Most businesses have digitally transformed their workflows and are exploring innovative ways to ensure they have robust digital end-to-end supply chains to improve their efficiency. Irrespective of the strategies embraced, modern supply chain management heavily depends on effective demand planning strategies. One of the top priorities of every organization should be developing a supply chain with utmost efficiency to minimize errors. Business leaders that want to manage demand and supply efficiently need to have the best strategies and tools for demand planning and forecasting. Leveraging the best demand planning and forecasting tools in the IT infrastructure will help businesses to minimize the risks and enhance the product, services, and information flow and deliver a top-notch customer experience.

Retail supply chains are under immense pressure to keep up with these rapid changes. Innovators have been quick to take advantage of the new virtual distributed environment. Also, e-commerce is growing at an unprecedented rate and customers expect faster delivery times and more personalized service. And retailers are facing pressure to keep costs down and increase profitability. Despite these challenges, organizations can take action and make a difference.

SAP Integrated Business Planning IBP S4/HANA Functional Lead REMOTE Duration : 6+ months MUST work CST time zone • 2+ years of SAP S4 experience • 10+ years of experience configuring deploying and managing SAP ERP with a focus on Demand Planning • IT Expertise in demand planning and demand…

Demand forecasting refers to the process of planning and predicting goods and materials demand to help businesses stay as profitable as possible. Without strong demand forecasting, companies risk carrying wasteful and costly surplus – or losing opportunities because they have failed to anticipate customer needs, preferences, and purchasing intent. Demand forecasting professionals have specialized skills and experience. When those skills are augmented with modern supply chain technologies and predictive analytics, supply chains can become more competitive and streamlined than ever. In the wake of the pandemic, companies are in an exceptionally fast-moving business climate.

The future of planning is connected, intelligent, and continuous. Yet many companies remain so far away from this vision; it often seems unachievable. With many planning processes being so siloed and disconnected from execution, they can feel ineffective. Fortunately, evaluations of the planning landscape reveal many organizations are adopting technologies that move towards a de-siloed, network-based approach to planning. To optimize planning capabilities, it crucial to achieve this connection at the enterprise level as well as into the broader supply network.

Last week we announced a new strategic partnership with Microsoft to further shape the future of AI and analytics in the cloud. This commitment will make it easy for SAS customers to move their analytics workloads to the cloud. And it will introduce SAS technologies to millions of Azure customers through APIs and deeper integrations that can enhance existing applications with analytics. To help illustrate how you can use SAS on Azure, I am sharing three inspiring examples from a recent SAS hackathon. Participants in this event were challenged to solve problems related to the United Nations Global Goals for Sustainable Development using SAS Viya .

From shortages of personal protective equipment to a variety of grocery items to electronics and apparel, coronavirus (COVID-19) has hit the global supply chain in expected and unforeseen ways, and it seems likely that it could take many months to recover. Bouncing back more quickly, said experts, will require supply chain managers to turn to new ways of managing the supply chain, including using Internet of Things (IoT) data, analytics and machine learning (ML). These tools will become the foundation on which supply chain managers gain insight into their markets and erratic supply and demand trends. "Having the right machine learning and AI technologies will help you understand the market and better manage your supply chain," said George Bailey, director of the Digital Supply Chain Institute. While the disruption is now global, its starting point was in China -- the 800-pound gorilla in global production.

Artificial intelligence (AI) continues to draw a lot of attention as companies and technology vendors look at how machine learning could improve supply chain operations. In particular demand planning, understood here as the process of developing forecasts that will drive operational supply chain decisions, is being touted as the next potential field for innovation. Technology giants like Amazon and Microsoft have announced AI tools for improving demand planning, and several consulting companies are promoting their skills to bring AI to companies' demand planning processes. In fact, a recent survey by the Institute of Business Forecasting and Planning (IBF) identified AI as the technology that will have the largest impact on demand planning in the next seven years.1 It's not hard to see the fit between AI and demand planning. Demand planning involves lots of number crunching and data analytics, and it is repeated cycle after cycle.

When I was a kid, I used to watch cartoons as I got dressed for school. My favorite was The Jetsons: the flying cars, the robot maid, food served hot at the touch of a button. The only thing I could never figure out was why – despite all the seemingly futuristic advances – George still went to work every day and pushed a bunch of buttons? It stayed with me, even as I got older, and when I'd find an old episode of The Jetsons on cable, it would really vex me. If a robot could do the household chores and give advice to Judy and little Elroy – couldn't a robot make Spacely Sprockets?

Sometimes the speed of Amazon's delivery is bewildering. No matter how obscure your order, the retailer frequently promises same-day delivery. Is it that your neighborhood is full of fly-fishing buffs, or whatever your niche interest may be? Instead, it is likely that the company has already shipped the product to your nearest warehouse because it thought that you might order it. Magical as this might sound, it is the application of a technology known as demand sensing.