CASE STUDY
Global Manufacturer Transforms
Demand Forecasting with IBM Planning Analytics
How a $2.4B manufacturer went from 58% forecast accuracy to 92%
— and eliminated $18M in excess inventory — in two quarters.
A $2.4 billion global industrial manufacturer operating four business units across North America, Europe, and Asia-Pacific. The company manages over 8,400 active SKUs through a multi-tier distribution network serving OEM, wholesale, and direct-to-consumer channels.
THE CHALLENGE: DISCONNECTED PLANNING WAS COSTING MILLIONS
The company’s demand planning process relied on a patchwork of regional spreadsheets, emailed
updates, and quarterly planning cycles that couldn’t keep pace with market volatility. Each of the
four business units maintained its own forecast in isolation, with no visibility into cross-divisional
demand patterns or shared capacity constraints. The consequences were measurable:
The company’s demand planning process relied on a patchwork of regional spreadsheets, emailed
updates, and quarterly planning cycles that couldn’t keep pace with market volatility. Each of the
four business units maintained its own forecast in isolation, with no visibility into cross-divisional
demand patterns or shared capacity constraints. The consequences were measurable:
- Forecast accuracy at 58%. Well below the 80% target needed for efficient production scheduling
- 45-day planning cycle. Forecasts were outdated before production even started
- $142M in inventory. $23M above optimal levels in raw materials and finished goods
- No demand signal integration from key retail and distribution partners
- Supply planning disconnected from demand. Production schedules based on last quarter’s actuals, not forward-looking demand
The VP of Supply Chain Planning put it bluntly: “We were planning next quarter based on what
happened last quarter. By the time we adjusted production, the market had already moved.”
“They didn’t just give us a forecast model
— they gave us a planning system that
connects demand to supply to finance. For
the first time, our S&OP process actually
drives decisions instead of documenting
them after the fact.”
VP OF SUPPLY CHAIN PLANNING
TECHNOLOGY STACK
- Platform: IBM Planning Analytics (TM1)
- Planning Model: ProfitCy®• S&OP Planning
- Excel Connectivity: Plaicel™ Web Add-In
- Data Integration: TurboIntegrator (ERP, POS, distributor feeds)
- Dashboards: Planning Analytics Workspace (PAW)
- Implementation Timeline: 12 weeks
*ProfitCy® is a pre-built suite of extended planning and analysis (xP&A) models built specifically to run on IBM Planning Analytics. Developed by Ironside’s delivery services partner, ForQuest Solutions, it functions as an add-on framework that integrates with IBM’s platform to accelerate financial, sales, and expense planning.
THE SOLUTION: INTEGRATED DEMAND & SUPPLY PLANNING ON IBM PLANNING ANALYTICS
ProfitCy® S&OP Planning — a pre-built demand and supply planning model deployed with
IBM Planning Analytics — configured for the client’s four business units, 8,400+ SKUs, and
multi-tier distribution network. The implementation took 12 weeks from kickoff to production.
IBM Planning Analytics Solution:
- Statistical demand forecasting with automatic seasonal decomposition and trend detection across all SKUs
- Consensus planning workflow connecting Sales, Operations, and Finance in a single TM1 model with role-based input templates
- Capacity-constrained supply planning that balances demand signals against production capacity, lead times, and safety stock targets
- Weekly rolling forecast replacing the quarterly cycle — automated refresh from ERP actuals via TurboIntegrator
- Plaicel™ Excel reports giving regional sales managers real-time demand visibility with writeback capability — no VPN required
- Demand-to-supply bridge connecting the demand plan directly to production scheduling and procurement planning
Why ProfitCy® made the difference:
Traditional consulting approaches would have required 6 – 9 months to design, build, and deploy a model of this
complexity. ProfitCy® S&OP Planning provided a production-ready framework that eliminated 70% of the build effort:
- Cube structures for demand, supply, inventory, and capacity were pre-built
- TurboIntegrator processes for ERP data loading were pre-configured
- Planning Analytics Workspace dashboards for consensus review were ready to customize
- Rules and feeders for statistical forecasting were proven across previous manufacturing deployments
BUSINESS OUTCOMES: MEASURABLE IMPACT WITHIN TWO QUARTERS
Traditional consulting approaches would have required 6 – 9 months to design, build, and deploy a model of this
complexity. ProfitCy® S&OP Planning provided a production-ready framework that eliminated 70% of the build effort:
34% Forecast Error Reduction
SKU-level forecast accuracy improved from 58% to 92%
within two quarters of go-live. Statistical decomposition
identified seasonal patterns that the manual process had
consistently missed, and weekly refresh cycles meant
forecasts reflected current demand signals rather than
45-day-old assumptions.
$18M Excess Inventory Eliminated
Better demand signals and capacity-constrained planning
reduced raw material and finished goods inventory
by $18M — from $142M to $124M — without a single
stockout on priority SKUs. Safety stock levels were rightsized based on actual demand variability rather than
blanket coverage rules.
45-Day Planning Cycle 4 Weekly
The quarterly 45-day planning cycle was replaced
with automated weekly rolling forecasts that refresh
from ERP actuals every Monday. Regional sales
managers submit demand adjustments through Plaicel™
in Excel — no training required, no VPN, no IT tickets.
Cross-Divisional Visibility
For the first time, all four business units plan from the
same model. Shared capacity constraints are visible
across divisions, and the demand-to-supply bridge
ensures production scheduling reflects consolidated
demand rather than siloed forecasts.
