Investor’s perspective: psychology of fundraising

“A compelling narrative fosters an illusion of inevitability.”
― Daniel Kahneman

Most successful investors in the world have a good understanding of common human (cognitive) biases. Cognitive biases are ‘hard-wired’ in us, and we are all liable to take shortcuts, oversimplify complex decisions and be overconfident in our decision-making process. Thanks to these (intuitive or experience-based) insights, investors have a significantly better understanding of investment opportunities (founding teams and their projects) and are able to systematically use these (behavioural) insights for better decision making, thus improving their investment odds.

There are three aspects for investors to consider in order to select only the best investment opportunities:

Identify and guard against biases in their own (investment-related) decision-making process
Identify biases [paste link to the entrepreneur’s perspective post here] entrepreneurs may use (in their materials/deck/pitching process) to gain a more favourable view of their projects
Identify and assess founders’ biases by observing how/what they pitch

Successful investor puts looks at opportunities via each set of lenses (from above three points) before deciding to invest.

1) Identify and guard against biases in their own decision-making process

Confirmation Bias + Loss Aversion. What is it: This is the tendency for people to favor information that confirms their preconceptions regardless of whether that information is true or complete. When layered in with Loss Aversion, it creates a deadly combination. How to defend against it: Because an investor is averse to losses, he is biased against any data that suggests that the initial investment decision was a mistake and will gravitate towards information that supports a follow-on investment. Confirmation-trapped people often seek out others who have made, and are still making, the same mistake.
Risk Seeking. What is it: Even if a company is really struggling, the following logic is very appealing: wouldn’t an investor be willing to spend $2M to save the last $8M he has already invested? Because investors usually buy preferred stock, they get paid first and so they only need the company to sell for the value of the preferred stock to get their money back. How to defend against it: As a result, you often see struggling companies raise inside rounds under this logic (often crushing employees’ equity in the process). Basically, investors avoid risk when their portfolios are performing well and could bear more, and they seek risk when their portfolios are floundering and don’t need more exposure to possible losses. This is largely due to the mentality of winning it all back. Investors are willing to raise the stakes to “reclaim” capital, but not to create more capital.

Other impactful biases include:

Delayed gratification (pressure to show immediate results)
Sunk cost trap (feeling lasting attachment to costs that cannot be recovered)
Oversimplification tendency (tendency to stay within your ‘circle of competence’ even when it is clearly counterproductive or destructive)

2) Identify biases founders use to gain more favourable view of their projects

As mentioned in the article, top biases that founders may deliberately use to gain more favourable view of their pitch and project are narrative bias (storytelling in deck and pitching), clustering illusion (that causes investors to observe appealing clusters of information and credentials), confirmation bias (founder shows the ‘right’ structure and contents to investors), pro-innovation bias (investors like to see innovative features and products), halo effect (founders show, via storytelling and credentials, a positive and likeable image or treat of themselves or their product, aiming for investors to think that the overall product and team are as good), zero-risk effect (founders pre-emptively show there are no risks or all potential risks are mitigated) and distinction bias (founders like to deliberately compare their product to one that is much inferior, thus highlighting the benefits).

3) Identify and assess founders’ biases by observing their pitch

Anchoring Trap. What is it: We can be excessively influenced by a starting point or first impression. Psychologists have shown that when people make quantitative estimates, their estimates may be heavily influenced by previous values of the item. For example, it is not an accident that a used-car salesman always starts negotiating with a high price and then works down. The salesman is trying to get the consumer anchored on the high price so that when he offers a lower price, the consumer will estimate that the lower price represents a good value. Anchoring can cause investors to under-react to new information. How to defend against it: In order to avoid this trap, an investor needs to remain flexible in his thinking and open to new sources of information, while understanding the reality that any company can be here today and gone tomorrow.
False Causality Bias. What is it: Many times, we falsely assume when two events occur together that one event must have caused the other. For example, founders are prone to show and quickly get credit for their previous success (exit or company sale). However upon careful analysis of the stated “success” (which a founder assumes to repeat with this new project) may show a confluence of external factors (such as technological development, favourable legislation, government support, etc), good timing and pure luck that were more important in the stated success. PayPal and Amazon are great examples, and founders of both are very careful not to claim full credit, but deliberate on more salient factors that weren’t in their control and how the sum total of their grit, perseverance and external factors helped in their eventual success. How to defend against it: Investors need to hear out founders’ stories but also conduct a thorough analysis of the context in which the previous success of the founder happened. Goal is to distill what really caused the success; was it mostly the hard work, visionary idea and perseverance despite or rather in addition to externalities?
Fundamental Attribution Error. What is it: Whereby we attribute a person’s behaviour to an intrinsic quality of her identity rather than a situation she is in. For example, let’s say you were interviewing a financial advisor. He shows up on time, in a nice suit, and buys lunch. He says all the right words. Will he handle your money correctly? Almost all of us would be led to believe he would, reasoning that his sharp appearance, timeliness, and generosity point towards his “good character”. Dan Ariely’s book about situational dishonesty and cheating illustrates that we may give an appearance that is expected only to behave differently in a similar context. How to defend against it: Before and during the fundraising pitch, we need to dig deeper and put appearances and our expectation in a proper context, aiming to find out whether the founder and his team really have all the necessary attributes (industry knowledge, team skills, leadership, vision for the product) required to give them the best shot at successful growth and scale up of their product.
Survivorship Bias. What is it: Our tendency to focus on successful people, businesses, or strategies and ignoring those that failed. Because of this, we adopt opinions, structure businesses, and make decisions without examining all the data, which can easily lead to failure. A Google search of “Successful founders who dropped out of college,” will turn up some of the biggest names such as Steve Jobs and Mark Zuckerberg as examples of entrepreneurs who had an idea, took a leap and became successful. But by equating their success to hard work alone, we ignore a very important fact: for every successful college dropout, there are hundreds, if not thousands, who weren’t as lucky.
The founders we put on pedestals worked hard, but there were also many circumstantial events that paved their way to success. In fact, research shows the majority of the United States’ most successful businesspeople graduated college – 94%, to be exact. How to defend against it: Look out for signs such as “In following legendary footsteps of XXX,” “We have some of the similar pedigree to YYY,” “Our team’s combined experiences in this industry are of ZZZ years”, etc which all have a common denominator of “based on previous success of such and such, we think we have a good chance at similar success.” Again, a more pragmatic assessment of team, product and market related to areas where the founder or his team claims some “heavy” credentials would help understand what the reality is.

In addition to the above, biases investors can look out for in founders include:

Information bias
Framing cognitive bias
Decoy effect
Choice supportive bias
Empathy gap
Illusion of control
Overconfidence and overoptimism
Scarcity priming

Using anchors to win deals

How do people know if the price is right? How do they decide if they want to buy something for a specific price displayed in the shop? “People make estimates by starting from an initial value that is adjusted to yield the final answer,” explained psychologists Tversky and Kahneman in their 1974 paper. “The initial value, or starting point, may be suggested by the formulation of the problem, or it may be the result of a partial computation. In either case, adjustments are typically insufficient. That is, different starting points yield different estimates, which are biased toward the initial values.” This means that the initial anchor serves as the benchmark for the rest of the pricing/deal negotiation – hence the cognitive bias ‘anchoring‘ that plays a huge role in our decision making process.

Now that we have an idea of what’s anchoring, how shall we use it to win deals/pricing negotiations? Let’s start with an elephant in the room. If you want to win a deal/negotiation, never be needy for the deal. Always appear to have your BATNA figured and ready. Keeping this in mind, let’s explore anchoring tactics that will help you win pricing deals/negotiations even in most difficult of situations.

Tactic 1: Use Bandwagon effect

Suggest a price to which the crowd is drawn. This must be the ideal price tag you want to draw your customer too.

Tactic 2: Use Ackerman Model

This tactic has been developed by Mike Ackerman, former CIA agent, for hostage negotiations. It’s one of the most effective negotiation tactics around.

Set your target price (your goal).
Set your first offer at 65% of your target price.
Calculate three raises of decreasing increments (to 85%, 95%, and 100%).
Use lots of empathy and different ways of saying “No” to get the other side to counter before you increase your offer.
When calculating the final amount, use precise, non round numbers like, say, $37,893 rather than $38,000. It gives the number credibility and weight.
On your final number, throw in a non monetary item (that they probably don’t want) to show you’re at your limit.

Tactic 3: Leverage Contrast Bias

a) Use an extreme anchor to put a benchmark from which rest of negotiation will follow. As we are susceptible to anchoring bias, an unreasonable anchor – however unreasonable it may be – sets the starting point of negotiation.

b) Another potential strategy is to show your competitors’ prices on your pricing page. This gives your customers a frame of reference from which they can evaluate your product, but also risks drawing in competitive options for them to choose from. Use this method if your offer is the best value amongst your competitors or can be framed as such competitors.

Tactic 4: Show genuine anger

When you show passion and conviction (to injustice or impossibility of working our the deal), this causes the other side to become more sensitive to anger/fear, which turns on flight-or-fight instinct in the amygdala. Channel that anger to the proposal/deal, not the person with something like “I don’t see how this would ever work” (strategic umbrage).

With above being said, when you don’t know the market value of the deal you are negotiating or are uncertain of the full information that your counterpart has, avoid making an initial anchor until you collect some information about your counterpart.

This article was published on e27.

Entrepreneur’s perspective: psychology of fundraising

The above quote is the truth. There is no one world – each of us lives in a world. And just like in anything, when it comes to money and fundraising for our projects, we live in our little world with our own idea of what an efficient fundraising process looks like. We do our research, then follow some steps we find convincing and voila! We fail. Generally speaking, startup fundraising is inefficient, lengthy and for most part fruitless, minus the few (statistical) exceptions. 95% of all startups launched die within the first 3 years, top second reason being shortage of capital. Capital is the oxygen to a startup, powering its launch and growth, and yet this oxygen turns out to be very hard to come by.

Why do most startup fundraising efforts take long time and frequently fail? Two reasons: 1) founders don’t understand, let alone incorporate, behavioural insights governing investors’ decision making process into their pitch deck and pitching process; 2) investors fail to see salient points and potential of startups thanks to lack of their time and focus, and not in small part, lack of founders’ lack of investors’ decision making process and mindset. i.e. point 1 above. One fundamental insight helps solve both issues: most decision making (of investors and human being in general) is instinctively guided and controlled by mental shortcuts (called cognitive biases), without them even being aware of those.

What are cognitive biases? Cognitive biases are mental shortcuts. They are bits and pieces of human character and behaviours that evolved over thousands of years to help us survive, initially in the context of hunter-gathering against predators and in the wild nature. While much time has elapsed, these biases are still present with us in the modern world.

Broadly speaking, cognitive biases can be split into two types: information processing and emotional biases. Information processing biases are statistical, quantitative errors of judgment that are easy to fix with new information. Emotional biases are much harder to change or fix as they are based on attitudes and feelings, consciously and unconsciously. Both types can have implications when you are a startup founder trying to fundraise because they operate to keep you within your comfort zone. The underlying belief that you’ll be safer, more secure and more comfortable with less uncertainty and risk dominates decision making. To fundraise efficiently and effectively, we need to do the opposite, by going after investors and selling our story (narrative bias), showing our vision (confirmation bias, clustering illusion) and getting them to buy into our team (halo effect) and product (distinction bias, zero-risk effect, pro-innovation bias).

Top seven biases that are critical for successful fundraising cover all aspects of successful pitch and pitching process. Entrepreneurs would be wise to incorporate these insights into their pitch decks, giving them the best shot at achieving their fundraising targets.

Narrative fallacy. What is it: humans (including investors) have a tendency to look back at a sequence of events, facts or information in a linear and discernable cause-and-effect way. Cause-and-effect morph into a story. How to apply: make your pitch deck – at least the beginning part talking about Problem, Opportunity and Solution – into an inspiring story, with clear causes, effects and inspiration.
Clustering illusion. What is it: investors tend to observe patterns in what are actually random events. How to apply it: you must showcase your team’s credentials, previous or relevant successes of exiting (or failing) startups or a successful career in an MNC, which will create a clustering illusion in an investor’s head that your team has been on a roll, and your current project’s vision will be achieved based on your team’s previous success. Also when you show traction/data to investors, make sure your case is compelling enough, even with little data using the clustering illusion to your advantage, by citing trends as validation of your vision.
Confirmation bias. What is it: investors believe what they believe based on experiences and expertise they have accumulated in startup investing. How to apply it: include all the main points investors expect to see in your pitch deck, resulting in an investor “confirming” that your project is commercially sound and to have a serious consideration of investment. Lastly, in your deck, show your present solution as consistent with investor’s prior beliefs (i.e. in line with the investor’s current former portfolio investment) and avoid contradicting any strongly held opinions of the investor during pitching.
Pro-innovation bias. What is it: novelty or “newness” are generally considered good by investors, hence showing a product innovation is a good idea. How to apply it: Pitch innovative features of your product and how they give you an edge over competitors, especially a competitive advantage. However, a caveat – investors know this well – is that you need to be very careful when pitching a business model innovation, as investors’ inclination is towards favouring business models that have proven track record, as opposed to completely new ones.
Halo effect. What is it: this is the psychological tendency many people (including investors) have in judging others based on one trait they approve of. This one trait leads to the formation of an overall positive opinion of the person on the basis of that one perceived positive trait. For example, people judged to be “attractive” are often assumed to have other qualities such as intelligence or experience to a greater degree than people judged to be of “average” appearance. How to apply it: show (in the pitch deck) or inform (during pitching) of achievements (former exit, speaking at a prestigious event, etc) in order to create a halo effect in an investor’s head, which will then colour his/her judgment positively for the overall project, and in conjunction with other factors, might lead to an investment. Also, if you can show a testimonial by a celebrity or a well-known business person of your product or one similar to yours, halo effect will do the rest!
Zero-risk effect. What is it: this is a tendency to prefer the complete elimination of a risk even when alternative options produce a greater reduction in risk (overall). How to apply it: in your pitch deck, it is important to either not show potential risks (scale up or product) or show a risk with a full mitigation of it. This is one of the main reasons that investors might not speak out or question you, but also decide not to go ahead with investment due to perceived risks in your product.
Distinction bias. What is it: this is a tendency to view two options as more distinctive when evaluating them simultaneously than when evaluating them separately. It can magnify the near meaningless differences between two very similar things to the extent they become decisive in which one we choose. How to apply it: in your pitch, compare your product with one or two competing products next to which yours has clear benefit. This comparison will clearly sway the investor to your product as a preference.

A more complete list of biases (excluding the ones mentioned above) affecting entrepreneur’s pitching ability can be found below.

availability heuristic
information bias
expertise trap
attribution error
framing bias
bandwagon effect
hyperbolic discounting
sunk cost fallacy
planning fallacy
omission bias
choice-supportive bias
illusion of truth effect
superiority bias
self-serving bias

Cognitive biases are particularly challenging for fundraising process as they have a profound impact on the creative right-side brain which is critical for creative ideas. Right brain thinking is more risky and prone to biases as it deals with abstract unknowns vs. left brain thinking which deals with more logical concrete knowns.

*This article was first published on WholeSale Investor

Economics, psychology and blockchain systems

Blockchain platforms are economic systems. And just like any economy, a blockchain requires that its designers define monetary policy (inflation), fiscal policy (block size), taxation (fees), voting (governance/upgrades), and provide for the common defence (securing the network). Yet, unlike traditional economies, they offer the possibility of greater freedom and transparency because they avoid the problems of centralisation and concentration of power.

So the blockchain is great for academic economists, because it is a kind of living economic laboratory. Economists have plenty of tools for designing such systems. Does it end there? No, because the blockchain does not evolve randomly but by attempts at designing new, and better, models for money, ownership, control, trade, lending, licensing, and investment. In other words, many of the key innovations of the blockchain are economic innovations, and that means we need economists to help design them.

The problem with traditional economics is that it has two major assumptions, based on which the entire economic system is built. First, it assumes humans are rational and always and consistently optimise their utility (happiness, satisfaction). Second, economic theory assumes that on macro economic level there is or tends to be an equilibrium or balance which economics systems need to attain. In other words, we assume wisdom of the crowds and efficient market hypothesis. But what if neither is true, at least some times?

Humans are irrational by design. Just look at some of the decisions each of us make on a daily basis. We may vote for policies that go against our own economic interests. We make food selections that are at odds with our physical health. So there’s no clear, codeable logic in much of our behaviour.

Blockchain systems are, by design, difficult to change once deployed. Repairs and improvements to these systems are difficult. Protocols with billion-dollar valuations could disappear overnight. Things can get very acrimonious. Check the infamous Bitcoin block size debate. And one of the most difficult aspects for blockchain platform creators is accurately predicting people’s behaviour. That would be a relatively easy task if humans had a consistency, rational behaviour or an overarching logic in how they go about their lives.

Good news is that there is an entire field studying this – human irrationality and how to incentivise humans – very phenomenon, including Nobel laureates Daniel Kahneman and Amos Tversky and former Clinton advisor Cass Sunstein, who discovered that changing the default setting from “opt-in” to “opt-out” on things such as organ donation on a driver’s license and 401k contributions at work could dramatically improve uptake. This seemingly little change tapped on our Default Bias, enabling individuals to adjust their contribution levels (to retirement), but even the flummoxed novice who did nothing is at least socking some money away for retirement and taking advantage of company matching payments.

It turns out that we have a huge number of cognitive biases and knowing these and knowing how to go around these or nudge or incentivise us to act in desired ways is the key to understanding and predicting human behaviour accurately. One of most commonly-observed cognitive biases is loss aversion. Loss aversion derives from our innate motive to prefer avoiding losses rather than achieving similar gains. Kahneman and Tversy conducted an experiment asking people if they would accept a bet based on the flip of a coin. If the coin came up tails the person would lose $100, and if it came up heads, they would win $200. The results of the experiment showed that on average people needed to gain about twice (1.5x – 2.5x) as much as they were willing to lose in order to proceed forward with the bet (meaning the potential gain must have been at least twice as much as the potential loss). However, from traditional economic theory perspective, one’s risk appetite to losing or gaining $100 is the same.

The most tangible of incentives on blockchain platforms are digital tokens. Tokens usually represent currency, digital asset or some form of value in given blockchain system. Getting incentives right is fundamental to network growth, reflected in increased token adoption that yields positive network effects. Once this flywheel gets started, it serves as the ongoing funding mechanism for future development. Without it, the network cannot achieve self-sustainability. The value of the community and the token is what incentivises new members to join initially. If that value is off, new people don’t join and a death spiral begins. Once members are in, there needs to be a sustainable and growing value in the system to keep them using the tokens, participating in the community and helping the system grow. While token was the allure, the incentive system needs to account for conflicting interests of different types of users, system changes and perceived value and expectations from the system and, most importantly, it cannot necessarily based on the value of token itself. There are a few systems that help evaluate blockchain projects, including T3CG framework which is pretty solid.

Cryptoeconomics is hard as it requires expertise and mastery of mechanism design, contract theory, game theory, behavioral economics, public policy, macro-economics, and a solid understanding of decentralized technology in order to the design robust, sustainable and valuable blockchain economies. Hence is boils down to designing incentive systems based on known biases – default bias, endowment effect, bandwagon effect, etc – and other factors, including cultural values, public policies, system-specific goals.

I am very excited by potential of blockchain systems but also humbled by the realization that we have just scratched the surface on how to build optimal blockchain systems.