Value creation in PE leveraging data science and machine learning

I work at a PE firm that specialises in investing into businesses where we feel there is an edge in developing data science and machine learning solutions to drive value creation. We have seen some good initial success through A/B testing for our new investments, though its too early to directly translate this into improved financial performance.

I was curious to hear how firms across the spectrum (geography, fund size, sector focus) are pursuing this, if at all? For example, this might include inventory optimisation through demand forecasting or optimising where to build new drive-through locations for a drive-through chain etc. 

How are your firms actually integrating data science and machine learning within your portco's?

11 Comments
 

I was curious as to what firms are doing, particular outside the megafunds who have (or are building) their own DS teams. I do believe they lack the scale to truly make an impact across all their portco's given the small DS headcount relative to portfolio size. 

For LMM/UMM firms I was wondering if they're outsourcing their work to MBB DS teams like QB or BCG Gamma etc?

Do you know what Warburg have done and on what scale? Is their approach to build their own DS team or are they outsourcing?

 

I believe they are building their own team. I talked with the person leading those efforts there ( networking to get a job lol) but got into what value creation was and what they were doing. I believe there are consultants hired externally as well. Got ghosted however :S

 

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