Prior to launch, there must be agreement – almost as if you had a contract in place – between your product, sales, marketing, and operations groups. In other words, all groups must own the forecast. Some reasons for this include:

• Sales must confirm and support their ability to meet sales targets

• Operations must ensure the company has the ability to produce product and deliver the production schedule

• Marketing must be able to validate their ability to create demand given the available budget

Without this buy-in from other functions, the result is the inevitable finger-pointing if actual sales don’t meet plan. This conflict can be eliminated by involving these team members throughout the product development process and particularly during key decision points such as giving a “go” to new product development or launch readiness.

This article presents a simple sales forecast tool we use in a team setting to develop a consensus-driven forecast.  As in all parts of the development process, applying collaboration to the new product forecasting process provides several benefits:

1. It allows more ideas and issues to be brought forward from multiple perspectives.

2. It removes the tendency for conflict and finger-pointing among forecast stakeholders.

3. It establishes cross-functional support and shared goals to drive decisions and launch planning.

While achieving accurate new product forecasts is important, understanding the assumptions behind the forecast is equally critical. In order to facilitate the discussion, we use a simple spreadsheet that can be projected on a wall so that each team member can participate in the discussion and see the impact of the assumptions.  The team can quickly build various scenarios as the forecast assumptions are considered. The key benefit of this tool is that it provides a framework for discussing the assumptions that underlie the forecast.

While there are a myriad of factors that impact a well planned forecast, we have narrowed the variables to those that are most important.  The team leader can conduct a session that addresses key assumptions as you systematically narrow the total market to those who will actually buy your new product.

The attached tool includes key factors that apply across most industries, and allows for the immediate input of assumptions that impact unit sales. By entering the values for your assumptions, you will see the resulting forecasts change immediately. If you choose to use this tool, you can add variables and modify the model to meet your forecast needs.

Let’s walk through the forecasting steps. Each step includes a corresponding line-item on the attached tool. An example is also included to show you how it works.

1. Potential Universe: Identify the superset of potential customers.  There are many ways of defining your target customers.  For example, Consumer Electronics products typically view their market’s Potential Universe as; “all global households”, “U.S. Households”, “U.S. Households with Children,” or similar. Gaining agreement on how to define the target universe is a great first step towards consensus.

2. Availability: Quantify how the rollout will limit the product’s availability to the Potential Universe.  In many launch plans, the product will be rolled out in limited geographic areas, distribution reach, or marketing reach.

3. Awareness: Determine the expected product awareness given the planned level of marketing effort.  While it is very difficult to estimate awareness for a new product, your sales and marketing team should be able to provide guidance on the relationship between marketing expenditure and market awareness for your new product at each period of the forecast.  The number entered here is the percentage of the target market that is familiar enough with your new product to consider buying. This can be a lively, but critical discussion.

4. Purchase (Take Rate): Determine actual purchase rates.  This is a tough factor to estimate and gain consensus.  If the category already exists, you may be able to use market adoption information, or a similar product whose adoption is known be may used as a proxy.  With a new-to-world product, a new adoption model may be required such an innovation diffusion model. E.g. Research has identified five types of variables that explain 50% of the variance in rates of adoption.  Everett Rogers’ book Diffusion of Innovations provides an excellent summary of the research in this area. 

5. Repeat Buy: Account for repeat purchases.  Repeat buys are extremely important in the consumer packaged goods and it is also a key consideration in other industries.  A “repeat” occurs when the same buyer purchases the product again.  For example, a 2004 poll by IBD/TIPP indicates that PC-owning households in the U.S. own 1.4 PC’s.  Your product may not be a PC, but how likely is it that a customer will buy your product multiple times or for multiple members of a household or company?  As you work these insights into your forecast, focus on the repeat buys for the period and how they relate to the first purchase market.

Forecasts are critical to evaluating and launching new product and service opportunities.  Building a consensus with sales, marketing, and operations, where each function owns the forecast, erases the potential for conflict. 

The tool we’ve provided can help your team consider the important forecasting variables to create accurate and supported new product forecasts.  Once you have the unit forecasts, you can then apply these assumptions and results to your pro forma P&L statements or business cases to launch successful new products.

Please let us know how this works for you and what tools you use to launch successful products.  

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Best of luck!

By Ed de la Fuente

Managing Director