Seasonal operation planner

Builds a store-level plan for a season peak so that stock, team, layout and services are ready the day customers arrive, not two weeks later.

When to use

• Preparing a season peak: winter sports, back to school (running, team sports, swimming), spring cycling, summer outdoor, or a sales or Black Friday period.
• The N-1 operation went badly (stock-outs, queues at the workshop, late implantation) and the manager wants to do better.
• An area manager wants the same retro-planning across several stores.
• Not for: the company-wide promotional calendar (use promo-calendar-planner), the marketing campaign itself (use campaign-brief), a one-day community event (use local-sport-event-planner), or the hour-by-hour schedule (use staff-planning-assistant).

Inputs

• Store(s), operation and dates (required), including the peak window (for example ski: first snow weekend to the end of the February school holidays).
• Objectives (optional, default: N-1 result + target if found).
• National or regional operation brief (optional, default: searched in Drive, Confluence and mail).
• Constraints (optional): surface, stock room capacity, team size, works, local competition.

Sources

1. Drive, Confluence, Gmail: the operation brief from HQ or the region, implantation plans, visual merchandising guidelines, N-1 debrief, deadlines for orders or signage. Quote them; never invent a date or a rule.
2. Databricks via Polco: N-1 weekly sales, visitors, conversion, workshop and rental volumes and stock-outs over the same weeks, by sport universe. Verify with Databricks SQL MCP after discovering tables; never assume columns; show the queries.
3. Tableau: season or category dashboards for targets and official KPIs.
4. Calendar: school holiday dates and local events only if present in calendars or docs; otherwise ask.
5. Airtable or Jira: operation trackers, signage or works requests.
6. Chat, Slack: N-1 lessons shared by teams, supply alerts. If a source is not connected or returns nothing, say so in one line and continue with what you have. Never announce a search without giving its result in the same answer. If the essential data is still missing, ask for it in one grouped question, show the outline you will fill, and use placeholders such as [to confirm] instead of invented examples.

Workflow

1. Learn from N-1: weekly curve of revenue and visitors over the season (when did the peak start, how high, how long), the top 20 models, OOS rate in peak weeks, workshop backlog peak, staffing gaps mentioned in the debrief. Write the 3 lessons that change this year's plan.
2. Objectives: revenue and key KPIs per peak week (target if found, else N-1 + stated assumption), plus 1–2 service KPIs (workshop turnaround, availability of top models).
3. Retro-planning from the opening date D (adapt timings to the brief found):

   When	Stream	Typical milestones
   D-90 to D-60	Stock	range validated, pre-orders and allocations checked, stock room space freed
   D-60 to D-30	Team	reinforcement needs, recruiting and onboarding, product trainings (boot fitting, bike sizing, ski prep)
   D-45 to D-21	Services	workshop capacity, rental fleet checked, second-hand intake prepared
   D-30 to D-14	Layout	implantation plan, hot zone and endcaps, signage ordered, mannequins and test areas
   D-14 to D-1	Execution	receipts, implantation done, price checks, team briefing, dry run of the checkout and workshop flow
   D to D+14	Run	daily KPI check, replenishment rhythm, staffing adjustment, quick fixes
   D+14 / end	Debrief	results vs objectives, lessons, actions for N+1

4. Stock readiness: expected weeks of cover at D for the top models vs the N-1 peak sales rate; size runs on footwear and boots; plan for replenishment frequency during the peak.
5. Staffing and skills: peak hours from N-1 traffic, number of reinforcement hours needed (rough estimate, refined with staff-planning-assistant), skills to train before D.
6. Layout and visual merchandising: the season universe in the hot zone, family-to-product logic (practice → equipment → accessories → services), price clarity, multi-sale bundles (skis + bindings + waxing).
7. Local communication: in-store signage, local partners or clubs, store social accounts if the store has them; align with the national campaign.
8. Risks (weather, supply delay, recruitment, IT) with mitigation and owner; then the debrief plan.

Output format

# <Operation> — <store> — <D date>
**Objective:** <headline KPI target> · **Peak window:** <dates> · **Owner:** <role>

## Lessons from N-1
1. <lesson + number + source>

## Objectives by week
| Week | Revenue obj. | N-1 | Visitors N-1 | Service KPI |
|------|--------------|-----|--------------|-------------|

## Retro-planning
| Date | Milestone | Stream | Owner (role) | Status |
|------|-----------|--------|--------------|--------|

## Readiness checklist
- [ ] Stock: <top models covered for x weeks at D>
- [ ] Team: <reinforcement hours, trainings>
- [ ] Services: <workshop / rental / second-hand>
- [ ] Layout: <implantation, signage>
- [ ] Communication: <local actions>

## Risks
| Risk | Likelihood | Impact | Mitigation | Owner |
|------|------------|--------|------------|-------|

## Debrief plan
<date, KPIs, who>

_Sources: <brief link, N-1 data queries, Tableau view>_

Quality checks

• Every milestone has a date, an owner role and a stream; nothing important happens « at D ».
• Lessons from N-1 are backed by data or the N-1 debrief, or marked as the user's view.
• Objectives state whether they come from an official target or from N-1 + assumption.
• Stock readiness compares cover at D with the N-1 peak sales rate, not the average rate.
• Dates from HQ briefs are quoted with the link; no invented deadline.

Guardrails

• No invented targets, budgets, order deadlines or HQ rules; mark them « to confirm ».
• Staffing numbers are estimates for planning; schedules and contracts follow staff-planning-assistant and human validation of labor-law points.
• Local communication using customer data must follow the company's consent rules; do not plan direct messaging to customers without that check.
• Draft only: no orders, signage requests, tickets or messages are created without the user's confirmation.

Example

Input: « Prépare la saison ski du magasin d'Annecy, ouverture de l'univers mi-novembre » → French plan. Illustration: if N-1 data shows the peak started with the first snowfall weekend and the boot-fitting zone was the bottleneck on Saturdays; milestones include boot-fitting training at D-30, ski-prep workshop capacity at D-21, rental fleet check at D-21, implantation at D-10; risk « late snow » mitigated by keeping a cross-country and hiking offer visible.