Retail Forecast Studio

A six-week programme that turns retail demand data into visual systems your planning meeting can defend.

Analytics dashboards displayed on a desk setup

Learning outcomes

  • Construct a baseline demand view with explicit comparison windows.
  • Design exception lanes that surface genuine outliers, not every dip.
  • Annotate festival and promo context without distorting the series.
  • Publish a limitation log that finance and ops can both accept.

Modules

Week 1 — Question before canvas

Frame one retail demand question and audit the exports you actually have.

Week 2 — Baselines that travel

Choose comparison periods that survive festive distortion and store openings.

Week 3 — Exception craft

Build heat and spike views that invite action instead of alert fatigue.

Week 4 — Context strands

Layer promo and calendar annotations using the Demand Mesh method.

Week 5 — Confidence & cuts

Practice saying what the data cannot support; draft a limitation log.

Week 6 — Studio review

Present a board to peers; revise for Monday-morning usability.

Instructor

Portrait of course instructor in professional attire

Farah Aziz

Former retail analytics lead who has coached planning teams across grocery and specialty formats in Malaysia. Farah focuses on visual judgement over tool allegiance.

Informational pricing

Individual access aligns with our Signal Desk path (RM 890). Teams of up to five typically enrol through Forecast Lab. No payment is taken on this page.

FAQ

Do I need a specific BI tool?

No. Exercises are tool-agnostic. We accept screenshots or exports from common platforms. The limitation: we do not provide enterprise licenses for third-party software.

Is this suitable if my POS history is short?

Yes—with caveats. Week 5 trains you to shrink claims when history is thin. If you have fewer than eight clean weeks, expect fewer aggressive forecasts and more diagnostic views.

How much time each week?

Plan for five to seven focused hours, including one critique submission. Peak festival weeks at work may require shifting a lab—extensions are available twice per cohort.

What is a real limitation of this course?

We do not automate replenishment orders. Graduates leave with clearer visuals and decision rituals; integration into your ERP or ordering tool remains your team’s engineering work.

Reviews from this course

Week 3’s exception craft changed how we triage SKUs. I still wish the sample grocery file matched our private-label mix more closely, but the critique notes compensated.

Hafiz · Inventory analyst, Shah Alam

Short take: Farah’s feedback on my baseline windows was blunt and useful. Our Deepavali board finally shows what changed versus last year without hiding gaps.

Lina M. · Merchandiser

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