I recently attended a panel organized by the Polsky Center for Entrepreneurship and Innovation at the University of Chicago's Booth School of Business for a panel discussion focused on how venture capitalists make the decision to invest in early stage companies.

The panel:

(1) Moderator: Eric Schurenberg, Inc. Magazine
(2) Steve Kaplan, Distinguished Neubauer Family Professor of Entrepreneurship and Finance at Booth, the Polsky Center's Faculty Director, research associate at National Bureau of Economic Research (NBER)
(3) Keith Crandell, co-founder and a managing director of ARCH Venture Partners
(4) Ira Weiss, Faculty Director of Hyde Park Angels, an angel investing group
(5) Kevin Miller, Partner at Chicago Ventures

Here's some of my key take-away points that should be of interest to individuals at the very early stages of developing at start-up.

(1) What are investors actually relying upon?

There are two inter-related yet distinct questions:

• The descriptive question: what do venture capitalists rely upon when making their investment decisions;
• The normative question: what should venture capitalists rely upon when making their decisions.

Aside: why both descriptive and normative elements are crucial for both parties

Lest I be accused of trying to highlight ways to take advantage of potential biases in investors, I feel that it is necessary to include this caveat and consider the importance of both these questions for both parties.

First, we must clarify: the normative question here is answered by solely in terms of predictive accuracy:

By predictive accuracy, I mean: if we can categorize the information available to the investor at the decision point:

• what information should we use?
• what should be the optimal relative weighting of these different pieces of information?
• what combination of inputs and weights produces the best prediction scheme for selecting successful startups?

So, for this discussion, lets leave theoretical or ideological commitments at the door for a moment. Lets just agree that if a piece of information is predictive, the investor ought to use it, even if she cannot verbalize or justify its use (of course, there are caveats to how far you should take this).

Having described the normative questions in terms of predictive accuracy for the investor, it might initially seem that - from the point of view of the entrepreneur seeking funding - the descriptive question is the proper target of interest. After all, you really want to know how you can position yourself in a manner that accounts for the investors' decision processes, leverages any predictable biases in their process, and increases the likelihood of getting your idea funded.

However, it quickly should become clear that the normative question is even more crucial for the entrepreneur. Lost time, energy, and hope is precious!

If you do not meet the normative standards, by definition, you are missing key elements that increase the likelihood that your endeavor will succeed. This should give you pause.

The goal here should not be to "game the system" and focus on getting funding by leveraging potential biases in VC investors. If you succeed in getting funding that you objectively should not have gotten, you are simply delaying the inevitable and suffering enormous opportunity costs - fail early, fail fast!

Money is cheap, especially when compared with potential damages inflicted upon your conviction, resolve, expertise, and reputation by willfully, blindly, and stubbornly pursuing a bad idea.

On that note, I can end my caveat: This is not a post on how to game the system! Even if it was, I strongly discourage you from doing so! You have been warned!

Descriptive Question: Empirical / Observational data Examining the Decision Process of VCs

First, lets begin with actual data collected and analyzed by Steve Kaplan (Booth, NBER) and his colleagues Paul Gompers (Harvard Business School, NBER), Will Gornall (Sauder School of Business), and Ilya A. Strebulaev (Stanford - GSB; NBER) in their recent paper:

How Do Venture Capitalists Make Decisions?
(last revised on 17 May 2017)

By administering a survey to 885 institutional venture capitalists at 681 firms, they tried to learn how the investors makes decisions in 8 areas: deal sourcing; investment decisions; valuation; deal structure; post-investment value-added; exits; internal organization of firms; and relationships with limited partners.

Based on panel discussion with Steve Kaplan (one of the core authors on the paper), it was clear that they found overwhelming evidence that in selecting investments the VCs prioritized the management team as more important than the business characteristics such as product or technology. This belief was supported by their attribution of success or failure to the quality of the startup. So, essentially, venture capitalists appear to be betting mostly on people because they think people determine the success or failure.

The panel of venture capitalists almost uniformly agreed with the exception of Keith Crandell, who was investing in early stage research from natural sciences / biotechnology and was more than happy to slap on an a A-grade management team to get a good idea of the ground.

What are they looking for in the team?

Almost uniformly, one of the major things they wanted to see was either: (a) "experience or expertise" in the domain OR (b) previous entrepreneurial experience. So, they wanted to be sure you either really knew the domain-specific problem space well or you really knew startup-specific problem space. From their point of view, they are trying to make a determination with the goal of increased value and a clear source of liquidity to allow exit.

*Most of them confidently agreed that - in order to receive funding - one (and, ideally both) of these two criteria must be met. * They also pointed out that - as VCs, they see lots of ideas, but expertise and experts are rare, almost by definition. So, the perception of expertise is really essential.

Is it really in the team: The (Untested) Pivot Hypothesis

However, Steve Kaplan - speaking from the position of empirical research - seemed to question whether the success or failure of companies actually had as much to do with the startup team and its past experience. To be clear, he is not saying the quality of management does not matter (see his other research).

It seems that much of this idea has come along as part of the "lean startup" craze. There have been other arguments put forth criticizing the lean-startup methodology. But, for the sake of the current discussion, the reasoning seems to be: early companies rarely bring the original idea to market. They must be fresh, lean, dynamic, and adaptable. In a word, they must be able to PIVOT.

Steve Kaplan cited data suggesting that the vast majority of start-ups that "truly made it" still have the same core business concept as Fortune 500s that they did as startups in a garage. Amazon sold books online. Google had a search algorithm. Uber helps you hail a cab. Airbnb helps you rent apartments. At this point, the VCs pointed to Twitter, Groupon, and Slack as examples of pivots. However, the difficulty they had in coming up with examples of "pivots" seems to suggest that its occurrence may be overestimated. In addition, despite some high profiles cases like Google or Facebook, most founders do not remain part of the company as it grows.

In fact, success seems to come down to really getting your product and marketplace nailed down. The horse seems to matter more than VCs may be acknowledging because they too focused on ensuring its ridden by the right jockey. And, the horse rarely changes form as dramatically as the pivot theory would suggest.

Compensating for Lack of Experience: Signalling

As is often the case, there are bring, talented, motivated entrepreneurs that enter a new marketplace with no previous entrepreneurial experience. If that is you, the above description may have left you feeling disheartened.

Here, some perception management becomes important. You have to signal to the VCs that the information they are getting from "past experience" can also be derived from your other actions.

Some of the things that the VC investors on the panel identified:

Bootstraps

They seemed to be particularly impressed by teams that pulled themselves up through the early patch by bootstrapping. This sends some obvious and clear signals. It signals something about your commitment / conviction towards the company. This is essential. It also signals that you are capable of managing internal cash flow and can show the caution necessary to ensure your expenses dont outstrip your capacity to stay afloat. Essentially, it appears that bootstrapping counts as "entrepreneurial experience." It also makes the firm attractive because it attests to the firms' survival abilities.

Accelerator / Grants

They also seemed to think that - if you really need the funds right away - approaching accelerators would be the right way to go. It bought allows them reassurance that you have been vetted by someone else and it has given you some runway to get closer to your MVC. It is also essential to explicitly acknowledge your stage of development and approach funds in the ecosystem that are focused on that particular portion of the lifecycle. VCs push companies between stages in the pipeline. Connecting with the right people ensures your hand-off also goes smoothly down the road as you grow.

Advisory Board

Another way to compensate for expertise, especially domain-specific expertise is to gather at least as few committed, experienced, and hopefully well-renowned experts to serve on your advisory board. However, it should be clear that any VC worth their salt will actually contact your advisory board. In essence, they are co-signing to overcome the "credibility gap" that results from a lack of industry experience.

Traction

The most fool-proof approach sounds obvious: get traction. Get users. Get people excited about what they are seeing. This is the ultimate solution to the lack-of-experience dilemma. That completely compensates for any lack of experience or limited expertise. Bootstrapping and traction gives the entrepreneur much needed leverage with the VC.

The Ask as a Signal

Building of that last point, finally, the VCs know: "the best of the best are not coming knocking on your door begging for money." See point above about bootstrapping / traction. Once you have done that, the VCs are coming knocking.

However, more generally, your "ask" should reflect the fact that you are not looking for just "any money." You are trying to determine "who is the best investment firm that can help me grow? what do they bring to the table? how can they help with talent needs?" Approach the problem as though you are looking for the right fit, not just any one who will accept you.

Regional Variation

At the end of the panel, there was discussion about startup locations and the impact on the VC environment. Although their appeared to be general theoretical consensus that a tech-firm can be based out of anywhere, the VCs tend to lean towards local investments and tend to absorb the local cultural values of their fund members. As a broad generalization, the panel suggested that VCs in the Bay Area put less emphasis on immediate revenue stream. They are more willing to burn cash while a revenue model is being conjured. On the flip side, they would not be happy with 3-20x returns. VCs in the midwest tend to emphasize revenue and insist that your idea has a marketplace. This may not actually be a bad thing: the constraint might force people to put their minds to developing a product, consumer base, and a concrete business plan to move towards self-sufficiency. These funds are also more willing to support "local companies" and consider 3-20x to be a perfectly good outcome.