The setting

Northwind Outdoor designs and sells camping gear, tents, sleeping bags, and stoves, through its own site and a handful of outdoor retail partners. You are the supply chain analyst, reporting to operations director Hannah Cole, with planner Sofia Reyes and buyer Omar Haddad on the team.

Every mission on this path happens at the same company, so context carries over the way it does in a real job: the data you cleaned in mission two is the data the finance lead questions in mission four.

The missions

1. demand planstarter

Build Northwind's demand plan for the summer quarter

Northwind's busy season is summer and the factory needs a build plan for July through September now, while there is still time to order materials. Guess low and shelves go empty in peak season. Guess high and cash sits in a warehouse.

You deliver: A summer quarter demand plan with monthly units by category, the Summit Sports order included, and stated assumptions.

Scored on: Reflects the seasonal shape, Applies growth, Includes the Summit order, Stated assumptions.

Working from: sales_history.csv, planning_notes.md.

2. inventory checkstarter

Flag Northwind's stockout risks before peak season

Peak season is close and Hannah wants to know which items will run out before replenishment can arrive. A stockout on a hero product in July is lost revenue you cannot get back.

You deliver: A stockout risk report ranking items by weeks of cover versus lead time, with reorder actions for the at-risk items.

Scored on: Weeks of cover math, Names the top risk, Other risks and overstock, Reorder actions.

Working from: inventory_status.csv.

3. supplier analysiscore

Recommend a tent fabric supplier for Northwind

Omar is about to place the fabric order for the next tent run and two suppliers are in the running. The cheaper one looks tempting on the quote, but the quote is not the whole cost.

You deliver: A supplier recommendation for tent fabric with defect-adjusted cost for both options and a total-cost case, not sticker price.

Scored on: Looks past unit price, Defect-adjusted cost, Reliability case, Clear recommendation.

Working from: supplier_scorecard.csv, sourcing_notes.md.

4. logistics fixcore

Fix the delays on Northwind's Reno lane

Retail partners near Reno keep complaining that Northwind shipments arrive late, and Hannah wants the pattern nailed down and fixed, not hand-waved. You have the outbound shipment log from May.

You deliver: A logistics fix plan naming the delayed lane and carrier, quantifying the delay, and proposing a root cause and fix.

Scored on: Isolates the lane, Quantifies the delay, Plausible root cause, Fix with fallback.

Working from: shipment_log.csv.

5. ops reportstretch

Write Northwind's supply chain report for the leadership review

Hannah presents supply chain to the leadership team next week and wants one report that ties the quarter together: where service is slipping, why, and what to fund. You have the KPI scorecard and the running notes from the team.

You deliver: A one-page supply chain ops report linking KPI misses to causes and ending with three ranked, quantified recommendations.

Scored on: Quantifies the misses, Links causes, Three ranked recommendations, Readable one-pager.

Working from: sc_kpis.csv, team_notes.md.

How the scoring works

Each deliverable is graded against the rubric written for that mission. Separately, every mission on every path is graded on how you used AI, against the same four criteria:

  • Understood the task. The learner framed the goal for the assistant clearly instead of pasting the brief and hoping.
  • Grounded in the material. The learner directed the assistant into the provided files and based the work on them, not on invented facts.
  • Verified the output. The learner checked claims, numbers, or coverage against the source material before submitting.
  • Iterated with judgment. The learner refined weak parts of the draft with specific follow-ups rather than accepting the first answer.

Both scores, with the work behind them, go on your proof profile. That is what makes a claim like "I can use AI for supply chain and logistics" something an employer can check.