Forecast Errors
Volume I, Issue 3, December 1, 2014

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.

Forecast Errors Must Be Eliminated According to Gartner

Ben YoKell reported in Supply Chain Management Review in the current environment of proliferating product portfolios and increasing demand volatility, there is a great deal riding on getting demand planning right. Inaccuracies in demand forecasts generate costly waves felt throughout the entire supply chain. As such, Gartner recently positioned forecast accuracy at the very top of its metrics hierarchy.  Regular analysis of detailed transactional data from many enterprises combined with process information on exactly how demand planning is performed within the enterprise(s) is needed. Individualized results from new analytical approaches have created previously unavailable insights. Read more here.

Forecast Errors More Frequent as Industry Demand for New Supply Chain Talent Rises

SupplyChain247.com reported the demand for supply chain talent has been on the rise across industries and types of logistics and supply chain positions. According to the U.S. Bureau of Labor Statistics, jobs in logistics are estimated to grow by 26 percent between 2010 and 2020, an average growth rate that is nearly twice as fast as 14 percent of all occupations.  The supply chain job growth has been affirmed by a variety of industry associations. For instance, CSCMP’s Career Center reported “very strong” hiring activity and job postings for all types of logistics and supply chain positions in 2011 and 2012. Similarly, surveys conducted by the Institute for Supply Management (ISM) indicated steady and strong climbs in hiring in both manufacturing and nonmanufacturing sectors in 2011. Already, demand for supply chain professionals is estimated to exceed supply by a ratio of six to one, according to R.J. Bowman, author of The Secret Society of Supply Chain Management. Read more here

Forecast Errors and Demand Sensing

Joel Argo wrote for SupplyChainBrain that one of the new buzzwords in the demand planning arena is demand sensing.  Developed around 2003, demand sensing has slowly been grabbing the interest of the CPG, energy, food, beverage, and chemical industries. The purpose of demand management is to devise a manufacturing plan aligning supply and demand.  Demand sensing is applied to the short-term forecast and automatically adjusts the consensus forecast within a 4- to 12-week time frame. The main purpose of demand sensing is to improve forecast accuracy slightly outside of lead time to help prevent unwanted product from reaching the inventory pipeline. Demand sensing also provides visibility to variations in supply and demand allowing an organization to prevent out-of-stock situations due to overselling product. Demand sensing does not generally incorporate the total supply chain, but focuses on select products and customers.

Forecast Errors Impact Buyers and Planners

Forecast error impact buyers and planners most.  Eliminating stock outs that would lead to time wasted by expediting orders would reduce inventory by 20-75%.  Automating purchase order transactions which integrate with any ERP system, preventing duplicate transactions would eliminate more forecasting errors.  Buyers and Planners would find beneficial any technology which streamlines the Request for Quotation (RFQ) process with suppliers as well as the ability to easily transition suppliers to Vendor Managed Inventory or Consignment Inventory. Read more here.