How to Forecast Revenue

Making predictions can be tricky, especially when it involves the future :-) Here is a simple way to forecast revenue for founders who are not clairvoyant.

As a founder, you learn early on to get very good at rationing resources in your startup. The ability to predict sales revenue is essential for survival, when cashflow is especially choppy. Can I make payroll this month? The ability to forecast revenue over the foreseeable future, and with any level of confidence, is also the key to de-risking decisions for growth e.g., What investments can I make? Who can I afford to hire, and when?

In physics, the observer effect is the "disturbance of an observed system by the act of observation; often the result of utilizing instruments that, by necessity, alter the state of what they measure" [Principles of Quantum Mechanics 4th Edition].? Forecasting revenue is not only essential to understanding cash flow needs and managing risk — much like the "observer effect," the practice of forecasting revenue has a positive impact on revenue growth.

Forecasting revenue forces transparency, accountability, and urgency among the sales team. It also stimulates creative solutions to obstacles that are preventing deals from moving forward. When making payroll or commission payments are on the line, wishing and hoping are not part of the discussion. In other words, forecasting revenue has a "positive disturbance" on both salespeople and revenue growth.

Forecasting revenue is both a data- and judgement-driven practice. Data forms the foundation, and is comprised of the “current status” of the potential value, sales stage, and timing of individual records in the pipeline. What does the data in the CRM say? Personal instincts — from experience, and boots-on-the-ground knowledge of individual customers— is the veto power: Do we believe the data?

Importantly, the forecasting method you choose must be simple. In my experience, over-engineering or introducing unnecessary complexities into your revenue forecasting model tends to increase the effort much more so than the reliability of revenue projections.

The Weighted Pipeline

The Weighted Pipeline is a simple and reliable method to calculate the current value of deals in a sales pipeline vs. the absolute potential value. Put another way, a weighted pipeline adds context and timing to the numbers. This is the difference between what is theoretically possible, and what is probable, given the current status and progress of individual deals in the pipeline.

To build a weighted pipeline, assign a probability factor to each step of your sales process. Initial steps at the top of the sales funnel e.g., discovery discussions, are assigned a low probability, with the probability increasing incrementally with each subsequent step of the sales process. For example, initial discussions with prospects who express interest may be assigned a low probability of 15%, whereas opportunities that are further along in your sales process are assigned a higher weighting factor of 50%.

The weighting percentages that you associate with the different stages of your sales process should mirror the historical "conversion metrics" among each stage of your sales process. This makes the basis of revenue forecasting data-driven, not based purely on conjecture. (More about this in a minute.)

The following revenue projections (example) are for a product that sells for fixed price of $50k, and a five-step sales process, ranging from 25% to 75% probability at the different stages of the sales process. With five total deals in the pipeline — each at a different stage of the sales process — the absolute (potential) value of the pipeline is $250k, but the current (weighted) value is much lower at $115k.

The individual steps of your sales process can vary greatly, depending upon the nature and complexity of your product, the buying-process of the market you are selling into, and other factors. Think through your sales process, and arrive at practical milestones and associated weightings that are appropriate to your business.?

The example below applies the same sales steps and weighting factors above, to a variable-priced offering (combination of product and services). Each potential deal value is multiplied by the corresponding weighting factor. Add “Timing” to this, and the current revenue forecast appears in the corresponding calendar quarter. You now have a revenue forecast for the upcoming four quarters.?

Here is where personal judgement enters the practice of revenue forecasting. Pressure-test each of your "top 10" opportunities, to see if there are valid reasons why you do not believe the data in the CRM, and make the appropriate adjustments to the forecast.

Note that the timing for “Company F” is unknown, so it is not included in the forecast. Among all types of data that factor into revenue forecasting, "customer timing" is often the most ambiguous and error-prone — so resist the temptation to plug "guesses" into your forecast. Leaving the expected close date empty is a signal that you need to gather vital information from the prospect.

These are two simple examples of a revenue forecasting framework. Depending on the product you are selling and unique aspects of your sales process, you may decide that one or two additional factors are also important considerations in your method. Most "additional factors" should surface during the final judgement phase of forecasting.

Unless you have a short B2B sales cycle e.g., fewer than six months, I recommend using calendar quarters to forecast revenue. This avoids the tedium of moving deals back a month or two every time you discuss revenue projections. And if (when!) you do push a deal out to the next quarter, you should have a very good reason. You decide what calendar periods best reflect your typical sales cycle.

Depending upon the maturity of your startup, and the number of deals you have already run through your sales funnel, conversion metrics among the different stages of your sales process can take up to one year (or more) before they can serve as reliable weightings to forecast revenue. The timeframe is never, if you fail to make proper CRM data hygiene a priority.

Before you get to this point, use the "Founder's Survival Hack." Simply divide your pipeline value by one-half, and 2x the projected close dates. This work-around may help you survive until you have a reliable, data-driven revenue forecasting method in place.

Your ability to measure “money out and money in” at a detailed level, and on a consistent basis, is one of the most important skills for growing a startup into a scaleup, and one of the most important things investors look for.