About the Customer

This global tier-one automotive parts supplier manufactures chassis and suspension systems, including struts, shock absorbers, and ride dynamics components, for the world’s largest OEMs, including Toyota, Ford, and Stellantis. Their business depends on anticipating how many vehicles each OEM will build, across every platform and variant, years into the future. A single vehicle platform can include dozens of trim variants, and a single vehicle requires multiple parts.

Multiply those variations across hundreds of platforms and a ten-year forecast horizon, and the data complexity is enormous.

The starting point for every forecast is IHS Market data (third-party projections of vehicle production volumes published monthly). IHS tells the supplier how many units of a given platform an OEM plans to build. It doesn’t tell them how many parts they’ll actually sell. Translating IHS volumes into product-level demand requires layering in penetration rates (what share of a platform’s volume the supplier expects to capture), parts-per-vehicle calculations, and manual overrides based on real conversations with OEM buyers.

Before Manufacturing Cloud, the supplier managed all that data in Excel. Once Manufacturing Cloud was implemented, the customer needed additional support with configuring it to meet their needs.

No Way to Connect Market Data and Product Demand

Most manufacturers forecast based on their own sales pipeline. Tier-one suppliers forecast based on someone else’s production schedule, and the math to translate vehicle volumes into product demand is specific to every platform, every part, and every OEM relationship.

Our customer had no system to bridge IHS vehicle volume data to product-level forecasts. Penetration rates, parts-per-vehicle logic, and manual volume overrides were managed across spreadsheets maintained by a dedicated forecasting team. There was no single source of truth, no live data, and no ability for sales leadership to trust the numbers driving supply chain planning.

They invested in Salesforce Manufacturing Cloud, but Manufacturing Cloud doesn’t solve a tier one supplier’s problems out of the box.

Our customer’s volume updates ran on two-hour batch cycles, where a rep would make a forecast adjustment, wait two hours, and often couldn’t tell if it had taken effect. Worse, the batch processes silently overwrote manual volume overrides. Reps would adjust a penetration rate based on a conversation with an OEM, only to find the change wiped the next time the batch ran.

New vehicle introductions compounded the problem. Onboarding a new platform variant required extensive manual setup. A single penetration rate change should propagate across every sales agreement that part touches — Toyota, Ford, Stellantis, etc. Instead, reps waited hours and painstakingly verified propagation record by record.

Leadership couldn’t trust the forecast. OEM reporting accuracy was at risk. The demand planning team spent its time reconciling data instead of planning.

A Purpose-Built Manufacturing Cloud Architecture That Delivers Actionable Forecasts

ForeFront was brought in to make the customer’s existing Manufacturing Cloud environment work the way a tier-one supplier actually needs it to.

Here’s how it works:

• The core of the solution is a custom data architecture that automatically ingests IHS vehicle production data and maps it through the supplier’s full forecast logic.
• IHS volume projections flow into Salesforce and are matched against vehicle platforms, platform variants, and the supplier’s sales agreements.
• The system handles the math that makes tier-one forecasting genuinely complex: Penetration rates that determine what share of OEM volume the supplier expects to capture, parts-per-vehicle calculations that translate vehicle units into product demand (one Camry equals four struts), and manual volume overrides where reps adjust projections based on real OEM conversations.
• Two-hour batch cycles were replaced with trigger-based automation. When a rep adjusts a forecast, the change propagates across all related sales agreements in seconds.
• A Manual Volume Override lock ensures that rep-entered adjustments are protected from automated processes, so changes persist through every system update.
• The interface was re-designed around how sales managers work. Reps can adjust and see downstream impact across every related agreement… without navigating through multiple screens or waiting on batch confirmations. The system is intuitive enough that the sales team adopted it without resistance, replacing a process that previously required a dedicated forecasting team to manage manually.
• Platform variant automation was rebuilt so new vehicles, IHS volume records, and product schedules trigger automatic record creation and propagation. What previously required hours of manual setup now happens through the system.

The solution was tested under real market pressure almost immediately. When tariffs hit, the supplier needed to reprice across every agreement and vehicle platform simultaneously. The system propagated changes that same day. What would have been a multi-day fire drill in the old environment became a routine adjustment.

Real-Time Forecasting, Protected Overrides, & Strategic Demand Planning

Volume updates dropped from hours to seconds, manual overrides are fully protected, and the demand planning team shifted from reconciliation to strategy. Here’s a deeper look at the key outcomes of our ongoing engagement:

• Volume updates in seconds, not hours: Trigger-based automation replaced two-hour batch cycles. When tariffs required rapid repricing, the supplier adjusted across all agreements same-day.
• 100% retention of manual overrides: Rep-entered forecast adjustments, like penetration rates, volume overrides, and pricing, now survive every automated process. Sales teams trust the numbers again.
• Approximately 75% reduction in forecasting time: Which allowed the demand planning team to spend less time on manual data reconciliation and more time on strategic, data-driven planning.
• 10-year forecast horizon in one system: The supplier manages its full forecast — across hundreds of vehicle platforms, thousands of SKUs, and multiple OEM relationships — in Salesforce instead of spreadsheets.
• Purpose-built for tier-one automotive: The solution handles IHS data ingestion, penetration rates, parts-per-vehicle logic, and manual volume overrides — the specific variables that make tier-one demand forecasting different from standard manufacturing forecasting.

ForeFront built something that didn’t exist off the shelf: A purpose-built demand forecasting solution in Manufacturing Cloud that’s optimized for how tier-one auto suppliers actually work. Our team delivered a system the customer’s sales team trusts and that leadership relies on for OEM reporting.