Startup Selection and Machine Learning: It Is Sooner Than You Think
Whether you are a business angel or part of an accelerator or venture firm, filtering and selecting startups is something you have to routinely go through. It may be fun the first and second time. However, it becomes a burden on you or your firm as you go.
Another issue is whether the current selection criteria are optimal. Yes, it is more art than science, but in an area where the key players hide their approaches, defining the best practices is no easy job. Adding to that the numerous factors we can assess startups by team strength, competition, product, customer feedback, legal aspects, revenue, returns, … etc
So we have two main problems in the initial startup selection:
- Time consumption.
- Defining the optimal selection criteria.
Two problems that machine learning and automation may solve one day. The issue is how can we make machine learning define the best startups. How to define the next Google, Uber, or Facebook? A high level of uncertainty will always be in place.
This is why we can shift the question. We can shift from screening startups by defining the best, to ruling out the worst. This makes the opportunity for machine learning to aid and take care of the initial startup screening a matter of when. Rather than making the machine predict the future, we can simply make it select out the bad startups.
Machine Learning for Startup Survivability
The idea of ruling out startups by machine learning is not new. One research found that machine learning tools can be used to significantly increase the odds of success by measuring and lowering risk.
Another study on 255 angel investors found that machine learning algorithms beat angel investors in general, while the best angels may still outperform the algorithms. This is mostly because most professional investors can tune out and fall into their biases.
With a large amount of data available on startups worldwide, using machine learning in the selection process is not really this far. Some investment funds like Google Ventures already have it in place.
The aim is not to rely 100% on AI and machine learning. As mentioned, predicting the future will always have a high uncertainty level, which leaves space for subjectivity. The key is using the machine learning tools as a guide and not a sole decision-maker.
Hybrid Decision Making for Startup Screening
Hybrid decision-making is using both the human mind and AI to make key decisions. It offers a unique solution to the screening process. We can leave the part that can be optimized with high processing power to AI and focus our efforts and time on the parts where the human mind is needed the most.
The initial screening process involves many factors. This is the part where we see if the startup can endure in the real world. With far more reasons for a startup to fail than succeed, investors need to be careful and check out as many critical factors as they can. These factors include:
- Team background and strength
- Quality of idea
- Product strength
- Competition scene
- Expansion strategies
- Opportunity size
- Strategic relationships
- Legal factors
Each of the mentioned factors can have multiple aspects branching from it. In a pool of 100 or 1000 applied startups, the screening process becomes daunting and overwhelming for the human mind. Machine learning tools, on the other hand, can use the available data out there on startups to define the importance of these factors for survival, as well as measure the odds of survival for the applied startups.
Using the rank obtained from the AI, we can rule out the startups with the least chances of survivability and move forward to later stages with the remaining companies.
VeFund’s Survivability Index
Using hybrid decision-making to enhance the investment process is at the heart of VeFund’s mission. We want a future where the gap between investors and startups is reduced by enhancing the daunting investment process.
We created the first public machine learning tool to measure the survivability of startups. Whether you are an angel investor or an accelerator, your machine learning guide is available for immediate implementation.
VeFund’s survivability index is your easy-to-use tool to enhance your selection process. Join us and select your next investments with VeFund.
