Demand forecasting is more challenging today, with pricing volatility, unpredictable consumer behavior, disruptive supply chains, and tariff conflicts. However, forecasts can help your business plan production accurately, manage inventory effectively, increase customer satisfaction, and achieve profitability. In this webinar, Don Lindsey helps you gain a deeper understanding of the basic principles of forecasting, including its processes, methods, and techniques. He examines the factors that influence demand and demonstrates how to apply mathematical principles and subjective knowledge to create accurate forecasts. Don also …

• Explains the tools in QAD that assist with your forecasting processes
• Demonstrates why forecasting is essential in today’s economic environment
• Outlines the challenges and limitations in forecasting
• Discusses the 32 Soft Data Loaders that can help you more effectively manage demand forecasting

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Questions from the webinar

	With QAD’s transition to private equity ownership, do you foresee any increased risk to QAD’s future?
No, in my conversations with people at both MWUG and WECUG, there is movement afoot to enhance significantly the forecasting possibilities and tools available to QAD. I think the future of QAD is strong, and we anticipate it will continue to compete with other top ERP systems. When it was developed, QAD was one of the few systems that utilized the APICS body of knowledge, which accompanies certification regarding the use of an ERP system, thus providing a firm foundation for future success.
	How does QAD measure and improve forecast accuracy?
QAD utilizes the sales order analysis module in conjunction with the invoicing process for sales orders to record the actual occurrence of demand. This is used to calculate the mean absolute deviation and other forecast tools that measure forecast inaccuracy.
	Can QAD’s forecasting system handle seasonal and abnormal demand patterns?
Yes, QAD allows for the entry and adjustment of forecasts for seasonal builds, holidays, and abnormal demand in the 22.9 Seasonal Maintenance module, ensuring the supply chain is prepared for fluctuations. The module calculates the average demand and then examines individual demand occurrences based on seasonality. It then makes an index and multiplies your new forecast so that the seasonal indexes can be applied to that new forecast. MRP is then driven to build in anticipation of that seasonal demand.