Supply Chain Management


The course focuses on 16 key objectives, including the techniques of Regression Analysis and CPFR – Collaborative Planning, Forecasting, and Replenishment with fundamental exercises and case studies.

Do you remember the old yarn that states that “a bird in the hand is worth two in the bush”? The premise that we were taught as a child was that if you grabbed the bird in your hand it would not fly away versus the ones in the bush – you may catch them but then again – they may fly away, as a bird’s reflexes is usually much faster than a human’s.  No, this course is not for the birds! but it does  illustrate the major premise of Demand Management.

Experts define Demand Management as the optimized coordination of both customer orders (analogous to the bird in the hand) as well as the forecast (analogous to the two in the bush).  A great example of a company that puts a prime focus on this is Wal-Mart.  Similar to a mother that gives birth to identical twin boys and one turns out to be a man of God whereas the other becomes a criminal, this is analogous to both Walmart and another company that started business around the same time (early 1970’s) – K-Mart.  If you do not know who K-Mart is, that is our point, most of their stores have closed and a few years ago, they almost totally went out of business.  Walmart, in contrast, has been growing and thriving since its inception – thus the analogy of the man of God vs. the criminal!

Walmart is a master of Demand Management and based on their Point-of-Sale (POS) systems, once an item is purchased from one of their stores, immediate (real-time) feedback is passed back up the supply chain which leads to optimized planning (covered in the CPFR objective as noted below).  It is therefore imperative that we first understand what influences demand (either internal or external).  Then we can look at the types of demand (such as dependent or independent).  Lastly, we can focus on the characteristics that we can plan for (such as seasonality) vs. the characteristics that we have to live with (such as error).

This leads us into the actual forecasting which is basically a prediction of the future.  The further out we are trying to forecast or if we do not have any demand history (such as the introduction of a new product) then we will do Qualitative forecasting which highly opinion-based.  The closer in we are or if we do have demand history, then we will do Quantitative forecasting which is the use of various formulations.  We must then check the quality of the forecast tool which is done by tracking the error.

To support all of the above, this course will be featured in SCE’s virtual classroom with all of the functionality featured in our DEMO and based on our teams working with major corporations in BIC-Best-In-Class practices.  It will be a blend of educational topics, pertinent case studies, and practical stories based on past practices.  You will learn vital skill sets but also have fun!

Upon completion of the Applications In Demand And Forecasting course, the participant will:

  • compare and contrast the influencers of demand such as the marketplace, competition, government regulation or internal planning
  • review the four major patterns of demand:  stable, dynamic, dependent, independent
  • understand how characteristics influence demand such as the ones you plan for:  seasonality (including a calculation), cycles and/or trends
  • understand how characteristics influence demand such as the one that will hit you “broad-sided” – standard deviation (error)
  • emphasize the role of good data preparation and collection
  • understand the four key principles that apply to any type of forecast
  • compare and contrast the typical forecasting intervals
  • differentiate between intrinsic vs. extrinsic forecasting
  • review the main types for qualitative forecasting techniques as well as their applicability
  • review the main types of quantitative  forecasting techniques as well as their applicability – including some calculations
  • understand the concept of Regression Analysis and how it relates to extrinsic quantitative forecasting
  • compare and contrast the two categories of error – Random Deviation vs. Bias
  • calculate and apply the Standard Deviation to address error as well as the Mean Absolute Deviation (MAD) and the resulting Tracking Signal to change the forecast method
  • determine which of these techniques best fit your company
  • define and apply CPFR – Collaborative Planning Forecasting and Replenishment and its applicability to your company and industry
  • emphasize the importance of sharing demand information with your suppliers

Depending on the learning style of the participant, this course is designed to be approximately 15 hours in the e-Learning – virtual classroom.  Additionally, at the end of the course – you will take an on-line quiz to make sure you have grasped the key points.

Upon completion of the Applications In Demand And Forecasting course, the participant will receive a certificate of completion with 15 ceus of credit.

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