» Demand Planning
Optimize your inventories using scientific methods
Available in the following formats:
Web Workshop, on-site workshop at your location, or as public training course.
Demand Planning and Sales Forecasting Tutorial Workshop Chicago, IL | Oct, 19-20 2016
CADP Certification Workshop Chicago, IL | Oct, 21 2016
Modeling & Metrics in SAP APO DP 1-Day Workshop Chicago, IL | Oct, 21 2016
Sales & Operations Planning Workshop Chicago, IL | Oct, 21 2016
Demand Planning and Sales Forecasting Tutorial Workshop Bangalore, India | Feb 2017
The objective of this workshop is to review the close link between forecast accuracy and inventory optimization and discuss the implications of forecast error for inventory strategies – Lead time uncertainty, safety stock, and planning to forecast. The workshop will also look at the mechanics behind the various demand metrics.
You Will Learn:
Accurate and timely demand plans are a vital component of an effective supply chain. Forecast accuracy at the SKU and DC level is critical for proper allocation of resources, both working capital as well as strategic assets.
Inaccurate demand forecasts often can result in supply imbalances which could ultimately cause inferior customer service and bloated inventories. In this session, we will discuss the process of evaluating demand plans, the pros and cons of different demand accuracy metrics, and the time-lag with which accuracy should be measured. We will also consider metrics that identify and track forecast bias.
With the above background, we will discuss how demand metrics can be leveraged in designing scientific inventory planning parameters. Typically, Organizations set safety stock in a set number of weeks or months to cover unexpected demand. Such methods of safety stock calculation as measure of weeks-forward coverage, also called WFC, can often be unscientific and extremely dependent on the judgment of the planner. Conceived in the slide-rule era, the WFC magnifies the effect of an inaccurate forecast.
Here, we review some scientific methods of setting safety stock strategies that are dependent on the history of demand error by sku. We also show how forecast bias will qualitatively affect safety stock policy.
To schedule a customized on-site workshop, please contact us.
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