Warehousing and logistics businesses are producing more data than ever before, but that means nothing unless it is harnessed properly. This is where data management comes in – and it is something that resellers can help customers with.
Warehousing and logistics are sectors under pressure. While they are fundamental to the smooth operation of the economy, customers at all parts of the chain are putting pressure on companies in the sectors to provide faster and better tracked services.
This means warehousing and logistics companies are seeking to become ever more efficient and this is where data comes in. Businesses in these sectors now produce a huge amount of data, and there is increasing recognition among leaders that if it is harnessed properly it can help to improve their business and, ultimately, the bottom line.
Becky Stables, GDPR expert at business intelligence consultancy Catalyst BI, says that logistics businesses are becoming more aware of the vast amount of data they generate and how this can be managed for operational improvements. “Logistics companies can utilise data analytics to spot potential risks and disruptions in their supply chains, like supplier issues,” she says.
“By examining past data alongside external influences, businesses can develop robust contingency plans to manage these challenges. This approach is essential for maintaining operational continuity and minimising financial impact during unexpected events.”
Chris Cunnane, supply chain product marketing manager at InterSystems, agrees that businesses across the board are more aware of the power of data. “But more data does not equal better data; the key is unified, actionable, quality data,” he notes. “Within the warehouse, there is an enormous amount of data on hand, including inventory levels, labour management, workforce utilisation, dock scheduling, receiving documentation, among other sources. This data lacks value without the ability to ingest and act upon it.
“The same is true for logistics businesses. Data management and sharing is a critical component of the network effect. The network effect exists when all components of the supply chain technology ecosystem work together and share data to improve the performance of the end-to-end supply chain.
“For example, from a transportation standpoint, the network effect relies on communication and data sharing between applications to make freight moves more efficient. This includes matching loads with capacity, using visibility tools to predict more accurate ETAs, optimising routes, and ensuring that trucks can be loaded and unloaded as efficiently as possible.”
Mike Barron, UK managing director at SYNAXON, adds that most warehousing and logistics companies are probably well aware that they have access to potentially valuable data. “Exactly how they can make use of that data is another matter,” he says. “It’s important to conform to regulatory requirements and to ensure personal and confidential information is protected, of course.”
Customer wants
This means that data management solutions are increasingly important to warehousing and logistics businesses. Customers in these sectors are specific in what they want from their data management solutions. “Customers are looking for data management solutions that boost efficiency, reduce costs and improve overall supply chain agility,” says Becky.
She adds that customers tend to have several key priorities. These include smarter inventory management. “Businesses need tools that analyse past sales trends and real-time demand to prevent stock shortages and excess inventory, cutting storage costs and improving cash flow,” she says.
Optimised warehousing is another priority. “Data-driven insights help companies design efficient warehouse layouts, reducing travel time, maximising storage and streamlining workflows for faster order processing and lower labour costs,” Becky notes. “Additionally, intelligent algorithms can boost picking accuracy by analysing order trends and item popularity, minimising worker movement and increasing efficiency.”
Becky adds that real-time analytics allow logistics teams to refine delivery routes, cut transport costs and improve delivery speed and reliability, especially within complex distribution networks.
Improved data security and compliance is another consideration. “With data privacy regulations tightening, businesses need secure data management systems that comply with legal requirements such as GDPR and protect against security breaches,” she says.
Finally, integration with IoT is often required. “IoT-powered maintenance tracking helps companies prevent equipment failures, cutting downtime and repair expenses while keeping warehouse operations running smoothly,” says Becky. “Companies also expect solutions that integrate effortlessly with existing ERP, WMS and TMS systems while offering the flexibility to scale as the business grows.”
Mohib Rahmani, managing principal and head of the data and AI team (IRIS) at Argon & Co, adds that warehousing and logistics teams increasingly see data as a strategic asset, rather than just an operational byproduct.
Within this, he sees several trends emerging. “First, there is a clear shift toward cloud storage and hybrid integration with on-site data,” he says. “Organisations are moving to platforms that can handle large volumes of data while delivering real-time insights.
“The sector has also seen a proliferation of self-service dashboards that empower non-technical users to gain insights without steep learning curves. This is a positive development that could help redress the growing skills gap affecting multiple industries.”
Power of AI
Another major trend is the increased use and adoption of artificial intelligence (AI) across the supply chain.
“There is a growing reliance on AI and machine learning to automatically clean, standardise and even predict trends in procurement data,” says Mohib. “By using demand forecasting with external data, such as weather forecasts, school holidays, social trends, and macroeconomic indicators, warehousing and logistics companies can radically improve their short- and long-term demand planning for customers.”
Chris adds that within warehousing, AI is helping to automate otherwise manual tasks. “This includes data analysis for decision making, demand forecasting and predictive maintenance on machinery,” he says. “The use of AI-enabled robotics is also becoming more commonplace. These autonomous mobile robots can navigate warehouses, pick and pack items, and collaborate with their human counterparts to prepare orders faster.
“For logistics customers, AI is a critical component of transportation strategies. AI can be used to learn about constraints, such as carrier regulations, available capacity and hours of service, and properly plan shipments. This gives more accurate ETAs of shipments to warehouses, stores, or consumers. Additionally, AI helps other aspects of transportation strategies, such as carrier selection based on service levels and route optimisation.”
Keep it simple
Data will continue to become increasingly important to businesses, but with it will also come increasing complexity, which means it will be crucial to keep data management solutions straightforward for customers.
“As technology advances and businesses continue to scale, data will provide a competitive edge, improving decision-making, streamlining operations and enhancing customer experience,” says Becky.
“However, as data grows in volume and complexity, it’s crucial to keep solutions straightforward. Simplicity ensures that businesses, especially those with less technical expertise, can easily adopt and make use of these solutions without feeling overwhelmed. The easier the solution is to use, the quicker businesses can realise the benefits of their data, which will make it more appealing to a broader customer base.”
Chris agrees, noting that unified, trusted, actionable data will become increasingly important, but noting that too much data can be overwhelming, especially when the quality of the data is poor. “For warehousing and logistics businesses, the ability to act upon the data is most important,” he says.
“This requires companies to integrate, harmonise and normalise disparate data and deliver it to the right consuming users and applications at the right time and in the proper format. This speeds up the ability to sense disruptions in real-time and optimally handle them when they do, enabling companies to be ready to manage the unexpected with confidence.”
Mobib agrees that as data becomes more central to operations and increases in complexity, then the need for simplicity also grows. “Generally speaking, the best solutions are those that deliver powerful insights while remaining user-friendly,” he says. “Keeping interfaces intuitive is crucial, as it drives adoption and ensures that even non-technical users can leverage data effectively.
“Straightforward solutions allow organisations to respond quickly to changes and make agile, informed decisions. While data will remain a key driver of business outcomes, the ability to harness that data without overwhelming the user will be a major competitive advantage.”
Reseller conversations
When talking to customers in the warehousing and logistics sector about data management solutions, there are certain things that resellers should highlight.
Mobib says that resellers need to highlight how their solution transforms fragmented, messy procurement data into a unified, actionable dashboard. “They should also emphasise ease-of-use which is a critical component for driving fast adoption of AI tools,” he adds.
“Resellers should emphasise the importance of strong data governance and audit trails to further reinforce the value of their platform to these customers specifically.
“Like any successful solution, the results need to speak for themselves. Resellers should present case studies or success metrics to demonstrate how data integrity has led to cost reductions, more accurate forecasting and improved decision-making among existing customers.”
Mike adds that resellers should be talking to their customers about data more. “There are big opportunities in processing, storing, analysing and managing that data,” he says. “With the advancements we are now seeing in AI, that potential is becoming ever greater. I think we will see some very rapid developments over the next couple of years with respect to AI and data management and processing – not only in warehousing and logistics, but in healthcare and other industries.”
