Invitrogen Case Study: Demand Forecasting for Biotech Lab Materials

Case studies

SCP

Invitrogen Case Study: Demand Forecasting for Biotech Lab Materials

How Invitrogen manages 10,000+ SKUs and kit/component forecasting using Demand Solutions Forecast Management integrated with JD Edwards ERP.

Published

June 4, 2026

Read time

3 min read

Source

This case study details Invitrogen's implementation of Demand Solutions to forecast demand across 40,000 products supplied to pharma, biotech, and research institutions. It covers the shift from sales data to customer order data for improved accuracy, dual-level forecasting for kits and components, and exception-based management of sporadic demand. The study also addresses SKU growth from acquisitions and the need for better sales pipeline visibility.

Key takeaways

Switching from sales history to customer order data improved forecast accuracy by capturing unfilled demand.

Dual-level forecasting at both kit and component levels enables accurate replenishment despite complex product structures.

Exception-based review processes and filtering tools are essential when managing over 10,000 SKUs with limited history.

Integration between Demand Solutions and JD Edwards ERP supports automated replenishment at component level.

Sales pipeline data from CRM improves forecast quality for products with sporadic or long-lead-time demand.

Market overview

SCR methodology note

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