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Home / Knowledge / News / Information Technology / JDA adds new capabilities in JDA Flowcasting retail suite
JDA adds new capabilities in JDA Flowcasting retail suite
10
Aug '15
JDA Software Group Inc. has added new capabilities in JDA Flowcasting that empower manufacturers and retailers to create their most accurate forecasts, increasing their ability to profitably sell across multiple channels.

JDA Flowcasting enables trading partners to work together from a single forecast and plan to improve profitability, productivity, and control.

Fred Baumann, group vice president at JDA Software said, “Recognising that forecasting and analysis teams don't have a lot of time on their hands, JDA has significantly invested in new capabilities in JDA Flowcasting that directly address these challenges. JDA has enhanced the automation level for the exception-resolution process, improved promotions forecasting workflows to increase accuracy, and enhanced the slow-moving products forecasting logic to support more profitable replenishment policies.”

Three foundational enhancements in JDA Flowcasting were developed to drive enhanced forecasting accuracy and ultimately improve profit margins in today's omni-channel selling environment. The first is adding new guided resolution workflows that support fast action for exceptions. While achieving pinpoint accuracy across thousands of bar codes may be impossible, exclusive new functionality in JDA Flowcasting enables the fastest-ever resolution of exceptions. Built-in analytics automatically identify common root causes behind multiple issue types, and intelligently highlight areas with greatest impact on the key metrics focused on by the planners, according to a press release.

The second is enhancement is improved promotion forecasting and replenishment accuracy. JDA Flowcasting Collaboration Workbench enables forecasting teams to easily import, export, and edit promotion-related data at an item or item-at-a-location level. The third is it allows more precise forecasting for slow-moving products. Users can extract a slow-mover demand profile at a cluster level across similar stores or similar products. Retail planners can make more intelligent purchasing decisions or delay orders when appropriate, leading to a reduction in total inventory and an improvement in profit margins. (GK)

Fibre2Fashion News Desk – India


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