Prioritize projects and manage tight deadlines

# 1) Prioritization and Sequencing (Framework, Assumptions, Decision Rule) Assumptions (explicit): - "Eng-weeks" are the limiting engineering capacity under my control (analytics/data eng + instrumentation). Design is a separate shared constraint; only (B) needs design; (A) and (C) have minimal/no design dependency. - Compliance lead time = 1 week means code complete date = launch date − 7 days. - No additional hires/contractors; if we need more capacity, it requires escalation. Scheduling guardrail: Latest Start Date (LST) - LST = Deadline − ComplianceLeadTime − Effort - If LST is in October, it must fit within the 2 eng-weeks before Oct 30; otherwise it must fit within November's 1 eng-week. Compute LSTs (before any scope cuts): - (B) Oct 30 launch → code complete by Oct 23 → effort 2.0 → LST = Oct 9. - (A) Nov 15 launch → code complete by Nov 8 → effort 1.5 → LST ≈ Oct 25. - (C) Nov 30 launch → code complete by Nov 23 → effort 1.0 → LST = Nov 16. Observation: With only 2 Oct eng-weeks total, (B) at 2.0 fully consumes October. November only has 1.0 eng-week, but (A)+(C)=2.5 eng-weeks. Therefore, without scope cuts or renegotiation, the plan is infeasible. Prioritization framework: WSJF (Weighted Shortest Job First) - WSJF = Cost of Delay (CoD) / Job Size (effort) - CoD components (relative 1–10): business value, time criticality, risk reduction/enablement. Baseline WSJF (pre-scope-cut, relative scoring): - (B) Dashboards: value 7, time 10 (QBR), enablement 5 → CoD 22; size 2.0 → WSJF 11. - (A) Cancellations: value 8, time 7, enablement 7 → CoD 22; size 1.5 → WSJF ≈ 14.7. - (C) Pricing: value 9, time 6, enablement 6 → CoD 21; size 1.0 → WSJF 21. Decision rule (practical): - Step 1 (Feasibility gate): Respect hard deadlines/compliance (must hit code-complete by the date or proactively renegotiate). - Step 2 (WSJF within feasibility): Sequence by highest WSJF, then adjust for design constraints. - Step 3 (Scope to feasibility): If infeasible, reduce scope to minimally preserve expected impact; if still infeasible, drive a trade-off decision with sponsors. Applying the rule: - (B) has a hard QBR deadline with compliance; must secure an October slot. - To accommodate (A) and (C), we must cut scope. The least-risk pattern: trim (B) to a QBR-ready MVP (no advanced drill downs), reduce (A) to the top root-cause fix + monitoring, and simplify (C) to a server-side multiplier test. High-level sequence (pre-incident): - Oct window (2.0 weeks): (B) MVP 1.5 weeks (Oct 9–23 code complete) → compliance Oct 23–30; remaining 0.5 week split before/after for either (C) or (A) pre-work. - Nov window (1.0 week): Split across (A) and (C) to reach code-complete before their compliance windows. # 2) Minimal Viable Scope (MVP) and Scope Cuts (A) Courier cancellations (target −10% by Nov 15): - MVP scope (reduce to 1.0 eng-week): - Instrumentation and monitoring: daily cancellation-rate monitor by city/vertical; alerts for spikes. - Root-cause taxonomy enrichment (e.g., structured reason codes from courier app and ops tools). - Top-1 or Top-2 cause fix or playbook (e.g., merchant item unavailable/long prep time; courier reassignment threshold tweak; ETA accuracy improvement via feature flag). - Cuts/defer: - Full ML ETA revamp; multi-cause surgical fixes; automated feedback loops. Rationale: one high-leverage fix + monitoring can deliver most of the early impact. (B) Merchant quality dashboards (QBR by Oct 30): - MVP scope (reduce to 1.5 eng-weeks + focused design): - Single landing page with 5 core KPIs (fulfillment rate, on-time readiness, cancellations, average prep time, defect rate) with daily refresh. - Filters: date range, region, merchant segment; download/CSV export. - Role-based access to QBR audience; productionized pipeline with data quality checks. - Cuts/defer: - Historical deep-dive pages, cohorting, alerting, time-series anomaly detection, merchant drill-downs. Rationale: QBR needs consistent single source of truth, not full self-serve v1. (C) Pricing uplift experiment (Nov 30): - MVP scope (keep at 1.0 eng-week total): - Server-side price multiplier (e.g., +x% on delivery fee or service fee) for a narrow region/category using the existing experimentation platform. - Predefined guardrails: conversion, take-rate, cancellations, customer support contacts. - Telemetry: exposure logs, assignment, key outcomes; no new UI/design. - Cuts/defer: - Multi-arm bandits, dynamic price elasticity model, broad rollout, complex stratification. Rationale: prove +2% feasibility on a small slice first. # 3) Stakeholder Communication Plan Commitments (pre-incident): - VP Ops (A): Commit to MVP focused on top cancellation driver + monitoring; code complete by Nov 5; compliance Nov 8–15; launch Nov 15. Risk: if top cause is not dominant, impact may be <10%; we will have a contingency next-best fix pre-scoped. - Head of Merchant (B): Commit to QBR-ready dashboard MVP code-complete by Oct 23; compliance Oct 23–30; launch Oct 30. Clear list of post-QBR enhancements. - CPO (C): Commit to a narrow-scope server-side price test: code complete by Nov 20; compliance Nov 23–30; launch by Nov 30. Guardrails and success review in early Dec. Trade-offs (made explicit): - To hit (B) QBR, (B) must be MVP. The freed 0.5 Oct week funds pre-work for (A) or (C). November’s 1.0 week must be split between (A) and (C), so both must be MVP and tightly scheduled. Illustrative schedule (pre-incident): - Oct 1–4: (C) MVP pre-work (0.5 wk) - Oct 9–23: (B) MVP build (1.5 wks) → Compliance Oct 23–30 - Oct 23–30: (A) MVP pre-work (0.5 wk) in parallel with (B) compliance - Nov 1–5: (A) finish (0.5 wk) → Compliance Nov 8–15 → Launch Nov 15 - Nov 16–20: (C) finish (0.5 wk) → Compliance Nov 23–30 → Launch Nov 30 Sample weekly status update (concise): - Status (as of Oct 18): - (B) Dashboards: GREEN. 65% complete; data model finalized; front-end MVP in progress. On track for code complete Oct 23; compliance scheduled Oct 23–30. - (A) Cancellations: YELLOW. Root-cause taxonomy validated; pre-work slated for Oct 23–30. Risk: data quality variance in courier reason codes; mitigation: add normalization step. - (C) Pricing: GREEN. Experiment design locked; exposure logging stubbed; 0.5 wk remaining in Nov. - Risks/asks: None this week; design fully allocated to (B) until Oct 23. Script for saying no (principled trade-off): - "Given a fixed 2 eng-weeks before Oct 30 and 1 eng-week in November, plus a mandatory 1-week compliance lead time, we can deliver the QBR dashboard and the cancellations MVP by their dates. To also deliver the pricing test by Nov 30, we would need +0.5 eng-week or to further reduce the dashboard scope. If additional capacity isn’t available, I recommend we keep the dashboard MVP for QBR and proceed with the pricing test as scoped, with a contingency to slip a few days if the cancellations work runs long. Which trade-off do you prefer?" # 4) Critical Incident on Oct 25 (0.5 eng-week): Plan Update and Renegotiation Impact: The Oct 25 data quality incident consumes the 0.5 eng-week planned for (A) pre-work during Oct 23–30. (B) remains GREEN (already code-complete on Oct 23). This creates a November capacity crunch. Updated capacity and schedule: - Oct: consumed by (B) 1.5 wks + incident 0.5 wk. No (A) pre-work in Oct. - Nov (only 1.0 wk total): - (A) now needs full 1.0 wk in Nov 1–7 to hit code-complete by Nov 7 → Compliance Nov 8–15 → Launch Nov 15. - (C) has 0.5 wk completed in early Oct but still needs 0.5 wk to reach code-complete by Nov 22. There’s no November capacity left. Therefore (C) slips unless we add capacity or reduce (A) further. Renegotiation plan (early, transparent, options-based): - With CPO (C): - Present options: (1) Slip launch to Dec 7 (code-complete Nov 30 → Compliance Dec 1–7), or (2) reduce (C) to a micro-canary limited to one DMA with a shorter observation period and accept lower confidence, still requiring 0.5 eng-week in early Dec; or (3) add 0.5 eng-week from another team between Nov 16–20. - Recommendation: Slip to Dec 7 with pre-computed guardrails/holdouts ready, so we protect (A) and keep (B) delivered for QBR. Commit to deliver pre-analysis and experiment configuration dry-run in parallel (non-eng tasks) so time-to-value is minimized. - With VP Ops (A): - Confirm we’re still GREEN by pulling the full 1.0 wk Nov 1–7. Offer to include a second tactical mitigation (playbook) if the incident root cause overlaps with cancellation drivers. - With Head of Merchant (B): - Confirm successful Oct 30 launch. Share backlog for post-QBR enhancements and the date we can resume work based on (A)/(C) outcomes. Trust-preserving actions: - Communicate within 24 hours of incident: impact, new plan, and clear rationale using capacity math and compliance gates. - Publish a one-pager with the revised timeline, risks, and explicit asks (e.g., +0.5 eng-week by Nov 16 if the CPO wants Nov 30 retained). - Keep a decision log noting who agreed to which trade-offs and when. # 5) Success Criteria (for My Performance) Leading indicators: - Milestone adherence: code-complete dates vs. plan; compliance submissions at least 1 business day before cutoff. - Risk burn-down: open risks count trending down weekly; all risks have owners and mitigations. - Stakeholder alignment: weekly status consumed (open/read), decisions recorded within 48 hours, no unplanned surprises. - Quality gates: unit/integration tests passing; data validation checks (freshness, completeness, invariants) ≥ 99% for (B); experiment telemetry completeness ≥ 98% for (C). Outcome indicators: - (B) dashboard usage by QBR audience (≥ 80% of intended viewers log in; data trusted, zero critical defects). - (A) measurable reduction in cancellations: at least −7% within 2 weeks as an interim target; plan to reach −10% with second mitigation if needed. - (C) experiment runs with guardrails respected; statistically valid read on primary metric within 2 weeks post-launch. Key risks and contingencies: - Compliance delays: submit early; have a pre-checked artifact list; reserve a 0.25 wk buffer before compliance. - Design contention: constrain (B) to a single layout; reuse components; avoid design for (A)/(C). - Data quality incidents: predefine triage SLAs; maintain rollback plans and feature flags; have a frozen change window 48 hours before compliance submission. - Capacity shocks: pre-agree a cut list (e.g., defer (C) to Dec) and an escalation playbook to request +0.5 eng-week if an incident hits during compliance windows. Summary of the updated plan after the incident: - (B) Launch Oct 30 (on track; compliance Oct 23–30). - (A) Code-complete Nov 7; compliance Nov 8–15; launch Nov 15. - (C) Slip to Dec 7 unless +0.5 eng-week is added mid-November; pre-work complete and ready to resume immediately after (A). This plan is feasible, preserves the most time-critical commitments, and manages trust by making trade-offs explicit, quantified, and jointly decided.