The VC industry is contracting with the capital under investment by VCs and the number of VCs - both declining - as well as the amount of money committed to VC firms. Healthcare focused VCs, despite having some strong opportunities, still have  challenges ahead with their portfolios.

Research by Shikhar Ghosh into 2,000 VCs found:

  • 30-40% return nothing to investors
  • 75% don’t return investor capital
  • 95% don’t achieve a specific growth rate or break even date

That suggests that it’s closer to 1 deal in 20 that returns a meaningful amount of money, and only 3 in 20 that return capital.

There has been a lot of news about software disrupting the VC industry but when you look into this, the software is just an automated version of the same thing already being done - linear analysis. So, VC firms would be able to reduce time doing what they are already doing, but they still won't get better results from their investment portfolio as it is essentially no change apart from automating what they already do.

This got me thinking about how powerfully Artificial Intelligence analytics could help VCs solve their challenges, whether their investments are early or late stage. This would be a far more powerful solution to the VC challenges as the actual outcomes (better win loss ratio, higher valuations, and quicker exits) for the VCs would be so much more powerful. Eularis Artificial Intelligence analytics can provide VCs with far more accurate answers to the following questions:

1. Pre-screening of potential investments:

    • Which company, or portfolio of companies, is the best to invest in for a high multiple and fast exit?
    • Which companies will be best to invest in to improve my win loss ratio?

2. Improving performance of existing investments:

    • How do I help my portfolio companies who are not doing well, turn themselves around and accelerate their growth?
    • What specific steps are needed to achieve a specific multiple on the investment?

Eularis work in Healthcare Artificial Intelligence analytics and can answer the questions above in addition to almost any question you can think of.  For example, if your investment is in vaccines, Eularis can use artificial intelligence to answer questions such as ‘What disease will be an epidemic in the next 5 years and what will be the magnitude of the epidemic?’ and so much more.

VCs currently have an in-house team to analyse these areas, and in examining this, the majority of them use assumptions, spreadsheets, linear statistics, and mathematics – and of course get poor results. 

Read the second half of my blog ‘Why Artificial Intelligence Crushes Linear’ here to understand why VC analyst teams, and even the automated software now available to do this (all linear approach based), are simply inferior and will not be able to provide VC firms with superior outcomes.

http://eularis.com/blog/eularis-main-blog/2016/03/07/why-artificial-intelligence-crushes-linear-approaches

So, the reason VCs are making poor decisions are achieving less investment - and poor results - is because they are using inferior methods to make their decisions. For more superior approaches using AI they should be speaking with Eularis. http://www.eularis.com