Do we still need tombstone plaques today?

Tombstone plaques are part of the private equity culture[1]. They symbolise the success of an investment team in closing a deal or achieving a targeted fundraise. It is a form of signalling by investors to investee companies, teams, and peers that they are backable. Tombstone plaques are the physical assets that capture a moment in time.

Digitisation begs us to question if the time has come for us to leave tombstones plaques behind and transition to a real-time equivalent more relevant to our times: decentralised community review systems. We believe that these systems, especially when enhanced with artificial intelligence (AI) and machine learning are a far better signal of an investment team’s credibility and promise than those outdated plaques collecting dust on a boardroom shelf.

What goes into a fundraise?

Before we discuss the potential benefits of decentralized reviews, let’s first take some time to understand what investors are looking for when allocating their money. In general, investor support is awarded to investment teams with the potential to meet or surpass performance expectations. That decision is usually made by vis-à-vis opinions that the investor forms after reviewing several data points. Some data point tends to be linked to the investment opportunity itself: a current or emerging sector or country dislocation. Other data points are linked to the investment team and their ability to capitalise on such dislocation. The right dosage of an emerging dislocation, along with an available team and investor mix, increases the velocity and scale of commitments to be awarded and, subsequently, the probability of attaining the traditional tombstone plaque.

One of the key responsibilities that fall on the investor’s shoulders is to seek social proof of the investment team through peers comprising previous investors, previous funds, investee companies, and other industry stakeholders. This task is usually done in the traditional sense of telephone and email exchanges between parties, sometimes involving different time zones. Existing time resources become even more constrained, not to mention the capacity of the human brain is limited in analysing all the unorganised information that is received at any one time and subsequently identifying patterns using below-the-surface data. This is a truly important point to explore. The human brain is limited to precisely 126 bits of information per second[2],  which means one’s ability to fully understand another in discussions is limited to data received from two people at the same time; try three and you are overloading. In our daily work lives, we are constantly bombarded with data. What we believe we know is not always what we are able to recall or process, most of the time. Humans, given our limitation, miss a lot of detailed information and thus are impaired when attempting pattern recognition. The truth is that much of reality is invisible[3]. Bearing this in mind, AI and machine-learning techniques can have a strong role to play in supporting investors in discovering who within their universe would be a great investment partner for them.

Decentralising peer reviews

One application of AI in particular that should be considered more closely is the use of decentralised peer reviews. Such review systems can add value to investors by shortening the time spent in seeking reviews the traditional way. For investment teams, the continuous visible acknowledgement from peers can not only help reinforce the team’s capabilities; it also introduces further transparency. Decentralised community review systems have proven to be both rewarding for buyers (investors) and sellers (investment teams; start-up founders) alike in a community and have been used across industries in different ways. 92.4% of B2B buyers surveyed by Heinz Marketing and G2 revealed they are more likely to buy into a product or service if they read a trusted review[4]—even more so if that review was recent. Employing an artificial intelligence system with accurate industry-specific labelling and machine-learning techniques within a decentralized review system would synthesise data points faster, escalate pattern recognition, and help an investor achieve her goal of social-proofing investment teams faster, in real time, with insights deeper than what is seen by human capabilities alone.

Perhaps, it's time to retire those tombstone plaques for good.

[1] By Private Equity culture we mean the encompassing private asset segment

[2] Mihaly Csikszentmihalyi, Flow: The Psychology of Optimal Excellence, 1990, 2008

[3] Steven Kotler, The Art of Impossible, 2021

[4] The Impact of Reviews on B2B Buyers and Sellers https://learn.g2.com/hubfs/Sell%20Microsite%20Files/The%20Impact%20of%20Reviews%20on%20B2B%20-%20Report.pdf