Why Financial Planning Is Exciting at Least for a Data Scientist

eng.uber.com

28 points·eaguyhn··2 comments

I'm always surprised at the lack of interest in modelling business processes here on HN.

This blog post from Uber is a case in point: 19 hours after posting, there are still zero comments.

When I started my career 25 years ago, I was a junior management consultant and often had to model the impact of the major corporate changes we proposed to our clients. One example I remember well was figuring out how a bunch of reengineering initiatives would change the work done across a network of 1000 retail bank branches. I built an Excel model that figured out branch-level workloads, proposed changes to the number and function of branches, and then presented the personnel, real estate and operational cost impact...

I am sometimes curious how these types of models would be built today. My natural assumption (as a data scientist) would be use Python in a Jupyter notebook to do it all. However, my attempts at web searches for examples of business modelling techniques never return anything relevant.

Maybe someone reading this (from BCG/McKinsey/Pwc/etc?) can explain how they model the impacts of large scale business change?

It really depends on the business model. There are some tools out there for some financial forecasting, but IMO, most are too specialized to do what you’re referring. Ultimately, things haven’t changed much. Most large corporations are still using these excel models to do the exact same thing.

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