Linking Revenue Projections to Staffing Plans

In today’s fast-paced AEC industry, the ability to predict staffing needs has become just as critical as the ability to deliver quality design. Yet many structural engineering firms continue to staff reactively by responding to project pressures or client demands reactively rather than planning proactively based on expected workload. This approach leads to operational inefficiencies, strained teams, and missed opportunities for growth.

As firms seek to scale responsibly, improve retention, and maintain high technical standards, it’s essential to align staffing decisions with future workload expectations. That alignment starts with accurate, actionable revenue forecasting.

Most firms track utilization, billing, and backlog. These metrics are useful for understanding what has happened. But staffing decisions are about the future. Forward-looking forecasting requires visibility into what work is likely to come in, when it might start, and how much effort it will require from staff across disciplines.

This is easier said than done. Proposals vary in scope and certainty, start dates and milestones are often fluid, and fee structures don’t always translate cleanly into staffing needs. Yet failing to build this kind of model leads to the all-too-familiar cycles of feast and famine, where firms alternate between overworked staff and underutilized teams.

Available industry data highlights this disconnect. Fewer than half of firms say they are confident in their ability to accurately forecast project costs and staffing needs. In many cases, project managers lack access to real-time project data, making it difficult to anticipate workload or inform hiring decisions. Meanwhile, staff shortages and retention remain among the top concerns reported by firm leaders, underscoring the need for a more predictive and integrated approach.

To improve alignment between current and future staffing needs, firms must develop systems that connect business development, project planning, and resource management. A basic framework includes three core elements:

Opportunity Tracking:
The starting point is a clear view of the active proposal pipeline. Opportunities should be categorized by project type, client sector, contract value, and anticipated start date. This allows firms to see not just how much work is in pursuit, but also how that work breaks down across meaningful business dimensions.

Probability and Timing:
Not every opportunity will convert into revenue, and not every project starts immediately. Firms that analyze historical hit rates—by client type, market sector, or contract size—can assign realistic probabilities to each pursuit. They can also calculate the average lag between contract signing and the start of billable work.

Combining these inputs allows firms to generate a weighted and time-shifted projection of future work. For example, a high-probability $25,000 feasibility study with a short activation lag may be weighted more heavily than a lower-probability public-sector project that could take many months to get started.

Factored Revenue Forecasting:
By applying win probabilities and activation lags, firms can produce a factored revenue forecast that distributes expected workload across future months. This is far more actionable than a flat backlog figure. It offers insight into not just what’s under contract—but what is most likely to impact staffing into the future.

Once a firm has created a forecasted view of incoming work, the next step is converting that forecast into staffing needs. This can be done by applying your firm’s work rates (hours worked per week) and production rates (revenue generated per hour) to the revenue forecasts.

Firms can use this information to:

The key is not to seek perfection in the forecast, but to establish a structured, recurring process for refining it. Regular updates based on new proposals, contract status, and project shifts help keep forecasts relevant and responsive.

While the value of data in forecasting is clear, it’s equally important to recognize its limits. No formula can fully account for the nuances of a longstanding client relationship, the subtle cues of a shifting market, or the political dynamics of a public procurement process. For this reason, experienced firm leaders and project managers remain essential to interpreting data, adjusting assumptions, and spotting patterns that are invisible to automated systems.

In practice, the best forecasting models combine quantitative analysis with professional judgment. A proposal may appear low-probability on paper but be all but guaranteed due to a trusted client relationship. Leadership intuition, grounded in years of experience, provides critical context.

Rather than replace intuition, forecasting tools should enhance decision-making by providing a clearer picture—while still leaving room for insight that comes from working in the field, understanding the market, and building client trust over time.

Current industry data shows that firms maintain, on average, nearly nine months of backlog. However, backlog alone is a poor predictor of staffing needs unless it accounts for actual start dates and resource demands. A large project with a 12-month design window may have minimal short-term impact on staffing, while a cluster of smaller projects could create immediate needs.

Additionally, only a minority of firms report having strong alignment between their business development and project delivery teams. This lack of coordination makes it harder to plan for resource needs in advance. When PMs are not involved in the pursuit pipeline—or when BD staff are unaware of current capacity constraints—forecasts become disconnected from operational reality.

Despite the growing availability of resource planning tools, many firms still rely on informal processes or siloed systems. Firms that integrate even basic forecasting—through simple spreadsheets or custom dashboards—report stronger confidence in hiring decisions and better control over workload planning.

Firms of any size can begin improving their forecasting process with the following actions:

Implementing a forecasting model doesn’t require perfect data, expensive software, or a dedicated analyst. What it does require is a shift in mindset. Relying solely on experience and intuition to anticipate when work will arrive often puts firms in a reactive position—scrambling to respond rather than preparing in advance. A structured forecasting model helps move the approach from reacting to work toward proactively planning for it.

Staffing is not just a financial consideration; it is a strategic function that shapes culture, quality, and client satisfaction. When firms align staffing decisions with predicted workload, they are better positioned to retain talent, manage risk, and grow responsibly.

The ability to forecast revenue—and directly connect that forecast to resource planning—is no longer a “nice to have.” It is a foundational business practice for firms that want to thrive in a competitive environment. With the right approach, staffing can shift from a reactive function to a proactive strength—one that combines data with the judgment and intuition that have long guided the profession.

To support firms in this effort, CASE is introducing a new resource: Tool 3-2 Staffing and Revenue Projection. This tool provides a practical framework to link projected revenue with staffing capacity, helping firm leaders turn forecasts into actionable strategies. It is one more way CASE is working to equip firms with tools to navigate today’s challenges and plan confidently for the future. ■

About CASE

The Coalition of American Structural Engineers (CASE) represents more than 200 firms committed to advancing a fair, profitable, and resilient structural engineering industry. CASE helps firms strengthen their businesses by sharing best practices to reduce risk and improve profitability.