Lessons: 4 Aug 21

Eeshita Pande
2 min readAug 4, 2021

Simplicity vs. Complexity in Financial Modelling


Today, I was working on our internal financial model and thinking about how we would simplify it for investors. Off the bat, I recognised that (i) we need the detailed internal model with its functionality preserved for KPI tracking and (ii) anything we present externally has to derive from our internal model, be consistent with it, and be relatively straightforward to update.


My solution is to segment our internal tracking model into three distinct units: (i) Product Unit Economics (ii) High Level Financials (iii) User and Subscriber Cohorts Buildup. The interactions between product economics and subscriber cohorts outputs the high level financials.

This would involve taking a lot of the work we have already accomplished over the last few months and repurposing it into simple outputs. As we already have the core components of the specified units built up, it would be a matter of making sub-units more consistent with each other, demarcating the units more cleanly, creating some simpler outputs, and ensuring that it is easy to update and extract the data from our internal model in a relatively straightforward manner.


In startups, we often build components in a quick and dirty manner to validate hypotheses, test ideas, and understand key drivers. Continuing to build in this fashion is complex and requires deep domain knowledge to correctly model outcomes. However, these outputs are usually not understandable to an external audience. They require unpacking into simpler outputs, more generalised trends, and more understandable metrics. It is important to draw the distinction between internal tracking which should be as granular as business needs demand and external presentations which should start from a more basic position, building up according to investor needs.



Eeshita Pande

Founder & CEO at TheaAI. Interested in health, wellness, and longevity. Using AI to build health solutions.