AI Sales Forecast Data Reconciliation Agent for Specialty Equipment Manufacturers

How Cassidy automates forecast reconciliation using AI

Step 1: Ingest and harmonize multi-source data

The Workflow triggers on a scheduled cadence or on-demand, pulling CRM pipeline data, CPQ configurations, dealer POS and order bank information, and ERP bookings/backlog. Cassidy maps product families and configurations to ERP items, standardizes fiscal calendars, and builds a unified product-configuration graph.

Step 2: Generate baseline forecast and process demand signals

Cassidy applies statistical models suited for low-volume, intermittent demand patterns common in specialty equipment. The agent converts CRM opportunities to demand using calibrated stage probabilities, explodes CPQ configurations to option-level forecasts, and incorporates dealer sell-out data to sense near-term demand shifts.

Step 3: Reconcile across hierarchies and channels

The Workflow aligns retail (sell-out) with wholesale (sell-in), eliminates double-counting between dealer orders and CRM opportunities, and reconciles top-down targets with bottom-up detail. Cassidy ensures forecast consistency across product, geography, account, and time hierarchies.

Step 4: Facilitate consensus review with governed overrides

Cassidy surfaces baseline, pipeline-derived, and dealer-based forecast views alongside accuracy metrics (MAPE, bias, FVA). Stakeholders submit overrides with reason codes through Human-in-the-Loop approval, with guardrails enforcing thresholds and preserving a full audit trail.

Step 5: Run supply scenarios and financial reconciliation

The agent evaluates constrained vs. unconstrained plans, flags capacity gaps and revenue-at-risk, and translates the operational plan to financial impacts. Cassidy enables rapid what-if scenarios on mix, lead times, and allocation policies.

Step 6: Publish plan of record and monitor execution

Cassidy publishes the approved one-number plan to ERP, MRP, and dealer portals. Ongoing monitoring tracks bookings vs. forecast, backlog health, and exceptions—triggering alerts when thresholds are crossed and maintaining plan-over-plan waterfall visibility.