Author

Charlie Chase
RSS
Executive Industry Consultant/Trusted Advisor, SAS Retail/CPG Global Practice

Charles Chase is the author of Next Generation Demand Management: People, Process, Analytics and Technology, author of Demand-Driven Forecasting: A Structured Approach to Forecasting, and co-author of Bricks Matter: The Role of Supply Chains in Building Market-Driven Differentiation, as well as over 50 articles in several business journals on demand forecasting and planning, supply chain management, and market response modeling. He is the executive industry consultant and trusted advisor for the SAS Retail/CPG global practice, and writes a quarterly column entitled, “Innovations in Business Forecasting” in the Journal of Business Forecasting. Author page

Advanced Analytics | Analytics | Artificial Intelligence | Data Management | Data Visualization
Charlie Chase 0
SAS and C.H. Robinson are rewriting the rules of transportation planning and management

What if you had a technology solution that creates a real-time link between the customer demand signal and what's happening on the ground? What if plans that are being steered centrally could  finally be connected to every shipping lane, while simultaneously, creating cost saving carrier adjustments? The first-of-its kind integration

Advanced Analytics | Analytics | Artificial Intelligence | Machine Learning
Charlie Chase 0
Is short-term demand sensing a key component of your digital supply chain transformation?

Depending on who you talk to, you'll get varying definitions and opinions regarding demand sensing. Anything from sensing short-range replenishment based on sales orders, to the manual blending of point-of-sales (POS) data and shipments. But a key component for retailers and CPG companies is accurately forecasting short-term consumer demand to

Advanced Analytics | Analytics | Artificial Intelligence | Machine Learning
Charlie Chase 0
Rapid demand response forecasting helps retailers adapt during COVID-19

Rapid demand response forecasting techniques are forecasting processes that can incorporate key information quickly enough to act upon in real time by agile supply chains.   Retailers and consumer goods suppliers are urgently trying to determine how changes in consumer behavior will affect their regions, channels, categories, brands and products during

Advanced Analytics | Analytics | Artificial Intelligence | Machine Learning
Charlie Chase 0
How do I explain a flat-line forecast to senior management?

How do you explain flat-line forecasts to senior management? Or, do you just make manual overrides to adjust the forecast?    When there is no detectable trend or seasonality associated with your demand history, or something has disrupted the trend and/or seasonality, simple time series methods (i.e. naïve and simple

Analytics | Artificial Intelligence | Machine Learning
Charlie Chase 0
Is machine learning practical for statistical forecasting?

There's been a lot of hype regarding using machine learning (ML) for demand forecasting, and rightfully so, given the advancements in data collection, storage, and processing along with improvements in technology. There's no reason why machine learning can't be utilized as another forecasting method among the collection of forecasting methods

Analytics | Artificial Intelligence | Internet of Things | Machine Learning
Charlie Chase 0
Practical approaches to new product forecasting using structured and unstructured data

When it comes to forecasting new product launches, executives say that it's a frustrating, almost futile, effort. The reason? Minimal data, limited analytic capabilities and a general uncertainty surrounding a new product launch. Not to mention the ever-changing marketplace. Nevertheless, companies cannot disregard the need for a new product forecast

Analytics | Artificial Intelligence | Machine Learning
Charlie Chase 0
Will artificial intelligence replace humans?

We have entered the “second machine age.” The first machine age began with the industrial revolution, which was driven primarily by technology innovation. The ability to generate massive amounts of mechanical power made humans more productive. Where the steam engine started the industrial revolution, the second machine age has taken

1 2 3