Whether an organization sells digital or physical goods or services, it must contend with both predictable and unpredictable elements, including the cost and availability of labor, energy, transportation, and production, as well as unexpected elements, including weather events, civil unrest, and other disruptions. Given the complexities of today’s supply chains, it is imperative to implement demand planning systems that enable organizations to nimbly respond to internal and external factors that can introduce variance between forecasts and actual events.

Failing to address demand planning can result in lost revenue, either due to inventory or supply issues resulting in not getting enough product to market, or wasting money producing, storing, and transporting surplus inventory. However, when done properly, demand planning can result in better end-to-end supply chain visibility. Within an organization, this planning will enable greater inventory control, shorter cycle times, and improved worker productivity, utilization, and efficiency.

While traditional methods of demand forecasting and planning have used rule-based forecasting, statistical methods, and time-series analyses, the increase in the type and volume of data that must be considered requires a multilayered approach to demand planning, incorporating a variety of statistical models, predictive and analytics-based machine learning, and generative AI-based tools. When applied to demand planning, these types of advanced tools can help organizations achieve better supply chain performance, with more granular visibility and control over elements within their supply chains.

In our latest Research Brief, Enhancing Demand Planning with Microsoft Dynamics 365, completed in partnership with Microsoft, we cover the challenges with managing myriad internal and external data signals that impact demand planning, the growing use of AI for forecasting, and the need to integrate and consolidate data and planning into a single system to improve agility, responsiveness, and accuracy.

In this brief you will learn:

• How demand planning data and forecasting has evolved over time
• The benefits of unifying myriad internal and external data sources to provide a more holistic planning and management process
• Insights into how Microsoft Dynamics 365 can be leveraged to link multiple data sources, improve responsiveness and agility, and improve planning workflows
• Discussion on how Copilot and generative AI tools can be used safely and responsibly to drive more efficient and effective planning and forecasting activities.
• Insight into how a Microsoft customer (Domino’s Pizza UK & Ireland) successfully leveraged Microsoft Dynamics 365 to speed up its planning processes and react more quickly to changing conditions, by letting the company rely solely on data to drive decision making. 

If you are interested in learning more, be sure to download your copy of Enhancing Demand Planning with Microsoft Dynamics 365, today.