Manufacturers continue to struggle with sales and inventory forecasting because critical data remains fragmented across ERP, CRM, and operational systems. As a result, forecasts rely on incomplete or inconsistent inputs. This gap quickly creates downstream issues, including excess inventory, stockouts, cash-flow pressure, and missed revenue. This webinar addresses those challenges head-on by showcasing a real-world customer use case and demonstrating how the right combination of process discipline and system alignment can materially improve forecasting outcomes.

In this session, we walk through how an Algorithm customer used Acumatica together with DataSelf to build a unified, analytics-driven inventory forecasting model. By consolidating ERP, CRM, and operational data into a single source of truth, the organization eliminated spreadsheet-based estimates. At the same time, it shifted from reactive planning to reliable, system-driven sales and inventory forecasts that scale with the business.

Finally, the webinar highlights how BI-powered forecasting changes the leadership conversation. Instead of analyzing variances after the fact, executives gain forward-looking visibility. This insight supports proactive inventory planning, lower carrying costs, and improved service levels. Attendees will see why accurate forecasting is not just a reporting exercise, but a strategic capability enabled by disciplined processes, clean data, and tightly integrated ERP and BI platforms.

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