Remove Demand Planning Remove Distribution Remove Sourcing
article thumbnail

Demand Planning: Whipped And Chained by Tradition

Supply Chain Shaman

Over the last two years, I actively engaged technologists and business leaders to redefine demand planning. In the industry, supply-centric techniques reign with lots of bravado and messaging on control towers, Demand-driven Materials Requirements Planning (DDMRP), and generative AI. Go to the source. The reason?

article thumbnail

Demand Sensing: How to Unlock Smarter Supply Chains with AI

Logility

A New Era of Demand Planning White Paper Learn more about these new demand models in this whitepaper. Download Now AI Solutions for Complex Demand Planning For supply chain professionals, managing demand involves analyzing multiple signals from diverse sources.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Supply Chain AI: 25 Current Use Cases (and a Handful of Future Ones)

Logistics Viewpoints

Demand planning engines have natural feedback loops that allow the forecast engine to learn. Since ML began being used in demand forecasting in the early 2000s, ML has helped greatly increase the breadth and depth of forecasting. The forecast can be compared to what actually shipped or sold.

article thumbnail

Quick Start Guide to Using Machine Learning for Demand Planning

ToolsGroup

Anyone who has done demand planning knows it is extremely complex, with forecasting challenges and rapidly shifting consumer demand, often exacerbated by seasonality, new product introductions, promotions, and myriad causal factors (e.g. Data Variety The more different types of data sources you factor in (e.g.

article thumbnail

Probabilistic Demand Forecasting: Revolutionizing Supply Chains

ToolsGroup

At ToolsGroup, we’ve long championed probabilistic demand forecasting (also known as stochastic forecasting) as the cornerstone of effective supply chain management software. In modern distribution networks, meeting service levels requires getting precisely the right inventory to the right locations at the right time.

article thumbnail

Decentralizing Supply Chains: How Regional Models Drive Resilience and Flexibility

Logistics Viewpoints

Companies that previously prioritized cost-cutting and centralized sourcing quickly found themselves exposed to serious production and distribution risks. In response, many organizations have shifted toward decentralized and regionalized supply chain models, distributing production and sourcing across multiple regions.

Modeling 163
article thumbnail

Managing Supply Chain Planning in the World of Scarcity

Supply Chain Shaman

The waste included: Negative Forecast Value Added (FVA) in demand planning. In 85% of organizations that I work with, conventional demand planning processes increase forecast error. This is amplified across the supply chain into an exponential impact on inventory and planned orders for manufacturing. Most likely.