News in the Channel - issue #37

DATA MANAGEMENT FOR WAREHOUSING

and credibility comes from understanding how finance, operations and warehouse processes fit together and what pressures the business is under,” he says. “That’s where our channel partners shine. “Customers want partners who can show how solutions support long‑term digital transformation, not just today’s

that can deliver this will enable businesses to respond faster to ongoing logistics challenges and operate with greater confidence in volatile supply chains. In the long-term, the ability to turn reliable data into timely decisions will define who stays competitive.” Mohammad says customers will increasingly expect their platforms to go beyond simply recording what happened and begin advising what to do next – and, in some cases, doing it automatically. “As a result, companies will increasingly demand more advanced capabilities from their technology platforms,” he adds. “Data fabric and data lake architectures will become essential, enabling unified enterprise datasets that replace fragmented, siloed data warehouses. These approaches provide the real-time, cross-domain context across inventory, labour, transport, demand and IoT that advanced AI depends on. “At the same time, there will be a growing shift toward advanced analytics and AI, moving beyond descriptive dashboards to predictive and prescriptive insights that support demand forecasting, slotting optimisation, labour planning, transportation routing and exception management. “To ensure these systems can operate at scale, organisations will also require automated governance workflows, with built-in enforcement of data quality, lineage, security and policy controls rather than relying on constant manual intervention.” Richard adds that as AI adoption continues, businesses will expect systems to take on more automated decision- making, respond in real time to disruption and keep performance on track as conditions change. “Expectations around intelligence, automation and adaptability will continue to rise. Warehousing and logistics organisations that invest early in modern, AI-enabled data platforms will be better placed to manage uncertainty, maintain service standards and support long-term growth,” he adds. n

challenges. Strong pre-sales and technical capability are essential in

explaining how solutions integrate with existing systems, scale with growth and support the move to cloud and SaaS.” Richard adds that attention also needs to be given to integration and long-term support. “Data platforms only deliver results when teams understand how to use them and trust the outputs,” he says. “Resellers who position themselves as long-term partners, providing guidance, training and ongoing optimisation, can help customers realise far more value over time.” Future This market will continue to grow and develop. “Warehousing and logistics companies will increasingly expect more intelligence, automation and visibility from their data management and success will come from solutions that are modular, interoperable and built on reliable data capture foundations,” says Benoit. “We believe the market is moving towards greater use of RFID and real-time tracking; deeper integration between physical operations and digital systems; and data platforms that support analytics, AI and compliance.” Resilience will be important going forward, Martin adds. “Logistics and warehousing companies face all kinds of disruption and moving beyond basic visibility towards systems that provide near real-time insight, predictive capability and the ability to act quickly when conditions change,” he says. “AI-ready platforms, strong data governance and seamless integration will become standard requirements. Resellers

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Warehousing and logistics companies will

increasingly expect more intelligence, automation and visibility from their data management and success will come from solutions that are modular, interoperable and built on reliable

data capture foundations.

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