The business problem
BrewLine Coffee Roasters is a regional specialty roaster: 85 business accounts, 5 delivery regions, three months of falling customer satisfaction. The CEO sent you the operational data and asked for answers by Friday. The data is real-shape messy — multiple sheets, different grains, missing fields. The first job is just figuring out what's happening; the second is figuring out why; the third is recommending what to change.
What "diagnostic case" means
Unlike a focused case (build a forecast, size inventory), this one doesn't tell you what method to use. You have to read the data, choose your decisions, and defend the choice. That's the actual operations-analyst job.
Case kit
Everything you need
- AI in OSCM — Student Activity GuideWalks the BrewLine scenario as a model workflow. Read this first.
- BrewLine Operations DatasetMulti-sheet workbook — orders, suppliers, staffing logs, CSAT scores.
- AI Lab InstructionsSpecific prompts that work well on this dataset.
- Prompt Engineering for OSCMIf you go the AI-augmented route, this is the prompting reference.
Deliverable
A one-slide recommendation to Maya Chen, the CEO. Three pieces:
- What's the real problem? One sentence, with the dominant cause named.
- What's the evidence? The two charts or numbers from the dataset that prove it.
- What to do this week. One concrete action small enough to start Monday, with the cost framed against the threatened account revenue.
Topics you'll be applying
- Decision 2 — Bottlenecks · the fulfillment process is suspect
- Decision 3 — Sourcing & Logistics · supplier records are part of the puzzle
- Decision 5 — Inventory & MRP · stockouts may be implicated
- Decision 6 — Quality · CSAT is a quality outcome metric