Remove DC Remove Forecasting Remove Metrics
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A New Decade: Give Science A Chance

Supply Chain Shaman

The SAS forecasting system implemented in 2019 was not tested for model accuracy. An example for this client would be to use 2017 and 2018 history to forecast 2019. So, I asked the questions, “Is your data forecastable? Data at this level of variability is complicated to forecast.) The reason? The answer?

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Supply Chain Leaders, Chained to Tradition, Face the Whip

Supply Chain Shaman

One of my stark realizations this year is that smaller companies are beating larger and often more established companies on growth metrics, inventory turns, operating margin, and Return on Invested Capital (ROIC). (In The metrics selection resulted from work with Arizona State University in 2013.) Look for the full report next week.).

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New Year’s Resolution #1 for Supply Chain Planners: Improve Performance Measurement

Demand Solutions

Relatively few companies have adequate measures of order fill rates or forecast accuracy. To fill the 8th line item complete we had to ship the product from a DC across the country. Make it your New Year’s resolution to start using this more granular metric. Don’t Forget to Measure Forecast Accuracy, Too.

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Until AI Can Solve this One Simple Task, I Wouldn’t Worry About It

Logistics Viewpoints

It also suggests that the total value delivered by AI will be more limited than consultants from McKinsey are forecasting. It is better to receive inventory on a loading dock, take the inventory needed for a hot shot shipment, and move that inventory through the DC to a shipping dock where it is loaded on a truck.

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Supply Chain Case Study: the Executive's Guide

Supply Chain Opz

Forecasting and new product introduction has always been the issues for many FMCG companies, P&G is no exception. The result is that the forecast accuracy is improved because a demand planner has an additional source data to make a better decision. . BMW uses a 12-year planning horizon and divides it into an annual period.

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How CPG Brands Can Harness the Power of POS Data

Silvon Software

Using POS Data for Improved Sales & Demand Planning By leveraging POS data, companies can additionally (and accurately) forecast future sales, which is crucial for demand planning. Improved Forecast Accuracy Since POS data reflects real consumer purchases, forecasts based on this data are more accurate.

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Mars Wrigley’s Highly Successful Supply Chain Digital Transformation

Logistics Viewpoints

Demand sensing involves the use of the external data sources – particularly the latest sales and market data – to improve short-term forecasting and then be able to use that improved understanding of consumer behavior to improve their supply planning. The stock rebalancing skill is designed to enable Mars to optimize DC to DC shipments.