No headcount forecast is complete without accurate data around payroll taxes, which represent more than 7% of direct employee expenditures.
Since the IRS sets the rates, some aspects of payroll tax rates are predictable – but other variables have significantly increased the complexity of payroll taxes. State and local taxes vary by jurisdiction. Remote work has significantly increased the variables involved in assessing and forecasting payroll expenditures as part of headcount forecasting as well.
Realtime, data-based headcount forecasting is a big part of why I founded Precanto, an AI/ML headcount forecasting platform. Accurate headcount data is the foundation upon which FP&A leaders can finally access realtime readouts of their expenditures, and forecast more accurately.
In this series, I examine some of the key data that powers headcount forecasting, and how the intricacies of this data can contribute to missed forecasts and poor financial planning.
Beyond paper tallies, missing the payroll forecast can hurt companies competitively, as they’re forced to keep cash in the bank to buffer any forecast issues instead of investing ahead in other strategic initiatives.
For example, one of our customers landed their overall personnel expense forecast within 2% of their forecasted expense – but over-forecasted their employer payroll tax forecast by $20 million. That’s $20 million they could have spent elsewhere, and that’s what Precanto helps illuminate.
What are employer payroll taxes?
Employer payroll taxes are mandatory contributions required by the Internal Revenue Service and other agencies that businesses must make on behalf of their employees.
These taxes, as set by federal, state, and sometimes local governments, are calculated based on employee wages and salaries. Key components often include Social Security and Medicare taxes, commonly known as FICA taxes, as well as federal and state unemployment taxes.
Employers bear the cost of contributions tied to the Federal Unemployment Tax Act (FUTA) and State Unemployment Tax Act (SUTA), which fund unemployment compensation programs for individuals who lose their jobs.
Payroll taxes tend to steadily increase year over year as salaries and companies grow. Even with the pandemic-related downturn in 2020, payroll tax revenue paid to the U.S. government stagnated, but it didn’t drop. It remained a key expenditure, despite revenue constriction.
How employer payroll taxes create forecasting obstacles?
Depending on the size of the company, total employer payroll taxes can tally in the hundreds of millions of dollars annually. Inaccurately forecasting such a large expense can cause companies to miss their profit targets.
Employer payroll tax rates and thresholds are different by country and state. Take New York City, for example. Employers must navigate city and county regulations, as well as state and federal taxes. The urban metro area includes several states, all within daily commuting distance of Manhattan offices. You don’t need to log a $100 million ARR to have employees living in New Jersey, Connecticut, and New York, and juggling those additional jurisdictions for payroll taxation purposes.
Extrapolate that out to the remote workplace of today, with Silicon Valley headquarters overseeing employees in numerous states and overseas.
Meanwhile, it’s not just the government jurisdictions that inform payroll forecasting. The taxes are assessed based on employee earnings, which can shift drastically over the course of a year and in ways not fully captured in original budgets.
The variables include:
- Salaries
- Bonuses
- Expenses
- Commissions
- Promotions
- RSU vesting schedules
Headcount pulled forward or pushed back also impacts payroll tax expenditures. If recruiting moves faster than expected and hires 90% against a quarterly plan at the start of a quarter, that could be an extra two months or more of payroll taxes per employee the company pays.
And someone has to track all of those data points.
Precanto: Payroll tax forecasting for modern enterprises
Most businesses, from enterprise down to nascent startups, leverage spreadsheets and custom formulas to ingest all the headcount forecasting data, including employer payroll taxes.
The FP&A team needs to source the data, which can lie across different departments and in different tech stack tools. Some of the information may be manually updated, which carries an added risk of human error. Finance leaders might create several models, and then adjust based on departmental feedback, which can lead to delayed forecasts and reports – a ripple effect through the strategic financial decision-making process.
Precanto was created by FP&A leaders who felt this pain acutely, and wanted to build a better way to forecast employer payroll taxes.
Precanto’s employer payroll tax engine does not depend on FP&A’s inputted assumptions. Instead, it factors in all of the complexity that is inherent with corporate employee calculations to output accurate employer payroll taxes per employee and open requisition or future hires. Tax rates get consumed by Precanto’s prediction engine – no manual formulas required.
Finance leaders can drill down to forecasts sorted by department, location, seniority, and, yes, payroll tax estimations – in real time, at the click of a button, with an accuracy based on tech stack integrations. Errors become less frequent; forecasts become far more accurate.
Instead of creating and manipulating spreadsheets for days on end, finance leaders have weeks of their time back each quarter to plan strategically.
No other platform helps customers with in-depth employer payroll tax predictions across all departments and locations for current and outer quarters and years.
Book a demo now.
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