This is a sample Blackbook Ideas Content.
The Blackbook Ideas are personal notes about systems that are not efficient and have cracks. The cracks can potentially be a matter of a solution that hasn’t been streamlined yet, or a far more systemic issue that could lead to a opportunity. The reader is requested to think about, debate and decide on the way forward.
The way we evaluate startups today is relative than absolute — that skews the system in the favor of investors than those creating value, i.e. the founders.
One of the questions that I get asked often about is about fundraising. An entrepreneur has a startup idea and is trying to scope out how to go about raising funds and what their strategy should be. Having met enough startups over the past 14+ years, I know what they are expecting is a checklist — like how a loan application is filled out; have x, y, z documents attached, and if you fulfill all these criteria then hooray you get funded. But ask any entrepreneur who has raised money and they’ll tell you it isn’t like that.
Venture Capitalists raise funds — and what the goal is, is to balance and manage a portfolio level profitability. All the bets are tactics, not strategy.
When the Managing Partners of a fund come together and make a plan — they have to identify the opportunity (called the investment thesis) and the plan as to how they will find these opportunities (dealflow pipeline), and what the ticket size will be (bet size), and how many companies they will fund. Contrary to popular belief, Venture Capital Funds have an elaborate fund model and fund economics sketched out to make the whole thing work — it is really not a series of random bets.
The amount of money, number of companies they would back etc is fixed early on — based on which the capital calls are agreed on (when the Limited partners from whom they raise money will give the money to them). For Investors this is important because if they raise money too soon and sit on it, it will affect their IRR — the key metric on which they are judged.
How does this affect Startups?
If the fund is looking to make two bets in the Retail Vertical — aligned to their investment thesis — then the associates will get started to scour every company in that space and create the master list. The goal then would be to set up meetings, calls and get as much information to do a ranking — and have a few of the top startups come and start doing partner presentations.
While Startup founders expect the process to be absolute — I have a great team, we are addressing a large opportunity, we have traction etc — the process is in fact relative.
So you could be #3 in the shortlist, based on how the partners and principals debate it out, and not make the cut — and that process isn’t obvious at all.
This is where luck becomes a factor, where it could be a time when there are very few good companies in the pipeline so you make it to the shortlist, or to your backluck the ecosystem is booming and there is a ton of good and really good choices to pick from.
How is the system broken?
Close-knit ecosystems like the valley leverage networks to achieve a predictable outcome (companies founded by ex employees often get acquired into the parent company).That sort of predictability doesn’t happen to most other ecosystems.
Tom Chi of Google, in an interview talks about what makes one product succeed and the other ones a bust — and he compares myspace, friendster and facebook and he gives the answer “better by a wee bit”. That sort of close difference can be very hard to evaluate — and can mean the difference between having a stake in a company that owns the market, or not.
Where can we go from here?
We pick teams with the best founders, with prior track record, chasing a big enough market, and some potential moat and let the market decide. This is where we are at right now.
There were some early discussions around creating a framework to predict outcomes. Chris Shipley the founder of the famous DEMO event, along with Mike Sigal create a framework called G/Score. The framework was created with the companies that they saw at DEMO that went on to become successful and crystalizing the parameters into a framework.
The G/SCORE measures companies on seven key factors of business execution providing concrete feedback on where the company is today and where it needs to go in order to build value into the business.
There are several attempts around this — The Wadhwani Foundation’s Venture Fast Track Program has a 12 point assessment method called Quantum Assessment that helps entrepreneurs understand where they are.
What the Future Could be :
There are roughly 11 risks that VCs evaluate for — and the reason why the evaluation process is so relative is because the assessment is qualitative.
The 11 Risks are legal risk, financial risk, venture management risk, platform risk, capitalization structure risk, technology risk, execution risk, business model risk, market risk (size, timing & adoption)
Founders still remain one of the big reasons why ventures fail — it isn’t easy to get opinionated founders to get along. Stats say that two founder startups are more geared towards success and on the other hand more than 60% of startups have co-founder issues. Even with single founder companies, not everyone transitions from an entrepreneur to a CEO very well — Mark Zuckerberg almost burnt it down, and so did Larry and Sergey. Today there are tools like Personality Mapping tools — at the least taking the Myers-Briggs personality test would help to know your strengths and weaknesses. For a bit more sophisticated analysis, tools like Predictive Index and Gallup exist — and from what I’ve understood of them, they seems like great tools to keep a pulse on executive dynamics even as the team expands beyond the founders. It’s just a matter of time before VCs will ask founders to do an evaluation — or even better, you proactively do it and attach it along with your pitch deck.
There is a opportunity to build a network with their PI profiles and match founders with complementary skill sets too.
Out of the 11, the four risks that are hard to evaluate are — execution risk and market (size, timing, adoption) risk. Execution risk can be mitigated with entrepreneurs with prior experience, but market is the big IF.
If there is a framework that can take inputs and pour through the vast amount of data — almost all big companies and emerging startups are indexed these days with lists like Tracxn, CB Insights etc — map entities (and have a sphere of influence based on size of operations) and market opportunities they are addressing, keep an eye on regulatory movements, global geopolitics etc, and arrive at a risk index, that would be one way to solve this in a big way. With trends like Open startups, there are just more transparent data emerging.
Could we leverage AI?
AI seemed fairly nascent when it could only play finite games — like Chess. But experiments like AlphaGo, and even real time strategy games like AlphaStar, means there could be a system that could help founders and executives assess the market — with the system running a large set of possible scenarios and give strategic advice and your odds.
This also means, there might be fewer companies — but then regulations + policies will kick in to balance in out, so not too worried on the economic and social balance there.
Investors today meet a lot of startups — and they have the vantage point of looking at the entire ecosystem, whereas entrepreneurs are perhaps looking at the incumbents and ignoring the scrappy startups that are out there to get the same piece of the pie that they are aiming for.
Every system that has thrived has made leaps and bounds when the system breaks information asymmetry.
Handing power back to Founders / creators seems to be systemically efficient and also will bring about capital efficiency, where investors don’t have to use capital as a moat to give a mediocre startup a leg up to squash a better solution. The market deserves better.
- There is an opportunity to build a network to find co-founders.
- Governments across the world look at entrepreneurs as the engines of growth — however there is a major chasm between what is a entrepreneurial mindset and a startup mindset. Tests that can help government agencies identify the right mindset and commit their (limited) resources to back the right entrepreneurs with the right resources will find takers.
- There is an opportunity to build a sophisticated market evaluation algorithm that can calculate the chances of your startup succeeding and give a regional, national and global ranking. (There is an opportunity to help small businesses too — thought : ask your kirana shop owner how he decided to setup that shop, in that area, in that street. There is zero intelligence backing that decision right now)
- Evolve the G/Score framework based on that metric.
- This will help startup founders to create a pull strategy where investors can make bids offering capital + resources, rather than the push model that currently exists.
Thanks to Amit Ranjan, Rajan Anandan, Ravi Kumar for reading early versions of this draft and for their honest feedback.
This post is put together from the bits and pieces of information that I had jotted down observing issues in the ecosystem and larger industry and wish for products and businesses that folks would build. If you’d like to be part of the weekly newsletter where I share more such industry opportunities, please subscribe.
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