DATA MANAGEMENT IN WAREHOUSING AND LOGISTICS BUSINESSES
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“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
Mike Barron managing director
synaxon-services.com
There are big opportunities in processing, storing, analysing and managing that data. “ ”
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