Case study
Inventory forecasting tool
Demand signals, safety stock suggestions, and exception queues—so planners spend time on decisions, not spreadsheets.
Overview
Inventory forecasting tool
Scope, timeline, and context—how the work was framed before a single sprint shipped.
A forecasting workspace that blends historical sales, seasonality, and lead-time noise into actionable reorder recommendations.
Organization
Atlas Grid
Duration
5 months
Project type
Operations analytics
Role
Data product
Case study
How we got there
From constraint to release: the problem, the approach, the build, and what changed after go-live.
The problem
Planners exported CSVs weekly; models lived in notebooks nobody trusted; stockouts and overstocks both hurt margins.
The approach
We productionized models behind a review UI—every suggestion shows drivers, confidence, and override history.
The solution
Teams filter by SKU category, accept or tweak recommendations, and push approved orders to ERP connectors.
Product views
Inventory forecasting tool
Interface moments that show hierarchy, density, and polish—the same bar we bring to stakeholder reviews.
Results
The result
Outcomes we optimize for: less manual work, faster decisions, and software that stays trustworthy in production.
Stockouts fell year-over-year, carrying cost stabilized, and planners reclaimed hours previously lost to pivot tables.
Stockouts
−28%
Year over year
Planner hours
−35%
Weekly manual work
Forecast accuracy
+12pp
Vs. baseline
Next step
Want a build like this?
We scope in milestones, ship in slices, and keep communication crisp—so your roadmap stays honest.