As supply chains become more complex, successful inventory management depends on more than better software. It requires better collaboration, better data, and better decision-making. In this customer panel, leaders from Sundqvist and DVA share how they moved beyond spreadsheets, introduced structured Sales & Operations Planning, and used AGR to improve forecasting, purchasing, and visibility across their organisations. Hear the practical lessons they learned about managing long lead times, supporting growth, and building supply chains that can adapt to change.
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How Leading Distributors Build More Resilient Supply Chains
Inventory planning becomes increasingly complex as businesses grow, expand into new markets, and manage longer supplier lead times. In this customer panel, representatives from Sundqvist and DVA share how they transformed their planning processes by moving beyond spreadsheets and using AGR to support better forecasting, purchasing, and collaboration.
The discussion explores the practical realities of inventory optimisation, from engaging sales teams in demand planning to improving supplier relationships and creating more structured purchasing routines. Rather than focusing solely on technology, both companies highlight the importance of combining reliable data with cross-functional collaboration to make better decisions and respond more effectively to change.
Whether you are implementing sales & operations planning for the first time or looking to improve forecasting accuracy, this session offers valuable lessons from businesses that have successfully modernised their supply chain operations.
Kim Petersen co-founded AGR Nordic more than 20 years ago and has helped hundreds of wholesalers, distributors, and retailers improve inventory planning and supply chain performance. He is passionate about making inventory optimisation practical and helping businesses make better decisions through data-driven planning.
Elva Sif Ingólfsdóttir has spent more than a decade helping businesses get the most from inventory optimisation software through training, enablement, and customer education. She is passionate about making complex supply chain concepts practical and empowering users to build confidence in data-driven planning.
Christina Eskilstorp has more than 20 years of experience in logistics and supply chain management. She specialises in demand planning, procurement, and Sales & Operations Planning, helping businesses replace manual processes with collaborative, data-driven approaches that support sustainable growth.
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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