Execution Scorecard

Mobile app that tracks badminton matches, rankings, and highlights

Mobile app that tracks badminton matches, rankings, and highlights scores 65/100 for execution readiness. The recommended next step is Recruit 3-5 local club organizers and run their next 4 weekly sessions through a no-code MVP (shared sheet + simple ELO script + a check-in form). Measure: do organizers keep using it unprompted week over week, do players ask for their rating between sessions, and would the organizer pay a monthly fee to keep the ladder running? Convert if 2+ clubs sustain use and an organizer commits to pay.

Bottlenecks

  • Rating integrity depends on honest self-reported scores; without referees, disputed or fabricated results can erode trust in the ladder and require dispute/verification tooling.
  • Crowded adjacent space: scoreboard apps, the official BWF app, club booking suites, and incumbent UBR could each extend into the gap, so the social/ratings network effect must be won club-by-club fast.
  • Two-sided cold-start: a rating is only meaningful once a critical mass of a player's regular opponents are on it, so single-club seeding and organizer-led onboarding are essential.
  • Highlights add real cost and complexity (storage, editing, copyright/likeness of bystanders) and may distract from the core ranking value if shipped too early.
  • A broad AI assistant can flatten differentiation unless the wedge is painfully specific.
  • The first release can become a generic dashboard if the job is not named tightly.
  • Needs real buyer access, not only desk research.

Accelerators

  • Can talk to the buyer before writing much code.
  • Can ship a narrow first-win demo quickly.
  • Can use local-first research artifacts to keep validation moving without a large team.
  • Use specificity as the wedge: one buyer, one workflow, one measurable result.
  • Show proof earlier than broad competitors with before-and-after examples and small pilot data.
  • Keep implementation lighter than incumbent suites or generic AI assistants.
  • Concierge review or paid template

Dated Plan

First 30 days to evidence.

The plan starts from build time and should be re-exported when the founder chooses a real start date.

2026-06-26

1. Frame the wedge

Write the one-sentence promise and test it in the strongest channel.

Proof: Recruit 3-5 local club organizers and run their next 4 weekly sessions through a no-code MVP (shared sheet + simple ELO script + a check-in form). Measure: do organizers keep using it unprompted week over week, do players ask for their rating between sessions, and would the organizer pay a monthly fee to keep the ladder running? Convert if 2+ clubs sustain use and an organizer commits to pay.
2026-06-29

2. Interview 10 people who match the buyer persona.

Create the lead magnet and use it to recruit interviews.

Proof: Problem resonance: 5+ calls or 10+ detailed replies.
2026-07-03

3. Ship a clickable demo or concierge workflow that produces the first useful artifact.

Build the smallest demo that proves the first win.

Proof: Activation: 25% of demo visitors complete the first-win path.
2026-07-10

4. Run one paid pilot or collect explicit pricing objections before automating the rest.

Delete any report section that feels generic before building.

Proof: Commercial pull: 3 paid pilots, LOIs, or concrete procurement next steps.
2026-07-17

5. Promote to a deeper build plan only after the wedge survives validation.

Run the lead magnet and first-win demo tests.

Proof: Fewer than five qualified buyers agree to discuss the workflow after targeted outreach.
2026-07-26

6. Execution checkpoint 6

Promote to deeper implementation only once the wedge survives interviews or paid-pilot outreach.

Proof: Promote to a deeper build plan only after the wedge survives validation.

First actions

  • Write the one-sentence promise and test it in the strongest channel.
  • Create the lead magnet and use it to recruit interviews.
  • Build the smallest demo that proves the first win.
  • Delete any report section that feels generic before building.
  • Run the lead magnet and first-win demo tests.
  • Promote to deeper implementation only once the wedge survives interviews or paid-pilot outreach.

Builder prompt

Create a dated execution plan for "Mobile app that tracks badminton matches, rankings, and highlights". Keep the first milestone tied to Recruit 3-5 local club organizers and run their next 4 weekly sessions through a no-code MVP (shared sheet + simple ELO script + a check-in form). Measure: do organizers keep using it unprompted week over week, do players ask for their rating between sessions, and would the organizer pay a monthly fee to keep the ladder running? Convert if 2+ clubs sustain use and an organizer commits to pay.. Use these bottlenecks: Rating integrity depends on honest self-reported scores; without referees, disputed or fabricated results can erode trust in the ladder and require dispute/verification tooling.; Crowded adjacent space: scoreboard apps, the official BWF app, club booking suites, and incumbent UBR could each extend into the gap, so the social/ratings network effect must be won club-by-club fast.; Two-sided cold-start: a rating is only meaningful once a critical mass of a player's regular opponents are on it, so single-club seeding and organizer-led onboarding are essential.; Highlights add real cost and complexity (storage, editing, copyright/likeness of bystanders) and may distract from the core ranking value if shipped too early.; A broad AI assistant can flatten differentiation unless the wedge is painfully specific.; The first release can become a generic dashboard if the job is not named tightly.; Needs real buyer access, not only desk research.. Use these accelerators: Can talk to the buyer before writing much code.; Can ship a narrow first-win demo quickly.; Can use local-first research artifacts to keep validation moving without a large team.; Use specificity as the wedge: one buyer, one workflow, one measurable result.; Show proof earlier than broad competitors with before-and-after examples and small pilot data.; Keep implementation lighter than incumbent suites or generic AI assistants.; Concierge review or paid template. Link the output to the Idea Builder prompt and do not expand beyond the first validated workflow.