Pressure is ever-increasing on warehousing and logistics businesses to deliver orders faster and more cost-effectively than ever. To help achieve this, many are looking to harness the power of their data – and this provides opportunities for resellers.
Warehousing and logistics businesses are increasingly under pressure to deliver more – in terms of volume of products, as well as speed of delivery – than ever before. To help achieve this, many operators are turning to data to bring efficiencies.
“Customers want faster delivery, tighter accuracy, lower environmental impact and rock solid reliability,” says Paul Flannery, VP of international channel sales at Epicor. “That puts warehouses and logistics under the spotlight, and it puts real value on the expertise of channel partners, who help customers navigate that pressure every day.
“As warehousing models change moving from big central sheds to smaller, decentralised sites closer to customers the role of channel partners becomes even more important. These models bring benefits, but they also add complexity. It is data, delivered through strong ERP and WMS ecosystems, that makes them viable. Without real time visibility across every location, service levels slip, costs rise, and you’re chasing demand instead of getting ahead of it.”
Benoit Charnallet, product manager for the EMEA region at TSC Auto ID, adds that ongoing labour shortages, cost pressures, service-level expectations and increasing regulatory requirements are also driving take-up of data management solutions. “Most organisations now recognise that data from labelling, identification and tracking systems is no longer collected just for compliance or execution, but leveraged as a strategic asset to enhance visibility, accuracy and decision-making across the supply chain,” he says.
But Mohammad Mesgarpour from Microlise notes that many warehousing and logistics businesses have not fully embraced data yet. “Most organisations are still in the early stages of data maturity,” he says. “Many logistics teams don’t fully trust their own data. In a supply chain industry study, about 50% of teams reported that data was inaccurate, incomplete, late or irrelevant for performance decisions. A significant portion of operational data is still managed in Excel, paper notes and isolated systems rather than integrated platforms.
“This undermines the ability to use data effectively. While executives consistently highlight the importance of data, the reality on the ground is that poor data quality, fragmentation and low digital adoption continue to limit the use of high-value analytics.
“There is enormous potential in combining and leveraging trusted data to create real value for organisations, but that value can only be realised when users have confidence in the data and in the decisions derived from it.”
Martin Tombs, field CTO EMEA at Qlik, adds that there can still be a gap between understanding how valuable data can be, and using it effectively. “Many businesses sit on large volumes of data, but it’s siloed across different systems, held in different formats, or sometimes just isn’t complete enough to make reliable decisions from,” he says.
“With logistics operations increasingly exposed to challenges like extreme weather and other disruptions, getting a handle on data is more critical now than ever.”
What companies want
The increasing embrace of data means that what customers want from data management solutions is changing. Martin says businesses want to see the clear end-to-end view of what is happening across their operations. “That means accurate, up-to-date information across all systems and tools that work together, and the ability to act on insights quickly,” he adds. “For example, real-time warehouse stock data can help logistics companies quickly identify shortages or overstock in different locations, so they can reroute shipments and ensure customers receive deliveries on time.
“As logistics operations become more complex and time-sensitive, predictive analytics and trusted data foundations are becoming essential rather than optional.
“That’s where partners have a significant opportunity. By helping companies clean up their data, making it consistent, and putting the right governance in place, resellers can build a trusted operational data foundation like linking warehouse inventories, shipment tracking and order systems so teams can plan accurately and respond quickly. Once data is trusted, businesses can start anticipating issues and resolving them earlier, instead of constantly firefighting.”
Manik Sharma, head of supply chain GTM AI at Celonis, agrees that warehouses need platforms that provide operational context and end-to-end visibility. “The trend is moving toward context-aware Enterprise AI, where systems don’t just optimise isolated tasks, but understand the full flow of operations, predict bottlenecks and recommend recovery actions in real time,” he adds.
“Companies are also looking for open systems that enable seamless collaboration across partners. We believe an open ecosystem enables organisations to ‘Free the Process’ from rigid systems and vendor-locked silos, seeking solutions that integrate with existing ERP and SCM systems while supporting composable AI solutions. This combination of context, openness and intelligence allows businesses to build trust in AI-driven decisions and adapt quickly to evolving demands – a shift that will increasingly define competitive advantage in 2026 and beyond.”
Paul says warehousing and logistics businesses are also looking for clarity and control. “Real time visibility is non negotiable, especially with stock spread across multiple sites. You need to know what you’ve got, where it is and how fast it can move,” he says.
“We’re seeing a shift away from siloed tools towards cloud platforms that integrate ERP, WMS and IoT for centralised insight and decision making. Flexibility matters too; solutions need to scale as operating models evolve. Again, the ERP foundation is key: one version of the truth that customers, partners and users can all trust.”
Mohammad says more companies are expecting data to be provided directly from their WMS and TMS operational platforms so they can interweave it with their own data resources and gain a holistic view of their business. “As customers gain greater analytical capability, they are demanding access to raw data rather than relying solely on prescribed outputs,” he adds.
AI impact
Of course, AI is impacting on data management too. “AI is adding value once reliable data is available but it’s only as good as the data it receives, which is why accurate data capture at source (labels, RFID, mobile data collection) remains critical,” notes Benoit. “In warehousing and logistics, AI is increasingly used to identify patterns and anomalies in inventory movement, support predictive maintenance and forecasting and improve demand planning and resource allocation.”
Manik says that with rapid digitisation, the warehousing and logistics sector has become incredibly data rich. “This is characterised by a high volume of different systems, formats and frequencies,” he says. “While AI and modern technology excel at consuming this multi-modal data at speed and scale, the real value lies in its application.
“There is no AI without PI (Process Intelligence). AI promises to reinvent operations, but without the essential context provided by PI, companies cannot unlock its full potential. PI provides the ‘common language’ and context needed to translate this massive amount of data into a true digital twin of operations.
“When implemented this way, AI becomes more than a tool, it becomes a trusted partner. It doesn’t just identify issues; it uses that dynamic digital twin to help teams understand why they occur and how to prevent them. This turns fragmented data management into true Enterprise AI, allowing organisations to enhance the entire supply network rather than just internal silos.”
Richard Skelson, managing director at Field Ascend, says that AI is changing data management from something that looks backwards to something that supports day-to-day decisions. “By analysing large volumes of live and historical data, AI can forecast demand, improve routing, automate replenishment and highlight maintenance issues before they cause disruption, helping teams move away from constant firefighting,” he says.
Work closely
With warehousing and logistics businesses often still getting to grips with data, resellers have a crucial role to play. “Resellers need to work closely with their customers first to fully understand their processes before mapping technology to meet their operational needs,” says Benoit.
Benoit adds that the focus should be on end-to-end data flow, not just individual devices, the importance of data quality at the point of capture, a future-ready approach that supports barcode and RFID and solutions that reduce manual intervention and human error.
Martin says resellers should focus on the business impact of good data management, not just the technology. “Data quality, visibility and governance directly affect how efficiently a business operates and how well it can respond to change,” he says.
“Ongoing support is just as important. Automated checks, monitoring pipelines, and maintaining compliance may not be flashy, but they make sure the data stays reliable as operations grow. Making that link between strong data practices and real-world outcomes helps position resellers as long-term partners rather than one-off suppliers.”
Paul agrees that resellers should start with the business, not the tech. “Warehousing and logistics are complex, 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 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 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.
