Wouldn’t it be nice to know how much of something you’ll sell before you even start selling?

SAS forecasting affords you that opportunity and then some by blending analytics with strategy and automation to produce the fastest, most beneficial, and most accurate outcome that will power you through your most pressing obstacles.

SAS and CT Global have been executing on that process for years. CT Global Solutions leaders Edward Katz, Peter Turney, Manash Ray, and SAS Institute leader Roger Thomas explained, in their webinar about forecast accuracy, how you can improve your forecast accuracy in times of uncertainty.

Six Key Takeaways from This Webinar

#1 Analytics + Proper Implementation = Profit

Before you can even begin to think about outcomes, your analytics must be sharp and refined. Forecasting itself can be challenging with labor costs, material costs, transportation issues, and recent shifts away from make-to-stock implementation strategies and towards engineered-to-order strategies in the market. Moreover, the consequences of poor forecasting can be costly. The goal is to turn your data into dollars through a combination of solid analytics and strategic implementation supported by a solid foundation of accurate forecasting.

#2 Forecasting Matters because Uncertainty Is Expensive

What is the manufacturing response to uncertainty? To develop islands of efficiencies based on silo-ed metrics that result in the “Bullwhip Effect” wherein businesses either create more inventory, try to slip delivery times, or do a combination of both. These are less-than-optimal operational practices that can cost you more money than save. The solution to this is to bring analytics into the picture and grab executive attention by what you DO with your forecasts rather than just having good forecasts to begin with, further emphasizing the importance of having accurate forecasts you can rely on and trust.

#3 Your Analytics Should Drive Your Initiatives

Analytics-driven initiatives can increase accurate forecasting by 10% to 33%, decrease inventory costs by 15% to 30%, increase availability by 20% to 30%, reduce wastes and shrinkage by 10% to 15%, and increase revenues and gross margins by 3% to 11%. This is why data readiness and trustworthy numbers are so essential to accurate forecasting.

#4 Common Forecasting Problems Are Still Common Today

Low forecast quality can result in too many adjustments made and too much micromanaging, like having to manually analyze phase-in and phase-out dates and make transshipment versus order decisions manually on an ad-hoc basis. These obstacles have been around ever since forecasting’s inception and are why strong, accurate forecasting is absolutely imperative for business strategy. Both strong and weak forecasting methods alike affect the same things, such as warehousing, marketing, sales, and manufacturing quality, and your usual forecasting methods involve a blend of pattern-utilization and the unexplained. SAS provides you with automated causal models to combat unknowns and increase accuracy: data is presented in the system and the system takes over, intelligent automation forecasting produces a game-changing forecast that’s accurate, and there’s no statistician needed. Here, automation is the driving force.

#5 Remember: Ready, Aim, Fire

Most organizations tend to choose “ready, fire, aim,” over “ready, aim, fire.” For instance, SAS helped a leading international CPG company that subscribed to “ready, fire, aim” overcome its obstacles with its patented forecasting methods. The company sold between 3,000 and 4,000 products and was having trouble ensuring accuracy in demand planning and reducing forecast bias as well as achieving stock balance and avoiding production delays. Through SAS forecasting, this company was able to enhance the process and accuracy of its demand planning, reduce forecast bias to less than half of what it was before that resulted in lower working capital, and adopt a more holistic approach with appropriate scalability, all through “ready, aim, fire” forecasting.

#6 Proper Implementation Preparation Is Paramount

Before you do anything else, evaluate your data readiness, your IT infrastructure, your business decision-making, and your financial management strategies. Proper preparation is key. Your sources of data must be high-quality, accessible, and actionable through entities like executive sponsors, value quantifications, and process definitions. Your analytics must be insightful, measurable, scalable, and trustworthy. These components work in tandem with each other to produce the best possible forecasting result.

Check out the forecasting-readiness assessment that SAS and CT Global can give you to see if you’re ready for game-changing forecasting!