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In an environment where labor costs account for about 60% of institutional spending, colleges and universities must have tools and processes to precisely and continuously monitor these expenses.[i] Many institutions rely on annual forecasting, a once-a-year projection that’s often outdated by the time it’s finalized. In-year labor forecasting offers a more agile and accurate approach that adjusts projections based on current conditions and empowers leaders to act on timely insights.

The University of South Florida (USF), a large research institution with 60,000 students and a $3 billion budget, struggled with creating consistent, accurate forecasts across diverse departments and funding sources. University leaders collaborated with Strata Decision Technology to design and implement a new in-year labor forecasting capability within the Axiom® Budgeting and Forecasting solution that provides greater accuracy, transparency, and control over labor expenditures throughout the fiscal year. This article provides best practices for in-year labor forecasting based on USF’s implementation and current planning model.

The need for in-year forecasting at USF
 

Prior to in-year forecasting, USF’s once-a-year forecasting process was time-consuming and tedious, said Kevin Toso, the university’s Budget Director. Forecasting was conducted in February each year, and directors had about a month to pull data and provide projections — but there was little consistency in how those projections were generated. “The level of quality varied significantly,” Toso said. “It was really all over the place.”

With Axiom’s in-year forecasting functionality, the USF budget team now leverages a built-in spread method that distributes projected expenses for each month throughout the year, based on the latest salary and benefits information. “The way we set up the spread method in actuals, the budget directors no longer have to build the whole thing from scratch — those building blocks are already there,” Toso explained.

The solution leverages Power BI to pull all the data together and identify any variances. The budget team then works through any anomalies before the forecast goes to senior leaders who prioritize funding allocations. “We don’t want to go into that room and talk about why the numbers are what they are,” Toso said. “We need to go into that room and say, ‘These are the numbers. What do you want to do as far as prioritizations?’”

The following five best practices can help budget leaders successfully integrate in-year forecasting at their organizations.

Best practice No. 1: Forecast at the position level

Forecasting labor by individual positions, rather than account-level totals, improves accuracy and visibility. Forecasting at this level allows budget officers to reflect real-time changes like vacancies, new hires, terminations, and salary adjustments.

Visibility into position-level data also helps institutions manage and maximize state allocations tied to labor roles. Leaders can forecast budgeted positions throughout the year, and input changes as they arise to avoid stale data. They also can shift funding from one position to another as needed to avoid leaving allocated dollars on the table.

“It provides you with a much more accurate forecast moving forward,” Toso said.

Best practice No. 2: Input monthly

For each quarterly forecasting cycle, USF updates actuals on a monthly basis. Monthly inputs provide planners with the granularity they need to track and refine projections, while also maintaining a manageable process.

This approach strikes a balance between detail and efficiency, Toso explained. It provides sufficient data to identify trends without overwhelming users or administrators with the high level of detail that would be involved in more frequent inputs. The result is an up-to-date, single source of truth that can be shared with department leaders throughout the year to drive more informed decision-making.

Best practice No. 3: Regularly incorporate actuals

Having the ability to routinely input actuals allows finance leaders to eliminate guesswork and ensure their plan files reflect the latest data. It allows them to slowly build two versions of the budget, original versus adjusted.

At USF, nightly imports pull in general ledger transactions, labor rosters, and labor distributions. Incorporating these actuals reduces the risk of material discrepancies later in the year. This is especially critical for labor, where missing or outdated information can have compounding effects.

The ability to incorporate actuals on demand is one of the most valuable features of the Axiom in-year forecasting tool, Toso said. “We actually bring in any budget adjustments on a nightly basis so department leaders can compare their projected expenditures versus their actual budget,” he explained. “It’s important to be able to incorporate those actuals within the tool to see how things are going throughout the year. It allows you to submit an accurate forecast for the remainder of the year based on actuals.”

Best practice No. 4: Allow flexibility in spread methods

Different positions — such as nine-month faculty, annual staff, and summer appointments — require different salary spread methods. USF’s Axiom in-year labor forecasting system[CK1]  supports a wide range of spread profiles, including nine-month spreads or different summer periods (summer A/B/C).

This flexibility allows users to align projected salary expenditures with the expected payout timing. Rather than reprogramming positions along with actuals, users can select the spread method that best fits the timing of future costs, even for vacant positions with uncertain hiring dates.

Best practice No. 5: Account for vacant positions

Vacant positions still represent future costs, because such positions presumably will be filled. Recognizing this, USF allows users to hold funds on vacant lines and distribute them based on anticipated hiring windows. This approach enables more realistic planning and better communication with leadership about unused but earmarked labor dollars.

USF allows forecasters to assign distributions to future months — even if a role is currently unfilled — if the timeline aligns with hiring expectations. “There are certain positions people hold money for that they know they’re going to spend,” said Toso. “They just don’t know when they’re going to spend it.”

Providing a centralized source for all labor forecasting

Labor costs should be centralized in a single forecasting module to ensure consistency, avoid double-counting, and provide a clear summary view of projected expenses. This helps avoid confusion for leaders who may be unsure where to forecast specific labor accounts, and who question whether they should be included in the dedicated labor module or in the broader operating forecast plan file.

University leaders should keep all labor-related forecasting — salaries, stipends, student workers, and pooled positions — in the dedicated labor forecasting tool. This ensures a complete and accurate summary view of total labor expense and reduces errors from fragmented forecasting practices.

As higher education institutions navigate tighter budgets, unpredictable funding cycles, and increasing demand for transparency, in-year labor forecasting enables leaders to stay proactive. By implementing a position-level, actuals-driven forecasting model, institutions like USF can transform forecasting from a once-a-year exercise into a dynamic, reliable financial management tool.

To learn more about the Axiom® Suite for Higher Education, visit Strata’s website or schedule a demo.

[i] Bell, M.: “Breaking Down Higher Education’s Financial Frontier.” EAB Blog, March 28, 2025.

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