Innovation Footprints

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Funding

Question Everything; My Remarks At FOCUS100 2014

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Startup Stock PhotosBackground: I gave these remarks at Digital Undivided’s FOCUS100 2014 Conference which was held between October 3rd and October 4th in New York City. A number of investors were invited to explain to the audience how they ought to pitch venture capitalists in order to win funding. Digital Undivided is a social enterprise that develops programs that increase the active participation of urban communities in technology. It has a particular focus on women. 1I have edited it by adding comments based on questions people at the conference asked me after I had spoken, mainly adding a little more context.

I am not very good at listening to what other people tell me to do, so rather than outline what I think you should do in order to get funded by a venture capitalist, I thought I should instead share with you some of my beliefs about founders, and startups, and how I think about my responsibilities as an early stage investor. I hope in doing so you will question some of the assumptions you hold about how you should go about raising capital.

  1. The kind of founder that really excites me does not need a venture capitalist. She simply needs some capital to enable her build her vision and transform the world. My job is to give that founder sufficient reason to decide that she wants to undertake that journey with KEC Ventures as a companion.
  2. To get past the first meeting, a founder has to inspire confidence. She has to make me want to follow her over the edge of a cliff, or into a burning building. She has to make me feel I could trust her with my life because come hell or high water, she’s going to figure things out. She’s smart, hard working, can process an enormous amount of unfamiliar information and take action based on what she’s learned, she knows or can learn how to build and lead a team that’s going to do something ambitious. She might be an introvert, or an extrovert. She gets me to buy into her vision of how things should be, and how she will use technology to accomplish that. She wants to win, and she knows how to win. I do not believe in “pattern matching” in the way some well known investors have described it. I don’t pattern match people. That’s an intellectually lazy approach to picking investments. Instead I pay attention to ideas, problems, and the characteristics of successful businesses. Meeting and investing in startups led by founders with a vision to make the world a better place is what makes me eager to wake up each morning and endure the cognitive dissonance that is a daily and ever present aspect of my job as an early stage investor.
  3. I do not believe in founders who lack the intellectual and emotional fortitude to debate and argue honestly about what is best for the startup with their investors and with others who might have opinions about what they should do. I believe that the best decisions are made when one can debate issues with one’s self, and when founders and investors can engage in healthy, critical and honest debates with one another and subsequently reflect and contemplate on everything they have learned through that process. I get frightened by founders who cheerily agree with everything investors say. If the founder is indeed creating something new, or solving a widely-overlooked problem, there’s no way the average investor has considerable experience and expertise in that area – by definition the founder is “the expert”. I expect the entrepreneur to know far more than the average investor about what will work, what will not work, and why. Cheery agreement with everything an “ignorant” investor suggests acts as a red flag to me that perhaps this founder does not understand the problem she is solving, or her market, as well as is required to do what she says she wants to accomplish.
  4. My primary responsibility to investors in KEC Ventures is to be skeptical; Skeptical about myself, and what I think I know, and skeptical about the founders I meet and the claims they make. This is the only way I can minimize the chance that I pass on an idea that seems inconsequential at the outset, but goes on to form the basis for a transformative business. I hope another consequence of my skepticism is that I also minimize the probability that I am too eager to invest in startups that fail because they are built on ideas that are obvious. (Note: I also need to be optimistic.)
  5. Most startups fail. Let me rephrase that, the overwhelming majority of startups fail. My only task is to find those that will succeed before they become well known by other people. Further, we should not invest in a startup unless we believe that our investment in that startup can return our entire fund. One founder at the conference suggested he could “guarantee” a 10x return if KEC Ventures would invest $250,000 in his seed round. That would be great, if we were investing from a $2,500,000 fund.
  6. The type of startup I want to invest in is a very specific thing; it is a temporary organization that has been created to search for a profitable, repeatable, and scalable business model while it solves a problem that has been overlooked in a certain market. It is designed for fast growth once that solution is developed and the business model has been found, and if it succeeds it completely transforms and overwhelmingly dominates the market in which it operates before it moves into adjacent markets. 2This definition is a composite that combines elements from definitions other investors have used. It is primarily derived from a definition that Steve Blank and Bob Dorf use in The Startup Owner’s Manual.
  7. Accepting the definition of a startup that I use as my guide, there are certain things that I listen for when I am speaking with a founder. Collectively, they are described as “Economic Moats” . . . Intellectual Property, Network Effects, Efficient Scale, Switching Costs and Branding. Even if these do not exist at the very outset, it has to be clear that they can be designed into the startup’s business model as it matures and that the founder has already been thinking about them. Also, I am not interested in situations where only 1 of those sources of an economic moat is present. I prefer 3 at a minimum, all 5 ideally. The durability of a moat is a something I worry about. Also, how wide or narrow that moat can be made is something I think about constantly. Essentially, I want to avoid the detrimental effects of competition.
  8. A venture capitalist does not provide capital to people who need it. A venture capitalist has a fiduciary responsibility to make the best effort possible to generate a positive return for investors in the fund.

References   [ + ]

1. ↩ I have edited it by adding comments based on questions people at the conference asked me after I had spoken, mainly adding a little more context.
2. ↩ This definition is a composite that combines elements from definitions other investors have used. It is primarily derived from a definition that Steve Blank and Bob Dorf use in The Startup Owner’s Manual.

How an Investor’s Behavioral Traits Might Completely Derail Your Pitch – Part I

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Many startup pitch meetings start out on a promising note, but things fall apart during the conversation between the startup and its prospective investor. Sometimes this could have been prevented if the startup team had studied a little bit of behavioral psychology beforehand. 1Any errors in correctly attributing work to my sources and references is entirely my fault. I’ll make corrections if you point an error out to me.

Traditional finance theory tries to tell us how investors should behave, if they act as rational economic beings. Behavioral finance is based on the observed behavior of investors. Traditional finance is based on economic theory. Behavioral finance is based on psychology. Traditional finance assumes that investors make their decisions based on all available information, that investors are rational, and that markets are efficient. 2The efficient-market hypothesis (EMH) states that financial markets are informationally efficient and that the price of a publicly traded stock incorporates all available information about that stock. Even if you think this is true in public markets, you have to agree that it is not the case in venture capital. It is especially true that the market for early stage venture investments is highly inefficient, prone to extreme uncertainty and severe information asymmetries. Behavioral finance makes none of the assumptions of traditional finance.

In this post, I will describe a few behavioral biases that an investor might exhibit during a pitch meeting with the founder of a startup. 3I am basing the outline of this post on portions of the CFA Institute’s 2013 Level III readings on Behavioral Finance. I will describe how each bias might be exhibited during a pitch meeting. I will also suggest how the entrepreneur might attempt to mitigate each bias. Failure to mitigate a behavioral bias could mean that the pitch gets derailed, and the entrepreneur fails to communicate effectively with the investor about the startup. I have developed the examples on the basis of meetings at which I have been on the side being pitched by entrepreneurs, after-the-fact reports about investor meetings that entrepreneurs I know have spoken with me about, and also from meetings at which I have been on the side pitching an innovation to potential business partners, and investors for a startup that I have been helping to incubate since January 2011. 4I am not a psychologist, so my discussion of this topic will certainly fall far short of even very modest expectations. However, I hope that budding entrepreneurs find this discussion to be a good starting point for some independent work on this topic.

The behavioral biases that I will cover in this post are categorized as cognitive errors. A cognitive error or bias stems from the inherent shortcomings people face as they try to process information that is unfamiliar and complex. Cognitive errors are further categorized as information processing errors or belief perseverance errors. This post will focus on a few belief perseverance biases. Behavioral biases generally can be grouped as cognitive errors, emotional biases, memory errors or social biases.

As you read the rest of this post you will notice that the lines between these biases is somewhat blurry – what one person sees as indicative of one kind of error could be seen by someone else looking at the same information as indicative of another bias. That seems to be the nature of those behavioral biases I have studied – there’s a lot of interconnection and it is difficult to assign an observed behavior to a single bias or error. More likely, the observed behavior arises due to a combination of biases and errors. That is why I think preparation beforehand is key. The entrepreneur can try various approaches to mitigating the observed bias until one approach leads to a break-through that restores the flow of ideas and communication between the entrepreneur and the potential investor.

Cognitive Errors – Belief Perseverance:

  1. Conservatism Bias: This occurs when a potential investor fails to revise his preconceived beliefs about your startup even when there is new evidence that suggests that his beliefs are incorrect. 5This can also be exhibited as a tendency to underestimate high-likelihood events and overestimate low likelihood events.
    • Case: Steve is 20 years old. He has quit college with two of his classmates to focus on building a startup – Disruptive Tech Startup (DTS). He meets with an early-stage venture capitalist to describe the work they have done so far and their vision for the future. Steve does not realize that the investor believes that he’s too inexperienced and too young to accomplish what he wants to accomplish with DTS. More specifically, the investor does not believe that Steve is experienced enough to steer DTS so that the investor realizes the minimum 10x return that the investor’s investment thesis requires. Steve thinks the meeting went well, but the investor later tells him that the fund has decided to pass on making an investment in DTS.
    • Mitigation: Steve should spend more time discussing his background, what he has done to learn how to run the startup, and how he will learn what he needs to learn in order to run the startup in the future. He should explicitly tackle the issue about his youth and relative lack of experience, and openly discuss steps he will take, or has already taken to ensure that his investors’ capital is not put at risk because of his youth and perceived inexperience. He should offer references who prospective investors might speak to about his leadership potential as it relates to managing a startup. He should not assume that the investor will conclude that he will continue to succeed in the future after seeing what he has accomplished at DTS so far.
  2. Confirmation Bias: This occurs when the investor focuses on perceived negative aspects of your startup while ignoring and dismissing your attempts togive an explanation with evidence that will contradict that perception.
    • Case: Steve is pitching DTS to another early stage investor. She thinks that the technology they have developed is trivial after having listened to Steve for about 20 minutes, and she tells them as much. Steve gets frustrated because he feels she does not understand what DTS is about. The meeting is a disaster because she keeps focusing on the notion that “But isn’t this just a simple bot that scrapes the web for data? If I were a software developer I could do this with very little effort.”
    • Mitigation: This investor likely does not understand the full extent of the problem that DTS is solving. 6The unstated assumption here is that DTS is not solving a trivial problem. If Steve is stuck in “Demo Day Pitch” mode he likely has not considered that in a small meeting the dynamic is different. He should “put away the deck” and go into “professor mode” – in this mode he is educating the investor about the problem, about how DTS is solving that problem, and also about the opportunity that presents for potential investors in DTS, all in a conversational setting – like a professor teaching a student a new concept during office hours. He should expect to follow this up with further information for the investor to consider. 7See this post for an example.
  3. Representativeness Bias: 8The Wikipedia entry for the Representativeness Heuristic is here. You should read it if you are building a startup and will be raising capital from investors. This occurs when the investor uses an if-then rule of thumb or mental shortcut toassess your startup because of the high levels of uncertainty associated with the decision the investor must make.
    • Case: Ademola is a Nigerian entrepreneur. He has been building an Internet software startup in Lagos for two years, African Technology Startup (ATS). He grew up in Nigeria and holds a master’s degree in computer engineering from the Obafemi Awolowo University of Science and Technology, one of Nigeria’s leading universities of technology. In order to grow ATS he has moved to New York and is raising capital from investors. ATS has customers from all over the world, and he believes ATS is solving a significant problem for them. Growth has been phenomenal. ATS has accomplished that growth on a shoe-string budget. Ademola has been building ATS with two other people, they are both co-founders of ATS as well. They will remain in Lagos to manage the technology and R&D efforts. Ademola is worried that many of the investors he will meet are ignorant about Africa. He is also worried that they may unconsciously harbor negative perceptions about ATS that they will not verbalize during a meeting.
    • Mitigation: Ademola has to work doubly hard to demonstrate his technical competence because the average early stage investor in the United States does not associate Africa with technical talent and competence. For example, investors might assume that ATS is relying on a contract software engineering consultant in Asia or Eastern Europe. If ATS is building its technology in-house, Ademola has to make that explicit. He has to talk about the technology in a way that demonstrates that he can fulfill the vision that he’s selling to his customers, and potential investors. He has to convince his audience that a software engineer trained in Nigeria can compete on the global stage. He has to remember that his accent could inhibit potential investors’ ability to understand what he is trying to communicate. 9Y Combinator’s Paul Graham inadvertently got embroiled in a pseudo-controversy over this subject. You should read what he has to say, and also read what others have said. Paul’s post on the subject is here. One response is here. Instead of hoping that they will ask him to clarify something, or explain something they do not understand he should practice speaking clearly and communicating effectively to people who have never encountered someone with his accent. He should avoid using colloquial terms and idioms that are used in Nigeria, but may not be commonly used elsewhere. Investors in NYC will not understand those terms. He should be friendly, but he should avoid the temptation to be unnaturally funny. His off-the-cuff attempts at humor could back-fire. The representativeness bias at play here could be “If ATS is an African startup then the probability that it is doing all this on its own is zero because all we ever see on TV about Africa is war, starvation, and political corruption and incompetence.” Ademola has to overcome that bias during his conversations. 10This blog post at 59 Ways is a clear, but brief explanation of this bias.

An investor’s cognitive biases play an important role in how that investor will hear and interpret the information that an entrepreneur is trying to convey. Time spent understanding this phenomenon and how to mitigate any possible negative effects of a prospective investors behavioral biases will invariably lead to more productive pitch meetings.

Wikipedia’s entry on cognitive biases is here. Wikipedia also has a much more extensive list of cognitive biases here. If you have the time, you should invest in a copy of Daniel Kahneman’s 11If you purchase it through this link I will receive a small portion of the sales proceeds from Amazon to help me maintain this blog. Thinking, Fast and Slow.

References   [ + ]

1. ↩ Any errors in correctly attributing work to my sources and references is entirely my fault. I’ll make corrections if you point an error out to me.
2. ↩ The efficient-market hypothesis (EMH) states that financial markets are informationally efficient and that the price of a publicly traded stock incorporates all available information about that stock.
3. ↩ I am basing the outline of this post on portions of the CFA Institute’s 2013 Level III readings on Behavioral Finance.
4. ↩ I am not a psychologist, so my discussion of this topic will certainly fall far short of even very modest expectations. However, I hope that budding entrepreneurs find this discussion to be a good starting point for some independent work on this topic.
5. ↩ This can also be exhibited as a tendency to underestimate high-likelihood events and overestimate low likelihood events.
6. ↩ The unstated assumption here is that DTS is not solving a trivial problem.
7. ↩ See this post for an example.
8. ↩ The Wikipedia entry for the Representativeness Heuristic is here. You should read it if you are building a startup and will be raising capital from investors.
9. ↩ Y Combinator’s Paul Graham inadvertently got embroiled in a pseudo-controversy over this subject. You should read what he has to say, and also read what others have said. Paul’s post on the subject is here. One response is here.
10. ↩ This blog post at 59 Ways is a clear, but brief explanation of this bias.
11. ↩ If you purchase it through this link I will receive a small portion of the sales proceeds from Amazon to help me maintain this blog.

Why You Should Apply The Less is More Rule of Seduction When You Meet an Investor

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Two weeks ago I had a meeting with an entrepreneur who has built an interesting startup. It was our first time meeting one another to discuss his startup. Before we met I had spent about 10 to 15 minutes studying the startup’s website. After doing that I sent him a list of questions that occurred to me based on other startups I had studied in the past which could be seen as pursuing a solution to the same problem he seeks to solve. You may have encountered his product on the internet without realizing it. I am impressed by what he has accomplished so far given the resources with which he started. 1I am thankful to readers who saved copies of the original version of this post before I deleted the first iteration of Innovation Footprints. This version of the post is largely the same as the original. I made minor changes to increase clarity and reduce misinterpretation.

Don’t you want to know what I think is the best thing about our meeting?

We talked for about 90 minutes. I wanted to make sure that I did not leave our conversation before learning enough about the market he is pursuing, the problem he is solving, the product he is developing to solve that problem, the team he has formed to do those two things, and the basic characteristics of the financing round that he is now raising. I also wanted to make sure I understood whether or not he has found any customers willing to pay for the product in its present incarnation. If yes, I wanted to understand what their reaction has been so far.

But, I digress.

It was not until we had discussed his work for well more than an hour that it hit me. What they are doing could be disruptive to a legacy set of tools and product suites that people have relied on for many years now to do some rather important work – making sense of proprietary and non-proprietary data. I should know, I used to spend my working hours trying to do just that using tools that were a pain to work with then, but they were the best we had.

I do not know if he planned it that way. He did not tell me that he thinks he is working on something that could be disruptive. Rather he gave me an exhaustive explanation of the problem he is trying to solve and the various customer segments that have found what he is doing valuable enough so far that they have started paying the startup for access to the product. He connected the dots for me, and helped me get to my own realization about how disruptive his product could become without ever once using a phrase for which I have learned to keenly pay attention. He did not say: “I am going to disrupt the . . . industry.” By doing so he preserved his credibility. I will explain why.

I am teaching my self about entrepreneurship, startups, innovation and venture capitalism. To do that I am relying on the body of knowledge that many other people have accumulated. I read other blogs, I read books, I try to do more listening and less talking when I am in the company of other early stage startup investors, and I enjoy chatting with entrepreneurs.

Here are two things I have learned.

What is a startup? Steve Blank defines a startup as a temporary organization that is formed for the purpose of searching for a scalable, repeatable, profitable business model. A startup becomes a company after it has completed that search. You already know that this process is usually set in motion because the startup is solving a problem, and is doing so on the basis of an innovation or a set of innovations that is the consequence of someone’s thinking, observation and experimentation.

But how might one think about innovation? What kinds of innovation should I expect to encounter?

Brant Cooper and Patrick Vlaskovits answer that question in their book; The Lean Entrepreneur. They describe two forms of innovation. The first form of innovation is Sustaining Innovation. It is characterized by; a problem that is well understood, a market that already exists and is well defined and predictable, resultant performance improvements that are incremental in nature – lowering costs by a small percentage for example, customers that already know they want this solution, and it is reliant on traditional business processes that already exist within that industry or that can be adapted from an adjacent industry.

The second kind of innovation is Disruptive Innovation. It is characterized by; a problem that we know exists but that is poorly defined and not well understood, the potential to create a new and
unpredictable market, outcomes that are dramatic and potentially game-changing, customers that do not yet know they want the solution being developed, and non-reliance on already existing business methods in that industry or adjacent ones because such methods will fail.

So there is much that is unknown when it comes to startups and their ability to disrupt an industry. Entrepreneurs and founders of early stage startups who make the claim to investors that their startup will disrupt the dynamic already at play in their industry make a very bold and audacious claim that they often cannot yet defend. Why? Because they simply do not yet have have enough quantitative or qualitative data that would prove the point.

The lack of evidence is not necessarily a bad thing. After all if the evidence about the disruptive potential of the startup were so obvious for everyone to interpret, I might not have been offered the opportunity to discuss possibly making an investment in the startup. But, I think founders and entrepreneurs make a mistake when they eagerly declare, early and often, how they will disrupt something or another. Often, we just do not yet know. Here are some observations to illustrate the point:

The startup may be solving a problem, but how do we know that it is solving the right problem? If the solution is truly disruptive, how can we predict how customers will behave when they encounter the solution the startup has developed? Do we even know if we have identified the right market, and how can we say how that market will react? Early adopters are probably not representative of the market. The startup will not attain a profitable business model wholly on the basis of early adopter enthusiasm. Since we can’t expect to rely on traditional business methods how do we know what we have to do in order for the startup to become a company?

I know, I am making the case that there is a lot that is uncertain. But that is okay. Uncertainty is not necessarily a bad thing. The entrepreneur should be seeking investors that want to help the startup answer the questions every early stage startup must answer, in exchange for the potential financial rewards that the investor might realize once the startup accomplishes its mission.

The next time you are meeting an investor to discuss your startup don’t start by telling that investor how you will disrupt your industry. In fact, don’t mention disruption at all. Simply describe the problem you are solving – in sufficient detail that they fully understand the pain that your potential customers are experiencing because they do not yet have your solution available to them. Explain why you decided to start solving that problem – may be you were motivated by what you learned at a prior job. Tell them about your assumptions. Tell them about your hypotheses. Tell them about the experiments you have performed up to that point. Show them the results of those experiments, and describe some of the conclusions that you think can be drawn from those results. Tell them about your value proposition. Let them connect the dots. Most case studies that discuss disruption are backward looking. You want the investors you speak with to look into the future and imagine what might be possible if you work together. Explain why you believe you will succeed.

To get me thinking and believing that your startup might disrupt its industry try applying the less is more rule of seduction, because the more strident your declarations that you will disrupt your industry the more skeptical I become.

References   [ + ]

1. ↩ I am thankful to readers who saved copies of the original version of this post before I deleted the first iteration of Innovation Footprints. This version of the post is largely the same as the original. I made minor changes to increase clarity and reduce misinterpretation.

After Our First Meeting, How To Help Me To Quickly Learn About Your Startup and Maybe Say Yes

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Let’s be open. I am not going to make up my mind about investing in your startup after just one meeting. And, I definitely am not making my decision wholly based on looking at your pitch deck.

I like to do my own homework. So I think of your pitch deck as only a starting point.  After I have met you I will spend some time describing what it is I think you do for myself. I will state the problem you are trying to solve in my own words. Once I feel I understand what you do, I will spend a lot of time trying to understand why your customers would care. Does it save them time? Does it make them safer? Does it make them more money? Does it make them happier?

After this I want to understand if there are alternatives to the solution you want to bring to market. What will people do if they don’t adopt the solution you have developed? I know. You have no competitors. Still, I need to confirm that for myself. If what you are doing is as important as you say it is, is it possible that no one else has thought along the same lines as you before now? May be they failed. That is fine. I just need to study and understand what happened. Doing so will give me a better sense of the biggest challenges you might face given what we know. Things change. Technology. Competition. Preferences, and tastes. Regulations. But, at least we would have a historical guide to refer to. I am not wedded to history, nor do I think history has to repeat itself. Nevertheless, I’d still like to know what steep hills and sharp corners we might encounter.

Next, I want to get a sense of how much value people assign to the solution you have developed. Is their perception of the value high, low, or somewhere in-between? I want to understand if they will perceive that its value increases the more they consume it, or if they will feel that it has less value the more they consume it. I don’t want to invest in a startup whose customers feel that they get decreasing satisfaction value from its product as their cumulative consumption increases. It may be too early to know the exact pricing for the product, but I want to gain a sense of the dynamic that might develop around how you price your product and how the market responds.

Then I’d like to get a sense of just how big you could get. Is this an opportunity that is purely domestic? Why? What prevents you from getting bigger? Are there regulations that prevent you from expanding? Is the barrier cultural? If there’s a barrier how might we overcome it once we start gaining traction and have overcome the growing pains that your startup will encounter?

But this is all preliminary due diligence that I will do before I determine if I want to proceed with further discussions. So here’s how you can help me.

Surely there’s some research that you read while you were in the planning stages, before you committed to actually building your startup. Share it with me. If there’s a website that covers the area in which your startup will be focused, send me the link. Send me enough information so that I can be more efficient in finding answers to the questions I will be thinking about as I engage in my internal-debate about the merits or demerits of an investment in your startup. It will move things along faster.

I am not asking for anything confidential, just public information. I was studying a startup doing something really unique related to a device billions of people use. Its technology could also be used by the businesses that serve content to those devices. That mode of content delivery has exploded as these devices have become more powerful.

After our first meeting, I dug around on Google and found two great research reports from Oracle that answered the most important questions I had been thinking about. It took me a few hours of searching the Internet, and reading through some other crappy material before I found that report. Of course I was delighted, and then I asked myself why the entrepreneur did not simply send that, and possibly another one – a report that’s published by Qualcomm every year – to me. Those two publications answered all the initial questions I had, but it took a few days before I found them, read them, and got all the answers I felt I needed.

What would I do if I were you? Prepare a draft email that you can send potential investors 1Katie Smith Milway describes The Art of Irresistible Emails at HBR. It would look something like this:

Dear Brian:

Thanks for meeting with me to discuss my startup. I look forward to hearing from you once you decide on next steps. I have attached a copy of our investor presentation. I have also included some links to publications and articles that will quickly help you find independent data and information about the problem we are solving and the potential for us to build a profitable business doing so.

1. The Problem

1. Link #1

2. Link #2

3. Link #3

2.The Competition

1. Link #1

2. Link #2

3. Link #3

3. The Customers

1. Link #1

2. Link #2

3. Link #3

4. The Market

1. Link #1

2. Link #2

3. Link #3

5. The Technology

1. Link #1

2. Link #2

3. Link #3

I hope you have more questions after you have had a chance to study the information that you will find there. I’d love to discuss your questions and give you a better sense of how we have interpreted the data and the information that we have studied so far.

Entrepreneurial Founder

This email should sit in your drafts folder, so that you can copy and paste it many times. Send it to every investor that you meet. Your goal is to help me see things the way you see them. At the end, I might disagree with you anyway. That is okay. But, at least using the approach I have suggested, you helped me gain perspective based largely on some of the same information you have relied upon up till now. You are now better positioned to try to interpret data and information that I might have misunderstood simply because I do not know the topic as intimately as you. In other words, you are more likely to succeed in walking with me as I try to make the intellectual journey that you and other people with whom you are building your startup have presumably made numerous times already.

A calculus textbook I owned in college 2I still own it. I know exactly where it is had this Chinese proverb inscribed inside the front cover:

I see and I forget. I hear, and sometimes I remember. I do, and it becomes part of me.

Notwithstanding your list, I will still do a lot of research on my own. The difference is that thanks to your email, I will know what to look for from the outset. That means I can spend more time thinking about your startup and your team, and less time reading crappy research reports. All else equal, that ought to tilt the scales in your favor.

References   [ + ]

1. ↩ Katie Smith Milway describes The Art of Irresistible Emails at HBR
2. ↩ I still own it. I know exactly where it is