New Product Forecasting

Line Art

3 ways to model product releases for better forecasting, planning and performance

Marketplace fluctuation raises the specter of product-release failure or underperformance. This makes new product demand forecasting and planning exceedingly difficult, especially for products with short and fast-changing consumer demand cycles.

The good news:

  • New products are usually comparable to older products. Applying the right shared attributes between old and new improves new-product forecasts.
  • 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.

About Comparable Forecasting

The problem with trying to forecast demand and adoption rates for new products is that there is no history to work with, at least no direct history. However, there may be similar products with comparable attributes and sufficient historical data to serve as a proxy.

Comparable Forecasting applies the patterns and parameters of similar previous products to the forecasting of new products. You can use it for both initial and later-stage adoption rates. It works best if your new product or service is substantially similar to an established, or previously launched item, or better yet, a set of items. With the right technology platform, you can select comparable past products by virtually any attribute, such as:

  • Product code
  • Product family
  • Region
  • Seasonality
  • Adoption profile
  • Life cycle span
  • A combination of attributes

About Spread Curves

In Vanguard Predictive Planning, a user with domain expertise can select the likely demand factors that will affect the adoption of a new product and apply them to the forecast. These effects can include seasonality, decay, launch time, life cycle, region, and more. Typically, Vanguard works with clients’ domain experts to discover, test, and isolate the effects of these key demand factors.

About Supersession

Supersession is an adjustment tool for a Time Series forecast that models the transfer of demand from one or more products to a new product or set of products. Supersession factors in the cannibalization effects of the new product introductions (NPIs), such as on existing products, or in cases where there is a staggered release of two or more products.

Supersession is useful in modeling:

  • Product transitions: One product replaces another product.
  • Phase-outs: One product slowly phases out and is no longer sold.
  • Cannibalization: A new product competes with an existing product and cannibalizes some of the existing product’s demand.

Supersession with forecast automation

With automated forecasting and planning software, the Supersession feature automatically maps old-item sales data to new items. This lets organizations easily model and map the gradual (or swift) replacement of existing or base products with new products. This is key to product demand planning, transition planning and strategy, and NPI execution.