Roll of the dice webinar CCH Tagetik
FinanceFebruary 02, 2022

Forecasting demand & supply feel like a roll of the dice? It doesn’t have to be!

Read more to learn how straightforward it can be to generate a trusted forecast for demand and supply while incorporating uncertainty and optimizing inventory.

In a recent webcast, we had the chance to discuss how to generate a trusted forecast for demand and supply – even while incorporating uncertainty and optimizing inventory. 

A daunting task … or is it? For many supply chain planners, it looks that way at first glance because forecasting and managing sales/demand planning, supply, production, and sales and operations planning (S&OP) are rife with uncertainty and risk. 

A best-practice approach and the right tools make it easier. 

The first step to taking the dice off the table in supply chain planning is to understand the types of uncertainties your organization faces. Uncertainties are events that are ambiguous or unpredictable. For example, is it that we don’t know what next month’s demand will be, or that we don’t know exactly when to expect an order from a vendor? Then think about how you currently incorporate these uncertainties into your planning process. 

The second step is to ask similar questions about risks. Risk is the exposure to loss, or factors and events that could result in not achieving goals. Questions to ask here include: Will demand be higher than expected? What if I don’t have enough inventory? Then I risk losing revenue. 

The third step is considering how you are incorporating these uncertainties and risks into your planning process. Are you truly modeling and planning to incorporate them, or are you making best guesses and assumptions? 

The fourth step is finding the appropriate forecasting method for your organization. There are many different forecast models, but they generally boil down to four main categories: 

  • Point Estimate 
  • Range 
  • Best, Worst, and Most Likely 
  • Probability Distribution 

Each model has its pros and cons, and we go into detail on each in our on-demand webinar. Two quick and important notes on the methods as we traverse the list from top to bottom: 

  • It becomes apparent that using only an average for forecasting is flawed 
  • We can easily recognize our brains inherently tend to shy away from predicting uncertainties and risks without the right tools and information 

Interested in learning more about these forecasting models and the fifth step in taking the dice off the table: implementing forecasting software that handles complexities with ease? Watch our on-demand webcast, Bring Certainty into Forecasting Uncertainty, and learn how easy it can be to simulate what could happen on a month-to-month basis – at what probability – so you can bring even greater value to the business without second-guessing your forecast.

Brian Lewis
VP, Product Management - CCH Tagetik

Brian has over 15 years of experience in predictive planning, advanced analytics, and supply chain optimization. Prior to joining CCH Tagetik, Brian worked at Ford Motor Company and UPS. He has a PhD in Industrial and Systems Engineering from the Georgia Institute of Technology, a MSE in Industrial and Operations Engineering from the University of Michigan, and a BS in Industrial Engineering and Operations Research from the University of California, Berkeley.

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