Revenue forecasting is more of an art than a science—for professional services firms at least. Although the inputs used are quantitative in nature, successful service executives will often layer in their perspectives on the business, the market, or key accounts. Perfecting the qualitative aspect of forecasting revenue comes with years of experience working in PS firms. The underlying forecast model, however, is something that every services manager should know how to build, and build well.
There are quite a few different approaches to building a revenue forecast, and in reality, firms will mix and match models to develop the most accurate forecast they can. Given that there are many different ways to forecast revenue, here are a few of the most common:
The Pipeline Approach
The pipeline approach to forecasting revenue involves tracking and measuring the organization’s sales pipeline. The idea being that some percentage of the opportunities the sales team is working on will turn into real work. The tricky part with this approach is trying to determine what the size of each deal will be and what the “some percentage” of the pipeline is. Many organizations will use the percent likelihood of an opportunity, represented by the stage it is in, to factor the total revenue forecast. That being said, it is usually not until much later in the sales process that a reasonable estimation for size and duration is made. This limits how far into the future this type of forecast can reach.
- Pipeline data is usually accessible and easy to understand.
- Historical win rates can add confidence to the model.
- Sales team could be overly optimistic, leading to inflated projections.
- Doesn’t include in-process work.
- Doesn’t provide great detail for when the revenue will be earned.
Similar to the pipeline approach, using backlog to forecast revenue looks at the total amount of revenue that you have contracted but not yet earned. When using backlog to forecast revenue you don’t need to worry as much about factoring for uncertainty, but rather realistically distributing the revenue over time. This distribution can be done by calculating the typical run rate of your team for a given period and dividing that into the total revenue figure. This calculation will represent about how long it will take the organization, at its current size, to earn what is currently in the backlog.
This approach works well when a high-level view is all that the firm requires. It also assumes the organization has a historical track record of delivering work very similar to what’s in the backlog. Quite often professional services firms will pair their backlog with their pipeline to build a more holistic revenue forecast.
- Easy to calculate.
- Doesn’t require heavy factoring.
- Can be translated into capacity.
- The timing of revenue is an approximation.
- Only valuable as a planning tool.
Sometimes called bottom-up forecasting, resource-driven forecasts require scheduling out all of the planned work a firm is aware of. Project managers will make their best estimates for when, and by whom, work will be performed, and use resource scheduling software to allocate the time to the proper team members. If work is far into the future or on a project in a proposal stage, they will use a placeholder resource to model out the work. This scheduled time is then translated into revenue via billing rates or a revenue allocation for fixed price work.
This approach creates very detailed and accurate forecasts but does require consistent maintenance to be actionable. It is typically well suited for larger organizations or firms that have more complex projects.
- Very accurate and detailed forecast.
- Can include both pipeline and in process work.
- Adjusts as project managers make schedule changes.
- Useful for highlighting capacity shortfalls or surpluses.
- Useful for highlighting projects that are ahead or behind schedule.
- Requires disciplined process to ensure accurate resource bookings.
- Sophistication in the tools used is needed to decentralize the process properly.
Historical Performance + Effects of Change
For firms that run a recurring revenue business model, such as managed service providers, this approach may work well. It involves looking at the same period in the past and assuming the firm will earn at least the same amount of revenue this period. With historical performance as a baseline, current conditions are then analyzed to assess how they may affect that performance. Winning or losing a major client, introducing a new service line, or outside market factors are all examples of events that should be taken into account.
- Can be performed quickly.
- Takes into account market factors in addition to backlog and pipeline.
- Can be performed in tandem with other approaches.
- Requires in-depth understanding of the firm, and the market it operates in.
- Needs to be consistently assessed for accuracy.
- Doesn’t highlight capacity requirements.
- Not appropriate for traditional services business models.
How Professional Services Firms Actually Forecast Revenue
So how do professional services firms actually forecast their revenue? The real answer is likely to be some version of “all of the above.” Not only does every professional services firm forecast revenue differently, but each one will also use a different mix of the techniques discussed here to come up with their final number.
Combining the backlog forecast, a bottom-up approach, and the pipeline method would be an example of how this might play out in a real-world setting. Firms that champion this approach typically leverage PSA software to aggregate and validate their predictions. For standardized, repeatable work that has already been won, the firm may use backlog to get a high-level view of revenue forecasts. Committed work that is more custom may require the addition of the bottom-up plan. From there it may make sense to layer on pipeline work by using opportunity size, start date, duration, and likelihood to model uncommitted revenue.
This allows the firm to both accurately time-phase their revenue forecast and gather insight into their capacity to deliver the work. Because resource-driven models understand capacity beyond the resource dimension (e.g. titles, departments, offices), the revenue forecast is useful for many decision-making processes.
What all Forecasts have in Common
Regardless of which approach a firm chooses, there is one thing that all professional services firms must do—check their work. Forecasts are only useful if they can be trusted. Professional services firms need to be consistently measuring how accurately they can forecast work. If accuracy is lacking, then it’s time to evaluate a new approach.
If forecast accuracy is a concern for your professional services firm, then take a read through our post: 6 Common Revenue Forecasting Mistakes Professional Services Firms Make. In it we take a look at some of the common issues facing revenue forecasting, and how to avoid them.