MBA Opportunity Assessment Card Template (TAM, SAM, SOM)

Opportunity Assessment Concept Card: [Opportunity, venture or course case]

A concept card for screening a new venture or new-business opportunity before money and years are committed: market sizing as TAM, SAM and SOM computed both top-down and bottom-up, problem severity measured in the customer's money, competitive alternatives including "do nothing", unit economics, a weighted scoring model with sensitivity checks, and written kill criteria that say in advance what evidence would stop the project. It is for MBA students in the entrepreneurship and strategy courses, founders and corporate venture teams, and investors who screen deals. Worked example A assesses a fictional Corvane Robotics product line and is fully solved; Worked example B is half solved and Exercise C is left for you, with a separate answer key. Source basis: Blank (2005) on customer discovery, McGrath and MacMillan (1995) on discovery-driven planning, Ries (2011) on testing assumptions, and Gupta, Lehmann and Stuart (2004) on customer value, written up in original words. Replace every [bracketed] value and every row marked Example. This is a learning aid, not investment advice.

Document control

Contents

• When to use it
• The idea in plain language
• Formulas and notation
• Assumptions and limits
• How managers and investors use it
• Worked example A (fully solved): Corvane Frost cold-storage picking
• Kill criteria
• Worked example B (half solved): Northfield gear rental subscription
• Exercise C (unsolved): Tallow Creek scheduling software
• Process diagram
• Connections to other cards
• Common mistakes and misconceptions
• Self-test questions
• My notes and next steps
• Sources and further reading
• Answer key
• Revision history

When to use it

One-sentence rule: an opportunity is worth pursuing when a specific customer has a costly problem, will pay enough to solve it with your offer rather than the alternatives, can be reached at an acquisition cost the customer's lifetime value repays several times, and sits in a market large enough to matter; write down what would prove each of these wrong and test the riskiest first.

Shane and Venkataraman (2000) defined the field of entrepreneurship around the discovery, evaluation and exploitation of opportunities. This card is a structured version of the "evaluation" step.

The idea in plain language

The assessment has five blocks. Each answers one question and each has a typical way of fooling yourself.

• Market size (TAM, SAM, SOM). Total addressable market (TAM) is the annual revenue if every possible customer bought the category. Serviceable available market (SAM) is the part you can reach with your product, channels and geography today. Serviceable obtainable market (SOM) is what you can realistically win within a stated horizon. A top-down estimate starts from a published or estimated total and applies shares; a bottom-up estimate multiplies the number of customers by units per customer by price. Bottom-up is more credible to investors because every number can be tested in interviews. When the two differ by more than a factor of about two, one of them has a wrong assumption.
• Problem severity. How much does the problem cost the customer, how often, and how urgently? Measure it in the customer's own money and time. A problem worth solving costs more than your price by a clear margin.
• Competitive alternatives. The real competitor is often the current workaround: spreadsheets, manual labour, an incumbent supplier, or doing nothing. Price and differentiation are judged against these, not only against start-ups with similar products.
• Unit economics. For one customer: gross profit per period, how long they stay, what it costs to acquire them. Lifetime value (LTV) over customer acquisition cost (CAC) and the CAC payback period summarise it (Gupta, Lehmann and Stuart 2004; mba/mba-customer-lifetime-value-card; finance/unit-economics-analysis).
• Scoring and kill criteria. A weighted score makes the comparison of options explicit and debatable. Kill criteria, written in advance, turn the riskiest assumptions into tests with thresholds (McGrath and MacMillan 1995; Ries 2011).

Formulas and notation

The LTV formula assumes constant margin and retention and that each year's margin is received at year end by the customers retained that year (Gupta, Lehmann and Stuart 2004). Other conventions (margin at the start of the year, monthly periods) give different numbers; state yours.

Assumptions and limits

1. Market sizes are hypotheses, not facts. Published market reports use different definitions; cite the source and year, and check the definition before applying shares.
2. SOM is a plan, not a forecast. It is only as good as the sales capacity, cycle length and win rate behind it.
3. Unit economics at small scale are noisy. Early CAC is often too low (warm leads, founder selling) or too high (no brand, no referrals). Treat the first cohort with caution.
4. Gross margin must match the business model. In a robots-as-a-service model the hardware sits on your balance sheet: gross margin after depreciation can look healthy while cash is consumed by fleet capital expenditure.
5. Scores hide judgement. A weighted score is a structured opinion. Its value is in making the weights and scores explicit and in testing whether the ranking survives other reasonable weights.
6. Severity is not willingness to pay. Customers may describe a painful problem and still not buy. Paid pilots and letters of intent are stronger evidence than interview enthusiasm (Blank 2005).
7. The assessment is a snapshot. Re-run it when evidence arrives; that is the point of discovery-driven planning.

How managers and investors use it

Commonly quoted practitioner rules of thumb, such as an LTV to CAC above about 3 or a CAC payback under about 12 to 18 months for business software, are conventions, not laws. Use them as prompts for questions, and compare with your own cost of capital and cash position.

Worked example A (fully solved): Corvane Frost cold-storage picking

Situation (fictional). Corvane Robotics, a growth-stage warehouse-robotics company, considers three new product lines: Frost, a picking robot for cold-storage (refrigerated and frozen) warehouses; a retail micro-fulfilment system for grocery back rooms; and a parcel sortation retrofit for existing hubs. Frost would be offered as robots-as-a-service (RaaS) at USD 42,000 per robot per year; a typical site uses 6 robots. All figures are fictional assumptions for the exercise.

A1. Market sizing, top-down and bottom-up

The two TAM estimates agree within 4% and the two SAM estimates within 5%, which gives some confidence in the order of magnitude. The sales-capacity SOM (112 sites, 2.67% of SAM sites) is lower than the penetration SOM and is the one to plan on, because it is tied to hiring. Annual recurring revenue at each year end would be USD 2.02m, 6.05m, 12.10m, 20.16m and 28.22m (cumulative sites 8, 24, 48, 80 and 112).

A2. Problem severity, in the customer's money

Interviews with cold-storage operators (fictional) point to labour availability in sub-zero conditions, high staff turnover and injury risk. Per site and year:

A benefit of 1.56 times the fee is attractive but not overwhelming; the case depends on the robots really replacing one full-time equivalent each across shifts, which is the assumption to test in pilots.

A3. Competitive alternatives

A4. Unit economics per site

The discounted LTV to CAC of 4.30 clears a 3x convention; the undiscounted figure is 3.6 times larger, which shows how much a lazy LTV formula flatters a long-lived customer. The fleet capital of USD 330,000 per site is not in CAC or gross margin but must be financed before revenue arrives: Frost is capital-intensive, a point for mba/mba-venture-finance-cap-table-card and for any lease or debt financing of the fleet.

A5. Weighted scoring of the three options

Scores run from 1 (poor) to 5 (strong); risk is scored so that 5 means low risk.

Excel: with weights in B2:B7 and Frost's scores in C2:C7, =SUMPRODUCT($B$2:$B$7, C2:C7) gives 4.10.

Sensitivity. With equal weights the scores are 4.00, 3.00 and 3.33; with a market-heavy set (market 35%, problem 10%, differentiation 15%, unit economics 20%, right to win 10%, risk 10%) they are 4.00, 3.45 and 3.30. Frost ranks first under all three; micro-fulfilment overtakes the sortation retrofit only when market size dominates, which says the micro-fulfilment case rests on market size alone.

Conclusion. Frost scores highest (4.10) and the ranking is robust to the weights. The recommendation is not "build Frost" but "fund a staged test of Frost against the kill criteria below", because the scores for severity and unit economics rest on interviews and assumptions, not on paid deployments.

Kill criteria

A failed criterion leads to one of three decisions agreed in advance: stop, pivot (change segment, product or model; startup/pivot-memo) or persevere with a documented reason. Ries (2011) calls the underlying beliefs "leap-of-faith assumptions"; McGrath and MacMillan (1995) recommend a reverse income statement and an assumptions checklist updated at each milestone.

Worked example B (half solved): Northfield gear rental subscription

Situation (fictional). Northfield Outdoor Co., a mid-size outdoor-gear retailer with stores and an online shop, considers a gear rental subscription at USD 29 a month in the three metro areas where it has stores.

Questions: (1) Fill the gaps. (2) Score the option with the weights of Worked example A, using scores of 3, 2, 3, 2, 5, 4; what is the weighted score? (3) Which single assumption would you test first, and with what kill threshold? (4) Why does a fast CAC payback not rescue a low LTV to CAC here?

Exercise C (unsolved): Tallow Creek scheduling software

Situation (fictional). Tallow Creek Medical Center, a regional hospital, built an operating-theatre scheduling tool that cut idle theatre time. A spin-out would sell it to other hospitals as software at USD 85,000 a year per hospital. Assume 6,100 hospitals in the target regions, of which 55% are regional hospitals of 100 to 400 beds (the segment the product fits). Sales capacity: 1, 2, 3, 4 and 4 account executives in years 1 to 5, each winning 5 hospitals a year, no churn within the five years. Gross margin 78%, annual retention 92%, CAC USD 120,000, discount rate 12%.

1. Compute TAM and SAM (in hospitals and in USD) and the year-5 SOM in ARR.
2. What share of SAM hospitals does the year-5 SOM represent?
3. Compute annual gross profit per hospital, LTV, LTV to CAC and CAC payback in months.
4. Score the opportunity with the weights of Worked example A, using scores of 3, 4, 3, 4, 3, 2.
5. Write three kill criteria. At least one must address the long hospital buying cycle and one the risk that the tool's results depend on Tallow Creek's own processes.

Process diagram

The flow matches the sections of Worked example A: frame the customer and problem, size the market twice, check alternatives and unit economics, score, then test against the kill criteria before scaling.

Connections to other cards

• Customer value in depth: mba/mba-customer-lifetime-value-card (cohorts, retention curves, margin definitions) and finance/unit-economics-analysis (the working document).
• Segment and positioning: mba/mba-stp-positioning-card; price-setting: mba/mba-pricing-card.
• Industry attractiveness and advantage: mba/mba-five-forces-card and mba/mba-competitive-advantage-card.
• Funding the opportunity: mba/mba-venture-finance-cap-table-card (how much to raise, on what terms).
• Staging and flexibility: mba/mba-decision-trees-card and mba/mba-options-real-options-card value the option to stop after a pilot.
• Market sizing practice: mba/mba-market-sizing-drills.
• Working templates: startup/customer-discovery for interviews, business/lean-canvas for a one-page model, business/feasibility-study and business/market-research-report for a fuller assessment, product/competitive-analysis for the alternatives.

Common mistakes and misconceptions

1. "If we get 1% of a huge market." A top-down share of a big number is not a plan. Build SOM from customers, capacity and win rates.
2. Calling TAM the whole economic category. TAM must be the spend your category of solution could capture, not the customer's entire budget.
3. Mixing units. Per robot and per site, per month and per year: put units on every column.
4. Measuring severity by enthusiasm. Count paid pilots, letters of intent and budget owners, not compliments.
5. Ignoring "do nothing". The status quo is free of switching costs and is the most common winner.
6. Using undiscounted LTV. Margin divided by churn ignores the time value of money and flatters long-lived customers.
7. Leaving capital out of unit economics. Hardware, inventory or fleet investment can make a high-margin model cash-hungry.
8. Fixing weights after scoring. Weights chosen once the scores are known can produce any ranking. Fix them first and run a sensitivity check.
9. Kill criteria without thresholds or dates. "We will see how pilots go" cannot fail, so it cannot inform a decision.
10. Treating the assessment as a one-off. The card should be re-run after each test.

Self-test questions

1. Define TAM, SAM and SOM in one sentence each.
2. Why do investors prefer a bottom-up market estimate? What does a large gap between top-down and bottom-up suggest?
3. A software product sells at USD 20,000 a year to 3,000 target firms; you can serve 40% of them today. Compute TAM and SAM.
4. Annual gross profit per customer USD 10,000, retention 80%, discount rate 10%. Compute LTV with the card's formula.
5. CAC is USD 15,000 and annual gross profit per customer is USD 10,000. What is the CAC payback in months?
6. Give two reasons a high LTV to CAC ratio can still describe a poor opportunity.
7. What is a kill criterion, and why should it be written before the test?
8. In Worked example A, why is the sales-capacity SOM the better planning number?
9. A weighted score ranks option X first only when one criterion carries 40% weight. What does that tell you?
10. Interleaving: which card or tool do you use? (a) Splitting ownership in a seed round. (b) Deciding whether to fund a pilot that can be stopped after six months. (c) Explaining why an industry earns low returns.

My notes and next steps

Sources and further reading

• Blank, S. G. (2005). The Four Steps to the Epiphany. Self-published (CafePress).
• Ries, E. (2011). The Lean Startup. Crown Business.
• McGrath, R. G., and MacMillan, I. C. (1995). Discovery-driven planning. Harvard Business Review, 73(4), 44-54.
• Shane, S., and Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1), 217-226.
• Gupta, S., Lehmann, D. R., and Stuart, J. A. (2004). Valuing customers. Journal of Marketing Research, 41(1), 7-18.
• Osterwalder, A., and Pigneur, Y. (2010). Business Model Generation. Wiley.
• Textbooks (by name only): Barringer, B. R., and Ireland, R. D., Entrepreneurship: Successfully Launching New Ventures; Aulet, B., Disciplined Entrepreneurship; Christensen, C. M., Hall, T., Dillon, K., and Duncan, D. S., Competing Against Luck.
• Open resource: OpenStax, Entrepreneurship (CC BY-NC-SA 4.0), chapters on opportunity recognition and feasibility.

Answer key

Worked example B. (1) SAM 172,800 households; SOM 4,320 subscribers; SOM revenue USD 1.503m a year; LTV USD 211.12 per subscriber; LTV to CAC 2.22. (2) Weighted score 3.00 (0.60 + 0.40 + 0.45 + 0.40 + 0.75 + 0.40). (3) Churn: at 35% a year the subscriber stays under three years on average; test retention with a three-month paid trial cohort, kill threshold for example monthly churn above 3% (about 31% a year). Even at 31% the LTV to CAC is only about 2.6, so price, margin or CAC must also move for the case to clear 3x. Adoption is the second test. (4) Payback measures speed of recovery, not total value; with high churn and a modest margin each subscriber returns only about 2.2 times CAC in present value, below a 3x convention, and the SOM revenue of about USD 1.5m is small for Northfield.

Exercise C. (1) TAM 6,100 hospitals, USD 518.5m; SAM 3,355 hospitals, USD 285.2m; year-5 cumulative hospitals 70 (5 x (1+2+3+4+4)), SOM ARR USD 5.95m. (2) 2.09% of SAM hospitals. (3) Gross profit USD 66,300; LTV USD 304,980 (=66300*92%/(1+12%-92%)); LTV to CAC 2.54; CAC payback 21.72 months. (4) Weighted score 3.30. (5) Examples: KC-01 three of the first ten qualified hospitals sign within nine months, else stop; KC-02 idle theatre time falls by at least [x]% at two hospitals that are not Tallow Creek, else pivot to a services model; KC-03 implementation under 12 weeks per hospital, else rework the product before scaling sales.

Self-test.

1. TAM: annual revenue if every possible customer bought the category; SAM: the part reachable with your product, channels and geography; SOM: what you can realistically win in a stated horizon.
2. Each input (customers, units, price) can be checked in interviews and data. A large gap means at least one share, count or price is wrong, or the two estimates define the market differently.
3. TAM USD 60m (=3000*20000); SAM USD 24m.
4. $LTV = 10{,}000 \times 0.8/(1.1 - 0.8) = 26{,}667$, about USD 26,667.
5. 15,000 / (10,000 / 12) = 18 months.
6. Examples: the market is too small to build a meaningful business; large capital needs outside CAC; the ratio rests on an early, unrepresentative cohort; CAC excludes costs such as founder selling time.
7. A measurable test of a critical assumption with a threshold and date that triggers stop or pivot. Writing it first prevents fitting the criterion to the result.
8. It is tied to hiring, ramp and win rates the company controls and can track; the penetration figure is a top-down guess.
9. The ranking is fragile and depends on one judgement; discuss that weight explicitly and gather evidence on the criterion that drives it.
10. (a) mba/mba-venture-finance-cap-table-card; (b) a decision tree or real-options analysis (mba/mba-decision-trees-card); (c) mba/mba-five-forces-card.

Revision history

Standard and licence note

Based on the opportunity evaluation and customer development literature listed above (Blank 2005; McGrath and MacMillan 1995; Ries 2011; Shane and Venkataraman 2000; Gupta, Lehmann and Stuart 2004). The text, examples, numbers and questions are original; no textbook text is copied or paraphrased, and Corvane Robotics, Northfield Outdoor Co. and Tallow Creek Medical Center are fictional. The template is independent and not affiliated with or endorsed by any business school, publisher or investor. Market data in your own assessment must carry its source and date. Template licence: MIT.