Forecasting Revenue

Forecasting revenue

The process of creating a revenue forecast is notoriously difficult in a start-up. Forecasting is never easy, but it is made more tractable by the existence of a history. In a new venture, there is no history. The forecast must be created from scratch.


Creating a reasonable forecast of future revenue or sales is perhaps the most difficult of many difficult planning exercises for a start-up. Given that so much guess work is involved, many entrepreneurs just throw numbers into a spreadsheet and treat them as though they constitute a plan. We believe this is a mistake.


This section lays out the elements of a sales forecast and a method for constructing a sales forecast. Instead of guessing at the totals, we present a method of guestimating the components of revenue. Although this method may appear to be overly formal for the start-up phase (when all of the component estimates may not be much better than guesses), we think that it is vital to the future management of the venture that a method like this be adopted very early in the life of the company for two important reasons.

  1. This method exposes the assumptions on which the business is based. This allows the entrepreneur to think critically about the business.
  2. This method lays the foundation for future management of the sales process. Although the revenue forecast and the sales plan on which it is based will be wrong in many respects, beginning with a structured model allows the entrepreneur to understand what assumptions are faulty. He/she can then make revisions as information is gathered. With experience, the sales model and forecast can be improved incrementally. Having a reliable sales model and forecasting ability is critical for managing the growth of the business. The sooner the foundation is laid, the better off the company is.

The method outlined here involves breaking up the market into segments, and then creating an estimate of adoption of the company's by segment. A segment is a collection of customers who are expected to behave similarly: they will respond to similar messages, they have roughly the same demand, they will adopt at roughly the same pace and will buy in a similar fashion. We then estimate revenue by segment.


STEP 1


Divide target customer set into segments.


Segments comprise customers who can be expected to behave roughly alike in terms of adoption pattern - rate of adoption and average revenue. Good segmentation will require solid market research as a foundation.


Many factors will be involved in segmentation. These include:

  • nature of the customer's business
  • size or income
  • propensity to adopt new products or services - leader or follower
  • decision and buying process

A segmentation must be granular enough that it is useful for planning purposes. But the segmentation should not be so fine that it is unwieldy or implausible. A reasonable number of segments in the early life of a venture is 6 - 15.


STEP 2


Estimate the number of customers in each segment.


STEP 3


By segment, estimate:

  • time to adopt
  • rate of adoption (if applicable)
  • average revenue per period (month or quarter) during the adoption phase and then steady state after that
  • sales effort required in all phases

The use of comparables can be a very useful tool in this process.


STEP 4


Model the selling effort by period (including a ramp up period for direct sales people or other channels).


All of the other estimates in this process create an upper bound on the revenue in each segment. This step is where the reality of customer resistance and the effort required to acquire customers and sustain a relationship are factor in. The topic is discussed in greater depth in Sales planning.


STEP 5


Run the model - revenue projections and direct sales expense by period will be generated.


NOTE: These forecasts will presume and depend on some set of facts and complementary activities that are not included in the forecasting process, including:

  • sales support
  • marketing activities
  • customer support
  • product competitiveness / strength of value proposition.