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Two new articles in Journal of Business Forecasting

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Two new articles in Journal of Business Forecasting

[ Edited ]

The Winter 2017-2018 Journal of Business Forecasting is a special issue on the future of demand planning & forecasting. It includes two articles by SAS authors:

 

Charlie Chase, "Real-Time Demand Execution Anticipating Demand at the Edge"

 

Executive Summary: Using real-time information as it is streaming in from connected devices on the Internet of Things (IoT), edge analytics is gaining attention as the IoT has become more widespread, streaming data from manufacturing machines, online purchases, and mobile and other remote devices. Using analytic algorithms as data are generated, at the edge of the corporate network, companies can set constraints to determine what information is worth sending to the Cloud, to a demand signal repository, or other data repositories for later use. The key benefit of edge analytics is the ability to analyze data as they are generated, which decreases latency in the decision-making process as the data are collected. Rather than designing consolidated data systems where all the data are sent back to an enterprise data warehouse (or data lake) in a raw state, where they have to be cleaned and analyzed before being of any value, why not do everything at the edge of the system, including demand forecasting, using advanced algorithms or machine learning? Are you stuck in a vicious cycle of planning demand using two-to-four-week-old data, or are you conducting real-time demand execution anticipating demand at the edge?

 

Mike Gilliland, "The Move to Defensive Business Forecasting"

 

 

Executive Summary: Despite continuing technological advances that take us to the limits of achievable accuracy, most companies still struggle with forecasting, with many forecasts less accurate than a naive model. More complex statistical modeling, by itself, does not provide the answer. Instead, significant performance improvement can come from a "defensive" approach to business forecasting, using tools like FVA analysis. With a defensive approach, organizations can identify the waste and bad practices that degrade forecasting performance, and can thereby achieve the full potential of the technological advances.

 

The full articles are available to JBF subscribers and Institute of Business Forecasting members.

 

 

 

 

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