Tag: Demand Planning

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 | Customer Intelligence | Machine Learning
Antonio Calvo 0
Has social distancing affected retail personalisation?

Few of us expected to experience problems with retailers during the lockdown. Most people have, after all, been happily buying online for years. Why would anything change just because some physical shops closed for a while, or some people could not go out? However, the challenges went a bit deeper

Advanced Analytics | Analytics | Data Management | Machine Learning
Charlie Chase 0
At the end of the day, it’s all about analytics-driven forecasting

Analytics-driven forecasting means more than measuring trend and seasonality. It includes all categories of methods (e.g. exponential smoothing, dynamic regression, ARIMA, ARIMA(X), unobserved component models, and more), including artificial intelligence, but not necessarily deep learning algorithms. That said, deep learning algorithms like neural networks can also be used for demand forecasting,

Advanced Analytics | Data Management | Internet of Things
Charlie Chase 0
Omnichannel is changing the way we view demand planning

Omnichannel Analytics are helping companies uncover patterns in big data to improve the customer experience.  Using those insights, companies can anticipate what consumers are planning to purchase and influence that purchase in real time.     Companies are experiencing unprecedented complexity as they look for growth and market opportunities. Their product portfolios are

Internet of Things
Charlie Chase 0
The Digital Revolution: Crossing the digital divide is changing the Supply Chain Landscape

The digital revolution has affected all aspects of business, including supply chains.  The Internet of Things (IoT), with its network of devices embedded with sensors is now connecting the consumer to the factory. Technologies such as RFID, GPS, event stream processing (ESP) and analytics are combining to help companies to transform their existing

Bob Davis 0
What does a successful supply chain look like?

I had the opportunity to interview an award-winning, fast-moving, consumer packaged goods (CPG) company in the early 2000’s. They were recognized as one of the best supply chain companies in the United States by all of the major retailers and their CPG peers. Indeed, it seemed every time a new

Charlie Chase 0
You can no longer hide behind MAPE!

There are four key areas that require continuous investment in order to become demand-driven: people, process, analytics, and technology. However the intent of your demand forecasting process along with business interdependencies need to be horizontally aligned in order to  gain sustainable adoption.  Adoption alone doesn't necessarily mean it will be sustainable.       As

Jack Hymanson 0
Getting demand in shape

For supply chain managers and analysts Getting Demand in Shape can mean collecting the most pertinent data to support specific business processes and activities. Identifying new or previously unused data sources can be especially important. My most recent article titled “Getting Demand in Shape” in the May / June issue of APICS magazine