What do you do if cognitive biases are clouding your logical reasoning in Venture Capital?

Se ha venido incrementando la creacion de startup en el mercado, y para los inversionistas es cada vez mas complejo entender y visualizar estos proyectos, por lo que se requiere de olfato y un analisis detallado del mismo que permita apostar al crecimiento y estabilidad del proyecto y que permita garantizar además, el retorno de capital

Let´s talk abut "Halo Effect,". This occurs when an investor's overall impression of a company, its founders, or its product unduly influences their evaluation of specific characteristics or aspects. In other words, a positive trait in one area may create a bias that overlooks potential issues in other areas. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞: Theranos, a now-defunct health technology startup. Elizabeth Holmes (founder), was initially lauded for her vision of revolutionizing blood testing with a single drop of blood 🩸. Her charisma, coupled with an impressive board of directors, created a positive halo effect around the company, leading many investors to overlook the lack of transparency surrounding the technology. You know what happened next 📉.

Argue against yourself. And take notes. Wherever you are convinced this is a good investment or a bad one, make arguments against your position. The easiest way to do that is to have someone you respect that have the opposite position to yours. Hear his argument, understand it and reformulate it in good faith until he agree that you understood his point. This is also useful in any conversation. It's the most efficient way that I know of to make sure you don't miss the point of the opposite view.

Como actividad obligatoria en mi labor, está el escuchar todas las versiones a favor y en contra de las oportunidades de inversión. Analizar y contrastar los argumentos que se tienen de uno y otro bando para tomar decisiones. Partir siempre de la posición del riesgo que estoy asumiendo para prever con mayor certidumbre las posibilidades.

Awareness: Simply being aware of cognitive biases is the first step. Educate Yourself: Learn about various cognitive biases and how they manifest in decision-making. Seek Diverse Perspectives: Surround yourself with diverse voices and perspectives. Data-Driven Decision Making: Rely on data and evidence as much as possible in your decision-making process. Use Decision-Making Frameworks: Implement decision-making frameworks that help structure your thinking and reduce the influence of biases. Challenge Assumptions: Continuously question your assumptions and challenge conventional wisdom. Scenario Planning: Consider multiple scenarios and outcomes when evaluating investment opportunities.

No todos los analisis para tomar decisiones a la hora de invertir en un proyecto, se basan exclusivamente de analisis numericos, éstos tambien deben implicar un analisis detallado de riesgo pais, riesgo de mercado, analisis de la competencia, experiencia de los estructuradores, entre otros, que permitan dar tranquilidad al inversionista y asi, buscar el exito del proyecto.

Picture this: investors spot an early startup in a new, hot market (think treasury management in 2022) with a flashy initial valuation, and they get stuck on that number without considering other vital factors like market competition or potential growth, leading to an overestimation of growth potential. Conversely, they might underestimate another startup in a peripheral market. To tackle this bias, investors often need to take a step back and analyze the whole scenario. Delve into market trends and the startup's unique strengths - what is their 'moat', and how defensible is it? By doing so, they can avoid being too swayed by that flashy first number and possibly make better fundamental investment decisions in the sector.

𝐄𝐱𝐚𝐦𝐩𝐥𝐞: Let´s suppose an investor has recently experienced success with a SaaS company, and as a result, they are more inclined to invest in similar SaaS startups. This investor may overlook promising opportunities in other sectors, such as Fintech or Web3, simply because they are less familiar with these industries. In order to counteract availability bias, the investor should actively seek information about various sectors, evaluate opportunities using a systematic process, and consider the advice of experts in different fields. So, they will be able to make more informed investment decisions that are not unduly influenced by recent successes or widely publicized trends.

En este tipo de proyectos, se debe tener en cuenta un tiempo prudente de perdidas ocasionadas por el arranque del negocio. Estas perdidas son la curva de aprendizaje, ya que es el tiempo en el que el negocio se da a conocer, es el tiempo en que cautiva los potenciales clientes, es el tiempo en el que los consumidores prueban la efectividad del producto, y una vez se afiance el proyecto,. empieza a tener ingresos, muchos inversionistas no valoran éste tiempo crucial de perdidas, que yo en ocasiones lo muestro como una tiempo de aprendizaje y de crecimiento.

Similar to the fear of failure, loss aversion can hold you back significantly. In my opinion, Nobel laureates Daniel Kahneman and Amos Tversky, described the tendency to feel the pain of losses more intensely than the pleasure of gains already in the best way. This psychological quirk can significantly impact our decision-making. Imagine receiving a $100 bonus versus losing $100 – the emotional sting of the latter is likely stronger, influencing your choices in risk-taking scenarios.

Thorough due diligence is a key to countering overconfidence bias as an investor, especially for those investing in an angel or in a pre-seed round. All too often, investors I've spoken with are focused on following someone else's lead, rather than doing any due diligence themselves. By scrutinizing all aspects of a potential opportunity, investors may gain a balanced view, uncovering opportunities that they may have otherwise passed on. Seeking diverse perspectives and expertise during due diligence can also help challenge assumptions and reduces reliance on past judgments. Ultimately, a disciplined approach fosters humility and can equip investors to make more informed decisions, mitigating the impact of overconfidence bias.

Whatever the bias, relying on factual data, possibly helped by "unbiased" algorithms, is the best way to avoid many biases in VC. For example, the systematic use of a CRM provides a base of real-world comparables (BP, metrics, etc....) enabling a new dossier to be compared with its peers. Another classic bias among apprentice VCs is the strong desire to make their first deals, which can lead them to underestimate or even conceal potential redflags in order to get a deal through. This decision pays off in the long term, of course, making it all the more difficult to detect and minimize.