Consumer Goods Demand Planning Sourcing Transportation 
Logility
AUGUST 31, 2023
The consumer goods industry may have experienced tremendous growth, but figuring out what consumers want is an ever-evolving puzzle. From where they shop and how frequently they buy to what price points entice them, consumer behaviors have been challenging to predict over the past year.
Unleashed
FEBRUARY 1, 2023
The onset of COVID and the rapidly changing environment of a pandemic-hit world has meant demand planning has become more difficult – and as a result, more critical – than ever. What is demand planning? Demand planning is the process of predicting what customer demand will be for a certain product.
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Logility
FEBRUARY 10, 2012
Consumer Goods Technology recently released its 2012 Consumer Goods Technology Reader’s Choice survey results. In Supply Chain Planning, Logility was voted highest in customer experience of all solution providers.
Logistics Viewpoints
JUNE 26, 2023
Mars is one of the largest fast moving consumer goods companies in the world. Beery concluded that the best transformation projects would be, one, improved supply chain planning. A 4PL is a company that plans and executes transportation on behalf of their customers. Mars took that recommendation.
Supply Chain Shaman
JANUARY 2, 2023
(The planning team was defending the status quo without questioning current practices and how to improve them.) The question was, “How can I redefine demand planning processes to use channel data?” Starting to understand the issue with multi-tier demand planning? Granularity also differs.
Elementum
MAY 19, 2022
The 50’s saw the development of “containerization” which enabled intermodal (ship, rail, air, truck) transport. Through the 70’s and 80’s, computers brought the next major advances, with sophistication and speed for tracking, routing, and higher-order functions like analytics and planning. Also in the US: 4.9
Silvon Software
JUNE 4, 2019
Globalization is also complicating OTIF because many manufacturers operate their sourcing, production and distribution systems around the world – making it more difficult for them to accurately predict their service levels. Because it requires pulling data from several sources to try to determine why a delivery missed its window.
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