Impact / results-led case
Northstar Retail improved forecast accuracy and reduced out-of-stocks
Try in PlaygroundExample brief
Northstar Retail, with 780 stores across 9 European markets, transformed their demand-planning process by consolidating various data signals and implementing a planner copilot, resulting in an 84% forecast accuracy, 18% reduction in out-of-stocks, EUR 11.6M in markdown savings, and a significant reduction in planner cycle time from 5 days to 11 hours, as measured in a pilot covering 42 high-variance categories.
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Brief path
curl -X POST https://api.slideforge.dev/v1/render/auto \
-H "Authorization: Bearer sf_live_..." \
-H "Content-Type: application/json" \
-d '{ "brief": "Northstar Retail, with 780 stores across 9 European markets, transformed their demand-planning process by consolidating " }'Structured intent (this template)
{
"pattern": "case_story",
"title": "Northstar's planning cockpit changed outcomes, not just analytics adoption",
"subtitle": "Demand-planning transformation - impact case",
"variant": "impact_results_case",
"client": {
"name": "Northstar Retail",
"industry": "Retail",
"region": "Europe",
"descriptor": "780 stores - 9 markets"
},
"context": "Northstar previously ran weekly Excel category forecasts with country-specific assumptions. We consolidated POS, promotion, weather and supplier-delay signals into a governed data product, added demand-forecast models, and embedded a planner copilot for exception review.",
"results": [
{
"value": "84%",
"label": "Forecast accuracy",
"sub": "from 72%",
"tone": "good"
},
{
"value": "-18%",
"label": "Out-of-stocks",
"tone": "good"
},
{
"value": "EUR 11.6M",
"label": "Markdown saved",
"sub": "annualized",
"tone": "good"
},
{
"value": "11 hrs",
"label": "Planner cycle time",
"sub": "from 5 days",
"tone": "good"
}
],
"proof_notes": [
"Pilot covered 42 high-variance categories",
"Benefits measured vs a matched-store baseline"
],
"source_note": "Northstar pilot results, 2026",
"takeaway": "It worked because planners trusted the exception workflow, not because the model was more complex."
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