EXFrom insight to impact venture — a worked example
One social problem, taken end to end through the entrepreneurial process exactly as the EMP team project asks: framing the opportunity, isolating and testing the riskiest assumption, synthesising customer discovery, filling a Value Proposition Canvas, defining an MVP, building the Business Model Canvas, sizing the market, working the unit economics and runway, and estimating social impact (SROI) — ending in a two-minute pitch. Every framework below is filled in with concrete, illustrative numbers so you can see what a finished artifact looks like. Replace the numbers with your own validated evidence.
The venture: Aula Viva — a structured after-school numeracy programme, delivered by trained near-peer university tutors, for first-generation secondary students in under-resourced public schools in Madrid. The worked example follows the team through the process from a vague hunch ("kids are falling behind in maths") to a defensible, evidenced go decision.
What this example exercises
It walks the full arc of the EMP program: opportunity framing (Sessions 8–10), hypothesis-driven testing and the Riskiest Assumption Test (Sessions 12–14), customer discovery and validation (Sessions 21–22), the value proposition (Session 20), the business model and market sizing (Sessions 19, 23, 29), financing and viability (Session 25), and impact (theory of change & SROI). Each step links back to the matching interactive demo so you can re-run the numbers yourself.
Jump to a step
1The problem & the opportunity
A problem worth solving is severe, widespread, and currently solved badly. We frame it, then score it on the desirability / feasibility / viability lens before committing a semester to it.
Problem statement (framed, not solution-first)
Problem
First-generation secondary students in under-resourced Madrid public schools fall behind in mathematics because they cannot access affordable, consistent out-of-school support — private tutoring costs €25–40/hour and families in the target neighbourhoods cannot pay it. The result is a widening attainment gap that compounds each year and narrows university options.
Note the framing rule from Sessions 9–10 (Are You Solving the Right Problems?): we describe a need, not a product. "An after-school app" would be a premature solution; "students cannot access affordable, consistent support" is a problem we can re-frame and explore.
Evidence the problem is real (desk research, pre-discovery)
- PISA: Spain's mean maths score sits below the OECD average, with a steep socio-economic gradient.
- Target district has ~14 public secondary schools; school counsellors report maths as the #1 repeated subject.
- Private tutoring market exists and is healthy (€25–40/h) — proof of willingness to pay where money allows.
Opportunity scoring (Session 8 lens)
We score the opportunity on five dimensions, 0–10, then read a weighted verdict. Weights emphasise problem severity and desirability, the two things hardest to fix later.
| Dimension | Score (0–10) | Weight | Contribution |
|---|---|---|---|
| Problem severity (pain) | 9 | 0.30 | 2.70 |
| Market size / reach | 7 | 0.15 | 1.05 |
| Desirability (do they want it) | 8 | 0.25 | 2.00 |
| Feasibility (can we build it) | 7 | 0.15 | 1.05 |
| Viability (sustainable motor) | 5 | 0.15 | 0.75 |
| Weighted score | 1.00 | 7.55 / 10 |
2Riskiest assumption + validation experiment
Before building anything, test the one assumption that would kill the venture if it were false. Plot each assumption by importance (damage if wrong) × uncertainty (how little evidence we have); the top-right corner is the Riskiest Assumption Test — the RAT, your real MVP (Sessions 13–14).
| Assumption | Importance | Uncertainty | Status |
|---|---|---|---|
| A1. Schools will let us run sessions on-site & refer students | 9 | 8 | ← RAT |
| A2. University students will tutor reliably for a small stipend | 8 | 5 | queued |
| A3. A funder (foundation/CSR) will pay per student-place | 9 | 6 | queued |
| A4. 12 weeks of tutoring measurably lifts maths grades | 7 | 5 | later |
Riskiest assumption (A1)
"Public secondary schools in our district will grant on-site access and actively refer students to a free, external tutoring programme." If false, our entire distribution channel and beneficiary pipeline collapse — so we test this first, before recruiting tutors or designing curriculum.
The experiment (cheapest test that could disprove it)
| Element | Design |
|---|---|
| Hypothesis | If we pitch a free numeracy pilot to school leadership, ≥30% will sign a letter of intent within 3 weeks. |
| Test | Cold-outreach + a one-page concept to all 14 district schools; book meetings; ask for a signed letter of intent (a costly signal, not a "nice idea"). |
| Sample | 14 schools contacted, target ≥10 meetings. |
| Success metric | ≥ 4 signed letters of intent (≈30%) committing a room + a referral list for a 12-week pilot. |
| Kill metric | ≤1 letter of intent → channel is broken; pivot to community centres / NGOs instead of schools. |
| Cost / time | ~€0 cash, ~3 weeks of two founders' time. |
Result (illustrative): 14 contacted → 9 meetings → 5 letters of intent (36%). RAT passed; A1 retired. The build-measure-learn loop then moves to A2 (tutor supply) and A3 (funding).
3Customer discovery → value proposition → MVP
With the channel proven, we ran customer discovery (Sessions 21–22), synthesised the insights, filled a Value Proposition Canvas (Session 20), and defined the smallest MVP that tests the value.
Customer discovery synthesis
We requested 60 interviews across three "customer" groups — students, parents, and the school as buyer. The funnel and the top recurring insights:
| Stage | Count | Conversion |
|---|---|---|
| Interviews requested | 60 | — |
| Scheduled | 39 | 65% |
| Completed | 31 | 79% |
| Revealed a real, urgent pain | 22 | 71% |
| Confirmed they'd commit (time / referral / budget) | 14 | 45% |
- Parents: want their child to keep up, but cost and trust are blockers — "free, at the school, with vetted tutors" removes both.
- Students: dislike feeling singled out; a near-peer university tutor feels like a mentor, not remedial class.
- Schools: care about pass rates and repetition; will refer if reporting is light-touch and on-site.
Value Proposition Canvas — fit (Session 20)
Customer profile (student + parent)
- Jobs: pass maths, keep up with class, feel capable, reach university options.
- Pains: tutoring too expensive; falling behind; stigma of "remedial"; no one at home can help.
- Gains: better grades, confidence, a relatable mentor, no extra cost or travel.
Value map (Aula Viva)
- Products: 2×/week on-site small-group numeracy sessions; trained near-peer tutors; progress snapshot.
- Pain relievers: free to family (funder-paid); on campus (no travel); peer tutor (no stigma); structured curriculum.
- Gain creators: measured grade lift; confidence; mentor relationship; university-pathway exposure.
Fit
Every top-ranked pain (cost, stigma, falling behind) and gain (grades, confidence, mentor) is covered by a reliever or creator → problem–solution fit reached on the highest-importance items.
MVP definition (Session 21–22 — "How to Build an MVP")
MVP
One 12-week pilot, one school, 2 tutors, 20 students, manual everything: paper sign-ups, a shared spreadsheet for attendance and a pre/post diagnostic test. No app. The MVP tests the value hypothesis — "12 weeks of near-peer tutoring measurably lifts maths attainment and students keep showing up" — at the lowest possible cost. Build it, measure attendance + grade delta, learn, then decide persevere vs. pivot.
4Business model · market sizing · unit economics
An impact venture still needs a sustainable motor. We chose a fund-the-place model — foundations and corporate-CSR budgets pay per student-place; the service is free to families. Then we size the market and check the unit economics (Sessions 19, 23, 25, 29).
Business Model Canvas (Session 23 / 29)
Key partners
- Public schools (channel)
- University career/volunteer offices
- Foundations & CSR funders
Key activities
- Recruit & train tutors
- Run sessions
- Measure & report impact
Value propositions
- Families: free, on-site, no-stigma tutoring that lifts grades
- Funders: measurable attainment gain per € — auditable SROI
- Tutors: paid, CV-building mentoring experience
Customer segments
- Beneficiary: 1st-gen students
- Payer: foundations / CSR
Key resources
- Trained tutor pool
- Curriculum & diagnostics
- School relationships
Channels
- Schools refer students (validated in RAT)
- University networks recruit tutors
- Impact reports reach funders
Customer relationships
- High-touch with schools & funders
- Mentor relationship with students
Cost structure
- Tutor stipends (largest)
- Programme coordinator
- Materials, training, reporting
Revenue streams
- Funder fee per student-place (~€450/student/term)
- Later: municipal contracts
Market sizing — TAM / SAM / SOM (Session 19, beachhead)
Top-down, then the beachhead we can realistically win. $$\text{SAM}=\text{TAM}\times s,\qquad \text{SOM}=\text{SAM}\times o$$
| Layer | Definition | Students | Funded value / yr |
|---|---|---|---|
| TAM | All under-resourced 1st-gen secondary students in Spain needing maths support | 300,000 | €135.0M |
| SAM | Madrid region public schools we can serve ($s=15\%$) | 45,000 | €20.3M |
| SOM | Beachhead: our district + reachable funders, 3-yr ($o=4\%$ of SAM) | 1,800 | €810,000 |
Unit economics — per student-place (Session 25)
Each place must earn back more than it costs to deliver and acquire. Here the "customer" paying is the funder; the unit is one student-place for a 12-week term.
| Line | Value | Note |
|---|---|---|
| Revenue per place (funder fee) | €450 | per student / term |
| Variable cost: tutor time | €230 | stipend × hours ÷ group size |
| Variable cost: materials & diagnostics | €40 | printed + test licences |
| Contribution margin | €180 | 40% gross margin |
| Funder acquisition cost (CAC, amortised) | €60 | per place across a multi-place grant |
| Avg places per funder relationship (lifetime) | 120 | renewing grants over ~3 yrs |
| Contribution after CAC, per place | €120 | positive → motor works |
Runway & burn (Session 25)
With a €60k philanthropic seed and a lean two-founder + part-time-coordinator team: $$\text{runway}=\frac{\text{cash}}{\text{net burn}}$$
| Item | € / month |
|---|---|
| Seed cash in bank | 60,000 |
| Monthly spend (stipends, coordinator, materials) | 7,500 |
| Monthly funded revenue (ramping) | 2,500 |
| Net burn | 5,000 |
5Impact — theory of change & SROI
For an impact venture, value is more than revenue. A theory of change links inputs → activities → outputs → outcomes → impact, and SROI monetises the social value created per euro invested (Session 11 impact demo).
Theory of change
| Inputs | Activities | Outputs | Outcomes | Impact |
|---|---|---|---|---|
| €60k seed, tutor pool, curriculum, school access | Train tutors; run 12-week on-site sessions; diagnostics | 20 students × 24 sessions; pre/post tests | Measured maths grade lift; higher attendance; confidence | More 1st-gen students stay on the academic track → university options widen |
SROI estimate (pilot year)
$$\text{SROI}=\frac{\text{social value of outcomes}}{\text{investment}}$$
| Line | Value | Basis |
|---|---|---|
| People reached (pilot) | 20 | students in MVP cohort |
| Social value per student | €3,000 | proxy: reduced grade repetition + lifetime earnings uplift, discounted |
| Gross social value | €60,000 | 20 × €3,000 |
| Attribution (our share) | 60% | net of what would happen anyway / other support |
| Net attributed social value | €36,000 | €60,000 × 0.60 |
| Investment (pilot) | €18,000 | direct pilot cost |
| SROI | 2.0 : 1 | €36,000 ÷ €18,000 |
6The 2-minute pitch + recommendation
The Process Story in two minutes — six beats that carry an audience from problem to ask.
- Problem. First-gen students in Madrid's under-resourced schools fall behind in maths because affordable, consistent support doesn't exist — the gap compounds and closes off university.
- Insight. 31 discovery interviews: families want help but can't pay; students reject "remedial"; schools will refer if it's free, on-site and low-admin.
- Solution. Aula Viva — free, on-site numeracy tutoring by trained near-peer university tutors, paid for by foundations per student-place.
- Evidence. RAT passed (5/14 schools signed letters of intent); MVP pilot shows attendance held and a measurable grade lift.
- Motor & impact. €120 contribution per place after CAC; 12-month runway on €60k seed; SROI ≈ 2:1 and rising with scale.
- Ask. €120k multi-year grant to reach 6 schools / 300 students and prove the model for a regional rollout.
Recommendation
Persevere and scale the beachhead. The riskiest assumption (school access) is validated, problem–solution fit is reached, the unit economics are positive, and the impact case (SROI ≈ 2:1) is defensible. The next loop should harden A4 — the grade-lift outcome — with a larger, longer cohort and an independent pre/post measurement before approaching a regional funder.
7Mapping to learning outcomes
How each step of this worked example evidences the EMP course learning objectives (LO1–LO6).
- LO1The end-to-end arc — problem → validated venture with a sustainable motor and social impact — demonstrates understanding of the entrepreneurial process and its impact at micro and societal level.
- LO2Re-framing a hunch into a problem statement, killing premature solutions, and prioritising the riskiest assumption practise the entrepreneurial mindset — comfort with uncertainty and evidence over opinion.
- LO3The example names and fills every key component: problem/opportunity discovery, value proposition, testing, the business model (desirability/feasibility/viability), resources and partners.
- LO4The RAT, the success/kill metrics, and the build-measure-learn loop demonstrate the value of experimentation in validating an idea cheaply before building.
- LO5The discovery funnel, interview synthesis, and willingness-to-commit signals show a real customer discovery & validation process identifying a launch-worthy opportunity.
- LO6The fund-the-place model, unit economics, 12-month runway, and the staged grant ask recognise the financing phase appropriate to an early impact venture.
8References & frameworks used
Course materials and frameworks this worked example draws on (see the course outline and syllabus PDF).
- Eisenmann, T. — Why the Lean Start-Up Changes Everything (HBR, R1305C). Build-measure-learn & validated learning.
- Riskiest Assumption Test — Why Your RAT Is The Real MVP (course multimedia, Sessions 13–14).
- Are You Solving the Right Problems? (HBR, R1701D) & Framing and Re-framing (ROT256) — opportunity framing.
- Osterwalder, A. & Pigneur, Y. — Value Proposition Design & Business Model Generation (Strategyzer canvases, Sessions 20, 23, 29).
- Aulet, B. — beachhead market & TAM/SAM/SOM (Session 19 multimedia: What is a Beachhead Market).
- Customer Discovery and Validation for Entrepreneurs (812097) & Hypothesis-Driven Entrepreneurship (812095), Sessions 21–22.
- Entrepreneurship Reading: Financing Entrepreneurial Ventures (8072) — runway & financing phases, Session 25.
- Social Return on Investment (SROI) methodology & theory of change — impact estimation.
- Course syllabus — Entrepreneurial Mindset & Practice, IE IMPACT, A. M. Sáenz Martínez (LO1–LO6).
All figures are illustrative worked examples for teaching, not validated field data. Per the syllabus AI policy, customer research and interviews must be conducted with real people and not simulated.