Logistics Viewpoints
MARCH 27, 2023
Some suppliers of demand management software can also provide excellent forecast benchmarking for selected industries. Demand forecasts are improved with access to downstream data (point of sale, Nielsen retail data, and access to competitor promotion schedules). forecasting product sales at 10,000 stores.
Kinaxis
DECEMBER 1, 2014
Demand management Gartner Supply Chain Managment General News Sales and operations planning (S&OP) Supply chain management Accenture Alibaba Arizona State University Big data Bloomberg Businessweek Business operations Gartner Supply chain White paper'
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Supply Chain Shaman
NOVEMBER 11, 2020
On September 30, the big data company Palantir went public in an initial 22B$ market valuation. I am frequently asked, “Can a big data data science company help to alleviate the current market pain in the supply chain?” Data science is only useful when companies are clear on the question to ask.
Supply Chain Shaman
OCTOBER 11, 2023
Instead, they are attempting to measure demand forecast error and lamenting the lack of perfection on imperfect demand data. Working in the area of demand management, requires the building of an organization that can work well in the world of gray where good is not black and white. Engines, Models and Workflow.
Kinaxis
AUGUST 18, 2014
Philip Evans shares how today’s consumer is sharing a colossal amount of data to come to a buying decision. Some people call this “Big Data”. Others consider how this “data” is used, and use the term “Omni-Channel” or “Internet of Things”. Get a method to capture, and USE all this “Big-Data”.
o9 Solutions
APRIL 2, 2021
o9 Solutions’ AI-powered platform operates as the digital brain of global enterprises and delivers strong demand management, supply management, integrated business planning capabilities optimized for each client’s unique business. Gartner, Inc.
Kinaxis
APRIL 17, 2015
Managing data should be everyone’s responsibility, says Martin, not just that of discrete departments within the organization. Another problem is the fact that so much data is transactional in nature. Right now, however, “I don’t think businesses know where to put those data scientists,” Martin says.
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