Supporting Quality of Earnings During an M&A Transaction Through HR Data and Workforce Analytics

Case Study

Challenge

During due diligence, the buyer’s financial advisors requested a Quality of Earnings (QoE) analysis to validate the sustainability and normalization of Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA). While the company’s finance team had strong financial reporting, there was limited confidence in how workforce‑related costs were being reflected in run‑rate earnings, specifically:

Are payroll and benefits costs normalized?
Are bonuses, commissions, and variable pay recurring or one‑time?
How much EBITDA volatility is driven by hiring, turnover, or wage inflation?
Are there non‑recurring people costs that should be added back?

Because wages represented the company’s largest expense category, incomplete or inaccurate people data created risk of valuation erosion, prolonged diligence, or unfavorable purchase price adjustments.

The company needed human resources and analytics to support the deal by translating HR system data into diligence‑ready workforce metrics.

What Is a Quality of Earnings (QoE)?

A Quality of Earnings analysis evaluates whether a company’s reported earnings accurately reflect sustainable, ongoing performance. In M&A, QoE is used to:

Normalize EBITDA by removing non‑recurring, non‑operational, or one‑time items
Assess earnings volatility and predictability
Validate assumptions used in valuation multiples
Surface risks that may impact post‑close performance

From a people perspective, QoE focuses on ensuring that compensation, benefits, and workforce structure accurately represent future-state operating costs.

By structuring HR data in a financial context, workforce costs shifted from a perceived deal risk to a value‑supporting asset.

Our Approach: Workforce Data as a Financial Asset

Step 1: Define Buyer‑Relevant People Metrics

Working with the finance team, we identified HR data points required for QoE, including:

Headcount by month (actual vs. budget)
Fully loaded compensation (base, bonus, commissions, overtime)
Employer payroll taxes
Benefits costs (medical, retirement, stipends)
Hiring and termination trends - The majority of the issue with the reporting was the turnover, which was a major concern of the deal.
One‑time or discretionary compensation
Contractor vs. employee mix

Step 2: Extracting QoE‑Ready Data from UKG

Using UKG as the system of record, we pulled historical and current‑state data with audit‑level detail.

Key UKG Modules Utilized

Core HR: Employee demographics, status changes, termination dates
Payroll: Gross wages, overtime, bonuses, commissions, employer taxes
Benefits Administration: Employer benefit contributions by plan
Compensation Management: Base vs. variable pay
Time & Attendance (where applicable): Overtime and utilization

Typical UKG Reports Pulled

Employee census by month (last 36 months)
Payroll register summaries by earning code
Employer tax and benefits cost reports
New hire and termination reports
Job/department cost allocations

Data was exported at the employee‑level and aggregated monthly, aligning exactly with the financial QoE period under review.

Step 3: Normalization & Analytics

Once extracted, we transformed UKG data into diligence‑ready insights:

Key Adjustments Identified

Non‑recurring bonus payouts tied to prior‑year performance and transaction retention
Temporary contractor costs used to backfill turnover spikes
Founder‑related compensation above market benchmarks
Seasonal overtime volatility not reflective of steady‑state operations

Deliverables Provided

Reconciled workforce cost bridge to the general ledger
Normalized run‑rate headcount and compensation model
EBITDA add‑back schedule tied directly to HR data
Headcount and cost trend analysis supporting buyer assumptions

Outcome

Results for the Seller

Reduced buyer questions related to payroll and benefits costs
Faster diligence cycle with fewer follow‑ups
Higher confidence in normalized EBITDA
Stronger defense of valuation assumptions

Results for the Buyer

Clear view of post‑close workforce cost structure
Understanding of retention and attrition risk
Reduced risk of post‑close earnings surprises

Strategic Impact

Because HR data was structured, validated, and presented in a financial context, workforce costs shifted from a perceived risk to a value‑supporting asset in the transaction.

Why This Matters

In middle‑market M&A, people costs often represent 50–70% of operating expenses, yet HR data is frequently underutilized in QoE analyses. This case demonstrates how a human resources technology company can bridge HR systems like UKG with financial diligence requirements, enabling:

Stronger earnings credibility
Smoother transactions
Better outcomes for both buyers and sellers

Frequently Asked Questions

What is a Quality of Earnings (QoE) analysis in an M&A transaction?

A Quality of Earnings (QoE) analysis evaluates whether reported earnings accurately reflect a company’s sustainable, ongoing performance. In M&A, QoE is used to normalize EBITDA, identify non‑recurring items, assess earnings volatility, and validate valuation assumptions prior to closing.

Why is HR and workforce data critical to Quality of Earnings?

Workforce costs often represent 50–70% of operating expenses in middle‑market companies. Without accurate HR data, payroll, benefits, bonuses, and turnover‑related costs may be misrepresented in run‑rate earnings—creating valuation risk and prolonged diligence.

What workforce costs typically impact EBITDA normalization?

Common people‑related adjustments include:

• Non‑recurring bonuses or retention payments

• Variable compensation tied to one‑time performance events

• Temporary contractor costs used to offset turnover

• Founder or executive compensation above market norms

• Seasonal overtime not indicative of steady‑state operations

How did HR data support the buyer’s QoE analysis in this case?

HR data was extracted, validated, and aligned directly with the financial QoE period, providing transparency into headcount trends, fully loaded compensation, benefits costs, and turnover. This allowed buyer advisors to confidently assess earnings sustainability and post‑close workforce cost structure.

What role did UKG Pro play in the analysis?

UKG Pro served as the system of record for workforce data. Employee‑level data from UKG Core HR, Payroll, Benefits, Compensation, and Time & Attendance modules was aggregated monthly and reconciled to the general ledger to ensure audit‑ready accuracy.

How does workforce turnover affect Quality of Earnings?

High or volatile turnover can drive hidden costs such as recruiting expenses, temporary labor, overtime, and lower productivity. In this case, turnover trends were a major concern—and detailed HR analytics helped distinguish temporary volatility from sustainable operating conditions.

What benefits did the seller gain from integrating HR data into QoE?

The seller experienced:

• Fewer buyer questions related to payroll and benefits

• Faster diligence timelines

• Greater confidence in normalized EBITDA

• Stronger support for valuation assumptions

How did this approach benefit the buyer post‑close?

The buyer gained a clear understanding of future‑state workforce costs, retention risk, and compensation structure—reducing the risk of post‑close earnings surprises and improving integration planning.

Is this approach applicable to other M&A transactions?

Yes. This HR‑driven QoE approach is especially valuable in middle‑market acquisitions where people costs are significant and HR systems data is underutilized. It can be applied across industries and HR platforms, including UKG, Workday, ADP, and others.

When should HR data be integrated into M&A diligence?

Ideally, HR analytics should be introduced during financial due diligence, often pre‑LOI or early confirmatory diligence, so workforce costs are accurately reflected before valuation and purchase price negotiations are finalized.

How can InteGreat Solutions support a Quality of Earnings analysis?

InteGreat helps organizations transform HR system data into financial‑ready insights by aligning workforce analytics with QoE, diligence, and valuation requirements, bridging the gap between HR, finance, and transaction advisory teams.

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