Cupertino, CA -- (SBWIRE) -- 01/20/2015 -- Forecast Errors newsletter reported that Chuck Fuerst shared the need for track and trace capabilities in industries such as food and beverage, manufacturing or automotive industries is obvious; the threat of contamination or recalls impacts public safety, and the responses to those events are highly regulated.
Organizations need to know what goes into their products and their location at all times. But increasingly, companies in other industries are taking a fresh look at the need for advanced tracking and tracing capabilities that are critical throughout the order process and can drive efficiencies the entire way through, from picking to returns.
Forecast Errors, a weekly e-newsletter, shares methods, modes, and tools used in a variety of supply chain industries. The newsletter explores forecast errors as the difference between the actual and predicted value. In the current issue, Forecast Errors argued that what separates best-in-class companies from those that struggle with accuracy is how they root out (and learn from) forecasting errors.
A forecast error is the difference between the actual and predicted value. The consequences are expensive inefficiencies that can be resolved with lean manufacturing technology.
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Ultriva's (http://www.ultriva.com) cloud-based platform leverages seamlessly integrates with leading ERP and MRP systems, to deliver an end to end pull based replenishment solution. Ultriva, based in Cupertino, CA, implements a global demand driven manufacturing model by providing full visibility, scheduling, and sequencing of production of customer orders. Ultriva was named one of the Great Supply Chain Projects of 2014 by Supply & Demand Chain Executive magazine and recently named one of 50 Best Supply Chain Blogs of 2014 by SupplyChainOpz. The company's global footprint is increasing rapidly with implementations in wide variety of industry sectors and enterprises such as Magellan Aerospace, CareFusion, Emerson, Ingersoll Rand, McKesson, Triumph Group, Regal Beloit, Thermo Fisher, and more.
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