The uniqueness of early-stage investors
What entrepreneurs should know about the distinctive thinking of investors in early-stage startups and factors they weigh when making investment decisions. Startup investment is a skill that is learned by doing; it is acquired by making multiple investments, many of which ‘go’ south, some that are missed opportunities (the deals the investor didn’t invest in and they become big), and few that succeed.
A mental model is an image of the world that we carry in our heads. It influences how we look at the world — what we see and notice, what we hear and listen to, how we think and interpret, how we decide what to do and how we behave. Our view of the world, of ourselves, of our capabilities, depends heavily on our mental models that are formed based on our ideas, beliefs, and past experiences.
Mental models are both like a ‘lens’ and a ‘toolbox’ to see, understand, and interpret a complex world.
Mental Models edit what we see by framing what we look at. Mental Models influence how we understand and interpret the edited data and information. Looking at new information is akin to looking at a jigsaw puzzle piece; looking at an individual piece of a jigsaw doesn’t understand how the pieces fit together. To complete the jigsaw, we need to understand each component in a relationship with a complementary piece. When we attempt to understand new ideas, information, and observations, we juxtapose them in the context of other existing ideas.
Early-stage investors are different.
Early-stage investors bring a unique ability to startup investing. And investors who have been entrepreneurs have the ability to identify early-stage investments.
They enter meetings with entrepreneurs with no preconceived ideas, even if they have read a pitch deck and may have experience in the domain. They know they don’t ‘have’ all the answers. They have learned in their entrepreneurial journey that opportunities emerge during execution, there are no prescriptive answers to business problems, and that many solutions are viable. And contrarian and quirky ideas are sometimes made to work by tenacious entrepreneurs.
They are adept at developing their thinking as they listen.
They are open-minded and objective, excellent listeners, and adept at helping founders develop their thinking. They know that entrepreneurs are engaged with their customers (startups with revenue and traction), aware of their challenges, and are trying to build their solutions.
They are self-aware that their role as investors is to redirect the entrepreneurial team’s thinking to discover answers.
Their entrepreneurial journey has made them adept at recognizing patterns. Yet, they know that pattern recognition is also a problem. Nothing ever happens the same way. They know that entrepreneurs dream of new ideas, they may be seeing something that others are missing, and what has worked in an earlier time and context can work in an entirely different way in the future. Openness to discover, learn, and adapt/grow helps in building startups. The real IP of a startup is ‘Implemented Learning’. A uniqueness of a startup that a new competitor may find difficult to create. Innovation (IP) is buried in the granular details of execution.
The limitation of ‘patterns’ (reaching conclusions too quickly) is that it may attribute 70–80% of the answers. And 80% is not a win. The real value may lie in the 20% unknown of going against conventional thinking.
This requires stepping back from their mental chatter. And looking at the following formula for decision making in the absence of data.
Probability of startup success = who X what X where X how
- Who — is the founder? Investors know that a good market and the right founding team can evolve into the right business model; the idea of founder-market fit.
2. What — is the founder trying to do? The size of the prize.
3. Where — the domain in which the startup is working. Is it a significant industry problem to solve (in the top 3 needs/wish list of customers)? And does the entrepreneur’s way of thinking and psychology make it winnable? Is the startup solving logistical complexity in the industry? Investors get an intuitive benchmark of product and category strength/influence.
4. How — is the team going to do it? Is their go-to-market strategy capital intensive to validate and scale? The quality of early traction is an indicator of the mindset of the founding team. How much focus do they have on customer acquisition and retention/engagement, evoking customer loyalty, and activating customer advocacy? Customer advocacy endows customer growth with natural momentum. Investors want a startup team to show that they visualize each customer as an asset (perpetuity) with a lifetime value. And for them, marketing is an investment with a measurable ROI. Entrepreneurs must show growth focused on ROI, balancing innovation, and efficiencies, a contrarian idea in a capital constraint situation most startups face.
5. How — risky is the journey? The gross margin of an early-stage startup is a good surrogate of the risk of a new venture. Margin gives an entrepreneur a buffer to take risks when creating a scalable business model.
6. How — and where will data be generated and captured by the startup? How will data create value in the startup? Even if the entrepreneur has only fuzzy ideas at an early stage. Will the business be able to develop systems of intelligence based on analytics using data? The above diagram is a good depiction of how the use of data and competitiveness derived from it is changing, from digitization as business hygiene to data (intelligence) as a competitive capability that delivers revenue streams.
7. How — Will the startup be able to develop a deep, sticky relationship with customers using data, and will the network of customers endow the startup with an advantage (potential of network effects)? Entrepreneurs who focus on nurturing customer communities (systems of engagement) as a growth engine, will be able to stand out and be noticed.
