Payroll is usually your biggest cost—and your most strategic lever.
That’s why salary forecasting matters. Not as a side task, but as a core input to your operating plan. It’s how you control burn, plan cash, and understand when you can afford to grow.
And the stakes are high: nearly 70% of startup budgets go to payroll and benefits.
Miss a hiring milestone or underestimate costs, and the entire model falls apart.
Salary forecasting isn’t about being conservative. It’s about being clear. When you understand total compensation, timing, and hiring trends, you make better calls before problems even show up in your financials.
Here are the ten most important salary forecasting metrics to track, and why each one matters.
What is salary forecasting?
Salary forecasting means projecting payroll costs over time—across base comp, equity, benefits, taxes, and bonuses—tied to:
- Expected headcount changes
- Role-level salary bands
- Timing of hires and internal moves
It answers questions like:
- How much will your team cost next quarter?
- Can we afford to hire two AEs now, or Q3?
- What happens to runway if we raise salaries by 5% next year?
It’s not just about base pay. True salary forecasting includes everything you spend to employ someone, and what that means for your financial model.
Why salary forecasting matters more for startups and SMBs
Larger companies can absorb planning misses. Startups can’t.
Fast hiring, rising salaries, and lean teams mean even small forecasting mistakes create ripple effects. You can’t afford budget gaps or late surprises. And most early-stage companies don’t have a full HR stack.
That’s why finance ends up owning salary forecasting, and why having the right metrics matters.
Tools like Runway help finance and ops align in real time. You don’t need HR software to model compensation. You need visibility, logic, and speed.
The top 10 salary forecasting metrics
These ten metrics help you forecast more accurately, model smarter, and plan growth with confidence.
1. Headcount forecast vs actuals
How well are you sticking to the hiring plan? This metric shows where expectations and execution diverge. Do you hire as fast as you plan, or does the org chart lag behind?
Calculate it: Subtract actual headcount from forecasted headcount each month or quarter. If you planned for 50 employees but ended at 45, that’s a variance of -5 (or -10%).
Use it to: Adjust future forecasts based on hiring velocity.
Example: If you planned to hire 10 people last quarter and hired 8, your variance is -20%. Adjust future run rate and recruiting assumptions accordingly.
2. Average salary per role or department
This shows what you actually pay each job group or team. You’ll see how average comp shifts over time, especially when roles change or seniority increases.
Calculate it: Divide total salaries for a team by headcount. Let's say you have 10 engineers earning a total of $1.2M. That’s an average of $120,000 average salary per engineer
Use it to: Detect salary inflation, spot team-level comp creep, and revise banding as needed.
Example: If your engineering team grows more senior, average salary may rise faster than headcount. BambooHR benchmarking saw tech salaries jump 5% from 2024 to 2025, while finance moved 3.2% higher.
3. Fully loaded labor cost
This is your actual cost per employee: salary + benefits + taxes + equity + overhead.
Calculate it: For example, with a $60,000 salary, you may have $6,000 taxes (10%), $10,000 benefits (16.7%) and $900 insurance (1.5%). That’s a total cost of $76,900—almost 30% more than base pay.
Use it to: See what’s really driving burn. Plan merit pools and benefit cost changes. This metric is particularly important to measure correctly as benefits alone can add 20-30% over the base pay.
4. Attrition or turnover rate
This is the percentage of employees who leave in a given period. US voluntary turnover averages 13%, but ranges by industry—retail can be as high as 26.7%, insurance just 8.2%.
High attrition means you’re always backfilling roles—which means recruiting, onboarding, cover, and lost productivity costs. This can add up quick, as replacing an employee can cost 75% to 200% of their salary.
Calculate it: (Leavers in period ÷ average headcount) × 100. If 5 people leave a 50-person company in a quarter, the attrition rate is 10%.
Use it to: Budget replacement hiring and retention initiatives. If you expect a 15% annual turnover, add that headcount replacement spend across the year.
5. Time to fill or hire (hiring lag)
This tracks the days from job post to new hire. The US average? About 36 days but varies by level—executives, directors, and entry-roles are all different.
Longer hiring lags slow product launches, drive up project costs, and shake up your forecasts. Crucially, plan when new salaries actually kick in. If you take 45 days to hire a position, adjust your cash flow and quarterly projections to reflect this.
Calculate it: Count the number of days from posting role to filling it (including screening, interviewing, hiring committees and notice periods).
Use it to: Forecast when new salaries actually hit the books, not when a role opens.
6. Ramp (or onboarding) time to full productivity
New hires need time to get the background knowledge and become performant in their new role. This metric tells you how long it takes new hires to hit their stride. Studies show that new hires bring just 25% productivity in month one. It rises by 25% each month after.
Calculate it: Measure the number of days from start date to the point the hire consistently meets role-level productivity (e.g., 100% of target output) and average it across new hires for the period.
There are tangible ways you can decrease this metric—companies that standardize onboarding see 82% better retention and double their speed to productivity.
Use it to: Adjust revenue and productivity forecasts for new roles. You pay full salaries, but output starts lower. Adjust your models for reality, not best-case scenarios.
7. Offer acceptance rate, and hiring yield
This is the percentage of extended job offers that get a yes. The US average is at 69.3% acceptance, so 3 out of 10 say no.
If candidates turn down offers, you need more prospects and spend more to fill the job. Low rates mean extra recruiting work and costs.
Calculate it: Acceptance rate = offers accepted ÷ offers extended. Hiring yield = hires ÷ candidates at each funnel stage (e.g., interviews, onsites, offers).
Use it to: Forecast recruiting costs and time to hire. Low rates mean more sourcing, interviews, and delays.
8. Vacancy rate (open requisitions vs. filled roles)
This metric compares job postings to filled seats. High rates mean teams feel stretched and goals get delayed.
Calculate it: Divide open roles by total roles, then multiply by 100. Example: 10 open out of 60 total = 16.7%.
Use it to: Forecast capacity and delivery risk. Unfilled seats mean unfulfilled work, and unused budget. And a persistently high vacancy rate signals hiring challenges or unrealistic plans.
9. Promotion, internal mobility and salary progression rate
This tracks who moves up, moves sideways, or gets pay bumps. High-growth companies promote more, so this can hit your budget fast.
If 20% get promoted in a year, plan their new salaries now, not later. Failing to do this leads to short budgets and tough choices. Make sure to work with HR to align promotion calendars, confirm pay bands, and lock in effective dates so the budget reflects reality.
Calculate it: Multiply last year’s promotion rate by your eligible headcount, then apply the average promotion increase to those roles and prorate by effective date. Roll in lateral moves with pay changes and update your salary run rate and merit pool accordingly.
Use it to: Model budget impact of internal mobility. Promotions can shift comp bands by 10–25%. Build this into salary forecasting.
10. Budgeted vs. actual salary, and hiring cost variance
The most important retrospective metric: did your forecast match what actually happened?
This one spots gaps in accuracy by comparing what you planned to spend and what you actually paid, across salaries, benefits, signing bonuses, and recruiting fees. Track it monthly and year-to-date so you see trends early and adjust before they snowball.
A higher actual than budget can signal faster hiring, richer offers, or unplanned backfills. Underspend can mean slower hiring or open roles dragging out. Use variance analysis to pinpoint the drivers and tighten future forecasts.
- Focus on total compensation, not just base pay
- Break variance into price (pay rates), volume (headcount), and mix (role levels and locations)
- Tie insights to actions: adjust hiring plans, recalibrate salary bands, or shift timing
Calculate it: Variance ($) = actual spend − budgeted spend. Variance (%) = (actual − budget) ÷ budget. Segment by team or role to see where it’s moving.
Use it to: Tighten future salary forecasting logic. Understand whether variance came from timing, rate, or mix.
Salary forecasting is a strategic lever (not just a line item)
The most accurate salary forecasts come from connecting HR data to finance logic.
With Runway, you can:
- Sync headcount and cost forecasts with revenue models
- Model scenarios with promotions, hiring delays, or pay adjustments
- Understand burn, runway, and margin impact in real time
- Replace messy spreadsheet models with one source of truth
Runway makes complex planning simple as you grow. You could boost forecasting accuracy by 800%, or replace 23 spreadsheets with one tool—all in one system.
Own your salary forecasting
Consistency beats complexity. If you track these ten salary forecasting metrics in one place, and use them to update your model frequently, your plans get sharper and your team gets smarter.
Runway connects to your HRIS, integrates headcount drivers, and updates forecasts as soon as things change. That’s how you move from reactive to proactive. From guesswork to planning. And from static budgets to strategic salary forecasting.
See how Runway can help you forecast with confidence, and plan smarter.