure a successful project it is important to understand the baseline you are competing with. For example: let's say I have a timeseries forecasting problem where I'm forecasting how much cash will be in some corporate account. One baseline might be: &quot;let's assume that tomorrow's net cash flows will be identical to yesterday's&quot;. Now that you have this benchmark you can evaluate how performant your solution is relative to this.
This can give you insight: &quot;my solution outperforms the benchmark by some % and increases the detection of future overdraft fees by 90%&quot;. Convert this 90% improvement into the total # of new overdraft fees detected by your system relative to the baseline. This can be translated to some dollar amount on an annual basis - and you can say &quot;my solution saves the business $###,### annually&quot;
Understanding the system you are replacing allows you something to compare to and can track results. This is also an effective strategy for communicating successes to management (something that is vital in larger enterprises).