Part 7 in 8 part series - Separating the Wheat from the Chaff
Blending Inputs Into a System with Feedback Loops in designing and implementing metrics that matter
Part 7 in 8 part series - Separating the Wheat from the Chaff
Author
Jonathan Neitzell
Jonathan Neitzell
Founder, Managing Partner, Anduril Partners

Part 7 of 8

What to Do with all the KPIs?
Anduril Partners and Equity Data Science (EDS)
Source: Anduril Partners and Equity Data Science (EDS)

How do we blend all these inputs of different types into a system with feedback loops?

Using financial services as an example in the diagram above, “What to Do With All the KPIs,” this “Tower of Babel” of decisions on inputs will not scale using Excel and Powerpoint. The difficulty is that data comes from different sources, speaking languages including near-term and long-term fundamental business model KPIs, technology requirements, math and data science integrity, historical and peer valuation, and risk factor influences.

There are several critical challenges here:

  1. These inputs are like trying to compare apples, oranges, and pears.
  2. Per our example on the horse races, academic research shows after a certain level of inputs, analysts flatline their predictive ability (overwhelmed).
  3. There are almost no transparent or consistent feedback loops without a software system for tracking and monitoring.

We love to talk about ML/AI opportunities, but those don’t exist until one has the data in a system with feedback loops.

Read another article in this 8 part series:

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