Original Air Date April 10, 2019
Original Air Date April 10, 2019
Original Air Date: November 18, 2019

Original Air Date – April 10, 2022
Original Air Date – March 13, 2023
Original air date May 13, 2023
It’s more fun to be a pirate than to join the navy.
Steve Jobs
Entrepreneurship is the creation of a new economic entity to do a job in society.
The hallmarks of entrepreneurship include a focus on solving a problem, creative exploration of solutions, experimentation to reduce uncertainty, formation and operation of a new organization, and dynamic planning based on new information. Skills in these areas are valuable not just in starting a new company, but in addressing new problems in existing organizations. Thus, many but not all of the elements of this handbook are relevant to those engaged in innovation within established enterprises.
Kerr and colleagues (2018) provide a comprehensive review of the academic literature on founder motives. (See “Notes” at the end of each chapter for links to references.) You can read that paper if you want to go deep. But, if not, here’s the TLDR. Founders are usually motivated by multiple factors to start businesses. These motives can be usefully divided into three broad categories: purpose, fun, and money.
Uma Valeti, a cardiologist by training, and founder of Upside Foods (formerly Memphis Meats), told me that he started the company because he wanted to detach slaughter from meat production. He recalled a birthday party he attended as a child in India in which there was a party celebrating life in front of the house, while others were killing an animal in back of the house. That event made a deep impression on him. Many years later when he worked on the technologies for growing human heart tissue in a medical context he recognized that his knowledge could be applied to another purpose in which he believed deeply. To pursue that purpose, he founded Upside.
Listen to some founder stories. A significant fraction will include phrases like “I had to do it” or “If I didn’t do it, who would?” or “I felt the world really needed this solution.” These are all expressions of purpose — a motive to create something new in order to provide a solution to a personally important problem to the world.
Steve Jobs said, “it’s more fun to be a pirate than to join the Navy.” That was certainly true for Jobs, but maybe not for you.
Some distinctive characteristics of the daily experience of being an entrepreneur include:
For me, these attributes are mostly positive, and my own skills and capabilities are pretty well suited for these aspects of entrepreneurship. Entrepreneurship also comes with some characteristics experienced as negative by some people:
On balance, most entrepreneurs seem to find the daily work of entrepreneurship fun, and preferable to working within an established enterprise owned by someone else. For some entrepreneurs, the adrenaline and satisfaction from the daily work of entrepreneurship is the most important motive for their career choice. For me, entrepreneurship has been personally demanding. I am extremely thankful to have been a full-time CEO when I was 39-43 years old. I’ve enjoyed being a part-time co-founder many other times. I’ve also been a business owner with ultimate responsibility for an established business for twenty years, but that has a very different stress profile from starting something from nothing. I do not need to have the experience of full-time founder and CEO again, and can get just the right level of fun without a lot of stress from being an investor and advisor.
The mean financial outcome for a capable and educated entrepreneur is likely a bit higher than for those who work in corporate jobs. However, the mean value masks a huge amount of variation. The modal and median outcome predicts that you will fail to realize significant value and would have been better off financially if you had kept your job instead of becoming a founder. Large financial payoffs are realized by a small fraction of entrepreneurs. In approximate terms, about 25 percent will do better than break even financially relative to staying on a traditional career path. About 5 percent of founders with your skills and capabilities will become reasonably wealthy (say USD 5-10mm after-tax pay out), and 1-2 percent will become downright rich (say USD 20mm+ after-tax pay out). For most people, the only way to have a decent chance at becoming wealthy in life (other than being born into it) is to start a business. But, it’s just a decent chance, say 10 percent or so, depending on your definition of wealthy. The probability distribution is also quite different for different types of ventures (more on that below). On the other hand, for most of you, the down side is not that bad. You had an amazing adventure. Worst case you gave up (a) savings worth a year or so of living expenses and (b) the opportunity cost of not having earned a market-rate salary for the years your business struggled. Then you went back to a regular job and did just fine. (See Botelho and Chang; and Amornsiripanitch et al. for a more comprehensive exploration of the implications for founders of returning to corporate jobs.)
I don’t have a large enough sample for statistical validity, but of the 100 or so Wharton alumni entrepreneurs I have followed closely or invested in, all live comfortable lives, take vacations, and send kids to college. Five-ish are what most would consider rich (e.g., USD 100mm+). Ten-ish are pretty wealthy as a result of entrepreneurship. Twenty-ish did just fine – let’s say better than having taken a corporate job. The other 65 percent would likely have been better off financially if they had devoted the attention they gave to their venture to a corporate job, and many of those are back working at such jobs.
If you really want to dig into the details on financial outcomes, the Angel List data is probably the best. An index of the available data is here:
https://www.angellist.com/blog-categories/data
You can find the data on venture returns here, from which you can impute a probability of a successful financial outcome.
https://www.angellist.com/blog/venture-returns
Angel List has also integrated its experience into a white paper here: https://angel.co/pdf/growth.pdf
Not all ventures assume the same level of risk and uncertainty.
Read this article from Outside Magazine about Steve Despain (or listen to the audio version of the story linked in the article). Steve is the founder of Firebox Stoves, a small business tightly coupled to his personal passions and lifestyle. What motivates Steve? How attractive is the Firebox Stoves business to you? (Here, I’m not necessarily asking you about your passion for the outdoors…but about owning and running a small business aligned with your passions.)
Now consider Blake Scholl (founder of Boom Supersonic). Here is an interview I did with Blake when he had just recently founded his company.
What motivates Blake? What does the financial payoff probability distribution look like for Blake vs. Steve? To make this concrete, what is the probability of a zero outcome for each? What is the probability of USD 100mm outcome for each? Estimate some probabilities in the middle, say USD 1 mm and USD 10 mm.
A key dilemma most founders make is to be rich or to be king. (See Wasserman for a full elaboration of the dilemma.) The skills and capabilities required to lead a large, successful organization are quite different from those required to kick start a new venture. Some founders, such as Bill Gates, Mark Zuckerberg, and Jeff Bezos, did just fine in making the required transition. More typically, a founder faces a dilemma. Do I prefer to retain full control and manage my own kingdom, even if small, or would I prefer to step aside if necessary to ensure a huge financial outcome for investors, including me. Founders do not have to make this decision on day one, but still benefit from thinking through their preferences in advance. A self assessment of your skills and capabilities, and your relative preference for financial success versus control, should influence the type of venture you start.
Founders are not typically kids. The mean age of founders of the fastest growing 0.1 percent of companies is 45. (See Jones, KIm, and Miranda.)
Founders do not require particular personality traits. No personality trait is predictive of success in entrepreneurship specifically, although the “big five” trait conscientiousness does predict career success more generally. (See Kerr, Kerr, and Xu.)
As long as you are not allergic to risk and uncertainty, your personality profile (e.g., introversion, agreeableness or lack thereof) probably does not disqualify you from entrepreneurship.
Every founder and every start-up is unique. Still, looking at the experiences of other founders can be instructive. Here is an unusually detailed analysis of how one founder spent his time in the first two years of his start-up.
Entrepreneurs often follow the hero’s journey and so their stories can be compelling. Take some time to immerse yourself in some entrepreneurial journeys. Select from the following options.
I know these films and books mostly feature white American males. (Chip Wars does feature Morris Chang, a Chinese-American entrepreneur, and includes mention of the remarkable contributions to the semiconductor industry of Lynn Conway, whose personal story as a transgender female is incredible.) If you have some suggestions for more diverse stories, please send them to me.
Interview of Uma Valeti, founder of Memphis Meats (now Upside Foods). by Karl T. Ulrich. SiriusXM Launchpad. February 28, 2017. https://shows.acast.com/wharton-entrep/episodes/uma-valeti
Mollick, Ethan. The Unicorn’s Shadow: Combating the Dangerous Myths that Hold Back Startups, Founders, and Investors. University of Pennsylvania Press, 2020.
Jones, Kim, and Miranda. https://ssrn.com/abstract=3158929
Wasserman, Noam. The founder’s dilemmas: Anticipating and avoiding the pitfalls that can sink a startup. Princeton University Press, 2012.
Tristan L. Botelho, Melody Chang (2022) The Evaluation of Founder Failure and Success by Hiring Firms: A Field Experiment. Organization Science 34(1):484-508.
Amornsiripanitch, Natee and Gompers, Paul and Hu, George and Levinson, Will and Mukharlyamov, Vladimir, “Failing Just Fine: Assessing Careers of Venture Capital-backed Entrepreneurs Via a Non-Wage Measure,” National Bureau of Economic Research Working Paper, No. 30179, June 2022. (Summarized by Harvard Business Review here https://hbswk.hbs.edu/item/why-a-failed-startup-might-be-good-for-your-career-after-all )
Azoulay, Pierre and Jones, Benjamin F. and Kim, J. Daniel and Miranda, Javier, Age and High-Growth Entrepreneurship (April 2018). NBER Working Paper No. w24489, Available at SSRN: https://ssrn.com/abstract=3158929
Kerr, Sari Pekkala, William R. Kerr, and Tina Xu. “Personality Traits of Entrepreneurs: A Review of Recent Literature.” Foundations and Trends in Entrepreneurship 14, no. 3 (July 2018): 279–356.
Angel List Power Law paper https://angel.co/pdf/growth.pdf
Most investors agree that the two most important factors in a decision to invest are the market size and the quality of the team. This chapter focuses on market size.
The most common ways to think about market size, and the estimates most institutional investors expect to see are:
Some investors, advisors, and entrepreneurs (including me), prefer to define an additional category, the beachhead market. Getting a company up and running is really hard. Going after the biggest market segment is not necessarily the best strategy. Often the biggest market segment will demand aggressive pricing and thus significant cost efficiencies. Most start-ups won’t be equipped to tackle the biggest segments from the start. A beachhead market is one that provides the easiest access, allowing the fledgling business to get started, to develop a little traction, to build some scale, and to refine its products. The beachhead market is always a subset of the SAM. The desirable characteristics of a beachhead market are:
The boundaries of these definitions are somewhat arbitrary, and so my primary recommendation is to be extremely clear about your definitions and careful with your assumptions. One of the biggest sources of delusion in entrepreneurs’ pitch decks is wildly unrealistic estimates of market sizes.
There are two ways to think about market definition and sizing, top-down and bottom-up. With the top down approach, start with all economic activity on earth – that’s the maximum size of the market for “do everything.” Then, successively narrow the definition of the market until you get to the “market for the job that we aspire to do in society.” That’s your total available market (TAM). Then, further narrow to markets for which you can offer a value proposition in the medium term with your solution – the serviceable addressable market (SAM). Then, further narrow to the first market segment you will focus on and for which you offer a value proposition — the beachhead market. Each narrowing is a defined subset of a larger market.
For example, let’s revisit MakerStock (originally described in the handbook as “University Panel Supply”).
The GDP of the entire planet (c2023) is approximately USD 100 T.
The subset of that GDP representing the market for plastic, wood, and metals used in making things, and excluding construction, is approximately USD 6 T.
The subset of that market for plastic, wood, and metal panels (e.g., large sheets of material) used in making things is approximately USD 700 B.
The subset of that market comprised of specialty plywood (which excludes softwood plywood used in construction), medium-density fiberboard, and acrylic sheet is USD 44 B.
The US portion of that market is USD 5 B. (Now we are focusing geographically.)
The US market for these materials in which the customer’s ideal format is a less-than-full-sheet custom size with delivery by conventional ground freight is USD 500 mm. This is the subset of the market for which a cut-to-size supplier of materials would offer a value proposition. This particular focusing step is where you might sense we are pretty much guessing. There is no place to look up market sizes for the “cut to size” panel market, and we are left to doing some back-of-the-envelope calculations. For this reason, top-down estimates become a bit shaky as additional focusing assumptions are made. Still, USD 500 mm is a reasonable estimate of the TAM for MakerStock — the market is certainly smaller than USD 1 B and it’s more than USD 100 mm. The definition of your TAM is somewhat arbitrary. For instance, this estimate of TAM is for the US only, but might we reasonably consider serving customers in Europe, for example? Given that many different assumptions are possible, just be very clear about the focusing decisions that underly your estimate of TAM.
MakerStock’s TAM includes cabinet makers and raw materials for factories producing finished goods in relatively large quantities. MakerStock is unlikely to be competitive for these segments in the medium term. The company is likely to offer a stronger value proposition to customers that prefer custom sizes and that order a variety of different materials, both wood and plastic, for use in their fabrication processes, largely laser cutting. The US market for such materials for university maker labs, do-it-yourself individual makers, and small- and medium-sized businesses such as sign making shops is approximately USD 100 mm. This is a reasonable estimate of the SAM for MakerStock.
Now, how will MakerStock get started? Where will it focus initially? MakerStock will focus on university maker labs. It will focus on those labs that can be served by FedEx ground freight within three days of Scranton, Pennsylvania. The beachhead market is for pre-cut specialty plywood, medium-density fiberboard, and acrylic sheet for university maker labs located within the three-day ground shipping territory from Scranton, Pennsylvania. Top-down estimates are going to be very approximate for the beachhead market. To do a top-down estimate, we might gather some estimates (guesses?) of a few knowledgable people and average them and assume that 10 percent of the SAM is the beachhead market, delivering a market size of USD 10 mm. Bottom-up estimates are much better for tackling this estimate, the approach I will explain below.
With each successive focus on a subset of a larger market, we are making a decision about which narrower market will be more readily addressable by the new venture. Each narrowing reflects a belief which may or not be correct. For instance, commercial sign makers may be a better beachhead market than university maker labs. So, as with any problem solving activity, considering alternatives and testing beliefs will likely result in better outcomes.
For the top-down approach, conventional internet search and current AI tools are probably the best source of raw data. By using a variety of queries and triangulating on the result, you are likely to be able to make estimates that are well within one order of magnitude of the actual value.
Estimating TAM and SAM requires that you assume some boundaries for your core business. For instance, if I conceive of my panel supply business as providing panels of any type to any user of panels globally, my TAM is USD 700 B. But I really have to stretch my imagination to believe I can address the need for particle board panels purchased by the Chinese factories that make the best-selling IKEA Billy bookcase. Those factories are likely purchasing many full truckloads of those panels per week directly from the mill that makes them. The definition of available and addressable determines your TAM and SAM. I like to think of addressable customers as those customers who have a job to be done for which the core business could reasonably be competitive in delivering a solution. For MakerStock, that core business is sourcing sheet goods by the full truckload, breaking the bulk delivery into sheets, cutting sheets to custom sizes, and delivering pieces by conventional ground freight. The job to be done is to deliver an assortment of the right materials, at the right time, in the right sizes, all with minimal fuss. The serviceable addressable market is the size of the market for which that value proposition makes sense, a market not of USD 700 billion but rather about USD 100 million.
The top-down approach is a useful way to put the business into a larger context, and to reveal possible additional market segments, and their sizes. However, the bottom up approach is usually more credible and less speculative. WIth the bottom-up approach, you start with a hypothesis about the beachhead market — the very first market you will tackle. You estimate the size of that market by creating an inventory of every potential customer in that market. This approach is called counting noses.
For example, the beachhead market for MakerStock is university maker labs located within the geographic region served by three-day ground shipping from Scranton, Pennsylvania, the initial location of the business. The business was located there because I as founder already had a facility and an available team member in that location, and because that location is a logistics hub, serving about one third of the US population within two days by conventional ground shipping. The geographic cut off reflects a belief that freight costs would be decisive in the value proposition to our customers.
Once that beachhead market is defined, counting noses is easy. First, there are about 5300 colleges and universities in the United States. Now, look up the ground delivery time map that FedEx provides. Identify those universities within the three-day shipping territory. That subset is about 2500 institutions. This set of 2500 potential customers can be identified and cataloged precisely and entered into a database. For each potential customer, say PennWest Edinboro University, an internet search can reveal whether or not it has a maker lab, and possibly unearth a name and contact information for the lab manager. In fact, an internet search for the PennWest Edinboro furniture design program yields a great description of the program, including photographs displaying specific details about the equipment and furniture in the shop. That search even produces a name of the program director, Karen Ernst, along with her contact information. We can now count Professor Ernst’s nose in our beachhead market. Doing a comprehensive search for all 2500 potential customers is probably not a good use of time until the business is actually launched, but doing that search for a sample of potential customers, say a hundred, produces an accurate estimate of how many labs would eventually be found in all 2500 universities. For this example, a preliminary search suggests that about 64 percent of these universities have at least one maker lab, a potential customer base of 1600 labs.
At this point, some assumptions are required about the average level of spending on speciality plywood, medium-density fiberboard, and acrylic by each lab. That estimate can be based on interviews with a sample of customers. By talking to about five potential customers, we found that the average spending seemed to be roughly proportional to the size of the university, with a university spending an average of about USD 4 on these materials per year per student enrolled. The labs serve an average of 1250 students each, so their average spending on materials is about USD 5000 per year. These figures lead to an estimate for the total size of the beachhead market of USD 8 million per year (i.e., 1600 labs at USD 5000 per year). This a pretty solid number. The real value might be USD 10 million or USD 6 million, but it’s not USD 50 million or USD 1 million.
Once you have identified and characterized a promising beachhead market, now consider the immediately adjacent markets. The adjacencies might be geographic. So, after considering colleges and universities in the northeast, consider those in the mid-Atlantic region, or the mid-west. The adjacencies might be in the goods and services offered, for instance extension of the product line from wood and plastic to metals. The adjacencies might be in the types of target customers, for instance from colleges and universities to secondary schools, or to small and medium-sized businesses using laser cutters. These adjacencies taken together comprise your SAM, as estimated using the bottom-up approach. As a matter of good planning hygiene, consider how your bottom-up estimate of adjacent markets compares with your top-down estimate of your SAM. These two ways of getting to SAM should not deliver wildly different results.

Recall that SOM is the market you plan to actually serve within your planning horizon, usually 24 or 36 months. For my taste I prefer estimating SOM with a bottom-up, counting noses approach of the beachhead market integrated with some estimates of the rate of customer acquisition of the go-to-market system.
Recall that we estimated that there are 1600 potential customers in this beachhead market. I believe we can acquire an average of two new repeat customer per week with the likely sales and marketing resources we will have, net of churn. (See the chapter on go-to-market systems for how to think about this.) Thus, within three years, we will have approximately 300 university maker labs as repeat customers. We estimated earlier that each lab orders approximately USD 5000 in materials per year. Thus the recurring revenue for the customer base at year three will be approximately USD 1,500,000 per year, at which point we will have about 19 percent market share of the beachhead market of USD 8 million. Of course, even though we will focus on the beachhead market, we will unavoidably reel in some customers from adjacent markets, and likely will also sell to some do-it- yourselfers via the MakerStock website. It’s even possible that an adjacent market will prove to be a better fit for the company than the beachhead market we had originally envisioned. Still, the bottom-up nose counting along with some realistic modeling of the go-to-market system is a grounded approach to forecasting the scale of the business.
None of you readers are too excited about recurring annual revenue from the beachhead market of USD 1,500,000 after three years. Investors likely would not be too excited either. Yet, that’s actually an above-average outcome for a start-up in year three. I have invested in over 50 start-ups. About five of those have achieved recurring annual revenue of USD 1,500,000 by the end of year three.
Every founder faces many dilemmas. One of the most pressing is whether to spin a compelling fable in the pitch deck, which probably represents a 95th percentile outcome, or to provide a realistic forecast of what you believe to be a highly obtainable outcome. I believe the level of conservatism in the forecast depends on the audience. If you are planning to be a closely held, bootstrapped, company, then you should strive for hard, cold realism, even pessimism. That was my approach with MakerStock. I funded the business with my own money. I wanted to have a realistic sense of how the business would unfold and how much cash I would need to burn to get to positive cash flow. MakerStock actually did substantially better than the forecast, largely because do-it-yourselfer and small- and medium-sized business customers turned out to be fairly easy to acquire and serve alongside universities. That was a pleasant surprise easily accommodated as the business developed.
If, however, your audience is institutional investors, then they are highly conditioned to see forecasts at about the 95th percentile. My advice is to be excruciatingly clear about your assumptions and logic in estimating TAM and SAM. Those need to be highly credible. Then, the estimate of SOM should likely skew a bit optimistic, assuming that you have all the resources you need, including that investor’s capital, and that things go well. Your SOM is going to be discounted by institutional investors seeing your pitch, so you should account for that fact in your presentation. (Yes, I realize this is a pernicious cycle of optimistic forecasting and assumed discounting by the investor. I don’t see a clear way around it.)
The most common way market sizes are shown in pitch decks is with nested circles, sometimes called an onion diagram, in which the area of the circle is proportional to the market size. Data graphic purists may prefer bar charts of some kind, but I think the nested circles work pretty well and you probably want to avoid bucking convention here. You can, of course, annotate this graphic heavily to support the numbers.

VC Factory Article on TAM, SAM, and SOM. Decent article from a venture capitalist’s perspective.https://thevcfactory.com/tam-sam-som/
This little piggy went to market,
Mother Goose
This little piggy stayed home,
This little piggy had roast beef,
This little piggy had none.
This little piggy went …
Wee, wee, wee,
all the way home!
Go to Market or GTM is a term of art originally used in the enterprise software industry in Silicon Valley. At first glance, you would understandably think the term referred to the activities a company takes to launch its product in the marketplace. The product is done, and then “this little piggy goes to market.”
But as used in Silicon Valley, go to market is better defined as:
The system by which a company transforms its addressable market into its customer base.
Another reasonable definition is:
How we convert a potential customer to a delighted customer.
Or even:
How we sell stuff.
(But, this last definition fails to emphasize the importance of deliberate management of customer success to ensure long-term value for both customer and supplier.)
GTM is an on-going operating system – an engine – which is developed, refined, and operated over the life of a product to grow revenue. In most settings, the GTM system is the second most important design challenge a new venture faces, closely following the design of the solution itself.
In some (relatively rare) settings the relationship between customer and supplier consists of very few transactions and a limited on-going relationship persists. For instance, one of my former students Ajay Anand founded Rare Carat, a marketplace for diamond engagement rings. Notwithstanding exceptional potential customers like actress Elizabeth Taylor who was married eight times, the modal number of transactions Rare Carat will have with a customer is one. Go to market for Rare Carat is pretty simple – gain awareness, encourage trial of the service, and convert trials to ring purchases.
At the other extreme are enterprise software companies like Salesforce. It may take significant effort to acquire a customer, but once acquired, that customer is likely to remain a source of revenue for many years.
Here are some of the activities that comprise the GTM system in many organizations:
Scaling a business requires efficient processes that can be reliably replicated. Just as an industrial process like making automobile tires could not possibly be scaled efficiently without a codified process, so a GTM System can not be scaled if not codified.
Although every GTM system is different to meet the specific needs of a company, two basic types of GTM systems are common: Product-Led Growth (PLG) and Sales-Led Growth (SLG).

An example of PLG is the video conferencing tool Zoom. Product situations for which PLG may be effective include:

An example of SLG is the human-resource management enterprise software product Workday. Product situations for which PLG may be effective include:
You can represent the GTM system with a GTM Canvas, a template which works for most settings. Here is a GTM Canvas as a Google Sheet. This is the GTM Canvas for the now familiar MakerStock example.

The backbone of the GTM System is the customer journey. To fill out the GTM Canvas, start with the customer journey.
The journey starts with the customer’s job to be done. The journey is complete when the customer is committed and delighted to be using your solution to do the job.
All customer journey’s include at least these touch points:
The development of key performance indicators (KPIs) for the GTM system begins with a metric for the desired result. For example, for MakerStock, the desired result is a satisfied customer, defined as:
MakerStock is the primary supplier of panel goods for the lab. The lab is purchasing in regular intervals with order sizes of at least USD 800. The institution has set up an account and is paying via bank transfer or check (to avoid credit card fees). We know the lab manager’s name and preferred mode of contact and have interacted one-on-one. The lab manager is highly satisfied with MakerStock’s services and would recommend MakerStock to others.
The KPIs for this desired result are the number of satisfied customers, the number of new satisfied customers obtained this week, and the average net promoter score (NPS) of satisfied customers.
KPIs should also reflect the state of the intermediate phases in the customer journey. For example, how many potential customers received a quote this week, and how many potential customers have received a quote within 60 days but have not placed an order.
Finally, KPIs should also reflect key actions that serve as inputs to the GTM system. For instance, how many outbound email inquiries to potential customers were made this week.
Ideally you will have just one GTM system, but will probably eventually have to create variants for very different segments. For each segment, proceed as follows.
Two complications are common in creating GTM systems: (1) platform and marketplace products and (2) multiple segments with multiple channels.
Platforms and marketplaces are sometimes called two-sided markets because they bring together suppliers of goods and services with consumers of those goods and services. The solution serves two very distinct types of customers and users. Some sales and marketing activities, such as general brand awareness, may serve both sides of the market. However, almost certainly, two very different GTM systems are required for two very different segments. The GTM systems can be conceived of independently. However, in operating the GTM systems, the two sides of the market must be kept is approximate balance — and so those responsible for the two GTM systems must coordinate with each other, and resources may need to be allocated dynamically across the two systems in order to keep supply and demand in equilibrium.
Good advice in general for new ventures is to focus on one beachhead market. In that case, the company will have just one GTM system. Inevitably some distinct market segment will emerge. Sometimes that segment can be accommodated with a variation on one or more steps within a single GTM. For instance, for MakerStock, the GTM system is designed for universities, but when a high school emerges as a potential customer, the GTM system can pretty easily accommodate it with some minor differences (e.g., awareness of summer shut down dates, central school district billing systems, higher price sensitivity).
Sometimes a new market segment is so different that it requires that the GTM system be forked. For instance, the do-it-yourself (DIY) consumer segment became important to MakerStock during the 2020, the year the Covid19 pandemic was most severe. At that time, the university GTM system was simply not relevant. Keyword advertising was the key mechanism for gaining awareness and trial for the DIY segment. The sales and marketing playbook for the DIY segment is so different from that of the university lab segment, that MakerStock created an entirely separate GTM system for that segment.
Complete a GTM Canvas for your new venture. Again, here is a template for the MakerStock example. (You will of course need to “make a copy” or “save as” in order to create your own version.) You need not use Google Sheets if you prefer some other tool (e.g., Miro).
Craft a one-slide description of your GTM system for the purposes of your pitch deck.
A pretty good free web-based “book” on GTM.https://unlock.survivaltothrival.com/
One of the most common challenges faced by founding teams is how to allocate equity in their enterprise. This is essentially equivalent to the challenge of how to value the different inputs required to create the product, service, or company. There are no predefined formulas, but basic economic logic applies here. This figure illustrates how value might be accounted for over the first three phases of a typical new venture.

Usually it is easiest to think about valuing inputs at each of several discrete phases. For example, at the beginning of the “Founder Phase” an entrepreneur has a business concept developed to some level of detail. The value of what the entrepreneur brings to the table at the beginning of the Founder Phase is labeled “IP contributed” on the figure and is shown in yellow. (Here I use the label IP to refer to all the intellectual property created to date, usually comprising business plans, technologies, and other information.) Over the duration of the phase, the venture will typically require two other inputs. One is cash, usually contributed by the founders. This cash is shown in green as “founder’s cash.” (This is usually a modest amount, typically $2,000 – $20,000.) The second input is the “sweat” that the founders commit to contribute over the phase. “Sweat” refers to the labor and ingenuity provided by the founders for which the venture does not pay them wages.
If the founders are successful in nurturing the business concept during the Founder Phase, they will have created some value and will usually seek additional investment. (The creation of value is reflected in the increased height of the blue bar. It is also possible, of course, that they will fail to create value, in which case the blue bar may decline in height.) The First Phase investment will usually be in cash (green) and in further sweat from the founders and some new team members (brown). Team members are almost never paid full market wages during the First Phase, thus they are still contributing “sweat.” The cash in the First Phase often comes from so-called angel investors, typically in amounts of $20,000 – 200,000.
If after the First Phase the venture still offers promise, the company may seek additional capital. For a few ventures this capital will be institutional investment from a Venture Capital fund, usually called the “Series A” investment. However, I refer to this phase generically as the “A Phase” whether or not investment is from a venture capital firm. At this point, members of the team and employees are usually paid something close to market wages. However, in most cases, the venture benefits from compensating members of the team in part with equity. I still refer to this as “sweat,” even though it might be more appropriately labelled incentive compensation. In most cases the sweat equity allocated in the A Phase is in the from of stock options, but for simplicity you can think of these options as an allocation of common stock to the team. Most investors expect to see about 10 percent of the total shares outstanding reserved for future incentive compensation. In almost all cases, institutional investors expect this 10 percent to dilute the existing shareholders and consider it part of the “pre-money” value of the business.
There are typically three inputs during the Founder Phase: (1) the IP created to date, (2) the sweat of the founders, and (3) cash. Of these three, only the cash is easy to value. A dollar of cash invested is worth a dollar. But, how do you value the sweat and the IP?
When you place a value on the sweat of the founders, you are essentially creating an equivalence between the cash contributed and the sweat contributed. In other words, an investor (usually one of the founders) who contributes $20,000 gets the same amount of equity for that contribution as someone who contributes $20,000 worth of sweat. In valuing sweat, I have usually taken the approach of estimating the opportunity cost of the time contributed by an individual and then applying a non-cash adjustment factor. For example, assume that during the Founder Phase, Billy will quit his job (or not take a job) foregoing $5,000 per month in income for the four months expected duration of the Founder Phase. Billy is contributing time with an opportunity cost of $20,000. From one perspective, he should get $20,000 worth of equity for his contributions, the same as a cash investor contributing $20,000.
However, I have often applied a “non-cash adjustment” factor to this sweat calculation. By that I mean that I have discounted the non-cash contributions by a factor before comparing them to the cash contributions. Here’s why:
Depending on how these factors play out in your situation, you will need to apply a non-cash adjustment factor to convert a dollar of opportunity cost of sweat invested to a dollar of cash invested. Having said all this, at the end of the day, the equivalence between cash and sweat is determined by an agreement between the individuals providing these different inputs.
Example 1: A new MBA graduate committing to work for a few months for sweat equity might forgo salary of $40,000. That would be equivalent to about $28,000 of after-tax income. This sweat should be valued the same as $28,000 in cash invested by another founder. (This salary would be for someone in a “normal” job. The masters of the universe who command seven figure salaries/bonuses as traders, etc. are not going to buy into this logic, and you probably don’t want them on your team anyway.)
Example 2: A freelance graphic designer who normally bills her time at $125 per hour agrees to provide 100 hours of sweat to the venture. This input would be valued at $12,500 at the marginal billing rate, but the designer is unlikely to actually forgo paying work to do this. The team agrees to value her time at one half of her billing rate, so this commitment of 100 hours would be valued at $6250 and she would receive as much equity as someone investing that much cash.
You can avoid actually putting a price on sweat if (a) you don’t need any cash, (b) all members of the team contribute equally, and/or (c) all members of the team contribute cash in the same ratios as they contribute sweat. Under those conditions you just allocate equity according the time people contribute. Such conditions rarely hold. Thus, at some point you are going to have to figure out what an hour of Billy’s sweat is worth relative to $1000 of Betty’s cash.
The short answer to how you do this is that it is a subjective judgment and/or the result of a negotiation between the original founder and the other members of the founding group. Some of the factors that influence the value of the IP contributed are:
I don’t think the originator of the raw opportunity would typically expect less than about 5 percent of the Founder-Phase Equity. I can also imagine an inventor of a new molecule with amazing properties and iron-clad patent protection to command 90 percent of the Founder-Phase Equity.
When dividing up equity for a venture, you benefit from making explicit what the different roles of the founders are and what contributions each will make. As an example, consider how Billy and Betty allocated equity for a venture that did not require significant external cash. Billy had invented a new device (let’s call it “The Widget”). Betty wanted to join in commercializing it. They agreed on the set of tasks that had to be completed. They then independently assessed who would do what and what each task was worth in “points.” (The total number of points ended up being, somewhat arbitrarily, 122.) In this case, they explicitly listed the work that had been completed to date, including the contribution of the “idea.” Remarkably, they agreed to a considerable extent on the relative allocation of points. Here is their actual spreadsheet. (“Billy” and “Betty” are pseudonyms, of course.)
There are two basic ways to grant equity to individual members of a venture team. You can grant them restricted stock or you can grant them stock options. Options are much simpler to administer, but as a founder you should avoid them if possible. Here’s why. First, an option is simply a right for a fixed period of time to purchase shares of a company for a predetermined price. If the share price increases, then an option holder can realize value by exercising the option. Options are rarely exercised unless the resulting shares can be sold for cash, as is the case for a publicly traded company or when a company is purchased by another entity. When you exercise an option and then sell the shares you acquire, any gains are treated as ordinary income. This will cost you at least twice as much in taxes than if you were taxed at the long-term capital gains rate. Second, options expire, usually just before they have any value. Third, options are hard to value. Most employees are clueless about valuing their options, pretty much ignoring the exercise price (the “strike” price) in their feeble mental accounting. Of course, as an evil manager, you could use these facts to your advantage and offer options to your employees in an effort to avoid sharing the wealth.
Restricted stock is a much better way to go for core members of the founding team. Restricted stock carries with it some, ahem, “restrictions,” meaning typically that it has a vesting schedule that determines when, if ever, you actually have the full rights of ownership of the stock. Because of the restrictions, the IRS allows the stock to be valued at substantially below the fair market value of the common stock of the company. This is important for tax treatment, in that you must typically pay taxes on outright grants of restricted stock. (At this point, I should warn you emphatically that you need to consult a lawyer and an accountant about the details of restricted stock grants. Otherwise, you could get whacked with a very ugly tax bill and have no cash to pay it…)
Of course, the ideal scenario is to be granted “founders’ stock” when the company is first formed and when that stock has essentially no value. Then, you have essentially no tax liability and any future gains eventually realized will be taxed at the long-term capital gains rate (which is just 15 percent in the US as of October 2011).
In my experience, often some members of a founding team do not deliver on their commitments. If you’ve allocated equity to them in expectation of delivery of a commitment, then you have essentially paid in advance for work that may or may not be done. There are several ways to deal with this problem, none of them perfect.
First, the stock you grant can “vest” (acquire its full value) according to some combination of time and performance milestones. If you can reasonably agree on the major contributions of each member of the founding team, then their stock can vest only when and if those contributions are delivered. The problem here is that it is very hard to determine in advance what all the tasks will be. I’ve been involved with companies in which stock vested proportionally to effort applied to the venture, but I’m not sure those agreements would be viewed favorably by the IRS. (Again, consult your attorney.)
Second, you can exercise caution and only grant equity for contributions expected over a quite limited time period, say half a year. If the team member doesn’t do his or her part, then you won’t make future grants, or will modify the grants in the future. The problem with this approach is that you will have to grant future equity when it presumably has significant value, which is going to have negative tax implications. (Unfortunately, for tax reasons you really want to grant most of the founder’s equity right when the entity is first formed.)
The analysis/graph shown above implicitly treats all equity alike. In reality, Series A investment is almost always “preferred stock.” Vanilla preferred stock simply provides for a liquidation preference over common stock. That is, in a down scenario, the preferred shareholders get paid first. Until their principal is returned, the common shareholders get nothing. Preferred stock can generally be converted to common stock before a liquidation event in an “up” scenario. Sometimes preferred stock includes payment of an extra dividend or converts on a greater than 1:1 ratio to common stock in an up scenario, a provision sometimes called “double dipping.” See Andrew Metrick’s excellent book on venture capital finance for details.
Are you looking principally for real advice or for a credential/endorsement? If seeking principally an implicit endorsement, see “Contribution of Intangibles” below. If you are seeking real advice, then you should be prepared to pay in equity for the cost of that advice. Advisors tend to value their time at somewhere between $3k and $15k per day. Remarkably, some otherwise saavy advisors don’t bother to analyze equity deals relative to the opportunity cost of their time. These folks have too much spare time on their hands.
Sometimes you wish to grant equity to advisors or others who are largely contributing their reputations and connections to the venture, rather than contributing significant chunks of time. In my opinion, a reasonable way to think about this is simply how much cash value their contributed intangibles are worth. Obviously, having Oprah Winfrey endorse your product is worth more than having your mother endorse it (except in the very rare case when your mother is Oprah or an equivalent.) You should think about what the intangibles are worth and negotiate an appropriate exchange of equity at the valuation at the time the equity is granted.
I enjoy cooking. I’m not one for recipes, and I especially like making savory stews and soups from seasonal vegetables, and with interesting spices, especially cumin. I usually make a big pot and after enjoying a nice dinner, I’ll stow away a few leftovers in serving-size containers in my freezer. Few moments give me greater happiness than when I remember I have something yummy in my freezer ready to heat up for lunch.
A while back I had an idea. Why don’t I create a service, which I’ll call 99 Bowls, which periodically sends me a carton of 12 containers of interesting soup? That way I always have something yummy to eat when I’m on my own at home for a meal.
I’m a serial entrepreneur, and this is how a new venture often starts for me. I’ve got some itch myself and I conceive of a company to scratch that itch. Let’s call this the raw opportunity.
A jobs analysis is a good first step in exploring an opportunity. It results in a clear and deliberate articulation of the job to be done for a focal customer (Christensen et al. 2016). The jobs analysis also comprises the first diamond in the triple-diamond model of design and design-thinking.
Let’s first talk about that focal customer. Before you even consider how to solve a problem, you really need to think about “for whom”? Returning to the 99 Bowls example, the product I would create for delivering pre-made meals to a school cafeteria would be dramatically different from the one I would create for a professional office worker or for a graduate student.
Two concepts are useful in identifying the focal customer. First, for zero-to-one products, you should identify the beachhead market. By this I mean the very first group of customers you will target. The best beachhead markets are those with the biggest need, the most acute pain point, and those that you can most easily reach. These markets are usually not the biggest markets. (See this chapter on defining markets for more.) The biggest markets usually have to wait until you have some experience and have started to spin up the flywheel of greater cost efficiency in your business. For 99 Bowls, a beachhead market could be relatively affluent professionals working from home at least two days per week.
The second useful concept is the persona. A persona is a description of a hypothetical customer that is highly representative of your target market. This is useful in making the challenge real to your team and to other stakeholders. A persona is usually constructed with specific attributes like age, gender, professional role, and even personality characteristics.
Let me tell you about the persona for 99 Bowls. Her name is Grace. She works as a product manager at Facebook. She’s 36 years old and lives alone with her cat Milo. She’s super fitness-conscious religiously going to a yoga class near her house in San Francisco every day. She works at home most days, although occasionally takes the Facebook shuttle to the main office about an hour away in Menlo Park. Grace is Korean-American and finds most prepared food too bland. She’s a foodie and likes a lot of heat and flavor. Makes it real, doesn’t it?

Your target segment will probably change, and after launching your solution you will almost certainly discover that there are other customer segments that your solution can address. You’ll also inevitably want to expand into adjacent segments. But, you have to start somewhere and specificity helps guide the creation of a solution.
I do a weekly podcast with entrepreneurs and my informal tally of past guests suggests that for about half of them the genesis of their business was a need that they themselves experienced. This raises the question of whether or not it is good practice to use yourself as a target customer.
Here are a few thoughts. First, you will find yourself in many professional situations in which you are not the target customer. If you are creating heavy equipment for the mining industry, you probably are not also a mine owner or equipment operator.
Second, when you are representative of your target market, I believe you are highly likely to create a product that satisfies at least one customer. You. That’s actually no easy feat. It’s a real luxury in entrepreneurship to have an immediate intuition about whether a solution is near the mark or not.
Still, designing for yourself does not guarantee a big market. You represent one data point and in most cases you aspire to serve thousands or even millions of customers. Disciplined and experienced entrepreneurs are able to leverage their own deep intuition about the job to be done while understanding that they need to be able to assume the perspective of the broader market for long-term product success.
In one of the most highly cited articles ever in Harvard Business Review, Theodore Levitt wrote “customers don’t want a ¼ inch drill, they want a ¼ inch hole.” Levitt’s insight was that when customers consider your product, they have a job to be done. They don’t typically want your product per se, they want the results of a job it can do for them.
But think about this example a bit more. I don’t know many customers who really want a ¼ inch hole either. They want to fasten a bookshelf to the wall. And do they really want to fasten a bookshelf to the wall, or do they want to store their books?
Every gap, as you first sense it, exists within an interconnected network of alternative problem statements, some more abstract and some more specific.
Here’s a technique called the abstraction ladder for elaborating the alternative ways you could state the design problem. You use the abstraction ladder for divergent thinking, to consider alternative ways you could frame the job to be done.
First, state the problem at the top of mind using the phrase “How might we…” For example, recall the 99 Bowls opportunity, which I could state as “How might we periodically deliver containers of prepared soup to work-from-home professionals?” You might write this on a self-stick note and place it on a wall or your desk.
As an aside, we use the phrase “How might we…” really just to put ourselves in a divergent frame of mind, considering many possibilities, some of which may not even be feasible.
Now, ask yourself what desirable outcome would be achieved if you solved the problem as stated. Or, in other words, why is that problem worth solving?
For example, we hope to deliver prepared soup so our customer always has something readily available to eat for lunch. Now, use that desirable outcome as the foundation of a second, more abstract, problem statement — “How might we provide a work-from-home professional with something to eat for lunch that is always readily available?” As these motives for doing the job come to mind, just write them down on separate notes and stick them higher up on your work surface.
You see what we’ve just done? We’ve moved up a rung on the abstraction ladder to state our problem a bit more generally. Now why is this a good thing?
Put simply, abstraction opens up additional solution concepts. For example, we’ve now opened up the possibility of a pre-scheduled daily lunch box drop-off, or of a meal kit that allows quick preparation of a fresh meal, or of a club in which a group of five people take turns making lunch for each other once a week. By broadening the definition of the problem, we have opened up the possibility of many more alternative solutions.
But why stop there? What is the benefit of providing readily available lunch? Well, perhaps a key motive is to increase available work time during the day? So, we could rephrase the job to be done as “How might we increase available work time during the day?” That would open up even more solution directions, maybe a virtual personal assistant to help with mundane tasks, professional or otherwise.
Of course, even this statement can be broadened. How might we be more productive? How might we better provide for ourselves and our families? As we ask why we would want to do a job, we broaden the problem definition until eventually we end up with jobs to be done like how might we improve well being in society?
Note that these increasingly general statements are not always strictly arranged on rungs of a linear abstraction ladder. There are typically many motives for any particular job to be done. Maybe a more significant motive for our target customer is to be able to control diet, or to introduce meal variety, or to enjoy more delicious food. Any given statement of the job to be done is located in a network of alternative problem statements, some more general, and some more specific.

So far in this example, we’ve always moved from more specific to more abstract, the why direction on the abstraction ladder. But, you can also step down a rung or two on the abstraction ladder by asking how — or what approach might we take to do the job. For instance, for the job to be done allow work-from-home professionals to enjoy more delicious food, we could take the approach of providing them with freshly cooked meals. That’s a more specific statement of the job to be done: How might we provide work-from-home professionals with freshly cooked meals?
Stating the job to be done more abstractly, and thereby opening up additional solution concepts seems like a great thing. But, at what point is the job to be done too broad, too abstract? If you state the job to be done as “How might we improve well being in society?” then a solution might be to provide free neck massages in waiting lines at the airport. Although I might use that service as a customer, somehow that solution would not motivate me to quit my job and start a company. You, specifically, as an entrepreneur have a vision, and if the job to be done doesn’t align with your vision, you’re veering off track.
When you set out to create or improve something, it’s motivated by a gap you have sensed. You own that gap. If you embark on a process to create something that improves the well being of individuals in society, and it does so, but it does not achieve your goals, then you have defined the job to be done too broadly.
I’ve described this process as a single effort that is one and done. In reality as you proceed in developing the opportunity you may find that you benefit from further broadening or focusing of the job to be done to better align with your mandate and vision as you better understand it.
Christensen, Clayton M., Taddy Hall, Karen Dillon, and David S. Duncan. “Know your customers’ jobs to be done.” Harvard business review 94, no. 9 (2016): 54-62.
Levitt, Theodore. “Marketing myopia.” Harvard business review. 82, no. 7/8 (2004): 138-149.