Demand Forecasting for New Products
From Comparables to Supersessions
Market fluctuation raises the specter of product release failure or underperformance. This makes demand forecasting for new products exceedingly difficult, especially for products with short and fast changing consumer demand cycles.
Across industries, some 80% of new products fail. Not surprisingly, one of the biggest contributors to that failure rate is unnecessarily inaccurate forecasting. While no system or organization gets forecasts 100% right, the best of the best get them consistently less wrong.
New products are inherently difficult to forecast because they have:
- No direct historical data to extrapolate
- Diverse or sometimes unknown buyer sets
- Harder-to-predict adoption rates and lifecycle spans
The good news, new products are usually comparable to older products, applying the right attributed between old and new improves demand forecasting for new products. And new products are often introduced to replace existing products, in which case statistical tools such as Supersession can help planners model the transfer of demand from one or more products to a new product or set of products.
Demand forecasting for new products is difficult because they lack any sales history. There are, however, tried and true statistical methods that get around this obstacle. Vanguard Software has two decades of experience applying comparable forecasting, spread curves, and supersessions to hard-to-predict product launches. The result is the matching of great products with effectively planned launches for maximum market penetration, sales, and profitability.
The Supersession feature in Vanguard Software’s forecasting & planning platform delivers the best-of-breed capability for predicting demand transitions from one product to another, one to many, many to one, or many to many. This combined with Vanguard’s unmatched arsenal of analytics, automation, and collaboration features, gives you an all-in-one enterprise Sales and Operations Planning (S&OP) solution in a single, cloud platform.