Forecasting Revenue

This post addresses a key question for start-ups, how do you model and forecast sales?

Please note that the technique below is best for enterprise-oriented companies rather than consumer Internet companies.

Forecasting Revenue
A key mistake start-ups make in raising money relates to how they model future revenues. This post explains a bottoms-up approach to forecasting revenue. My favorite bottoms-up forecasting method is the productive sales rep model.

In this model, future bookings are NOT a function of market share, size, and penetration rates ($500m market x .005 penetration, or $2.5m) but rather of how many mature sales reps are in the company and the expected sales rep quota and productivity.

A top-down approach is simply too hard to handicap and fails to ensure that a company matches an investment in sales resources with projected bookings and revenue.

First Model Bookings
Bookings = mature reps x quota per rep x productivity
Bookings = purchase orders
Mature reps = the number of reps with sufficient market and product experience to be effective (typically six months with the company)
Quota = bookings quota per year (typically $1-2m per rep in a start-up, and $2+m per rep in a mature company)
Productivity = percent of total quota achieved, on average, by the sales force

Therefore, for a start-up, with two mature reps entering the year, one rep joining in January, a $1.5m quota, and an expectation of 75% productivity, bookings would equal:

2.5 (mature reps) x $1.5m (quota) x 75% (average productivity as % of quota), or $2.8125m.

Then Assume Bookings Mix and Revenue Recognition Policy
To get to revenue, we then need to assume 1) a revenue recognition policy and 2) a bookings mix across license, maintenance, and professional services. This mix is typically 70% license, 15% maintenance, and 15% professional services.

Wrt revenue recognition, license revenue is recognized either at the time of sale for perpetual model or ratably for SaaS vendor, while maintenance and professional services revenues are recognized pro-rata over the course of the year/project. For example, assuming the bookings mix above a $1m purchase order (booking) on April 1 would contribute the following revenue in the year:

License revenues: $1m x 70%, or $700k
Maintenance revenues: $1m x 15% x 9/12, or $112.5k
Services revenues: $1m x 15% x 9/12, or $112.5k.

While there were $1m in bookings, revenues would be $925k, with the $75k difference on the balance sheet at year-end as deferred revenue.

The key issue is make sure that sales projections are tied to tangible investments in sales resources and are based on reasonable assumptions of sales rep productivity, time to maturity, and quota. Finally, think through how bookings translate to revenue. A sophisticated approach to the problem will go along way in gaining credibility with a prospective investor.