Securing venture funding is a hard-hitting goal for most startups globally: less than 1% successfully obtain such backing. Ironically, many of these overlooked ventures harbor immense potential, far surpassing yet another CRM or AI generator.

This is because venture capitalists' decisions are often clouded by stereotypes and biases that, in our experience, tend to boil down to three main issues. Today, we will describe these issues and ways to address them.

👉 Even venture capital investors avoid venturing in favor of the familiar

Investors often play it safe, sticking to the information that aligns with their existing beliefs. They have a knack for gravitating towards people who mirror their own background and experience, sometimes overlooking those who bring fresh perspectives to the table.

This primarily affects inexperienced, solo investors but even seasoned ones often cling to their initial impressions, making it hard to change their minds even when new data rolls out. 

Of course, these biases hurt entrepreneurs who are not part of the business mainstream: even in the US, companies led by women receive less than 3% of venture money, echoing challenges faced by non-white founders. And it's not just founders who feel the pinch; investors are also missing out on potential goldmines. Research shows that teams with diverse gender and ethnic backgrounds generate 30% higher returns on investment than their cookie-cutter counterparts.

👉 Tunnel vision makes investors miss the forest for the trees

Venture capitalists are always in a hurry (yes, we're guilty of some serious FOMO). This leads to a rush to what's right in front of us — a fixation on the obvious and the hyped. 

Image: PrayingForExits on Instagram

We're drawn to founders who dominate conversations at parties and grace the pages of the media. We chase projects that mirror Uber and ChatGPT. As a result, most opportunities remain in the shadows, while popular ideas and teams don't get proper validation (Theranos, rest in peace).

Let us sign up after the words of Mark Buffington, CEO of BIP Capital. (Image: Mark's article on Linkedin)

Investors' hyperfocus on zeroing small risks while neglecting larger, more consequential risks is another pitfall of this tunnel vision. 

👉 Both data overload and fear of admitting failure cause decision paralysis

By definition, entering the venture world involves risk and uncertainty — after all, it's the power law at work. Yet many investors fall into the trap of overconfidence, relying too much on gut instinct and ignoring valuable data. They continue to pour money into projects that have turned into black holes.

The fear of admitting defeat and accepting an irretrievable loss is so overbearing that investors often convince themselves that success is just a few hundred thousand dollars away.

At the other end of the spectrum, we find shaky venture players who endlessly seek more data before making a move. But overaccumulating info doesn't necessarily eliminate errors — in fact, researchers suggest that it only increases confidence in the accuracy, not accuracy itself. Eventually, this quest for more and more data becomes not only pointless but harmful, leaving such investors behind in the race.

🤔 How to tackle these biases 

Acknowledging the bias is almost like overcoming it, but let's face it — fighting the subconscious is not easy in the hustle and bustle of everyday life.

So here's what you can do:

1. Raise awareness: Keep an eye out for stereotypes and biases in your area, and don't hesitate to speak up when you spot them.
2.  Embrace data: Base your decisions on hard facts rather than emotions or persuasive rhetoric, even if it comes from trusted sources. But don't wait indefinitely for the data to make the decision for you.
3. Take the long view: Look beyond the hype or one-off successes and consider historical data.
   
4. Diversify your network and seek input from other investors. Consider working in syndicates for more pro opinions.
   

And here's a bit of wisdom from Matthew Burris, a partner at Savvy Tinkers Studios: (1) develop a learning mindset, (2) recognize that your ideas aren't flawless from the get-go, (3) actively seek out information that contradicts your beliefs. 

Image: Matthew's account on Linkedin

Also, the evolution of technology might be the key to combating biases. Yes, the same AI models are trained on biased data (check out Serhat Pala's experiment with generating portraits of angel investors) — but at least they can provide enough analytics to prevent, for example, favoring one founder over another simply because of a shared alma mater.

Cover image: Unsplash