Inventory planning is no longer just about placing purchase orders. In this practical session, Duncan Reed shares how Vital Pet Group transformed its inventory management by moving from manual, spreadsheet-driven processes to a more structured, data-led approach with AGR. He explains how better forecasting, cleaner data, and greater automation helped improve availability, reduce inventory, and give the team more time to focus on strategic supply chain decisions.
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Moving Beyond Manual Inventory Planning
As product ranges expand and supply chains become more complex, traditional purchasing methods are no longer enough. In this customer presentation, Duncan Reed, Director of Category at Vital Pet Group, explains how his team modernised inventory planning by introducing AGR and shifting from manual ordering to data-driven decision making.
Using practical examples from their own implementation, Duncan shares how better forecasting, automated purchasing, and improved data quality enabled Vital Pet Group to reduce inventory, increase product availability, and build a more resilient planning process. He also explores how the role of inventory planners is evolving as AI and automation take over routine tasks, allowing people to focus on higher-value decisions.
Duncan Reed leads category management and inventory strategy across a large product portfolio. He focuses on using data, forecasting, and technology to improve supply chain performance, helping the business increase product availability, reduce inventory, and build more resilient planning processes through automation and smarter decision making.
AI-driven inventory management uses machine-learning models to forecast demand at SKU level, detect anomalies in sales history, and propose replenishment orders that planners can approve in one click. In AGR, AI runs continuously on ERP sales and stock data and surfaces only the exceptions that need human attention.
Automation executes rules you already defined — for example, auto-generating a purchase order when stock hits a reorder point. AI improves the rules themselves: it learns seasonality, promotions and supplier lead-time variability from historical data and updates forecasts and safety stock without manual tuning.
Most AGR SaaS customers go live in 4–8 weeks. The standardised data model and prebuilt ERP connectors (Microsoft Dynamics 365 Business Central, NAV, SAP, NetSuite, Sage, IFS, Jeeves) remove the multi-month integration work typical of legacy supply-chain tools.
AGR has prebuilt, supported connectors for Microsoft Dynamics 365 Business Central, Dynamics NAV, SAP, NetSuite, Sage, Visma, IFS and Jeeves. Other ERPs connect via REST API or flat-file integration.
Across AGR’s customer base, companies typically reduce inventory holding by up to 11% and cut stockouts by up to 40% within the first 12 months — based on AGR customer benchmark data, 2025.
Yes. AGR is used by 400+ companies across wholesale distribution, specialty and FMCG retail, and manufacturing with raw-material and finished-goods planning. The same forecasting and ordering engine adapts to each vertical via configuration, not custom code.
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