Revenue forecasting is critical for businesses across industries. Accurate predictions enable an organization to set rational goals and improve resource utilization. On the flip side, inaccurate forecasting can severely impact overall resource utilization as well as organizational efficiency. Revenue forecasting is even more significant for professional services organizations with large footprints. Therefore, organizations of all sizes must choose the right revenue forecasting model to induce accuracy and precision in predictions.
Through this blog, we will discuss the key revenue forecasting models for professional services organizations.
What Is Revenue Forecasting?
As the name suggests, revenue forecasting is the process of predicting future revenue. It is an important process for every professional services organization to carry out, so they can make informed decisions and devise data-driven strategies.
Although revenue forecasting is highly dependent on quantitative analytics, don’t ignore the value of a qualitative approach. Successful professional services executives will always apply their intuitive business knowledge when forecasting. No matter how simple forecasting may sound, it takes years of hands-on experience to gain expertise in revenue forecasting.
What Are the 4 Common Revenue Forecasting Models?
Four different types of revenue forecasting models are commonly used by businesses. Each model comes with an inherent set of benefits and weaknesses. Therefore, it can make sense to mix and match different models for accurate forecasting and predictions. Professional services organizations should build a hybrid model that suits their business while ensuring accurate forecasting.
Here are the 4 most common revenue forecasting models:
The Pipeline Revenue Forecasting Model
The pipeline revenue forecasting model involves comprehensive analysis, tracking, and computation of an organization’s future sales or sales pipeline. This model primarily revolves around the idea that some percentage of sales forecast will be converted into real opportunity and revenues. However, it is quite tricky to guess the exact conversion percentage. Moreover, organizations often find it difficult to estimate the size of each deal.
Making estimates is difficult because organizations usually rely on the percent likelihood of a sales opportunity, considering the stage the prospect is in. Thus, a reasonable estimate of revenue size and duration can only be made when a prospect enters the later stages of the sales cycle.
|Strengths of the Model
|Weaknesses of the Model
|Pipeline data is readily available and accessible
|Optimism often leads to inflated projections
|Historical win rates enable accurate forecasting
|It’s hard to predict when the revenue will be earned
The Backlog Revenue Forecasting Model
The backlog revenue forecasting model involves evaluating the total amount of revenue currently secured under contract but hasn’t been paid. This is an improvement on the pipeline approach, as you don’t have to consider uncertainty or make estimates.
With this model, you need to realistically distribute revenue growth over time. This often becomes tricky as you need to consider the typical performance and success rate of your sales team. Accurate distribution may sound challenging; however, it can be carried out by simply calculating the typical run rate of the sales team during a particular time span and then dividing that amount into the total revenue figure.
This calculation can help organizations figure out how long it will take to earn the potential revenue currently in their sales backlog. But, remember that this calculation assumes that your historical track record of delivering solutions will apply to the backlog. Professional services organizations often synchronize their backlog with their pipeline to create a more reliable and holistic revenue forecast.
|Strengths of the Model
|Weaknesses of the Model
|Easy to calculate without much forecasting
|Tricky to distribute revenue growth over time
|Helps in demand capacity planning
|Timing the revenue requires an approximation
The Resource-driven Revenue Forecasting Model (Or Bottom-up Forecasting)
Resource-driven forecasting is often referred to as bottom-up forecasting, wherein organizations rely on their best judgment and on resource scheduling software. Organizations ask their teams to schedule all planned work and use software to align their plans with appropriate resources. Planned work includes both types of projects – ones in the execution stage and ones in the proposal phase. Then, organizations categorize the scheduled work into time-phased revenue forecasts. This provides an insight into an organization’s capability to deliver the project within the estimated time frame.
Resource-driven forecasting requires teams to have a clear understanding of the project pipeline, so resource schedulers can align appropriate resources to the project workload. This type of revenue forecasting needs continuous monitoring and adjustment to account for capacity shortfalls or surpluses. Regular monitoring also allows resource schedulers to identify and handle projects that are failing to meet the schedule.
|Strengths of the Model
|Weaknesses of the Model
|Provides accurate and detailed forecasts by considering both proposed and in-process work
|Requires a sophisticated resource management tool
|Highlights capacity shortfalls, surpluses, and projects that fail to meet schedules
|Requires a disciplined process for bookings, monitoring, and adjustments
Revenue Forecasting Through Historical Performance and Effects of Change
The Historical Performance revenue forecasting model is highly effective for organizations that have a recurring revenue business model. It assumes that an organization will earn or generate at least the same amount of revenue in a given timeframe as it did in the same span in the past. Organizations take their historical performance as a baseline and then analyze the current conditions to evaluate its effects on revenues.
While forecasting revenue using this model, organizations must consider all the factors that can potentially influence their revenue generation capabilities. Some common factors include acquiring new clients, losing major existing customers, or introducing a new service line.
|Strengths of the Model
|Weaknesses of the Model
|Provides easy, fast, and accurate forecasting
|Requires analysis of market and external factors
|Considers all external or market factors
|Does not highlight capacity requirements
|Considers the whole work of backlog and pipeline
|Cannot be adjusted as scope/schedule changes
|Can be performed with other approaches simultaneously
|Ineffective for traditional services business models
How Do Consulting and Professional Services Organizations Forecast Revenues?
What is the best approach for consulting firms or professional services organizations to use when forecasting revenues?
Well, it is the perfect blend of all the four models discussed above. In fact, every professional services organization has a different approach to revenue forecasting. These organizations leverage a different mix of techniques and revenue forecasting approaches that best suits their financial models.
Large organizations usually combine different aspects of revenue forecasting models to meet the requirements of real-world business settings. They combine the backlog model, the bottom-up approach, and the pipeline forecasting method to ensure accurate revenue forecasting. Whatever combination of methods they use, organizations leverage the revenue management functionality of a professional services automation (PSA) tool to validate overall predictions.
Organizations utilize their backlog to develop an overview of revenue forecasts for all the projects they have already won. Similarly, they rely on bottom-up forecasting or resource-driven predictions for projects that undergo dynamic changes or modifications. Then, they pay attention to pipeline work and analyze opportunity size, project duration, and date of commencement to confirm revenue predictions by making phase-driven forecasts. Furthermore, organizations leverage capacity planning methodologies to ensure the timely delivery of services; This model also helps businesses make other resourcing decisions, like title and department assignments.
Irrespective of which revenue forecasting model they choose, professional services organizations must always monitor their actual revenue generated to confirm forecasts are as accurate as possible. If your combination of methods results in inaccurate forecasts, you should refine your approach. Once you are able to forecast work accurately using your chosen forecasting model, half of the battle is won!
Revenue Forecasting: 5 Common Mistakes
Professional services organizations rely heavily on their ability to forecast revenue. Different organizations perform different types of forecasting, such as profitability forecasting and utilization forecasting. However, all these types of forecasting are simply subsets of revenue forecasting. Once an organization has accurately forecasted its revenue, it can optimize its workforce size and ensure a healthy service mix. Conversely, inaccurate revenue forecasting can result in suboptimal resource utilization and high turnover. That’s why organizations must pay due attention to revenue forecasting.
Despite being immensely important, revenue forecasting often fails to receive the attention it deserves in professional services organizations. Although high-performing professional services organizations often take forecasting seriously, they may still need to optimize their efforts for accurate predictions.
Different factors can influence the accuracy of predictions. Some companies grow rapidly, giving them nothing to base forecasts on, while others don’t have access to the right forecast modeling tools. Given these differing factors, organizations must understand that there is no one-size-fits-all approach; one approach cannot guarantee accuracy in every circumstance.
Organizations often make the following mistakes while forecasting revenue:
1. Resource Scheduling
Top-performing organizations pay due attention to matching resources’ skills with appropriate projects through resource scheduling. These companies count on resource scheduling software, which provides managers with a centralized view of resource availability and upcoming work, so they can control and supervise the resource chain. On the other hand, many professional services organizations do not leverage this type of software, forcing project managers to create schedules for their teams without a full view of requirements and availability. This kind of ad-hoc scheduling is inconsistent and deprives managers of insights they could use when making decisions.
When you use a resource scheduling system, it allows your leadership team to translate the dashboard’s information into actionable insights. This helps in ensuring accurate revenue forecasting and optimal resource utilization. The only thing you need to be cautious about is updating your schedules in a timely manner.
2. Be Careful With Rates!
Although billing rates are typically standard across organizations, you need to consider each aspect of rates while performing revenue forecasting. Resources come with standard rates, but your projects and contracts may represent a discount from that standard rate. Therefore, organizations must tie their rates to granular items – such as scheduled hours – to forecast accurately. This becomes even more significant in managing fixed-price projects. Besides paying attention to price, organizations must also consider when the revenue will be realized. You can also leverage revenue recognition tools to match the overall revenue with phase-driven projects. This will help you forecast future earnings and allocate a proper amount to every task.
3. Treat Each Project Differently
Once you have a comprehensive schedule and a realistic rate, it becomes easy to forecast revenues accurately. However, you must know that each project and task comes with a distinct set of inherent challenges. You should meticulously analyze the pipeline projects and calculate how many of the proposed bids will be converted into revenue. Additionally, you must assess whether any projects are at risk of ending abruptly; you may want to use different standards when forecasting revenue for at-risk projects.
4. Predict and Measure Variability
When you forecast revenue for a shorter period, such as a month, it stays close to the actual revenue; The actual revenue will probably deviate from the estimate by approximately 5% or so. However, when you try forecasting for a longer duration, your predictions will likely vary quite a lot from actuals. So, you need to account for this type of variability and build it into your forecasting equations. By predicting and measuring variability at the outset, your revenue forecasts will be much more accurate.
5. Don’t Confuse Revenue With Cash Flow
Many professional services organizations emphasize cash flow and ignore revenue forecasting. Although cash forecasting is important, a blind eye to revenue forecasting can hurt your business down the line. Be aware that cash forecasts mainly consider financial activities, such as invoicing or collections. On the other hand, revenue forecasting revolves around operational activities, such as project staffing. Cash forecasting can help you analyze how much you can earn, but it won’t allow you to assess whether or not your organization has the right mix of people to deliver the work.
How to Choose a Perfect Mix of Revenue Forecasting Methods
If your organization experiences any of the mistakes discussed above, it implies that you need a new mix of revenue forecasting methodologies. You may need a more sophisticated tool for aggregating and disseminating information gathered on schedules or Excel sheets. That’s where professional services automation (PSA) software can help in revenue forecasting efforts.
A PSA platform can help organizations better predict their work, which can lead to more accurate revenue forecasting. A PSA platform is a flexible system that can help you model revenue contracts and quickly reconcile revenue with contracts, WIP, and billing. Some PSA solutions also come with an in-built billing and invoicing platform, which paves the way for effective revenue recognition and forecasting.