Evaluating Opportunity Attractiveness

Opportunity attractiveness is scored, not declared

RelayOps is a B2B (business-to-business, selling to companies) SaaS (software as a service, subscription software delivered over the internet) venture improving dispatch and scheduling for mid-market field-service companies and the anchor venture for ENT 301. Founders Maya Chen (CEO, former dispatch manager at regional HVAC operator Summit Climate) and Jordan Okonkwo (CTO, former platform engineer) left Summit Climate in 2025 after living dispatch-center chaos firsthand. Their initial beachhead is 80-to-200 technician residential-heavy HVAC and plumbing firms, later expanding to commercial HVAC in Phoenix and Dallas with 50 to 150 field technicians. Discovery work confirmed 10 to 15 percent overtime on peak weeks and missed first-visit appointment windows tied to same-day capacity loss when dispatchers rebalance schedules across phone calls, whiteboards, and legacy CRM tabs without a live view of technician skill, location, and parts. Competitors include ServiceTitan (heavy and expensive for mid-market), spreadsheets and whiteboards (status quo).

Throughout this course, RelayOps evolves from opportunity hypothesis to scaled venture. Elective depth lives in ENT 401 (Customer Discovery and Opportunity Validation) when you want a full unit on that phase. ENT 301 teaches the integrated journey so you can advise founders, invest, or launch with disciplined evidence.

Attractive opportunities combine painful jobs, reachable buyers, credible founder edge, and economics that survive mid-market scrutiny. Evaluating opportunity attractiveness turns those factors into weighted scorecards, market sizing discipline, and kill criteria before MVP and fundraising narratives harden.

RelayOps targets $33,600 ACV (100 technicians × $28/month × 12) in a beachhead where interview WTP (willingness to pay, stated price acceptance) ranged $89-$149 per technician per month. Attractiveness is not "big market." It is whether RelayOps can reach cash-flow proof within runway.

This lesson closes Unit 0 by deciding whether H1 dispatch rebalance deserves Unit 1 customer validation spend.

Weighted opportunity scorecards

Scorecards prevent cherry-picking favorite metrics. RelayOps uses weighted criteria: pain intensity (×3), frequency (×2), existing spend (×2), buyer access (×2), founder edge (×1), competitive gap (×2), timing (×1). Each scored 1-5 with evidence notes.

Scores are comparable across hypotheses H1-H5. H1 ranked top in explore. Scorecards must be updated when new evidence arrives, not frozen for investor decks.

Attractiveness thresholds: promote to validate if weighted total exceeds preset bar and no single criterion scores 1 on buyer access or pain.

RelayOps H1 scorecard (post-explore):

Threshold to validate: ≥52 ✓

TAM, SAM, and SOM without fantasy

TAM (total addressable market, revenue if 100% share) for U.S. field service software is billions; irrelevant for seed decisions. SAM (serviceable addressable market, reachable segment) for RelayOps: mid-market HVAC/plumbing 80-200 techs in target metros. SOM (serviceable obtainable market, near-term winnable revenue) is 18-40 logos in 24 months.

Bottom-up SOM beats top-down TAM. RelayOps SOM math: 30 firms × $33,600 ACV ≈ $1,008,000 ARR (annual recurring revenue, subscription revenue recognized per year).

Attractiveness requires path from SOM to SAM, not slide from SAM to TAM.

Unit economics preview and ACV

Early attractiveness checks rough unit economics: ACV, gross margin, CAC (customer acquisition cost, sales and marketing per new logo), payback. RelayOps assumes 80% gross margin on software, founder-led CAC ~$12,000 per logo early, monthly gross profit per logo at 100 techs: $28 × 100 × 0.8 = $2,240.

Payback months ≈ CAC / monthly gross profit = 12,000 / 2,240 ≈ 5.4 months. Attractive if retention holds; premature if churn unknown.

Attractiveness without retention evidence is conditional, not proven.

Kill criteria and opportunity portfolios

Kill criteria make attractiveness falsifiable. RelayOps validate-stage kills: <6/10 unprompted rebalance pain; <3/10 COOs cite overtime hook; median WTP stated below $60/tech; IT security review >90 days in majority of sample.

Portfolio view: keep H4 monitoring on 20% time cap while H1 validates. Do not starve winner; do not hide losers.

Presenting attractiveness to capital partners

Investors want scorecards, SOM math, and kill criteria, not adjectives. Angels writing $250k checks ask whether $400k runway reaches paid pilots with clear persevere/pivot rules.

Operators want proof attractiveness ties to their P&L, not vendor TAM theater.

Maya presents opportunity gate memo combining scorecard, SOM, and kill criteria to Jordan and an angel advisor.

Part A: SOM build

Beachhead metros Phoenix + Dallas: ~220 firms in 80-200 tech residential-heavy HVAC/plumbing (desk research + association lists). Year-1 target 5% penetration = 11 logos.

ARR = 11 × $33,600 = $369,600.

MRR = $30,800.

Check: 11 × 33,600 = 369,600 ✓

Part B: Runway coverage

Burn $45,000/month. Validation phase budget 3 months = $135,000. Remaining post-validate $265,000 ≈ 5.9 months for MVP pilots.

Attractiveness requires ≥3 paid pilots before month 9 to justify seed raise narrative.

Part C: Decision

Score 58/65 equivalent exceeds threshold. Promote H1 to Unit 1 customer validation. Publish kill criteria in memo appendix.

Part D: Managerial read

Advisor question: "Is $369k ARR enough?" Answer: "It funds proof of repeatable founder-led sales in one beachhead, not victory. Attractiveness is sufficient to validate, not to declare PMF."

MediRoute (fictional) claimed $8B TAM in healthcare transport. SAM required hospital procurement and HIPAA (Health Insurance Portability and Accountability Act, U.S. health data privacy law) reviews. SOM for two founders was effectively zero in 18 months. RelayOps SOM stays in a buyer segment Maya can reach without procurement committees.

Updated data: 5/12 COOs mention overtime hook (below 3/10 kill if scaled). WTP median $95/tech. Scorecard pain still 5.

Tasks: (1) Recalculate weighted total if buyer access drops from 4 to 3. (2) Does kill trigger? (3) Recommend proceed, widen sample, or pause.

Solution

(1) Buyer access weighted was 8; new score 3×2=6; delta -2; new total 56.

(2) COO hook 5/12 = 41%; kill criterion was <3/10 = 30% at validate gate; not triggered yet at n=12 if threshold applies at n=10 only. Widen sample before kill.

(3) Proceed with 8 more COO interviews; if hook stays <30%, pause H1.

Check: 56 still ≥52 threshold ✓

Key takeaways

• Opportunity attractiveness uses weighted scorecards, not intuition.
• SOM bottom-up math grounds seed-stage decisions; TAM does not.
• Preview unit economics and payback with explicit assumptions.
• Kill criteria convert attractiveness into a portfolio decision.
• Gate memos should precede Unit 1 validation spend.

1. Build a one-page scorecard for a venture you follow with weights.
2. Compute SOM ARR for 15 logos at RelayOps ACV.
3. Continue to Unit 1, Lesson 1: Customer Discovery.

Applying Evaluating Opportunity Attractiveness at RelayOps

When RelayOps applies evaluating opportunity attractiveness, Maya Chen and Jordan Okonkwo anchor decisions in field evidence, not slide optimism. Their beachhead (80-to-200 technician residential-heavy HVAC and plumbing firms, later expanding to commercial HVAC in Phoenix and Dallas with 50 to 150 field technicians) experiences 10 to 15 percent overtime on peak weeks and missed first-visit appointment windows. Discovery interviews suggested $89 to $149 per technician per month in discovery interviews. Competitors include ServiceTitan (heavy and expensive for mid-market), spreadsheets and whiteboards (status quo). Every framework in this lesson should translate into a falsifiable claim about that segment, not generic startup advice.

Consider how opportunity discovery and problem selection changes capital allocation. RelayOps started with roughly $400k runway and ~$45k monthly burn before seed. A one-month delay on the wrong opportunity costs more than a month of disciplined interviews. That is why evaluating opportunity attractiveness is a CEO-level skill, not a brainstorming exercise.

Document owners alongside metrics. Maya owns discovery synthesis; Jordan owns build scope tied to assumption ranks; both sign kill criteria before pilots. When definitions live in a shared glossary (pilot versus beta, activation versus login), the team avoids comparing incompatible cohort charts after Dallas expansion.

Extended RelayOps scenario: cross-functional read

Imagine RelayOps's quarterly review for evaluating opportunity attractiveness. An angel investor asks whether dispatch pain justifies another build sprint. A pilot COO asks whether overtime reduction pays for software. A dispatcher lead asks whether the console survives Monday heat-wave call volume. A weak opportunity discovery and problem selection answer pleases one stakeholder. A strong answer links evidence: interview prevalence, timed shadow data, pilot median dispatch time, and renewal intent.

Work a conservative arithmetic example. Suppose RelayOps targets 100-technician firms at $28 per technician per month ($2,800 MRR per logo). Closing 18 beachhead logos yields $50,400 MRR ($605k ARR). If CAC (customer acquisition cost, sales and marketing to win one paying customer) is $18,000 per logo, payback in months equals CAC divided by monthly gross profit. At 80% gross margin on MRR, monthly profit ~$2,240; payback ~8 months. Check: 18,000 / 2,240 ≈ 8.0 ✓. Founders who skip this math raise before they know whether GTM is repeatable.

Stakeholder conflict is normal. Jordan may push feature breadth; Maya must protect RAT (riskiest assumption test, cheapest experiment that falsifies the highest-impact uncertain belief) scope. Evaluating Opportunity Attractiveness gives language to negotiate with pre-registered metrics rather than charisma. If evidence is descriptive only, label it and fund the next test instead of scaling spend.

For deeper study on this unit's specialty, see ENT 401 (Customer Discovery and Opportunity Validation). ENT 301 integrates the full arc; electives provide textbook-depth units you can take after this core course.

Technical mechanics and checks (RelayOps patterns)

For evaluating opportunity attractiveness, show work the way finance shows reconciliations. Opportunity scorecards print weighted criteria and explicit kill rules. Interview synthesis tables show code frequency with qualified denominators only. MVP scorecards list assumption rank, build weeks, runway share, and kill criteria. Cap tables after SAFE conversion show pre-money, post-money, and founder ownership with check lines.

Use plain-language hypotheses before instruments. Example: "If fewer than six of ten operations leaders rank same-day rebalance in top-three pains, RelayOps deprioritizes hypothesis H1." That hypothesis is falsifiable without code. Weak hypotheses hide inside feature roadmaps.

Spreadsheet grain matters. Customer-level tables suit funnel conversion; logo-month tables suit retention; assumption-level tables suit experiment backlogs. RelayOps forbids ambiguous metrics like "engagement" without operational definitions tied to dispatch jobs routed per active day.

Common executive questions (and disciplined answers)

Executives ask short questions that require long disciplined answers. "How sure are we?" maps to evidence labels (exploratory, descriptive, causal), not bravado. "What is the dollar impact?" maps to overtime saved, slots recovered, or MRR with stated assumptions. "Can we ship faster?" maps to risk of untested adoption during live emergencies. "Why not copy ServiceTitan?" maps to wedge focus and beachhead economics, not feature envy.

RelayOps's credible answer format for evaluating opportunity attractiveness is three bullets: recommendation, evidence strength, and next test if limitations matter. A fourth bullet states what would falsify the recommendation within 60 days. That discipline prevents founders from becoming either bottlenecks or rubber stamps for investor narratives.

Judgment under uncertainty (RelayOps decision log)

Founders who master evaluating opportunity attractiveness keep a decision log: date, decision, evidence at time, dissent captured, review date. When RelayOps chose emergency-queue MVP over full suite parity, the log recorded HeatRoute's LOI-to-active failure mode as contrast case. When Phoenix beat Dallas on retention, the log triggered segment screener review rather than blaming sales tone.

Your workbook should mirror that log format for one venture you follow. If you cannot write dissent and kill criteria, you have a story, not a decision. Evaluating Opportunity Attractiveness is how teams convert stories into capital-efficient learning.

Applying Evaluating Opportunity Attractiveness at RelayOps

When RelayOps applies evaluating opportunity attractiveness, Maya Chen and Jordan Okonkwo anchor decisions in field evidence, not slide optimism. Their beachhead (80-to-200 technician residential-heavy HVAC and plumbing firms, later expanding to commercial HVAC in Phoenix and Dallas with 50 to 150 field technicians) experiences 10 to 15 percent overtime on peak weeks and missed first-visit appointment windows. Discovery interviews suggested $89 to $149 per technician per month in discovery interviews. Competitors include ServiceTitan (heavy and expensive for mid-market), spreadsheets and whiteboards (status quo). Every framework in this lesson should translate into a falsifiable claim about that segment, not generic startup advice.

Consider how opportunity discovery and problem selection changes capital allocation. RelayOps started with roughly $400k runway and ~$45k monthly burn before seed. A one-month delay on the wrong opportunity costs more than a month of disciplined interviews. That is why evaluating opportunity attractiveness is a CEO-level skill, not a brainstorming exercise.

Document owners alongside metrics. Maya owns discovery synthesis; Jordan owns build scope tied to assumption ranks; both sign kill criteria before pilots. When definitions live in a shared glossary (pilot versus beta, activation versus login), the team avoids comparing incompatible cohort charts after Dallas expansion.

Extended RelayOps scenario: cross-functional read

Imagine RelayOps's quarterly review for evaluating opportunity attractiveness. An angel investor asks whether dispatch pain justifies another build sprint. A pilot COO asks whether overtime reduction pays for software. A dispatcher lead asks whether the console survives Monday heat-wave call volume. A weak opportunity discovery and problem selection answer pleases one stakeholder. A strong answer links evidence: interview prevalence, timed shadow data, pilot median dispatch time, and renewal intent.

Work a conservative arithmetic example. Suppose RelayOps targets 100-technician firms at $28 per technician per month ($2,800 MRR per logo). Closing 18 beachhead logos yields $50,400 MRR ($605k ARR). If CAC (customer acquisition cost, sales and marketing to win one paying customer) is $18,000 per logo, payback in months equals CAC divided by monthly gross profit. At 80% gross margin on MRR, monthly profit ~$2,240; payback ~8 months. Check: 18,000 / 2,240 ≈ 8.0 ✓. Founders who skip this math raise before they know whether GTM is repeatable.

Stakeholder conflict is normal. Jordan may push feature breadth; Maya must protect RAT (riskiest assumption test, cheapest experiment that falsifies the highest-impact uncertain belief) scope. Evaluating Opportunity Attractiveness gives language to negotiate with pre-registered metrics rather than charisma. If evidence is descriptive only, label it and fund the next test instead of scaling spend.

For deeper study on this unit's specialty, see ENT 401 (Customer Discovery and Opportunity Validation). ENT 301 integrates the full arc; electives provide textbook-depth units you can take after this core course.