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.
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Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.