Optimising warehouse management: How AI and Microsoft Dynamics 365 are transforming supply chains

Gary Regan, Chief Operating Officer at DAC Systems. (Image: Supplied)

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In today's unpredictable supply chain environment, manufacturers are struggling with issues such as erratic demand, labour shortages and escalating costs. Warehouses, serving as critical points in manufacturing supply chains, often encounter inefficiencies, limited visibility and manual processes. These result in a constant struggle of trying to keep up with the pace of business.

Addressing these issues requires more than just minor adjustments. This is where Microsoft Dynamics 365 Finance and Operations (D365 F&O), along with its Advanced Warehouse Management (AWMS) module, come in to improve the resilience and competitiveness of manufacturers.

D365 F&O's AWMS module is designed to manage the complexities of modern manufacturing warehouses effectively. Key features include:

• Real-time inventory tracking: Allows for immediate monitoring of stock levels, locations and movements. This system helps manage stock efficiently by reducing uncertainties and preventing over-stocking or under-stocking, which can affect manufacturing processes.
• Automated workflows: Optimises processes like picking, packing and shipping through system-directed tasks, minimising manual errors and delays.
• Mobile device integration: Equips workers with intuitive handheld devices for scanning and executing tasks, thereby improving productivity on the shop floor.
• Wave planning: Efficiently co-ordinates outbound processes, ensuring timely fulfilment of sales and production orders.
• Warehouse layout optimisation: Uses data analytics to identify inefficiencies and redesign layouts for maximum throughput.
• PFE (shop floor execution): Enhanced real-time shop floor monitoring provides managers with instant insights into ongoing production activities, helping to swiftly address issues and optimise resource allocation.

These transform warehouses from static storage spaces into more dynamic components within the supply chain. For manufacturers, this translates to faster order processing, reduced carrying costs and improved inventory visibility.

The impact of AWMS is particularly significant in manufacturing, where warehouse performance directly influences production outcomes. Benefits include:

• Optimised picking processes: System-directed picking prioritises tasks based on production needs, reducing pick times and ensuring timely delivery of parts to assembly lines.
• Reduced downtime: Real-time visibility empowers managers to reroute materials instantly during unexpected disruptions to minimise idle time.
• Complete production integration: Aligns warehouse activities with master production schedules. It automatically stages raw materials for high-priority orders and prevents bottlenecks.
• Resource management: It excel in both machine and resource planning, offering automatic selection based on availability and performance requirements. This capability ensures optimal production time, reduces bottlenecks and enhances overall efficiency.

These advantages result in lower operational costs, higher throughput and increased customer satisfaction. In a volatile market, AWMS enables manufacturers to adapt swiftly to changes, whether responding to sudden demand surges or supply interruptions.

Microsoft's AI integrations further enhance AWMS's capabilities, providing immediate value. Notable tools include:

• Copilot for process automation: Embedded in D365 F&O, Copilot automates routine tasks such as workflow approvals and order assessments. Warehouse managers can use natural language queries to obtain instant, actionable insights, saving time on manual analysis.
• Azure AI for predictive analytics: By analysing historical data, Azure AI forecasts inventory needs and identifies potential disruptions. For example, it can alert managers to stock up on critical components ahead of anticipated supplier delays, based on patterns it detected.
• Advanced AI scheduling: The system dynamically adjusts production schedules based on real-time data, ensuring resources are allocated efficiently and production workflows are streamlined. This capability minimises downtime, enhances productivity and adapts swiftly to changes in demand or production capacity.

These tools improve decision-making and performance. Implementing Copilot can reduce task planning time, while Azure AI's insights help anticipate demand shifts and reduce stockouts, which provide companies with a significant advantage in the face of labour shortages and cost pressures.

Microsoft's 2025 release wave one roadmap indicates an AI-driven future for AWMS. Over the next three to five years, some of the anticipated advancements include:

• Generative AI for demand forecasting: Building on Copilot, generative AI will refine demand planning with detailed explainability, helping manufacturers predict regional order surges and position inventory accordingly to reduce lead times.
• IOT-driven anomaly detection: Integrated with Azure AI, IOT sensors will monitor equipment and inventory in real-time, detecting anomalies such as equipment failures before they disrupt operations, potentially increasing uptime.
• Autonomous warehouse agents: Intelligent AI agents are expected to automate complex tasks, like dynamically rerouting shipments during logistics challenges, with minimal human intervention.

These innovations promise warehouses that become more efficient and can act autonomously – anticipating needs, self-optimising and allowing leaders to focus on strategic initiatives.

Adopting AWMS and its AI capabilities is a strategic move with clear steps:

1. Assess current gaps: Evaluate warehouse operations to identify areas where AWMS can add the most value, such as reducing picking times or improving visibility.
2. Define success metrics: Set measurable goals, like reducing order fulfilment time or cutting excess inventory, to assess return on investment.
3. Partner with experts: Collaborate with a Microsoft solutions provider experienced in D365 F&O to tailor AWMS to your workflows and integrate AI tools as effectively as possible.
4. Pilot and scale: Begin with a single warehouse to test the solution, refine processes, and then expand across the network.
5. Train your team: Equip staff with the necessary skills to use mobile devices and interpret AI-driven insights, ensuring successful adoption.
6. Keep optimising: Continuously monitor performance metrics and gather feedback to identify areas for improvement. Embrace an ethos of constant learning and enhancement, leveraging data to fine-tune operations. This approach not only maximises the benefits of the system but also fosters a culture of innovation and adaptability.

Starting with a focused approach and scaling thoughtfully can accelerate deployment, ensuring timely realisation of benefits.

The supply chain landscape of 2025 demands agility, visibility and intelligence. By addressing current challenges with real-time tracking, automated workflows and AI-driven insights, AWMS positions manufacturers to thrive amid volatility.

Looking ahead, Microsoft's AI roadmap suggests a future where warehouses operate efficiently while innovating through advanced forecasting and IOT precision. As a trusted Microsoft partner, DAC Systems is prepared to guide manufacturers through this transformation, turning vision into tangible results.

For more information, go to: https://www.dac.co.za/.