MBA Entrepreneurship Course Guide Template

Entrepreneurship Course Guide: [Your programme, course and term]

A course guide for the core or first elective entrepreneurship course of an MBA: opportunity recognition, customer discovery and the lean startup, effectuation, business models, product-market fit, venture finance, founding teams and equity, scaling, entrepreneurship through acquisition and search funds, and corporate venturing. It is for MBA students taking the course, admitted students preparing for it, and working managers who want the same toolkit. It gives the competencies the course builds, a 13-session roadmap, a key concepts table linking every card, an original mini-case on an early Corvane Robotics with exhibits and a teaching note, assignment rubrics, an exam plan, a reading list and a self-test with answers. Source basis: Blank (2005, 2013), Ries (2011), Sarasvathy (2001), Osterwalder and Pigneur (2010), Shane and Venkataraman (2000) and the venture finance literature, written up in original words. Replace every [bracketed] value and every row marked Example. Course content differs by school: check your own syllabus. This is a learning aid, not investment, legal or tax advice.

Document control

Contents

• What the course is for
• Prerequisites
• Session roadmap
• Key concepts and where to learn them
• The main ideas in brief
• Mini-case: Corvane Robotics chooses its first market
• Teaching note
• Typical assignments and how they are graded
• Exam preparation plan
• Common struggles
• Reading list
• Self-test questions
• Sources and further reading
• Answer key
• Revision history

What the course is for

The entrepreneurship course teaches how to create a new venture, or a new business inside an existing firm, under uncertainty that cannot be removed by more analysis at a desk. It replaces the planning habits of an established business (forecast, plan, execute) with a cycle of hypotheses, cheap tests and staged commitments, and it adds the financial and legal mechanics of raising money and sharing ownership. Shane and Venkataraman (2000) framed the field around how opportunities are discovered, evaluated and exploited, and by whom; the course follows that order.

Graduates of the course should be able to judge whether an idea is an opportunity, design and run customer discovery, build and test a business model, size a market and its unit economics, choose and negotiate financing, set up a founding team and equity split, and explain when to scale. Those who will not found a company use the same skills in corporate innovation, venture capital, consulting and product roles.

Prerequisites

Session roadmap

Key concepts and where to learn them

The main ideas in brief

Customer development and the lean startup. Blank (2005) argued that start-ups fail more often for lack of customers than for lack of product, and proposed a customer development process run alongside product development: customer discovery (test the problem and the customer), customer validation (test that customers will buy, repeatably), then customer creation and company building. Ries (2011) combined this with iterative product development into the lean startup: state the leap-of-faith assumptions, build a minimum viable product, measure, learn and decide to pivot or persevere. Blank (2013) summarised the approach for a general management audience in the Harvard Business Review. The method is a discipline for learning cheaply, not a licence to skip analysis or ship poor products.

Effectuation. Sarasvathy (2001) contrasted causation, which starts from a given goal and selects means to reach it, with effectuation, which starts from given means (who I am, what I know, whom I know) and lets goals emerge through commitments with stakeholders. Expert entrepreneurs, her research found, lean towards effectual reasoning: they decide what they can afford to lose rather than forecasting returns, form partnerships that pre-commit resources, and treat surprises as material rather than deviations. Effectuation and the lean startup are complements: both prefer action and evidence to prediction where the future cannot be forecast.

Business models. Osterwalder and Pigneur (2010) popularised a nine-block canvas (customer segments, value propositions, channels, customer relationships, revenue streams, key resources, key activities, key partnerships, cost structure). The lean canvas (business/lean-canvas) is a start-up variant. The mini-case below shows that the same product can support very different business models, with different cash needs and risks.

Product-market fit. The term, popularised in venture circles in the mid-2000s, describes the point at which a product satisfies a market strongly enough that demand pulls it: retention curves flatten, customers refer others, sales cycles shorten. There is no single test. Teams combine cohort retention, the share of users who would be very disappointed without the product (a widely used practitioner survey), organic growth and sales-cycle data.

Venture finance. Start-ups finance themselves in stages so that investors can stop funding when the evidence turns against the venture, an idea documented in the contracts Kaplan and Stromberg (2003) analysed: cash flow rights, board and voting rights, liquidation preferences and vesting are allocated contingent on performance. The mechanics (SAFEs, notes, priced rounds, the option pool, waterfalls) are in mba/mba-venture-finance-cap-table-card.

Teams and equity. Wasserman (2012) showed that founders' early choices about co-founders, roles, equity splits and investors create trade-offs between keeping control and building value. Equal splits made quickly, missing vesting and unclear decision rights are frequent causes of later conflict.

Scaling. Greiner (1972) described organisations growing through phases of evolution, each ending in a revolution (a crisis) that requires a new way of organising: growth through creativity ends in a crisis of leadership, direction in a crisis of autonomy, delegation in a crisis of control, coordination in a crisis of red tape. For a scaling start-up the first two matter most: the founders' informal, hands-on management stops working (leadership), and then centralised direction frustrates the managers who were hired to run functions (autonomy). Culture drift as new hires arrive is a further, practitioner-noted risk.

Entrepreneurship through acquisition and search funds. Instead of starting a company, an entrepreneur can buy an established small business and run it. In the traditional search fund model, investors fund a searcher (often a recent MBA graduate) for a period of search; when a target is found, the same investors usually have the right to fund the acquisition, and the searcher earns equity in stages tied to the acquisition, time and performance. Self-funded search and acquisitions financed with seller notes or government-backed small business loans are common variants. Stanford GSB publishes a periodic study of search fund returns and characteristics; check the latest edition on gsb.stanford.edu for current figures rather than relying on numbers quoted second hand. Valuation and leverage tools are in mba/mba-dcf-valuation-card and mba/mba-paper-lbo.

Corporate venturing. Established firms create new businesses through internal ventures, corporate venture capital, partnerships and acquisitions. Burgelman (1983) described how internal ventures arise from autonomous initiatives below top management and must win strategic context to survive. O'Reilly and Tushman (2004) argued for ambidextrous organisations that separate exploratory units from the core while integrating them at the top. Chesbrough (2003) described open innovation, in which firms use external ideas and paths to market. Kill criteria and staged funding apply in corporations as much as in start-ups.

Mini-case: Corvane Robotics chooses its first market

Situation

Maya Okafor finished her robotics doctorate with a prototype she called the tote picker: a mobile robot with a gripper that could pick plastic bins from warehouse shelves and bring them to a packing station. Her co-founder, Tomas Lindqvist, had spent eight years running night shifts at a regional distribution centre and knew exactly what a missed truck cost. They incorporated Corvane Robotics with 4,600,000 shares for Maya and 3,500,000 for Tomas and set aside a pool of 900,000 shares for the first hires, none of them yet granted.

For six months the founders did little but talk to warehouse managers. They focused on two segments that Tomas knew: mid-size third-party logistics providers (3PLs), which run warehouses for several brands under contracts of two to five years, and grocery distribution centres, which run their own warehouses on thin margins with strong unions in some regions. The interviews followed a script that asked about the last time a shift went wrong, what it cost and what the manager had tried. Exhibit 1 summarises what they heard.

With a small grant and their savings, they ran two eight-week pilots at 3PL sites in a chilled section and an ambient section. The robots picked more slowly than experienced staff but could run two shifts with little supervision, and they made fewer picking errors. Exhibit 2 shows the pilot data. One site manager said he would "take ten tomorrow if I didn't have to buy them".

That remark started the founders' longest argument. Tomas wanted to sell robots outright at USD 120,000 with an annual service contract, because each sale would bring in cash immediately. Maya wanted to offer robots as a service (RaaS) at USD 3,500 a month per robot, including maintenance and software, because customers on three-year contracts could not justify capital spending on a robot that might outlive the contract. The finance volunteer on their advisory board built the comparison in Exhibit 3 and pointed out that RaaS meant Corvane would have to own the fleet.

The next decision was money. Monthly burn would be about USD 120,000 once they hired four engineers. An angel group offered USD 1.5m on a post-money SAFE with a USD 10m valuation cap and could close in two weeks. A seed fund offered to lead a USD 2.5m priced round at a USD 10m pre-money valuation, with a 10% unissued option pool post-money to be created in the pre-money; legal work would take six to eight weeks and the fund wanted a board seat. Exhibit 4 compares the two.

On a Sunday evening the founders sat down with three questions: which segment to pursue first, which business model, and which offer to accept. Both knew that the three answers were connected: the business model drove how much capital the company needed, and the segment drove how fast it could prove that robots replaced labour. Maya wanted to decide that night. Tomas wanted one more month of data.

Exhibit 1: Customer discovery summary (fictional)

Exhibit 2: Pilot results at two 3PL sites (fictional)

Full-time equivalents replaced = 88.78 x 16 / (110 x 8). Loaded cost of a picker: USD 58,000 a year.

Exhibit 3: Business model comparison per robot, five years, 12% discount rate (fictional)

Exhibit 4: Financing offers (fictional)

Discussion questions

1. Which segment should Corvane pursue first? Use Exhibit 1 and say what further evidence you would want.
2. Is the pilot evidence in Exhibit 2 strong enough to claim that one robot replaces more than one full-time equivalent? What could make the pilot results better or worse than a full deployment?
3. Compare the two business models from the customer's and from Corvane's point of view. Why are their NPVs per robot so close, and why does that not settle the question?
4. Which financing offer should the founders accept, given your answer to question 3?
5. Write three kill criteria for the next nine months.
6. Tomas wants another month of data; Maya wants to decide tonight. Using effectuation and the lean startup, argue for one of them.

Teaching note

Segment (Q1). The 3PL segment shows stronger pull at every step of the funnel: 70.8% rank labour availability top-3 against 43.8% for grocery, 37.5% against 18.8% agree to a pilot and, most tellingly, 16.7% against 6.3% offer to pay. Paid pilot offers are the closest thing to purchase evidence at this stage (Blank 2005). Sample sizes are small (24 and 16), so a single interview moves the grocery figures by about six percentage points; the founders should add interviews in both segments but begin with 3PLs. A 3PL beachhead also has a structural feature that matters for the model choice: contracts of two to five years make customers reluctant to buy long-lived equipment.

Pilot evidence (Q2). The robot's effective rate is 88.78 picks per hour against 110 for an experienced picker, but it works 16 hours, so each robot does the work of 1.614 full-time equivalents, worth about USD 93,600 a year at a USD 58,000 loaded cost. Errors fall by 67.6%. Reasons for caution: two friendly sites, eight weeks, a novelty effect on supervision, and the best SKUs may have been chosen. Reasons the full deployment could do better: tuning and fleet learning. A kill criterion should test the full-time equivalent figure at a third, less friendly site.

Business model (Q3). Per robot, the NPVs are close (USD 62,977 for a sale, USD 59,772 for RaaS at 12% over five years), and the RaaS figure ignores any residual value of the robot after year 5, so on value alone the models are similar. They differ in three ways that matter more. (a) Customer adoption: for a 3PL on a three-year contract, RaaS turns a USD 120,000 capital decision into an operating expense of USD 42,000 a year that is well below the USD 93,600 of labour saved, so Corvane captures about 45% of the value created; the buying decision is faster. (b) Capital need: 40 robots under RaaS tie up USD 2.8m of fleet capital, while 40 sales bring in USD 2.0m of gross profit. (c) Risk and learning: under RaaS Corvane keeps the robots in the field under its own service, collects data and improves the product, but bears the technology and utilisation risk. A defensible answer is RaaS for the 3PL beachhead with the fleet financed separately (equipment leasing or asset-backed debt once utilisation is proven), and outright sale only for large customers with long horizons.

Financing (Q4). The SAFE is fast and cheap and sells 15% of the Company Capitalization, but USD 1.5m gives 12.5 months of runway and cannot fund a RaaS fleet. The priced seed sells 20% (founders 70.0% fully diluted; the pool shuffle adds 257,143 shares inside the pre-money, worth about USD 0.28m at the seed price of USD 1.0802), adds a board member and takes longer, but gives 20.8 months of runway, enough to reach the kill criteria below with a margin. If the founders choose RaaS, the seed fits better; if they choose outright sale, the SAFE plus customer cash could suffice. Note that the 76.5% after the SAFE is not comparable with the 70.0% after the seed: the SAFE holders' percentage is fixed only until the next priced round, when everyone is diluted again. Students should model both paths with mba/mba-venture-finance-cap-table-card.

Kill criteria (Q5). Examples: at least three paying RaaS customers within six months (else revisit the model); a third pilot site at 1.3 or more full-time equivalents per robot (else rework the product); fleet utilisation above 85% across customers (else slow deployment); signed equipment financing for the next 40 robots by month nine.

Decide now or wait (Q6). Effectual reasoning favours acting within affordable loss and using commitments from stakeholders (the 3PL manager's "ten tomorrow") to shape the venture; lean startup reasoning favours deciding once the next test is designed, not when uncertainty is gone. Another month of interviews will not resolve the questions that matter (FTE replacement at scale, utilisation, financing), which only deployments can answer. A good answer decides the segment and the model tonight, chooses the financing that funds the next tests, and writes the kill criteria so that the decision can be reversed cheaply.

Numbers for instructors. Customer buy NPV at 12% over five years: USD 185,045 per robot with unrounded savings (=-120000+PV(12%,5,-84623) returns 185,047 with the net saving rounded to 93,623 minus 9,000 service), so buying is attractive for customers with capital and a long horizon. RaaS NPV =-70000+PV(12%,5,-36000) = 59,772 and IRR =IRR({-70000,36000,36000,36000,36000,36000}) = 42.75%. Sale NPV =50000+PV(12%,5,-3600) = 62,977. Seed pool increase =ROUND((0.125*9000000-900000)/(1-0.125),0) = 257,143; seed price USD 1.0802.

Typical assignments and how they are graded

Common assignments: an opportunity assessment (individual or team), customer discovery notes with a synthesis, a financing exercise (cap table and term sheet comparison), case write-ups (mba/mba-case-write-up), and a final pitch with a business plan or venture memo (startup/pitch-outline, business/business-plan).

Exam preparation plan

See mba/mba-exam-prep for a general plan and mba/mba-concept-flashcards for spaced review.

Common struggles

1. Falling in love with the solution. Students describe the product in detail and the customer in one line. Start every assignment from the customer and the problem.
2. Interviews that ask for opinions. "Would you use this?" invites polite yeses. Ask about past behaviour and money spent.
3. Top-down sizing only. Instructors and investors discount it. Build the bottom-up count.
4. Treating the lean startup as "no planning". It is a plan for learning, with explicit hypotheses, tests and thresholds.
5. Cap table arithmetic. Most errors come from the share base: pre or post, fully diluted or outstanding, pool in or out. Practise until it is automatic.
6. Confusing ownership with proceeds. A waterfall at several exit values corrects this.
7. Equal equity splits without vesting. In team projects and real ventures, agree roles, vesting and decision rights first.
8. Ignoring capital intensity. Hardware, inventory and fleets change the financing story.
9. Pitching features, not evidence. Panels respond to traction, learning and a credible plan.

Reading list

Classic works: Blank, The Four Steps to the Epiphany (2005); Ries, The Lean Startup (2011); Osterwalder and Pigneur, Business Model Generation (2010); Sarasvathy, Effectuation: Elements of Entrepreneurial Expertise (2008); Wasserman, The Founder's Dilemmas (2012); Christensen, The Innovator's Dilemma (1997); Chesbrough, Open Innovation (2003). Textbooks and practitioner books (by name only): Barringer and Ireland, Entrepreneurship: Successfully Launching New Ventures; Aulet, Disciplined Entrepreneurship; Feld and Mendelson, Venture Deals; Metrick and Yasuda, Venture Capital and the Finance of Innovation. Open resource: OpenStax, Entrepreneurship (CC BY-NC-SA 4.0). For acquisition entrepreneurship, the periodic search fund study published by Stanford GSB (latest edition on gsb.stanford.edu).

Self-test questions

1. What are the four steps of customer development, and which two does the course concentrate on?
2. State one difference between causal and effectual reasoning and give an example of each in a start-up.
3. Name the nine blocks of the business model canvas.
4. In the mini-case, why are the NPVs per robot of the two business models similar, and what makes the choice anyway?
5. Give three types of evidence for product-market fit.
6. A start-up raises USD 2m at USD 8m pre-money. What share do the investors buy?
7. Why do venture investors stage their financing?
8. Name two causes of founder conflict that vesting and a founder agreement can prevent.
9. Describe the traditional search fund model in three sentences.
10. Why might a large company separate an exploratory venture from its core business, and what risk does that create?
11. What makes a kill criterion useful? Give one for a venture of your choice.
12. In the mini-case, which financing offer fits a robots-as-a-service model better, and why?

Sources and further reading

• Blank, S. G. (2005). The Four Steps to the Epiphany. Self-published (CafePress).
• Blank, S. (2013). Why the lean start-up changes everything. Harvard Business Review, 91(5).
• Ries, E. (2011). The Lean Startup. Crown Business.
• Sarasvathy, S. D. (2001). Causation and effectuation: toward a theoretical shift from economic inevitability to entrepreneurial contingency. Academy of Management Review, 26(2), 243-263.
• Sarasvathy, S. D. (2008). Effectuation: Elements of Entrepreneurial Expertise. Edward Elgar.
• Osterwalder, A., and Pigneur, Y. (2010). Business Model Generation. Wiley.
• Shane, S., and Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1), 217-226.
• Kaplan, S. N., and Stromberg, P. (2003). Financial contracting theory meets the real world: an empirical analysis of venture capital contracts. The Review of Economic Studies, 70(2), 281-315.
• Wasserman, N. (2012). The Founder's Dilemmas. Princeton University Press.
• Greiner, L. E. (1972). Evolution and revolution as organizations grow. Harvard Business Review, 50(4), 37-46.
• Burgelman, R. A. (1983). A process model of internal corporate venturing in the diversified major firm. Administrative Science Quarterly, 28(2), 223-244.
• O'Reilly, C. A., and Tushman, M. L. (2004). The ambidextrous organization. Harvard Business Review, 82(4), 74-81.
• Chesbrough, H. W. (2003). Open Innovation. Harvard Business School Press.
• Y Combinator. Post-money SAFE documents and user guide (ycombinator.com/documents, checked 2026-10-28).
• Stanford GSB. Search fund studies (gsb.stanford.edu; check the latest edition).

Answer key

1. Customer discovery, customer validation, customer creation and company building (Blank 2005). The course concentrates on discovery and validation.
2. Causal reasoning fixes a goal and chooses the best means (write a plan to reach a forecast market share, then raise the money it requires); effectual reasoning starts from available means and affordable loss and lets goals emerge through partner commitments (sell a first pilot to a former employer and let that customer shape the product).
3. Customer segments, value propositions, channels, customer relationships, revenue streams, key resources, key activities, key partnerships, cost structure.
4. Upfront gross profit from a sale roughly equals the present value of the extra margin from RaaS over five years (USD 62,977 against USD 59,772). The choice turns on customer adoption (opex instead of capex for 3PLs on short contracts), Corvane's capital need (USD 2.8m for 40 RaaS robots) and who bears technology risk.
5. Cohort retention that flattens, a high share of users who would be very disappointed without the product, organic or referral growth, shorter sales cycles, rising win rates without price cuts.
6. 2 / (8 + 2) = 20%.
7. To keep the option to stop funding when evidence is poor and to price later rounds with more information; staging also aligns founders through milestones (Kaplan and Stromberg 2003).
8. A co-founder leaving early with a large stake; disagreements over roles and decision rights; unequal contribution under an equal split.
9. Investors fund a searcher's salary and expenses while they look for a business to buy. When a target is found, the investors usually have the right to fund the acquisition. The searcher becomes the chief executive and earns equity in tranches tied to the acquisition, time and performance.
10. To protect the venture from the core's processes, metrics and resource allocation, which favour existing customers. The risk is isolation: the venture loses access to the core's assets or is not adopted, so integration at the top is needed (O'Reilly and Tushman 2004).
11. It is measurable, has a threshold and a date, tests the riskiest assumption and triggers a pre-agreed decision. Example: fewer than 2 of 8 qualified prospects sign a paid pilot within 90 days, then stop or pivot.
12. The priced seed: USD 2.5m and 20.8 months of runway can carry the first fleet deployments and the tests that unlock equipment financing; USD 1.5m on the SAFE covers 12.5 months of burn and none of the fleet capital.

Revision history

Standard and licence note

Structure aligned with the common content of MBA entrepreneurship courses and with the primary works listed above (Blank 2005 and 2013; Ries 2011; Sarasvathy 2001; Osterwalder and Pigneur 2010; Shane and Venkataraman 2000; Kaplan and Stromberg 2003). The competency list follows the style of the AACSB competency areas used across this library. The text, mini-case, exhibits, numbers and questions are original; no published case or textbook text is copied or paraphrased, and Corvane Robotics and its people are fictional. The template is independent and not affiliated with or endorsed by any business school, accelerator or publisher. Check your own syllabus and the current versions of any financing documents before you rely on them. Template licence: MIT.