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Due Diligence

User Manual: The Early Stage Startups I Want To Hear About Most in 2017 and 2018

December 25, 2016 by Brian Laung Aoaeh

Source Unknown

About KEC Ventures

We are a team of early-stage investors based in New York City. We invest in information technology startups that are pursuing business models with the potential to transform the way business is done in their market. In such startups, we invest in the first institutional Seed Round. Often, but not always, we act as the lead investor. On rare occasions, we might invest earlier than this when we meet a founder pursuing a vision that we believe in. Currently, we focus on investing in startups based in the United States or Canada. Very rarely, we may invest in a startup based in Israel, but that is in the process of establishing a presence in the United States.

On our team at KEC Ventures, I have been largely focused on finding and meeting the founders that we can become most excited about. I will continue to maintain that focus over the course of 2017 and 2018.

Here are some notes for the founders of the startups I am most eager to meet.

Why I Love What I Do

My mom and dad have been running small businesses since 1981 when my mom quit her job as a teacher in Kano, Nigeria. She started a school in 1986 which they have been growing since under conditions of high uncertainty. I am intimately familiar with the pressures entrepreneurs face. I wake up every day trying to be the kind of investor my mom would have loved to have at her side.

I am most content when I am thinking about and trying to solve ill-defined problems – the types of problems other people may describe as being too difficult and not worth the trouble. I am abnormally enthusiastic about the research process that leads me to develop answers to such problems. I think of myself first and foremost as a research analyst. I embrace uncertainty. I am not afraid to be different.

Connecting With Me

If you know someone who knows me, an introduction would help. If you do not, never hesitate to communicate with me directly. I am easy to reach on the major social networking platforms. Also, I hold regular and frequent office hours at various co-working spaces in New York City. Some allow non-members to sign-up and attend.

The best time to start communicating with me is at least 6–9 months before you believe you will raise a round in which KEC Ventures might invest because I believe it is important to build trust before entering into the kind of working relationship that exists between startup founders and their early stage investors.

That also gives me sufficient time to understand the problem you are solving, so that if we invest, we are doing so with conviction. Time enables me to become a more effective advocate on the startup’s behalf when my colleagues and I have discussions about making an investment.

Communicating With Me

If we are not meeting through an introduction, I will respond quickest to founders who get straight to the point, and explain why we should meet in 250–400 words in their first email to me. Founders do not need a warm intro in order to communicate with me in order to start a dialogue.

I try my best to respond. However, depending on what else I have going on, I may not respond if I feel the startup is outside KEC Ventures’ areas of interest and that the founder could have easily found that out before emailing me. Please follow up with me once or twice if you believe I have made a mistake.

If you are not connecting with me or anyone else at KEC ventures through a warm intro, you can email me at: brian@kecventures.com. For your subject line use; Pitch: {insert name of your startup}. This way I can easily filter my inbox for these emails when I review them each week.

Characteristics I Look For in Founders, and Teams

I look for teams in which the founders have known one another for a considerable amount of time prior to launching their startup. I look for teams in which the level of trust and respect between the co-founders is high. I look for teams that will not have difficulty attracting other great people to join the startup. I look for founders who inspire confidence and loyalty from others because they are good at what they do, the kind of people I could picture myself working for.

I look for founders for whom solving the problem that their startup is solving has become their life’s mission and they plan to solve that problem with or without help from outside investors. I look for founders who have an unconventional opinion about the market opportunity they are pursuing, and can explain why their position is correct with evidence which investors can analyze independently.

At the outset I look for teams that can focus on building a simple product that their initial customers love, and who can focus on a niche within which to launch their product. I look for teams that are judicious and frugal in how they deploy the startup’s resources.

I look for founders who value teamwork, and who can become great leaders if they desire to do so. I value transparency, honesty, and openness. I value self-awareness. I like people who are determined and tenacious, who do not give up just because the going gets uncomfortable and things seem bleak.

I look for founders who have a hard time doing something simply because it is what someone else expects them to do. I look for founders who are not afraid to be different.

I like founders who marry a strong technical background with a deep understanding of  the important role marketing and sales will play in determining the success of their startup. I like founders who demonstrate a singular focus on creating value for their customers/users.

Characteristics I Look For In Markets

I look for large markets that could ultimately be served by the startup’s product, even though the initial target might be a small portion of the whole. I look for customers capable of and willing to pay for the product, and who are looking for and eager to find a solution to their problem.

I look for markets in which the pain is acute because the problem suppresses customers’ profits significantly, or because the problem makes users less happy than they could be.

If currently the addressable market is between $1B and $10B, I want to see evidence that it is growing quickly enough to support the startup’s future goals, and the competition that I assume will quickly follow if the team is successful.

In certain markets where I believe there are invisible barriers to innovation, I look for industry expertise on the founding team.

If your team is based outside one of the first- or second-tier cities for startups, it helps a lot if I can drive, take a train, or take a direct flight from NYC or Newark to come and meet you.

Characteristics I look For In Business Models

I look for products and business models that:

  • will benefit from network effects as time progresses,
  • can scale efficiently and quickly, and
  • can eventually benefit from an economic moat.

If you have the time you can read my work on economic moats here in order to understand what I will be thinking about as I conduct my independent analysis of your startup.

My Philosophy

I believe my primary responsibility as a seed stage investor is to discover founders solving problems in a manner that has the potential to positively transform industries and markets before other investors have heard of them.

We help founders focus on finding product-market fit by creating an environment in which they can focus on 4 things;

  1. Keep existing customers/users as happy as possible so that they stay and use the product more often over time,
  2. Improve product features that create and deliver additional value to existing customers/users,
  3. Hire new teammates in order to enable the team improve the product in order to deliver increasing value to existing customers/users, and finally,
  4. Attract new customers and users in order to grow the startup into a company.

I think if our founders do those 4 things well, at an increasing cadence, and with increasing efficiency and productivity, we greatly raise the odds of success of the startups in our portfolio. We strive to be good thought-partners as our founders make this journey.

The Themes I Am Focused On

Notes:

  1. My mental model of how our team functions is akin to how a soccer team functions, or how an athletic relay team functions. We take a team-first approach – it matters more that you communicate with one of us, and less on who specifically you communicate with. In turn, we will make sure that the right people on our team collaborate with a startup’s founders as we conduct our due diligence.
  2. These themes cut across different industries and sectors. That is a deliberate choice. Once you meet one of us, you’ll understand how we think about this.
  3. The technology sector evolves constantly. Accordingly, our team’s interests might ebb and flow in response. The themes I have described below should serve as a rough guide to how I think about the universe of startups in which we wish to invest.
  4. A startup raising its first institutional seed round should have raised less than $1.5M  or so prior to the round in which KEC Ventures would be investing. I personally prefer that the startup has raised $1.0M or less prior to the round in which we would invest.

I am currently interested in hearing about:

  • Marketplaces: Platforms that enable the participants in large, global markets to interact with one another in ways that reduce waste or create new, untapped opportunities.
  • Interconnectivity: Platforms that enable large numbers of different types of connected devices, machines, apps, and websites to communicate with one another seamlessly, and with the people managing or using them, within a secure environment.
  • Data & Analytics: Platforms or applications that help people or other machines to manage, analyze, interpret, make decisions, and take actions based on vast and growing troves of centralized or decentralized data.
  • Effectiveness & Happiness: Products that enable people to accomplish more at work, or to become happier outside work. Products that help large enterprises and other types of businesses and organizations to grow or function more effectively.
  • Distribution: Products that make it easier to create, manage, distribute, and consume existing and emerging forms of digital media and content.
  • Asset Management: Technologies for managing different forms of enterprise, business, or individual assets. Technologies for managing different forms of enterprise, business, or individual risk.
  • Other: New, and as-yet unknown technologies and innovations founders are building to solve problems that exist only because no one else has developed a solution.

Some, but not all, of the markets that fall within these themes include artificial intelligence – including all its existing and potential applications in different industries, software-as-a-service for enterprises – I am especially interested in products that help SMBs accomplish much more for a relatively small investment, virtual and augmented reality, distributed ledgers and other distributed computing systems, financial technology, insurance technology, educational technology and healthcare technology – where the founders discover a business model that addresses the concerns venture capitalists typically express about those markets.

Note: Starting in July 2017 I will function as the subject matter specialist on our team for investments in seed-stage startups building Internet Infrastructure, Supply Chain, and Transportation Services software.

Internet Infrastructure Software is; The software that connects computers, machines, devices, and people on the internet. Hardware is an important component of internet infrastructure, so I am willing to speak with founders who are developing a product that combines software and hardware.

Supply Chain and Transportation Software is; The software that enables networks of organizations, people, and information involved in moving products and services from one part of the world to another. This includes; Supply Chain Management, Supply Chain Logistics, and Supply Chain Finance. I have a particular interest in the application of artificial intelligence (e.g. computational stochastic optimization and learning), connected devices, and distributed ledger technologies, to the solution of problems in global supply chain networks.

Think of my focus as the union of Digital/Virtual Supply Chains and Physical Supply Chains. Virtual Supply Chains enable the movement of information within a network. Physical Supply Chains enable the movement of goods, services, and people within a network.

Things I am Not Interested In

  1. Exploding rounds: An exploding round comes with a caveat like “Seed round in ground-breaking tech startup closing in 1 week!” I do not like exploding rounds, not even exploding rounds that are being led by a name-brand VC. I need time to do my own homework.
  2. Meetings led by an advisor: I prefer my first few interactions with a startup to be with the team of co-founders, not with an advisor. It is okay for an introduction to come from an advisor, but I do not like to have advisors or mentors micro-manage my interactions with startup founders. That does not inspire confidence.
  3. Lack of control over core technologies: I try to avoid situations in which the startup has a product that has launched to the public, but the startup’s team has no primary responsibility for actually building the core product.
  4. Founders who will not share bad news: I only want to work with founders who will not hide bad news until it is too late for investors to do anything that might help the startup make a course-correction. I absolutely want to hear about difficulties, challenges, and problems. I expect the good news, but I think we have an obligation to try to fix the bad stuff before it becomes unfixable.
  5. Buzzwords: I do not believe in buzzword investing. I focus first on understanding the problem the startup has set out to solve. Only after I understand that do I concern myself with the specific technology or business model being employed to accomplish the founders’ goals.
  6. Obfuscation: “Trust me. Our algorithm is so complex and sophisticated that there’s no way you could possibly understand it.” Don’t say that. I’m willing to teach myself what I need to learn in order to understand what you do, and I need to understand the basics of how you will accomplish your vision before I can develop enough conviction to recommend an investment by our team.

My Commitment to Startup Founders

  1. I believe in Gil Dibner’s VC Code of Conduct, and will adhere to it in my interactions with founders.
  2. Given that we approach conversations with founders from the perspective of a potential lead investor, we always try to move as fast as we can to get to an answer without being sloppy about our due diligence. I wrote this guide so that founders can help us speed the due diligence process along.
  3. Other founders tell us they appreciate our team’s transparency about our due diligence process. We know founders’ time is invaluable, and we do not want to waste it if the probability that we’ll make an investment is nonexistent.

Update #1: Sunday, July 2, 2017 at 22:55 EST.

  • To reflect ongoing subject matter specialization on Internet Infrastructure and Supply Chain software.
  • To reflect institutional seed-stage focus.
  • To clarify approach to investments in Israeli startups.

Update #2: Thursday, August 17, 2017 at 08:47 EST.

  • To add Transportation.
  • To clarify that supply chain finance and supply chain management are part of our areas of interest.

Update #3: Thursday, October 26, 2017 at 09:30 EST.

  • Clarifications to themes I am focused on, and investment stage.
  • Add “Why I Love What I Do” section.

Filed Under: Deal Flow, Investment Themes, Investment Thesis, Operations, Pitching, Startups, Strategy, Venture Capital Tagged With: Dealflow, Due Diligence, Early Stage Startups, Entrepreneurship, Fundraising, Pitching, Venture Capital

Revisiting What I Know About Intangibles & Startups

October 26, 2015 by Brian Laung Aoaeh

IMG_1050
My notebook and pencil. a book I was reading, and my headphones.

 

This is the third post in my series of blog posts on economic moats. I have already written about Network Effects and Switching Costs. The remaining three sources of an economic moat are Cost Advantages, Efficient Scale, and Intangibles. ((Any errors in appropriately citing my sources are entirely mine. Let me know what you object to, and how I might fix the problem. Any data in this post is only as reliable as the sources from which I obtained it.))

In writing this post I am trying to consolidate what I have learned about intangibles & startups for myself.

I also hope that it is useful for first-time seed-stage technology startup founders who are trying to build a product, achieve product-market fit, and raise financing from venture capitalists. Often such founders are trying to accomplish all that while they also try to learn strategy, management and other subjects they perhaps had not been exposed to before they decided to build a startup. My goal in that sense is to provide one example of how an early stage venture capitalist might be thinking about these issues while assessing startups for a potential investment.

To ensure we are on the same page, I’ll start with some definitions. In the rest of this discussion I am primarily focused on early stage technology startups. If you by-chance have read the preceding posts in this series, you would have seen some of these definitions already.

Definition #1: What is a startup? A startup is a temporary organization built to search for the solution to a problem, and in the process to find a repeatable, scalable and profitable business model that is designed for incredibly fast growth. The defining characteristic of a startup is that of experimentation – in order to have a chance of survival every startup has to be good at performing the experiments that are necessary for the discovery of a successful business model. ((I am paraphrasing Steve Blank and Bob Dorf, and the definition they provide in their book The Startup Owner’s Manual: The Step-by-Step Guide for Building a Great Company. I have modified their definition with an element from a discussion in which Paul Graham, founder of Y Combinator discusses the startups that Y Combinator supports.))

A company is what a startup becomes once it has successfully navigated the discovery phase of its lifecycle. As an early stage investor one of my responsibilities is to assist the startups in which I am an investor to successfully make the journey from being a startup to becoming a company.

Definition #2: What is an economic moat? An economic moat is a structural barrier that protects a company from competition. 

That definition of a moat is the one provided by Heather Brilliant, Elizabeth Collins, and their co-authors in Why Moats Matter: The Morningstar Approach To Stock Investing.

I take things a step further in thinking about startups and companies with business models that rely on technology and innovation. I think of a good moat as performing at least two functions; first, it provides a structural barrier that protects a company from competition. Second, it is an inbuilt feature of a company’s business model that enhances and strengthens its competitive position over time.

As a result I have arrived at the following definition of an economic moat pertaining specifically to early stage technology startups;

An economic moat is a structural feature of a startup’s business model that protects it from competition in the present but enhances its competitive position in the future.

Definition #3: What are Intangible Assets? An asset is a resource that is owned by a startup with the expectation that it will provide an economic benefit to the startup in the future. Intangible Assets are assets that are not physical in nature; intellectual property, brands, skill in research and development, regulatory environment, culture and management.

Baruch Lev explains why intangibles matter:

Intangible assets—a skilled workforce, patents and know-how, software, strong customer relationships, brands, unique organizational designs and processes, and the like—generate most of corporate growth and shareholder value. They account for well over half the market capitalization of public companies. They absorb a trillion dollars of corporate investment funds every year. In fact, these “soft” assets are what give today’s companies their hard competitive edge.

– Baruch Lev, Sharpening The Intangibles Edge, Harvard Business Review June 2004 Issue ((Baruch Lev taught me accounting while I was an MBA student at NYU Stern, his constant emphasis on intangibles increased my interest in getting better at assessing the connection between intangibles and competitive advantage from an investment analyst’s perspective.))

In the remainder of this post I will discuss each broad category of intangibles from the perspective of an early stage startup and the issues such a startup’s founders ought to be aware of.

Intellectual Property

Bottom line: All things equal, a startup with a sophisticated understanding of the role that IP plays in creating value for customers and shareholders will be more attractive to shareholders than its peers.

According to the World Intellectual Property Organization: “Intellectual property (IP) refers to creations of the mind, such as inventions; literary and artistic works; designs; and symbols, names and images used in commerce.” As far as early stage technology startups are concerned I am mostly interested in copyrights, trademarks, patents, and trade secrets.

I am not an IP attorney, so please consult an IP attorney if you read this and have specific questions about how to protect your startups IP. The goal of this discussion is not to examine the intricate legal details and nuances of IP law, but rather to offer a broad view of the IP landscape with pointers about some of the issues to which first-time founders should pay attention.

Copyrights: This is a form of protection that is granted to the original author of any piece of work that can be stored in some form of fixed media. A copyright protects the original author’s work from indiscriminate copying by other people. Among other things, copyrights protect computer software, computer programs, blog posts, advertisements, marketing materials, videos, pictures etc etc. Merely creating the work in a form of fixed media establishes the copyright. In other words, an algorithm that exists in my mind is not protected by a copyright, but my copyright comes into existence the moment I commit it to software or document it some other tangible way – for example, in a notebook.  While it is not necessary to register the copyright in order for the right to exist, there is a benefit to copyright registration with the appropriate legal jurisdiction. In the United States, a copyright holder can not file a lawsuit for infringement if the copyright is not registered with the United States Copyright Office.

It is important for early stage startup founders who rely on outside vendors and other contractors to understand the “work for hire doctrine” and its implications on copyright ownership. According to the United States Copyright Office: “If a work is made for hire, an employer is considered the author even if an employee actually created the work. The employer can be a firm, an organization, or an individual” The parameters for determining who is an employee is not very straightforward in an environment within which the early stage startup; exerts little or no control over the how the work is done, exerts little or no control over the employee’s work schedule over the duration of the contract, or does not provide the employee with benefits or withhold income taxes from the employee’s pay. Due to these ambiguities, I think that early stage startup founders should make it a practice to protect some of the work done by contractors and vendors with work for hire agreements. A good work for hire agreement will state unambiguously that the work product covered by the agreement between the startup and the contractor is a work for hire to the benefit of the startup.

For  an individual, copyrights extend for the life of the original author and for an additional 70 years beyond the author’s death. For a startup, the copyright extends for 120 years from the date of creation or 95 years from the date of publication.

Trademarks: According to the US Patent and Trademark Office “A trademark is a brand name. A trademark or service mark includes any word, name, symbol, device, or any combination, used or intended to be used to identify and distinguish the goods/services of one seller or provider from those of others, and to indicate the source of the goods/services.”

Establishing a trademark is an important part of how an early stage startup begins to communicate its brand with its customers or users. Trademarks can take different forms, for example a distinctive sound can be used as a trademark.

Similar to copyright protection, merely using the mark in the course of doing business establishes the trademark right for the startup that owns the mark.

According to the International Trademark Association trademarks are:

  1. Fanciful Marks – coined (made-up) words that have no relation to the goods being described (e.g., EXXON for petroleum products).
  2. Arbitrary Marks – existing words that contribute no meaning to the goods being described (e.g., APPLE for computers).
  3. Suggestive Marks – words that suggest meaning or relation but that do not describe the goods themselves (e.g., COPPERTONE for suntan lotion).
  4. Descriptive Marks – marks that describe either the goods or a characteristic of the goods. Often it is very difficult to enforce trademark rights in a descriptive mark unless the mark has acquired a secondary meaning (e.g., SHOELAND for a shoe store).
  5. Generic Terms – words that are the accepted and recognized description of a class of goods or services (e.g., computer software, facial tissue).

A fanciful mark has the strongest trademark protection. A generic mark has the weakest protection. Over time, the protection afforded a fanciful mark can wane if that term becomes a generic term that is used to describe a category.

A startup founder seeking trademark protection should seek the advice of an IP attorney since this is a more complicated topic than copyright protection.

Patents: According to the World Intellectual Property Organization “A patent is an exclusive right granted for an invention. In other words, a patent is an exclusive right to a product or a process that generally provides a new way of doing something, or offers a new technical solution to a problem. To get a patent, technical information about the invention must be disclosed to the public in a patent application. The patent owner may give permission to, or license, other parties to use the invention on mutually agreed terms. The owner may also sell the right to the invention to someone else, who will then become the new owner of the patent. Once a patent expires, the protection ends, and an invention enters the public domain; that is, anyone can commercially exploit the invention without infringing the patent. A patent owner has the right to decide who may – or may not – use the patented invention for the period in which the invention is protected. In other words, patent protection means that the invention cannot be commercially made, used, distributed, imported, or sold by others without the patent owner’s consent.”

A utility patent is used to protect the functional features of an invention. Most of the patent applications made to the US Patent and Trademark Office are for utility patents. A design patent is used to protect the appearance of an invention. Utility patents generally provide broader protection than design patents, also it is easier to avoid infringing on a design patent. Utility patents are more expensive to obtain and take longer to obtain.

To receive patent protection an invention must be:

  1. Patentable,
  2. New, or novel,
  3. Useful,
  4. Non-obvious, and
  5. Adequately described.

Additionally, software and business process patent applications will likely be subjected to a “machine or transformation test.” The machine test means that software or business processes can not be patented unless they are combined with a machine of some sort – a computer. The transformation test means that software or business processes cannot be patented unless they transform one thing into another, different thing, or into a different state.

An invention is “adequately described” in a patent application if “someone of ordinary skill in the arts” can replicate the invention using nothing but prior background in that technical field along with the inventor’s description in the patent application.

An invention is non-obvious if someone of ordinary skill in the arts would not necessarily have reached the deductions made by the inventor on the basis of prior art in that technical field.

A theory will not receive patent protection, in and of itself it is not useful in a practical application.

There are two main patent award systems; first to invent, or first to file. In first to invent jurisdictions, the first person or group of people to conceive of an invention will be awarded patent protection if they go through the application process successfully and can demonstrate that they indeed conceived of the invention first. In a first to file jurisdiction the first person or group of people to file an application for patent protection will be awarded the patent irrespective of when they conceived of the invention relative to other inventors pursuing the same invention. The United States is a first to invent jurisdiction.

In the US, the clock starts ticking when an inventor first discloses the invention to the public – such disclosure could happen during a presentation to investors, a sales pitch to potential customers, or a presentation at an industry conference. Once public disclosure of the invention has occurred, the inventor has one year within which to file a patent application. If a year elapses without the inventor filing for patent application, that inventor then forfeits patent protection for that embodiment of the invention.

To avoid this, a provisional patent application can be filed with the USPTO to preserve a filing date. A final, or utility application has to be filed within 12 months of the provisional application. The utility application is what the USPTO examines in order to determine the merit of the inventors appeal for patent protection.

Outside the United States, inventors do not have the benefit of a grace period. As a result any international patent applications must be made as soon as possible, in order to preclude public disclosure by the inventor.

Public disclosure causes the invention to become part of the “prior art” in the field of the invention.

In 2009 I worked on an intellectual property audit with the management team at David Burke Group, that process culminated in the issuance of a patent, US 20100310736 A1 which describes a process for aging meat. The dry-aged steaks served at DBG restaurants are prepared using this process. That was my first experience securing intellectual property rights on behalf of a company.

In 2011 our team at KEC Holdings ((KEC Holdings is the parent company of KEC Ventures.)) invented a family of financial derivatives. I assumed responsibility for (1) ensuring that our valuation methodology was justifiable on the basis of widely accepted financial and economic principles, and (2) working with an IP attorney to attempt to obtain patent protection for the idea. Our electronic documentation of the idea came to 50+ pages of background, mathematical derivations and proofs, problems and worked solutions to demonstrate how the invention might be used in practice, valuation tables etc etc.

In 2012, I worked with a team of founders in Ghana who wanted to seek a patent for their idea. I was a volunteer mentor/advisor to the team. They worked with a patent agent in India. The working relationship was ineffective for reasons that were entirely preventable if the team had embraced some simple suggestions about how to work with a patent agent/attorney working on their behalf.

What have I learned about how to work with a patent attorney or patent agent?

Generally, a patent attorney or patent agent is unlikely to be an expert in the technical field of an invention even if they specialize in the legalities of obtaining a patent in that field; a software patent attorney is unlikely to understand the nuances of a software product as well as a software engineer. For that reason, it is the inventor’s responsibility to transfer as much background knowledge as possible about the technical field of the invention and specific nuances of the invention itself to the patent agent/attorney. First, this will help the attorney perform a more complete and comprehensive patentability search. Second. it will ensure that the patent application is drafted correctly from the outset. That has the benefit of minimizing rework. Third, it will also help the attorney answer questions and respond to objections during the period when the patent is being examined by patent examiners.

Here are some additional suggestions:

  1. Maintain “excruciatingly detailed” notes about the invention. You should describe the invention such that someone of considerably less expertise than you can understand the description. Also, keep pictures, drawings, figures, and any data that you create as you go through the invention process. It is a good idea to maintain a “lab-book” with numbered pages, dates, and handwritten notes about how you have tested your invention using theory, as well as the steps you have taken to test the output of what you have created. These can be supplemented by electronic notes created with MS Word, and also saved as PDF files as well as spreadsheets you have developed to test the idea further.
  2. Describe of prior attempts to do what your invention does, and keep notes about why those prior attempts did not work.
  3. Keep notes about the alternatives to your invention, and descriptions about how your invention is unique. You should describe the advantages of your invention over the prior art and alternative approaches.
  4. Keep records about any discussions you have had about the invention with people outside of the immediate team working on your startup’s product.

Assuming it makes sense, you should discuss the possibility of obtaining international patent protection with your IP attorney. In certain instances it is possible to speed up a patent application in the founders’ home jurisdiction by first obtaining a patent abroad using the Patent Cooperation Treaty (PCT) between different jurisdictions. You should ask your attorney about this, and come up with a strategy that works given your specific circumstances.

Here’s one illustrative example:

A startup founder in the United States must decide how to protect her idea with a patent. If she files in the US it will likely take 5 years or more before the patent is granted. If she files in the UK the wait is much shorter, 2 years or less before she may expect to be granted the UK patent. What should she do? She would like to obtain patent protection in the US and the UK since she believes these are her startup’s two most important markets. She should ask her patent attorney about using the PCT and Fast Track Examination under the Patent Prosecution Highway (PPH) to speed up the process.

What is the PPH? According to the USPTO: “The Patent Prosecution Highway (PPH) speeds up the examination process for corresponding applications filed in participating intellectual property offices. Under PPH, participating patent offices have agreed that when an applicant receives a final ruling from a first patent office that at least one claim is allowed, the applicant may request fast track examination of corresponding claim(s) in a corresponding patent application that is pending in a second patent office. PPH leverages fast-track examination procedures already in place among participating patent offices to allow applicants to reach final disposition of a patent application more quickly and efficiently than standard examination processing.”

In the scenario I painted above, our founder should apply for the UK patent and then use that as the basis for requesting fast track examination of her US patent application at the appropriate time. In which case she might obtain her UK patent as well as her US patent within 24 months of filing her patent application in the UK; 18 months to get her patent granted in the UK and 6 months under PPH to get her patent granted in the US. Remember, I am not a patent attorney. Discuss this with you lawyer.

Trade Secrets: A trade secret is any confidential and non-public information that confers a competitive advantage on the owner of that information because of it is not known to the public, and especially because it is not known to competitors in that market. The owner of the information must make demonstrable effort to keep the information secret.

Trade secrecy can be lost by legitimate means, such as reverse-engineering by a competitor. Also, trade secret protection lasts for as long as the information remains confidential and undisclosed to the public. Any kind of information can be designated as a trade secret by its owner.

The key to maintaining trade secrecy is the creation of internal practices and procedures that are designed to protect the information designated as “trade secrets” from being divulged to the public.

The mystique behind the formula for Coca Cola is one famous example of a trade secret.

Trade secrets have the following advantages, among others:

  1. It is cheaper to obtain IP protection through trade secrecy than by going through the process of obtaining a patent.
  2. A trade secret can cover subject matter that would not qualify for patent protection, for example; mathematical formulae, algorithms etc.
  3. Protection of IP through trade secrecy comes into effect almost instantaneously, and that protection can last indefinitely if appropriate processes, procedures and practices are put in place.

Trade secrets have the following disadvantages, among others:

  1. As previously stated, trade secrets can be reverse engineered by others.
  2. Information protected by one party (A) could legitimately be “independently invented” by another party (B) which then proceeds to seek and obtain patent protection for the invention. In that case A would be in violation of B’s rights as the patent holder. I do not understand how this works in “first-to-invent” jurisdictions, so it is worth speaking with an attorney if a choice has to be made between trade secrecy and patent protection.
  3. Once trade secrecy is lost, it is lost forever.
  4. Trade secrecy provides a significantly lower degree of protection than protection obtained from holding a patent.

https://www.youtube.com/watch?t=216&v=AQpaKJjEQR8

Brand

Bottom line: To build a strong brand early stage startup founders must start by building a product that wins wide and sustained adoption by the market because the startup has intimate knowledge of its customers/users.

A startup’s brand develops primarily as its users and customers build an accumulation of experiences with its product or service over time. Ideally, these accumulated experiences should lead to customers and users having a positive affinity towards the product or service. The positive feelings that users or customers feel towards the startup and its product should be amplified through public relations, media and press commentary about the startup, community outreach, marketing, and advertising. Trademarks, copyrights, design, and iconography should all reinforce the positive emotions that the startup is accumulating within its users/customers towards itself. Lastly, knowledge that a startup has developed “trade secrets” which contribute to the pleasant experiences customers/users have each time they use the product/service can serve as a powerful source of implicit brand affinity and loyalty.

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Austin McGhie puts things succinctly in his book Brand is A Four Letter Word when he defines a brand as:

  1. “A brand is emotional shorthand for a wealth of accumulated or assumed information.” or
  2. “A brand is present when the value of what a product, service, or personality means to its audience is greater than the value of what it does for that audience.”

According to Heather Brilliant, Elizabeth Collins, and their co-authors in Why Moats Matter: “A brand creates an economic moat around a company’s profits if it increases the customer’s willingness to pay or increases customer captivity. A moatworthy brand manifests itself as pricing power or repeat business that translates into sustainable economic profits.”

Austin McGhie emphasizes throughout his book that a company’s brand embodies the market’s response to:

  1. The company’s product,
  2. The customer/user’s experience when they use the product, and
  3. The company’s marketing strategy, which should lead to a differentiated and valuable positioning of the company and its products relative to its competitors.

Early stage technology startup founders commonly treat marketing as an afterthought. That is a mistake. The excuse I have encountered when we discuss this topic is that there is insufficient capital for the startup to devote to marketing. The problem with that line of thinking is that it exposes a lack of imagination; marketing is not a one-size-fits-all proposition, nor does it always have to be expensive in order to be effective. Moreover, a startup’s founders are its most effective marketers in the very early days of its existence.

What should marketing look like during those early days when capital is scarce and the startup appears to lurch from one near-death experience to another? It should be a simple, uncomplicated strategy to:

Communicate to customers;

  1. What – What problem does the startup’s product solve for them?
  2. How – How is this better than the current alternative?
  3. Why – Why should they accept the risk that comes with trying a product from an early-stage startup? Why will they gain more than they stand to lose?

One complexity that early stage technology startup founders must contend with is that marketing in technology is multifaceted in the sense that there are numerous constituencies engaging with the startup’s marketing at any given time. Prospective customers want to know if they should switch to the new product/service. Investors want to know if they should make an investment. Potential distribution partners want to determine if there is a benefit for them in forming a partnership. Employees want to get a sense of how much job-security they can expect. Technology press and bloggers want to be first to scoop the next big thing. Regulators want to make sure that consumers are protected. Oh, and don’t forget competitors too. They’ll be paying rapt attention.

Research and Development

Bottom line: Research and development should purposely seek to strengthen the startup’s ability to win and retain customers, and increase profitability.

To understand why an early stage startup founder’s attitude towards research and development (R&D) matters, we first need to understand what it is.

Paraphrasing Investopedia, R&D is:

The set of systematic, investigative, and exploratory activities that a business chooses to conduct with the intention of making a discovery that can either lead to the development of new products or procedures, or that can lead to an improvement of existing products or procedures, and in the process create better ways of solving customers’ problems, creating new profit opportunities for the business.

Notice the key elements of R&D:

  1. It is systematic, investigative, and exploratory – it seeks to expand the boundaries of organizational knowhow and organizational capacity.
  2. It seeks to solve customers’ problems in a better way than the status quo.
  3. It seeks to create new opportunities for the startup to make profits.

For those reasons, R&D is one important means by which any organization that operates in a competitive market can create an enduring competitive advantage for itself.

There is only one valid definition of business purpose: to create a customer.

– Peter Drucker

If you agree with that definition, then it follows that activities that make a startup more likely to create and hold onto new customers must be pursued. Those activities are what we call R&D.

Research demonstrates the important role that R&D can play in investment returns:

In this paper, we examined the future excess returns of R&D intensive firms. Firms with R&D intensity measure greater than (lesser than or equal to) that of the industry are classified as Leaders (Followers). We show that Leaders have sustained future profitability. However, the future risk-adjusted excess returns are higher for Leaders than Followers, suggesting that the stock price does not incorporate the R&D relevant information in a timely fashion. We then directly examine the difference across Leaders and Followers of two risk measures: stock return volatility and future earnings variability. We find that Leaders have lower stock return volatility and earnings variability, ceteris paribus. We then examine whether the financial analysts’ help mitigate the apparent lack of information with respect to R&D, and find that even though the longterm earnings growth estimates for Leaders is high, they revise these estimates downwards perhaps as a reaction to short-term earnings. Overall, it appears that the stock market does not incorporate the Leaders’ potential for sustained future profits as argued in the strategy and economics literatures.

– Baruch Lev, Suresh Radhakrishnan, and Mustafa Ciftci. The Stock Market Valuation of R&D Leaders ((Lev, Baruch and Radhakrishnan , Suresh and Ciftci, Mustafa, The Stock Market Valuation of R&D Leaders (March 2006). NYU Working Paper No. BARUCH LEV-15. Available at SSRN:http://ssrn.com/abstract=1280696))

So what does this mean for early stage investors? All else equal, invest in startup founders who show indications of being capable of building organizations that will become R&D leaders in the markets in which they have to compete.

How might one go about assessing this? How often in the past have the founders’ started with the same information as everyone one else, but examined it in a way that led to unexpected results that proved to be correct and so enabled them to exploit an opportunity others ignored or did not know existed?

Culture and Management

Bottom line: The early stage startup founders who excite me the most have convinced me that they know how to build an organization that will become exceedingly more valuable than the sum of its parts. They must inspire excellence from their co-founders, from other early team members they recruit to join the startup, and they must inspire devotion from their early customers.

Does the startup’s culture, and the assumptions that its founders make about the core assets it should acquire and how it should be structured as an organization lead to an overwhelmingly positive reaction from the market and from its customers?

One aspect of seed stage investing that I feel is not sufficiently discussed explicitly is how much of a bet seed-stage investors are taking on the founders’ decision-making skill as managers of entrepreneurial risk, and the assumptions that drive those decisions.

What are the kinds of decisions seed-stage investors are betting founders will make, and make correctly on a consistent enough basis to yield a return on the investors’ capital?

Below, I paraphrase some definitions of an entrepreneur to help highlight this idea.

Jean-Baptiste Say: An entrepreneur shifts resources out of an area of lower productivity and into another area of higher productivity and return. (1800)

Frank H. Knight: An entrepreneur is someone who confronts a business challenge and is confident enough to risk financial loss in order to overcome that challenge. (1921)

Joseph Schumpeter: An entrepreneur is someone who exploits market opportunities through technical and organizational innovation. (1965)

Peter Drucker: An entrepreneur is someone who always searches for change, responds to it and exploits it as a business opportunity. (1970)

Robert Hisrich: An entrepreneur is someone who takes the initiative to organize social and economic factors of production in order to create something unique that is of value to society, and accepts financial and social risk in the process. (1990)

In some cases, including the entrepreneurial context, uncertainty includes not only uncertainty about others’ actions, but also uncertainty regarding the courage and willingness of others to act.

– Ross B. Emmet, Frank H. Knight on the “Entrepreneur Function” in Modern Enterprise (PDF)

What are some of the decision-making pitfalls that can cause the failure of an otherwise promising seed-stage startup? I’ll list some examples I have encountered since 2010.

  1. Insufficient focus on the customer, too much focus on the technological innovation.
  2. Sub-par outcomes regarding recruiting great people, and empowering them to bring the founders’ vision into reality.
  3. Inability to think creatively about new organizational designs and structures that will yield better insights about shifts in the expectations of existing customers, the potential pockets of potential new customers, and opportunities that might be going unrecognized by competitors.
  4. Incongruities between what the startup needs to accomplish in order to satisfy its customers and achieve product-market fit, and the choices that the founders make. For example, relocating the startup and its team to a geographic region that makes it difficult to reach its most promising potential early customers and makes it difficult to recruit the people it needs.

There are many others.

One problem seed-stage investors face in trying to sort founders who go on to build successful companies from founders who fail to get past the startup phase is that it is very hard to differentiate between skill and luck at that stage because the financial ratios and metrics that one could use to make that determination do not yet exist. Managerial decision making skill only reveals itself over time.

So what is a seed-stage investor to do? Study the founders’ past accomplishments and try to determine which aspects of that track record result from decision-making skill. Isolate them from the other aspects of the founders’ past accomplishments that could be attributed to luck. Weigh those two things during the assessment of what that means for the startup. I try to provide sufficient time to observe founders’ decision-making skills and abilities before I have to make a final decision – individual skill matters just as much as collective skill. As a result I am interested in the role that each co-founder plays in the final outcome. For example, did the CTO fail to prevent the team from making an incorrect choice of the technology on which to build the product? If so, does the CTO take personal responsibility for that failing, or does the CTO attempt to pass blame and make excuses?

Culture is the way in which a group of people solves problems.

– Geert Hofstede

It is also important to remember that the culture of a startup is determined predominantly by the attitude, behavior, and personality of the founders. In trying to understand the kind of culture that will develop as an early stage startup evolves I am interested in trying to understand if the following things are true.

  1. The founders are self-aware, and understand how their behavior affects the startup through the response it elicits from members of their team, from their early customers/users, and from their early investors. Example: They hire strong performers who have complementary skills, and they empower those people to excel.
  2. The way the founders talk about themselves and the organization they are building is distinctive, it illuminates the founders’ beliefs about the world, and about the reality they will create as a result of those beliefs. Example: No one could confuse this startup with another startup because the distinction between the two is unambiguous.
  3. The founders understand what they need to do to build a winning team. They also know why they need to do those things if they want their team to succeed. Example: They communicate clearly. They hold themselves accountable. They are adept at reducing harmful internal conflict. They promote and moderate the types of internal debate and disagreements that will help their team make better decisions. They motivate people to work hard, and in exchange offer fair reward and recognition for the hard work it takes to build the startup. They encourage experimentation, and learning from failure. They are great teachers, and great students. They bring out the best in others by inspiring great performance.
  4. The founders understand that culture is not something they can ignore until things are falling apart, rather it has to be tended continually. Culture matters just as much as engineering, sales, and other organizational functions that are much easier to measure and manage. Example: They understand that an organization with a strong culture is easier to manage, and often will have a longer period of sustained excellence than an organization with a weak culture.

Culture is the collective programming of the mind which distinguishes the members of one group from another.

– Geert Hofstede

Regulatory Environment

Bottom line: If it is appropriate I want to see some evidence that founders have an understanding of the role that regulations might play; will they be a catalyst or an impediment? What can the startup do to make regulations work in favor of the business model that the startup has set out to create?

I have to admit that this is the most difficult intangible for me to discuss for a number of reasons. First, I have relatively less experience on this subject than on the preceding ones. Second, it is such a specialized subject that it is most likely a function that will largely be outsourced to a lobbyist, at least in the United States. Last, this is unlikely to be something a startup needs to worry about until it has grown considerably, which is likely to happen well beyond the seed stage.

The regulatory environment is the framework of rules, laws, and regulations that the startup and its competitors have to adhere as they go about their operations.

Startup founders who can play a role in shaping the regulatory environment that is developed to govern their activities have a better chance of influencing events in their favor than founders who demonstrate an inability to influence legislation.

In the United States there are many examples of regulators requesting comment from participants in an industry during the period when rules, laws, regulations are being crafted to govern the activities of organizations within a given market.

It’s worth observing that the benefits of this asset accrue to every entity that decides to enter that market after rules have been established by regulatory bodies. As a result, first-movers who bear the cost of creating a favorable regulatory environment might be at a relative disadvantage to other organizations that decide to enter the market after a regulatory framework has been established since the first-mover would have borne all the social, political, and financial risks of putting the regulatory environment in place. In comparison to the first-mover, fast-followers get a free-ride.

Concluding Thoughts

Assessing intangibles and their potential impact on the future of an early stage startup is hard work that can seem to rely on information that is even more qualitative and less data driven than other aspects of early-stage startup analysis. Nonetheless, it is important to think through the issues carefully since that work can lead to important conclusions that highlight potential risks, point to future areas of opportunity, and yield better decisions about when and where the investor should deploy scarce capital.

Collectively, intangibles are important because once a startup establishes them as an asset, it is impossible for that asset to be replicated in exactly the same way by a competitor.

Additional Reading

Blog Posts & Articles

  1. Most Company Culture Posts Are Fluffy Bullshit – Here’s What You Actually Need To Know
  2. 80% of Your Culture Is Your Founder
  3. The Ultimate Guide To a Startup Company Culture
  4. Netflix: Reference Guide on Our Freedom & Responsibility Culture (PDF)
  5. A Summary of Peter Drucker’s Innovation and Entrepreneurship
  6. Peter Drucker’s Life and Legacy – A Drucker Sampler

Books

  1. Reinventing Organizations
  2. Delivering Happiness
  3. Work Rules
  4. Setting The Table
  5. Small Giants
  6. Good To Great and Built to Last (See also: Was “Built To Last” Built to Last?)
  7. Innovation and Entrepreneurship

Filed Under: Business Models, Entrepreneurship, Funding, Innovation, Management, Strategy, Technology, Venture Capital Tagged With: Brand, Business Model Canvas, Business Models, Due Diligence, Early Stage Startups, Economic Moat, Innovation, Intangibles, Intellectual Property, Investment Analysis, Margin of Safety, Persuasion, Strategy, Venture Capital

A Note on Startup Business Model Hypotheses

March 29, 2015 by Brian Laung Aoaeh

Light bulbs on Staircase

One of the observations I have arrived at over the course of meeting founders of early stage startups is that often it is not clear during our conversations if they have spent time examining the hypotheses that underlie the business model for the startup they are building.

This post ((Any mistakes in quoting from my sources are entirely mine. This post is an updated and adapted version of my posts The Startup Customer Development Model and Customer Discovery Phase I: State Your Business Model Hypotheses? which were published at Tekedia.com on September 3rd, 2012 and January 21, 2013 respectively. Large portions of this update are identical to the originals.)) is my attempt to outline some of the areas that I consider as I try to understand an early stage startup’s business model and the hypotheses that are the foundation on which its success must rest. ((I have adapted portions of: Chapter 2 and Chapter 4 of The Startup Owner’s Manual Vol. 1: The Step –by-step Guide for Building a Great Company, Steve Blank and Bob Dorf, Pub. March 2012 by K and S Ranch Publishing Division.))

To ensure we are on the same page, first some definitions;

Definition #1: What is a startup? A startup is a temporary organization built to search for the solution to a problem, and in the process to find a repeatable, scalable and profitable business model that is designed for incredibly fast growth. The defining characteristic of a startup is that of experimentation – in order to have a chance of survival every startup has to be good at performing the experiments that are necessary for the discovery of a successful business model. ((I am paraphrasing Steve Blank and Bob Dorf, and the definition they provide in their book The Startup Owner’s Manual: The Step-by-Step Guide for Building a Great Company. I have modified their definition with an element from a discussion in which Paul Graham, founder of Y Combinator discusses the startups that Y Combinator supports.))

Definition #2: What is a business model? A business model is the description of how a startup will create, deliver and capture value. Alex Osterwalder’s Business Model Canvas is one framework for describing and documenting the elements of a startup’s business model.

Definition #3: What is Customer Development? Customer Development is a 4-step process by which a startup answers the questions it needs to answer in order to find a business model that is repeatable, scalable, and profitable. Step 1 and step 2 of Customer Development cover the “search” phase of a startup’s life-cycle. Step 1 is Customer Discovery. Step 2 is Customer Validation. More on those a little later.

Definition #4 What is a hypothesis? A hypothesis is a statement, or a group of statements, that proposes an answer to a question, or a solution to a problem, in a manner that is testable through experimentation. The goal of experimentation and testing is to determine if the hypothesis is correct, and to inform the subsequent actions that the startup should take on the basis of that evidence.

Step 1 in the Customer Development Process: Customer Discovery – this involves translating the initial vision behind the startup into a set of hypotheses about each component of the business model. This allows experiments to be performed that either validate or invalidate each proposed hypothesis. In my experience the exercise of testing hypotheses about the business model with prospective customers accomplishes at least two things. First the startup entrepreneur gets to hear directly from customers about the elements of the business model’s value proposition that are most critical from the point of view of the startup’s customers or partners. Second it jump-starts the sales process even before the startup has invested much time or money into building a product. The founders of a hardware startup discussed their idea for an innovative new product with a potential partner. The partner’s input proved crucial in determining the direction they followed with regard to product design – it evolved from a product with one offering to one with three distinct but complementary offerings.

The revenue model also changed based on those discussions. Even better, the partner agreed to work with this startup to bring the product to market when it is ready. Obviously, there’s still a lot to be done – product design, product development and manufacturing for example. Yet those initial discussions have been critical in conferring the kind of credibility that has made it possible for the startup to seek an audience with other potential partners. Customer discovery for this startup also involved market research to determine the priority of features from the perspective of individual end-use customers – the men and women who might actually decide to purchase the startup’s offering once it becomes available to consumers.

Step 2 in the Customer Development Process: Customer Validation – this step proves that the work done in step 1 is easily repeatable, scalable, and capable of delivering the customer volume required to build a profitable company. The startup I described above is now building prototypes based on all the information it gathered during the Customer Discovery process. Eventually we will test our ability to deploy the product in the field – a few hundred first, then a few thousand, and barring any major setbacks, tens-of-thousands, then hundreds of thousands.

During that process we will test how well the back-end software works with the hardware that we have designed and manufactured once people are actually using the device. At each step I expect we will go back to the drawing board on several aspects of the product and the business model. For example, our pricing model may not reflect reality since our market research confirmed the hypothesis that our potential customers have never encountered a device like the one we are developing. We may discover that customers will gladly pay more for the value proposition we offer than we currently plan to charge. It is important to note that we have gone through a number of product pivots during Customer Discovery. For one, we made an incorrect hypothesis about the amount of space our partners would be willing to devote to this new device, never mind all the assurances they gave us during early conversations.

We also made a number of pivots in terms of the user experience and the interface through which users will interact with the device because we realized that a number of hypotheses we had made about certain design, engineering, and manufacturing issues related to the product were just flat out wrong. The product we will soon show to our partners satisfies the desires individual end-use customers told us they seek in a product like ours ((Market research involved nothing more than a description of the device. In other words, we relied on potential customers’ ability to imagine a future in which they could use the device we were setting out to develop.)), in a manner that accounts for the constraints our partners expressed they would eventually have to contend with in deploying the devices when they come to market. Moreover, this exchange of information led us to develop a product with performance characteristics far superior to what we would have achieved within the parameters of our previous vision. We expect to make a few more pivots before all is said and done.

Developing Hypotheses During Customer Discovery

The first step in customer discovery is developing a rough estimate of market size and sketching an initial business model for your startup using the business model canvas, which I have discussed in some detail in What is Your Business Model? Using the business model as a guide, develop a hypothesis brief for each component of the business model canvas. A hypothesis brief should contain a succinct statement of the hypothesis itself as well as a sufficiently detailed but brief outline of the information that makes the hypothesis a reasonable and valid one for that business model component.

The market size hypothesis is probably the most critical, even though it does not correspond directly to any of the business model canvas components. Investors like to back companies that target potentially large markets. At the same time, be careful to differentiate the total addressable market opportunity, the serviced addressable market, and your target market. Needless to say, your initial target market will be the smallest of these three. In most cases a bottom-up estimate is better than a top-down estimate because it is relatively easy for an investor who wishes to do so to replicate a bottom-up estimate. Whereas, a top-down estimate could be viewed as “hand-waving” with no basis in reality.

The value proposition hypothesis should discuss the problem your startup solves for its customers. A segment of this brief should capture product features, and a minimum set of initial product features that early customers would be willing to pay for. This is the minimum viable product, a bare-bones version of your product that solves the “core” problem your customers face. Put another way, your minimum viable product is the least developed product that you can create in order to validate your most important hypotheses about the problem you are solving and what your customers or users will accept.

The customer segments hypothesis forces you to answer the questions “Who are my customers?” and “What problems do my customers face?” The hypothesis brief should discuss customer problems, types, and archetypes respectively. Understanding “a day in the life” of your typical customer is a powerful way to understand your startup’s customers. Finally, Steve and Bob suggest you develop a customer influence map. There is an important aspect finding customers that can be overlooked. What is the smallest group of customers that is experiencing the pain or problem you are solving most acutely? Perhaps they do not have enough money to be attractive to incumbents. Or, perhaps they are a niche that is considered weird and unprofitable by your competitors. Start your experiments there. Why? If your product indeed solves their problem, they will adopt it quickly. On the basis of broad adoption within that niche, you can plot a path to other communities of customers who are facing the same problem. In other words, find the groups of people who will be your “Innovators” and “Early Adopters” and focus your early efforts on those groups.

The channels hypothesis should differentiate between physical, web, and mobile channels. An important consideration during the development of this brief is whether your product fits the channel. At this stage it is important to pick the channel with the most potential and to focus on gaining customers and cultivating sales through that channel to the near exclusion of every other alternative. With very few exceptions, since you are still testing your hypotheses, developing your business model, and determining what product is best positioned to solve your customers problems avoid the temptation to launch via multiple channels.

I was having lunch with the founder of an early-stage startup on Thursday, last week. She was giving me an update – the struggle to raise seed capital from investors, what she’s learning about building a team, and so on. We got to talking about how she would distribute her startup’s MVP. Her initial plan would have cost her a lot of money – capital she can’t afford to spend and a significant portion of the round she’s trying to raise, because she was thinking about traditional channels – the most obvious route to the customers she thinks she needs to get to. I pointed out that without further testing, she was taking a very risky gamble whose most likely outcomes do not favor her startup. Instead I suggested she spend the least amount of money she can to test non-traditional channels, and maximize the yield from those avenues before she does anything big and splashy through traditional channels. In this example, her hypothesis was poorly formed because it failed to take her startup’s capital constraints into full consideration.

The market-type and competitive hypothesis discusses the nature of the market into which your startup is entering and tries to anticipate the competitive landscape of the market that you will be attacking. You might consider it the second half of the value proposition hypothesis – your product solves a product for a group of customers, or a market. In broad terms a market already exists, or your startup is creating a completely new market where none existed previously. Your market entry strategy will depend on the market type you identify, as will your cost of entry into that market. In an existing market, your startup will have to position itself against the competition in a manner that ensures it can win given the basis upon which you have chosen to compete.

The customer relationships hypothesis describes how you get, keep and grow your customers. It is similar to the LBGUPS model, which I discussed in What Is Your Business Model? There’s no need to emphasize that this is an important hypothesis brief – without customers or users your startup will die a not premature death. How you get, grow and keep customers is very channel dependent. Your analysis should take that into account, and should also factor in related costs.

The key resources hypothesis discusses how you’ll obtain resources that are critical to your startup’s operations but that you do not have within the startup. These resources might be physical resources, financial capital, human capital, or intellectual property. In each case it is important to list the resource and an outline of how it will be secured to enable the startup run its operations. For example, servers can be rented in the cloud at a cost that is lower than managing your own server. Another example, a first-time founder who does not yet have a technical co-founder might partner with an outsourced software development shop to build and MVP with which to run some experiments. Often the devshop will remain as a service provider till the startup becomes self-sufficient enough to bring that work in-house. I have a bias for startups that control their intellectual property.

The key-partners hypothesis describes the partners that are essential to enabling your startup to succeed. It also describes the value-exchange that keeps the partnership alive. For example, a startup might have all its development and design work done by a software engineering consulting firm established for that specific purpose. In this case the startup pays the software engineer money in exchange for software engineering related to its product. Key-partner relationships might take the form of a strategic alliance, a joint new business development effort, a key supplier relationship, or co-opetition. Certain of these are more common early in the startup lifecycle, and others are more common late in the startup lifecycle. It is important to realize that a partner should not have control over anything that is critical to your startup’s ability to exist and do business.

The key activities hypothesis summarizes your startup team’s understanding and assumptions about where its energies should be most focused in order to create the most value for its customers. These are those activities that you feel cannot be left to one of your startup’s key partners. For example, a hardware startup might view design as a key activity, while assembly is left to a manufacturing partner in a low-cost manufacturing jurisdiction.

The revenue and pricing hypothesis brief is important because it ensures that the startup can extract value for itself and its investors. It asks a number of simple questions all related to revenue. The nature of the specific questions asked depends on the channel, but the essence of those questions remains the same. Together they should enable you determine if there’s a business worth pursuing along the path you have chosen for your startup.

The cost structure hypothesis brief forms the second half of the value extraction hypotheses – the first being the revenue and pricing hypothesis. Your startup’s cost structure must ensure that it can effectively deliver on the value proposition it has promised customers, and keep a portion of the revenues that the startup cultivates in the form of profits. Here too the questions asked will be relatively simple, and will reflect the channel and the market type. For example, a startup whose only channel is the web will have a lower cost structure than one with a physical channel.

Once your hypothesis briefs are complete, your entire startup team should discuss the output. Seek contradictions, conflicts and inconsistencies. The most important reason for developing these hypotheses is to ensure that the actions that your startup is taking have the highest probability of yielding success that is possible.

During my conversations with founders I listen carefully to determine if the startup has thought about these issues, or is thinking about them – it depends on the stage. I become concerned when I get the sense that important questions have been left unasked and unanswered.

Filed Under: Business Models, Customer Development, Entrepreneurship, Funding, How and Why, Innovation, Lean Startup, Long Read, Startups, Venture Capital Tagged With: Business Model Canvas, Business Models, Due Diligence, Early Stage Startups, Persuasion, Pitching, Venture Capital

What Is Your Business Model?

February 1, 2015 by Brian Laung Aoaeh

“It is a B2B2C business model.” is generally not what I am hoping to hear when I ask “What is your business model?” #BusinessModelGeneration

— Brian Laung Aoaeh (@brianlaungaoaeh) February 2, 2015

Invariably, when I am meeting the founder of a startup for the first time to discuss the possibility that KEC Ventures might invest in their startup I ask this question; “What is your business Model?” ((This post is an updated version of 4 separate posts authored by me, and first published at Tekedia between Sept. 18th, 2011 and Oct. 30th, 2011. Any similarities between this article and those posts is deliberate.))

Typically, the response I get is unsatisfactory. In this post I will discuss what I expect startup founders to include in their answer.

To ensure we are on the same page about what a startup is, I will begin with a definition; A startup is a temporary organization built to search for the solution to a problem, and in the process to find a repeatable, scalable and profitable business model that is designed for incredibly fast growth. The defining characteristic of a startup is that of experimentation – in order to have a chance of survival every startup has to be good at performing the experiments that are necessary for the discovery of a successful business model. ((I am paraphrasing Steve Blank and Bob Dorf, and the definition they provide in their book The Startup Owner’s Manual: The Step-by-Step Guide for Building a Great Company. I have modified their definition with an element from a discussion in which Paul Graham, founder of Y Combinator discusses the startups that Y Combinator supports.)) As an investor, I hope that each early stage startup in which I have made an investment matures into a company.

That leads to another question; What is a business model According to Michael Rappa; “In the most basic sense, a business model is the method of doing business by which a company can sustain itself – that is, generate revenue. The business model spells-out how a company makes money by specifying where it is positioned in the value chain.” Alex Osterwalder and Yves Pigneur say that; “A business model describes the rationale of how an organization creates, delivers and captures value.”

Other definitions exist, but taken together, these two statements provide us with enough basis for understanding what we should expect to learn from an adequately developed business model.

The business model should tell us how the entrepreneur expects to create value. To do this, the entrepreneur must decide what activities are core to the business the entrepreneur wishes to start. The question of how the entrepreneur creates value is also important because the answer to that question will often contribute to an understanding of the customer base that the business can expect to rely on.  This might seem trivial at its face. It is not. Understanding the customer base for which the business expects to create value is central to many other decisions that the business will have to make as it matures and approaches the launch of its product or service on the market.

Our definition of a business model raises a second question; how does the startup deliver value? I expect the startup founders I meet with to have started thinking about the process by which the value that the startup creates will be delivered to its target customers.

Given a reasonably well defined customer value proposition, our entrepreneur must now decide how that value is going to “be put in the hands” of the people that will become customers of the startup. The process of delivering the product or service that the entrepreneur has developed involves several distinct phases; Learn, Buy, Get, Use, Pay and Support. Employees of AT&T are believed to have developed the acronym LBGUPS (pronounced ELBEEGUPS) as a means of remembering the phases of this process as it relates to AT&T’s products. It is most effective to think of LBGUPS as a continuous, circular, and repetitive process.

  • Learn – when new customers first become aware of the product or service and acquire information and knowledge about how they may benefit from its use. Typically the startup accomplishes this through some sort of marketing, sales and public relations activity.
  • Buy – when customers decide to make a purchase after having learned about the new offering and communicate the desire to act on their decision to someone in a position to initiate the next phase of the process.
  • Get – when customers actually take delivery of the new product. This might happen in a physical or virtual store. It might involve shipping the product to the customer. If the customer is buying a service then this typically happens in person, or the service could be delivered remotely.
  • Use – when customers actually use or consume the product, or benefit from the service.
  • Pay – when customers pay for the product. This might happen simultaneously with buy. Sometimes there’s a time-lag between buy and pay – for example, in a fine dining restaurant a guest dines before before paying for the meal.
  • Support – when customers are provided with additional information that is aimed at resolving any problems they may have encountered during any of the preceding phases. Support should serve as an opportunity to encourage customers to remain, or to come back the next time they need to purchase a similar product or service. This is the role of technical support, customer service and customer relations. Done well, support should lead right back to learn.
How will your startup deliver value?
How will your startup deliver value?

Every startup must ask, and find answers to a number of questions while going through the process of delivering value to customers. What is the most effective channel for marketing, advertising, public relations, and sales? Where should we place our product or service in order to enable evaluation by potential customers as they make the buy decision? How do we put the product or service in a customer’s hands once that customer has made a purchase? What do we need to do to ensure that the customer uses our product after they have bought it and we have delivered it? How do we ensure that our customers are paying us, in full and on time? What is the mechanism by which we get paid by our customers? What problems might our customers encounter, and how should we help them resolve those problems in order to ensure that they come back to learn more about our other offerings and buy more from us in the future?

Often, each question that the startup seeks to answer will give rise to other questions that must be answered as well. This process requires trade-offs. It might be too costly to attempt to exploit every possible marketing channel and so the entrepreneur must choose only a few out of many. An over elaborate support structure might prove too expensive to maintain over the long term. Also, that might create bad-habits that the startup’s revenue structure has not been designed to carry without tipping the company into a position where it is experiencing difficulties, this touches on the issue of pricing.

Next, let’s examine the third question that our definition of a business model raises; How does the business capture value? A startup founder should be able to describe how the startup will create value, deliver that value to its customers and in-turn capture some value for itself and its investors.

Michael Rappa’s statement about business models emphasizes the importance of revenue streams. Revenues comprise the cash that a startup’s customers exchange for the product or service that the startup provides. In the process of this exchange, a transfer of ownership or usage rights takes place – in an outright sale, the customer assumes ownership. In a lease, licensing or rental agreement ownership remains with the seller, but the buyer is granted usage rights for a contractually agreed period. Revenue streams can be one-off or recurring.

I have no argument against the suggestion that startups should focus keenly on developing and growing revenue streams. However, my experience has taught me that startups must focus equal attention on profit, and on the related issue of costs.

Why?

In order to reach self-sustaining growth, a maturing start-up must quickly put itself in a position to invest in areas that are critical to its ability to create and deliver value to its customers – it has to invest in those assets that make its revenue streams possible. Costs represent the price the company pays to obtain the resources it must bring together in order to create and deliver value to its customers. A business earns a profit when its total revenues exceed its total costs. A successful business model should lead to an outcome in which customers perceive the entrepreneur as adding value. They demonstrate this by paying more for the product than it cost the entrepreneur to produce it – leading to a profit for the entrepreneur.

Earning a profit makes it possible for the startup to invest in the assets that are most critical to its ability to create and deliver value. Controlling and managing costs effectively while growing revenues will ensure that the startup maximizes its profit.

How will your startup capture value? You should be able to describe how your startup will grow revenues, manage costs, invest for growth, and maximize profits. This is not a static process. It should be dynamic and ongoing. Your startup will not be operating in a stagnant market. Therefore, your product and pricing strategies will need to adapt from time to time in response to competition as well as other market forces.

Also, depending on the stage at which KEC Ventures is considering an investment, it might not yet be clear which revenue model will work best for the startup. A seed stage startup might not yet have settled on a revenue model. A startup to which we are speaking about a series A financing should have some well formulated ideas about its revenue model, and in fact should be running some experiments to validate its hypotheses. An existing startup in our portfolio in which we are contemplating making a follow-on series B investment should most certainly have settled on a revenue model, and be in the process of scaling the business model in a repeatable, and profitable way.

I will end this discussion with some related observations;

First; It is often tempting to assume that one startup can simply copy or imitate the business model of one of its competitors. That may work in the short-term. In my opinion that is not an approach that confers a lasting competitive edge, certainly not in fledgling markets and industries, and often not in mature industries either. An important aspect of business model development is the deliberate and conscious selection among a number of alternative choices regarding product design, customer development, revenue models and cost structure; the wholesale copying of a business model simply because it has worked for another startup suggests the entrepreneur has abdicated responsibility for understanding the dynamics at play in each of those critical areas. That is a recipe for a failed startup adventure in which I am not eager participate.

While I oppose the wholesale copying of a business model that someone else has developed, I am a strong proponent of learning from the experience of other startups – the successes and the failures. There is real value in knowing what has ensured that some startups thrive. There is even more value in knowing what has proved fatal to others.

Second; It might take several attempts before a startup discovers the business model that works best – reflecting an industry in its earliest stage of development. Even then, the business model must evolve with the passage of time. Technology changes. Labor markets shift. National economies expand and contract. Opportunities not present in the past will present themselves in the future. Competitive threats that did not exist at the time the startup was formed appear as soon as other individuals notice a new chance to earn economic profits. Regulations emerge as a result of changes in political mood. A business model that does not adapt and evolve reflects a startup founder who does not grasp the nature, extent and complexity of the numerous challenges that lie ahead. Such founders, and the startups they are building, are bound to fail.

Third; The business model is not the business plan. Your business plan should certainly discuss your business model, yet the two are distinct and different. The business model is a framework within which the startup’s activities occur. The business plan is a document whose main purpose is to serve as a record of the startup’s goals, the reasons why those goals make sense and can be achieved, the manner in which the goals will be accomplished and the timeline within which the startup expects to implement its plan – presumably the plan is to become profitable as soon as possible within the tenets of the business model.

I am a fan of The Business Model Canvas. In fact, I use it each time I sit down to study a startup in which I believe KEC Ventures should invest. Using it ensures that I understand the business model, that I understand the risks that might lie ahead, and that I am comfortable that the startup indeed has found an opportunity to create, deliver, and capture value.

Filed Under: Business Models, Entrepreneurship, How and Why, Innovation, Long Read, Pitching, Uncategorized, Venture Capital Tagged With: Business Model Canvas, Business Models, Due Diligence, Early Stage Startups, Investor meeting, Long Read, Pitching, Value Creation, Venture Capital

The Most Important Thing A VC Needs To Know About Your Startup

February 12, 2014 by Brian Laung Aoaeh

Over the past 6 months I have been spending more time meeting many first time founders in New York City and elsewhere. One question has arisen over and over again. What are the most important things a venture capitalist wants to know about my start up in order to invest? I will attempt to answer that question in this post. ((Any errors in appropriately citing my sources are entirely mine. Let me know what you object to, and how I might fix the problem. Any data in this post is only as reliable as the sources from which I obtained them.))

To set the context, I am assuming that the potential investor and the entrepreneur are meeting one another for the first time, and that the startup is an early stage startup raising a seed or series A round of capital. There are still numerous questions to be answered, but the entrepreneur has made some progress and is well beyond just having an idea. There’s a product that is in a really early iteration and has had some user testing, but is still far from “perfect”. The startup has already raised some capital from friends and family, and subsequently from angel investors.

Some of my comments are directed towards startups building products for enterprises, but the same logic applies to startups building products for individual consumers.

First, as the potential investor, I want to understand the market in which you think your startup will exist. ((In this blog post from July 2007 Marc Andreessen argues that the market is the only thing that matters: http://pmarchive.com/guide_to_startups_part4.html)) I want to know as much about that market as possible. How many potential customers are there? How much did those customers pay in the past year for solutions to the problem you are solving? If this is a small but growing market, at what rate is that  growth occurring? How do we know that? If you are trying to convince me that you will somehow “grow the market”, how will that happen? How big is the market today? I would much rather bet on an entrepreneur building a product for a big market. The bigger the market the better. What is the current market structure? Who are the biggest incumbents in the market? How might they respond? What barriers to entry do you have to overcome? How difficult is it going to be for you to reach potential customers? ((In this blog post from December 2013 Rob Go describes why the choice of market is important: http://blogs.hbr.org/2013/12/great-entrepreneurs-pick-great-markets/))

I want to understand the market because it is the most important factor in determining the success or failure of your startup. A great market is one in which customers will find you if your product works. They might complain that the product could be better and they might ask for more features, but if it works they will find you and they will buy your product. In a bad market your product is irrelevant. If you are selling to an industry with very thin profit margins, there may simply not be enough money available for additional expenditures on a new product. Also, it is very hard to displace a product that your prospective customers have learned to use and around which they have built their business processes.

Closely related to my questions about the market, I want to understand the problem that you are solving for that market. Too often I meet founders who are unable to succinctly and clearly describe the problem they are solving. In a typical week I speak with many founders about their startups. The startups I most easily remember are those that make it easy for me to understand the problem they are solving. It is important that I have a firm grasp of the problem the entrepreneur is solving. Why? My understanding of the problem will direct how I perform my independent research. It will also ensure that I study the information and data that I find on my own from a perspective that is congruent with the point of view of the entrepreneur.

Second, I want to know if the founder or founding team has an ability to learn. I am certain that the founder will encounter many unfamiliar questions in the future if the entrepreneur is building something truly unique and solving a problem that has not yet been solved by someone else. It is important that the founder is someone who can gather unfamiliar information, process it, interpret it and then make decisions about strategic and tactical choices. A founder who lacks the ability to process large amounts of unfamiliar information quickly but thoroughly is at an extreme disadvantage. Market structure changes. Regulations change. Consumer tastes and preferences evolve in ways that might escape notice till it is too late and business has deteriorated. Technology changes constantly. The economy shifts between upswings and downturns. Rivals and competitors enter the scene without warning. All this generates volumes of information and data. I much prefer to back founders and entrepreneurs who I believe possess an inherent ability to learn. It is equally important, that they can build teams around them of people who have this same quality. It is the only way that their startup will move from the early stages of its lifecycle and into the growth phase. ((In this blog post from January 2014 Brad Feld reflects on his strong preference for CEOs who are learning machines: http://www.feld.com/wp/archives/2014/01/invest-ceos-learning-machines.html))

You will often hear venture capitalists say that they consider things in this order; market, product, team, and deal. Their analysis of the market and the product belong in the same category as the first factor in my preceding discussion – market. The question is this; is this a great market, and will someone pay to use this product in that market? Their analysis of the team falls under the second factor – is this a team that can learn what it needs to learn in order to succeed?

Every other question is simply an attempt to fill in the details.

 

Filed Under: Entrepreneurship, Innovation, Pitching, Venture Capital Tagged With: Due Diligence, Early Stage Startups, Investor meeting, Pitching, Venture Capital

Ceteris Paribus: When A Startup’s History Really Matters

August 18, 2013 by Brian Laung Aoaeh

Once in a while I meet a startup that makes me scratch my head in bewilderment. At first glance everything looks fine, but I can’t help but wonder if I might be missing something. In such instances I think to myself; Is there some important detail that is not so obvious, and that is concealed such that my normal due diligence efforts might not be enough?

I am not suggesting that anything is concealed in an attempt at dishonesty. It is just that under normal circumstances certain pieces of information do not seem relevant and so for purposes of brevity, such information is excluded from the information that is shared with potential investors. ((For example, decisions made 3, 4 or 5 years ago might not be explained in any great detail in the due diligence documentation.))

Historical analysis can prove useful under such circumstances. ((One might describe this line of analysis as a forensic historical analysis. While the conclusions of this analysis are not shared with a court, the investor will use the results of this analysis to argue for or against an investment in the startup.)) What is a historical analysis? ((I am relying on a paper I wrote in my Global Perspectives on Enterprise Systems class at NYU Stern for inspiration. If you are interested you can read my analysis of Toyota and Deutsche Bank here: PDF – Ceteris Paribus, Does History Matter?)) The fundamental goal of a historical analysis is to understand if there are signs from the past in a startup’s existence that give some indication about what a potential investor might expect in the future. In my analysis I will be looking for patterns of past behavior, activity, choices and trade-offs that may affect the way the startup functions now, or how it might function in the future. An effective historical analysis must look at the startup’s history through various phases of its development. Such analysis must also study the startup’s leadership, how the startup has navigated various crises, its strategy, and its culture. ((Numerous academic studies suggest that a startup’s culture is directly and significantly affected by the behavior and cultural norms of its founders and the founding team.))

Historical choices have a direct connection to the strategic options that will be available to the startup. For example, historical choices affect operations, technology, and infrastructure. The capabilities that the startup builds internally versus the capabilities that it acquires through partnerships with external organizations are directly related to choices that were made in the past. Such choices directly affect where the startup faces the greatest risk and uncertainly in its business model. Certain past choices will constrain the startup’s ability to pursue new, previously unforeseen opportunities in the future, while other past choices will give it enough flexibility to make rapid adjustments to keep up with new developments in the market.

Most historical analyses look at events after the fact and mainly focus on connecting the dots between the past and the present. In the context of an investor studying a startup, connecting the past and the present is important, but more important is connecting the past with the present and then extrapolating to possible outcomes in the future. ((This is not as straightforward as it might seem. I attempt to study the question of relying on experience to predict a startup’s future potential here: Tekedia – How To Recognize, Hunt And Invest in Big-Game Startups.))

Here’s a list of questions that I might start with in conducting a forensic historical analysis. ((This only serves as a starting point. I would need to create a specific list of questions for each case.))

  1. What is the original hypothesis that led to the formation of this startup? How did that change over time? If it changed, why did it change? Has that shift proved to be one that will benefit new investors or is it one that will  be a disadvantage? What does that tell me?
  2. Given the amount of capital that has already been consumed by the startup, would one expect more or less progress than has already been made in solving the problem it set out to solve? Why? If less progress has been made than one would expect, is that a result of reasons I feel can be justified objectively, or did the entrepreneur make costly but avoidable mistakes along the way? How do I know that such mistakes will not be repeated in the future? What does this tell me? Are there signs to suggest this entrepreneur will continue to make mistakes that hinder the startup’s ability to succeed? Why?
  3. What promises did the entrepreneur make to previous and existing investors? Do those investors feel that the entrepreneur has fulfilled those promises? ((It is not enough to look only at financial returns, because past results might not be sustainable if the startup’s choices have locked it into a rapidly deteriorating position.)) How has the startup performed against its historical budgets and operating targets? What does that tell me about what I should expect in the future?

Many more questions need to be asked, but this is a good start. Ultimately, my goal is to decide if I should say yes or say no.

Filed Under: How and Why, Venture Capital Tagged With: Due Diligence, Early Stage Startups, Historical Analysis, Venture Capital

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