Mavenlink & Kimble have joined forces to become Kantata. Learn More

Contact Us

Revenue Forecasting With PSA Software vs. Without

Revenue Forecasting is a critical process for any scaling professional services organization. The revenue forecast impacts the entire organization, not just finance. Organization leaders base important decisions on the calculations presented in the revenue forecast, so they need to be confident that the forecasts are accurate. That means a rigorous revenue forecasting process is required to keep a handle on profitability at your services organization. This article will discuss the impact of revenue forecasting and compare the advantages and disadvantages of forecasting manually as opposed to using technology such as Professional Services Automation (PSA) software.

What is Revenue Forecasting?

Revenue forecasting is the calculation of the amount of money that a company will recognize from sales or services during a particular period of time. Revenue forecasting requires visibility into projects both in the pipeline and in progress.

According to TSIA, a reliable revenue forecast should be able to answer the following questions:

  • What is the revenue/margin that will be earned over a given period of time?
  • What type of skills are needed to deliver projects across all clients? How many of these skills? When do they need to be available?
  • How will the revenue forecast reflect changes occurring throughout the project lifecycle?

Why is Revenue Forecasting Important?


A proper revenue forecast sets a business up for success. It lights the way to where your business is going; if you are on a path that strays from your original revenue target, it helps you take corrective action early. Forecasting revenue with accuracy allows leaders adequate time to make proactive, rather than reactive, business decisions that directly impact project delivery, hiring decisions and profitability.

Organizations that struggle to forecast revenue properly tend to base decisions on gut or experience rather than formalized data. Revenue forecasting allows organizations to get one step ahead of project, budget, or resource changes before they have too great of an impact on the bottom line. The art of reliable revenue forecasting requires the intersection of the three critical components detailed below.

Components of a Revenue Forecast

Revenue forecasting involves considering the aggregate projected revenue from all revenue generating work at an organization. To get an accurate aggregate, keep three critical components in mind: the commercial structure of the engagement (the total revenue, timeframe, and revenue recognition policy); up-to-date delivery data (what has actually been done); and a view of revenue that might come in from opportunities in the pipeline.

The commercial structure

The foundational component of revenue forecasting is the commercial structure of the work being done, which sets the rules for how much revenue you expect to make and when you expect to recognize it. The commercial structure can be broken down further into three parts.

  • Revenue amount: how much revenue will the work bring in?
  • Timeframe: over what timeframe will this work occur?
  • Revenue recognition policy: what are the rules dictating how the revenue will be recognized over that timeframe?

The revenue recognition policy is determined by the finance department and most organizations use a variety of different methods. Some popular revenue recognition methods include time & materials, cost percent complete, and effort percent complete.

The commercial structure is just one aspect of forecasting revenue for a project; the other aspect of your forecast calculation for a project will take either progress or probability into account. If a project is contracted and already in progress, you need to access to up-to-date delivery data to get an idea of how project delivery is going. If the project is not contracted yet, you need to understand how likely it is that the work will be won and set a realistic timeframe (start date and end date) based on that probability.

Up-to-date delivery data

This component of revenue forecasting involves tracking the work that is currently happening on a project and estimating how much work remains based on that data. It is important that revenue forecasts for live projects are not based on where you thought work would be when the project commenced. The amount of remaining effort as a percentage of total effort needs to be adjusted regularly by project managers with input from the resources doing the work. Without a clear and accurate picture of the work that has already been done, it is nearly impossible to calculate an informed revenue forecast for the future. Keep in mind the following when forecasting revenue: Can you trust the information is current? Even if you have a thorough process for collecting project data, are you basing the revenue forecast on outdated data?

Pipeline data

Forecasting revenue for uncommitted work requires analyzing the sales pipeline, assessing potential revenue the business stands to earn. Incorporating revenue from an opportunity requires information from salespeople to be reliable and easily accessible. First, what is the probability the opportunity will be won, unlocking the associated revenue? You are unlikely to take an opportunity that has a 5% chance of being won as seriously as you would take one t has a 95% chance of being won. How your organization decides to prioritize or weight probabilities will vary, but one thing always remains true: you do not want to be forecasting based on an inaccurate or out-of-date win probability. The same idea holds true for the close date of an opportunity and proposed start date of the ensuing project – there will always be some guesswork involved in gauging the kickoff date for uncommitted work, but it is critical that you are forecasting on a salesperson’s current best guess and not their first guess. The timeframe of an upcoming project has major effects on where revenue will fall in the forecast – an important basis for decisions your business will make about where it’s headed – so this information should be as accurate as possible.

Revenue Forecasting Methodology

In order to accurately forecast revenue, financial advisors suggest using the same calculation that you will use to recognize revenue. Using this approach, a revenue forecast is essentially a precalculation of the revenue you will recognize based on the most up-to-date data available.

Many professional services organizations recognize revenue based on the percent of the work done by allocated resources rather than the amount invoiced, avoiding “lumpy” revenue results that are overly reliant on major revenue milestones. Where this is the case, revenue forecasts should also be calculated with expected resource effort at the center. This approach is referred to as resource-based or bottom-up revenue forecasting and is usually a better fit for services organizations than other common revenue forecasting practices like trend, straight-line, or top-down forecasting.

Forecasting Revenue Without PSA

When a professional services organization is managing a handful of resources and assignments, an automation tool likely isn’t required to keep track of all the resource and finance details that lead to an accurate revenue forecast. Forecasting revenue from the bottom-up using a manual process is a realistic option for smaller organizations running a relatively limited number of projects, especially if those projects largely use the same commercial model to recognize revenue.

At most professional services organizations, manual revenue forecasting is accomplished through a multi-step spreadsheet approach. An individual, or even a team of professionals, spend time forecasting revenue within spreadsheets and workbooks, collecting necessary inputs from finance, operations, project managers, and the sales team. Since, even at a smaller scale, aggregating this data into an up-to-date revenue forecast can be very complex, this tends to be managed by trusted individuals who spend most or all of their time collecting and calculating forecast data.

This manual process tends to get increasingly complicated as the number of inputs scale with an organization. As an organization grows, multiple changes – including delays in calculation of revenue recognition for a period and teams becoming siloed as they grow reducing the reliability of pipeline and project data – affect an organization’s ability to produce accurate, timely revenue forecasts.

In these situations, teams might default to forecasting based on an educated guess. Many times, this guess is not even educated and is simply based on gut instinct or optimistic numbers. This tends to result in poor decision-making or decisions made too late in the game to have an actual impact.

There comes a time where a growing organization requires the right technology to support growing inputs. It is up to an organization to decide at what point adopting technology, such as a Professional Services Automation (PSA) solution, will provide an adequate return on investment. An organization can justify keeping revenue forecasting a manual process if it is not reducing operational efficiency or if they are not planning to scale the process. However, when contemplating a scalable forecasting process, it is worth it to invest in technology that automates important aspects of revenue forecasting.






How do PSA Solutions Help with Revenue Forecasting?

Business leaders rely on trusted, accurate revenue forecasts to make informed business decisions. PSA software provides not only the framework for systematic collection of detailed, up to date, forecast data across your entire services portfolio, but also the real-time automation needed to enable confident, timely decision making.”

PSA systems like Kimble combine ongoing project data with pipeline data being fed from the customer relationship management (CRM) system—so all projects, current and future are taken into account. In this way, PSA tools give you a realistic picture of resources and the work they’re doing and could be doing, leading to a more accurate forecast.

Professional Services Automation software also inspires greater data governance within an organization, further ensuring an accurate revenue forecast based on up-to-date information on both potential work and work in progress. PSAs make it possible for even the largest professional services organizations to use resource-based or bottom-up revenue forecasting at scale.

While most PSAs integrate resource planning and the sales pipeline, making it easier to access data required for calculations, not all PSAs put equal emphasis on automatically providing clear, real-time revenue forecasts that enable more proactive decision-making at your business. Unlike other PSAs, Kimble puts revenue forecasting at the center of the entire process of services delivery. Kimble is here to relieve teams that have spent years calculating revenue forecasts in spreadsheets. When evaluating the right PSA application for you, make sure that it can enable the following improvements in the revenue forecasting process.

Forecasting Revenue with PSA

It becomes easier to get updated data from all teams teams providing inputs for revenue forecasting

Professional Services Automation (PSA) software closes the gap between sales, resourcing, and delivery teams, which tend to become siloed as your business grows. It can be difficult in growing services organizations to keep all teams on the same page without one central location for updated project status and data. The PSA application not only serves as the central hub/the one source of truth, but it also prompts these once siloed teams to collaborate and keep their data accurate. Automated data collection is critical as the revenue forecast becomes skewed when it is fed with inaccurate information. PSAs circumvent this issue by automating the collection of these inputs.

Period close and revenue recognition become more agile.

PSA enables organizations to close down a period and lock in revenue recognition numbers for a period much more quickly than manual methods. Without a PSA, organizations run the risk of having delayed revenue recognition calculations, which may lead to unrecognized or lost revenue being left out of forecasts. For example, a lucrative opportunity that was projected to close and start within the period being closed has not been set as closed or updated. It is important to catch these inconsistencies while closing periods and to act on them quickly, because the revenue forecast will not be accurate until you understand if this means:

  • The opportunity was won but the sales person didn’t update it in the system.
  • The opportunity was lost and not updated in the system.
  • The sales team is still fighting to win the opportunity but the close date needs to be pushed out for the revenue forecast to be accurate.

PSAs ensure that you have an aggregate view of all the revenue that hasn’t been actualized during that period but may actually come later. Even if you have the best process or systems to support revenue forecasting, if the revenue recognition for a period takes weeks or months to get approved by finance, you will never have an accurate forward-looking picture.

The actual calculation of revenue becomes an automated task with automated inputs.

At most companies, the revenue recognition process is not an automated one. Professional Services Automation (PSA) software turns the revenue collection and calculation process into an automated and instantaneous process that simply runs in the background. A PSA typically frees up the individual or team that was once dedicated to forecasting in spreadsheets. This allows the “forecasting” team to spend more time analyzing, rather than collecting, data. Most importantly, when a change occurs (i.e. when a milestone shifts), the PSA will automatically adapt and shift all revenue numbers based on that change. This is one of the most significant differences from forecasting manually in spreadsheets – the more complex your organization becomes, the more time and effort it takes to adjust increasingly complex spreadsheets to account for changes.

See Kimble In Action

Watch Demo