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Evaluate Pay-for-Performance Alignment Through Executive Compensation and Peer Benchmarking

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·28 min read
Data in Action

Executive compensation is often discussed through a single headline number. A large pay package may attract attention, while a year-over-year increase can quickly be interpreted as evidence of weak governance. But total compensation alone does not show whether pay changed in line with company performance, executive responsibility, or peer-market norms.

The more useful question is whether compensation growth is supported by operating results. Revenue growth can indicate business expansion, operating-income growth can show whether that expansion translated into stronger profitability, and ROIC can help assess whether management generated stronger returns on invested capital. Viewed together, these measures provide a better basis for evaluating pay-for-performance alignment than compensation alone.

Peer context also matters. A compensation package that appears high in absolute terms may be more understandable when the company is materially larger than comparable businesses or when peer executives receive similar pay. Conversely, compensation may require closer review when it rises faster than both company performance and peer benchmarks without clear size, role, or incentive-design context.

Even then, the analysis should remain neutral. A high compensation figure does not automatically mean an executive is overpaid, and weak financial performance in one year does not prove that the compensation structure is misaligned. Long-term equity awards, CEO transitions, retention grants, acquisitions, restructuring, and differences in fiscal timing can all affect the comparison.

This article uses the FMP MCP server through Claude to evaluate pay-for-performance alignment across Coca-Cola, PepsiCo, Mondelez International, and Colgate-Palmolive. The analysis compares CEO compensation trends with revenue growth, operating-income growth, ROIC, peer compensation medians, and company-size context across the latest three completed fiscal years.

The objective is to identify whether compensation appears aligned with performance, partially supported, structurally decoupled, or in need of analyst review. The result is not a shareholder-voting recommendation or a conclusion about executive quality. It is a structured governance-review framework for identifying cases where the relationship between pay, performance, and peer context deserves closer examination.

Key Takeaways

  • Executive compensation should be assessed against operating performance and capital efficiency rather than viewed as a standalone figure.
  • Revenue growth, operating-income growth, and ROIC provide complementary evidence of whether compensation changes are supported by company results.
  • Peer compensation becomes more meaningful when company size is considered alongside the pay comparison.
  • Strong performance does not automatically justify every increase in compensation, particularly when one-time or multi-year equity awards distort the annual change.
  • CEO transitions, partial-year service, retention grants, and severance payments can reduce comparability and require analyst review.
  • The final classification is a governance-review signal, not a judgment about whether an executive is overpaid or a recommendation on shareholder voting.

Turning Compensation And Financial Data Into Alignment Evidence

Executive pay becomes more meaningful when compensation trends are evaluated alongside operating performance, capital efficiency, company scale, and peer norms. The framework uses a fixed four-company peer group and compares the chief executive officer or principal executive officer across the latest three completed fiscal years.

The analysis uses annual data only. Quarterly and trailing-twelve-month values are excluded so that compensation periods and financial results remain as comparable as possible.

A fixed peer group improves reproducibility, but it does not make the comparison perfect. Differences in business mix, geography, revenue scale, brand strength, operating complexity, and executive responsibility can still affect compensation levels. That is why the framework treats the output as a review signal, not as a final governance conclusion.

Keeping The Executive Role Consistent

Executive compensation records can include several senior officers, former executives, and partial-year appointments. The comparison should therefore use only the CEO or principal executive officer for each company.

The same executive should be followed across the three-year period whenever possible. A CEO transition, interim appointment, sign-on award, severance payment, or partial-year service period can materially distort the comparison.

When executive continuity is unclear, the result should be marked Review required rather than combining compensation records from different roles or individuals. Compensation data is most useful for governance analysis when the executive role, fiscal year, and reporting basis are consistent.

Measuring Compensation Change

The latest total reported compensation is compared with the previous comparable annual record:

Year-over-year compensation change = latest total compensation ÷ prior-year total compensation − 1

Total compensation is used because it captures the full reported compensation package, including salary, bonus, stock awards, option awards, non-equity incentive compensation, change in pension value and above-market earnings on nonqualified deferred compensation, and other reported compensation. The analysis uses the reported total compensation figure rather than reconstructing the total from individual components, since some components may be reported differently across companies or years.

The complete three-year record should still remain visible. A sharp increase in the latest year may reflect a one-time equity grant, a multi-year award, or a retention package rather than a permanent change in annual compensation. Analysts should review the components before interpreting compensation growth as a recurring pay trend.

Measuring Performance Support

Compensation growth is evaluated against three operating indicators:

  • revenue growth
  • operating-income growth
  • three-year ROIC trend

Revenue growth shows whether the business expanded, while operating-income growth indicates whether that expansion translated into stronger operating profitability. ROIC adds a capital-efficiency measure that can reveal whether management generated stronger returns from the capital employed in the business.

The latest annual growth rates are calculated as:

Revenue growth = latest annual revenue ÷ prior-year annual revenue − 1

Operating-income growth = latest annual operating income ÷ prior-year annual operating income − 1

Operating-income growth should also be reviewed for base effects and material non-recurring items. When operating income changes sharply while revenue changes much less, the numerical growth rate should remain visible, but the indicator should be treated as provisional until the prior-year operating-income base is confirmed to be comparable. If a material charge, remeasurement, restructuring item, or other non-recurring effect distorts the comparison, the operating-income indicator should not be counted as confirmed performance support until analyst review is completed.

The ROIC trend compares the latest annual value with the earliest value in the three-year period:

Three-year ROIC change = latest annual ROIC − earliest annual ROIC

ROIC is classified as:

ROIC Change

Classification

Increase greater than 0.50 percentage points

Positive

Change between -0.50 and +0.50 percentage points

Stable

Decline greater than 0.50 percentage points

Negative

The overall performance-support classification follows a fixed rule:

Performance Evidence

Classification

At least two indicators are positive

Strong support

At least two indicators are negative

Weak support

Any other combination

Mixed support

These rules prevent one favorable metric from automatically outweighing deterioration elsewhere. They also keep the review focused on the relationship among growth, profitability, and capital efficiency rather than on a single headline result.

Adding Peer Compensation Context

Absolute compensation is difficult to interpret without a benchmark. The analysis compares each CEO's latest compensation with a leave-one-out peer median.

For each company, the benchmark is calculated using the other three companies:

Pay-to-peer ratio = latest CEO compensation ÷ median latest CEO compensation of the other three peers

The peer context is classified as:

Pay-To-Peer Ratio

Peer Context

Below 0.75x

Below peer range

0.75x to 1.25x

Within peer range

Above 1.25x

Above peer range

Using a leave-one-out median prevents the company's own compensation from influencing its benchmark. The peer set still needs judgment. A reproducible benchmark is useful, but comparable peers should still be reviewed for business model, scale, geography, and operating complexity.

Adjusting For Company Size

A company with substantially greater operating scale may reasonably support a higher compensation level than smaller peers. Latest annual revenue is therefore used as a simple size proxy.

Relative company size = latest company revenue ÷ median latest revenue of the other three peers

The size context is classified as:

Relative Revenue

Size Context

Below 0.75x

Smaller than peers

0.75x to 1.25x

In line with peers

Above 1.25x

Larger than peers

This does not establish that higher pay is justified. It provides context for determining whether a compensation premium is broadly consistent with company scale.

Converting The Evidence Into An Alignment Classification

The final assessment combines compensation growth, performance support, peer pay, and company size.

  • Aligned: Compensation is stable, declining, or increasing moderately while operating performance is strong; or compensation falls materially when performance is weak.
  • Partially aligned: Some performance support exists, but compensation growth is high, peer pay is elevated, or company-size support is incomplete.
  • Decoupled: Compensation increases despite weak performance, or pay remains materially above peers without sufficient performance or size support.
  • Review required: CEO continuity, compensation components, reporting periods, financial metrics, or peer comparisons are not sufficiently comparable.

These are fixed analytical rules for the demonstration, not universal governance standards.

The resulting classification does not determine whether an executive is overpaid. It identifies where compensation trends appear supported by results and where the relationship between pay, performance, and peer context requires deeper governance review.

FMP Data Inputs For Pay-For-Performance Analysis

The assessment uses three focused FMP datasets. Together, they provide the compensation, operating-performance, and capital-efficiency evidence required for the three-year comparison.

Analytical Role

FMP Dataset

Use In The Assessment

Measure executive pay

Executive Compensation API

Retrieves executive name, role, salary, bonus, stock awards, option awards, non-equity incentive compensation, change in pension value and above-market nonqualified deferred-compensation earnings when reported, other compensation, and total reported compensation

Measure company performance and size

Income Statement API

Retrieves annual revenue and operating income across the three completed fiscal years

Measure capital efficiency

Key Metrics API

Retrieves annual ROIC using a consistent definition across the peer group

The analysis uses FMP's reported total compensation as the authoritative annual total rather than rebuilding it from selected components. When the equity-award share is calculated, only stock awards and option awards form the numerator, while the complete reported total compensation—including pension and nonqualified deferred-compensation amounts when applicable—remains the denominator.

The peer group is fixed inside the prompt, so a separate peer-discovery endpoint is not required. Each company's latest CEO compensation and revenue are compared with leave-one-out medians calculated from the other three companies.

Using these inputs, the analysis calculates:

  • latest total CEO compensation
  • year-over-year compensation change
  • latest revenue and operating-income growth
  • three-year ROIC change
  • leave-one-out peer compensation median
  • pay-to-peer ratio
  • relative company-size context
  • performance-support classification
  • pay-for-performance alignment
  • governance-review flag, confidence, and analyst follow-up action

All financial inputs use an annual reporting basis. Compensation, income-statement, and ROIC records should be aligned to the same completed fiscal years wherever possible. A CEO transition, missing compensation component, inconsistent fiscal period, or non-comparable ROIC record should lead to Review required rather than a forced classification.

The Executive Compensation API provides the executive-pay records, while the annual Income Statement API and Key Metrics API supply the performance and ROIC fields used in the comparison.

Accessing FMP Data Through Claude MCP

The analysis can be run by connecting the FMP MCP server directly to Claude. Before configuring the connector, obtain an active API key from the FMP dashboard.

In Claude, open Settings, select Connectors, and choose Add custom connector. Enter a recognizable name such as FMP, then paste the following endpoint into the Remote MCP Server URL field:

Remote MCP Server URL

https://financialmodelingprep.com/mcp?apikey=YOUR_FMP_API_KEY

Replace YOUR_FMP_API_KEY with the active key associated with the FMP account. Save the connector and begin a new Claude chat so the available FMP tools can be discovered for the analysis. The complete connection process is also available in the FMP MCP server documentation.

The API key should not appear in shared prompts, screenshots, notebooks, repositories, or published examples. Use the placeholder endpoint whenever demonstrating the setup publicly.

The prompt in the next section defines the peer group, annual reporting basis, executive-role rules, calculations, classification thresholds, access checks, and output structure required for the pay-for-performance assessment.

Running The Pay-For-Performance Assessment Through Claude

The prompt uses a fixed peer group: Coca-Cola, PepsiCo, Mondelez International, and Colgate-Palmolive. It limits the comparison to the chief executive officer across fiscal years 2023, 2024, and 2025.

Each company requires three FMP requests: executive compensation, annual income statements, and annual key metrics. This limits the complete run to 12 primary requests, with no more than one additional retry for a failed core request.

The prompt applies the same formulas, peer benchmarks, classification thresholds, and review rules introduced earlier. It returns two compact tables covering the underlying evidence and the final pay-for-performance assessment.

Claude Prompt

Use the FMP MCP connection to evaluate CEO pay-for-performance alignment for exactly these four companies:


1. The Coca-Cola Company (KO)

2. PepsiCo, Inc. (PEP)

3. Mondelez International, Inc. (MDLZ)

4. Colgate-Palmolive Company (CL)


Do not add, replace, or dynamically discover peers.


OBJECTIVE


Determine whether changes in CEO compensation are supported by operating performance, capital efficiency, company size, and compensation levels among the fixed peer group.


This is a neutral governance and stewardship assessment. It is not:


- A judgment about whether an executive is overpaid or underpaid

- A shareholder-voting recommendation

- A conclusion about executive quality

- An ESG score

- An investment recommendation

- A prediction of future company performance


ACCESS AND DATA-FAMILY CHECK


Retrieve the following KO datasets first:


1. Executive compensation

2. Annual income statements

3. Annual key metrics containing ROIC


Reuse these results in the complete analysis.


If any request returns an explicit plan-tier, subscription, permission, or data-family access restriction:


- Stop immediately

- Do not query PEP, MDLZ, or CL

- Do not perform calculations

- Do not generate the final tables

- Return only a concise access-validation note stating the exact error category


Do not infer an access restriction unless the FMP connection explicitly returns one.


Continue with the complete assessment only when all three required data families are available.


DATA SCOPE


Use exactly fiscal years 2023, 2024, and 2025.


Use annual records only. Do not use quarterly, interim, trailing-twelve-month, estimated, or forward-looking values.


For each company, retrieve only:


1. Executive compensation records required to identify the CEO or principal executive officer and the following annual fields:


- Executive name

- Executive title

- Compensation year

- Salary

- Bonus

- Stock awards

- Option awards

- Non-equity incentive compensation

- Change in pension value and above-market earnings on nonqualified deferred compensation, when separately reported

- Other reported compensation

- Total compensation


Use the reported Total Compensation field as the authoritative annual compensation total.


Do not reconstruct total compensation by summing selected components.


If pension or nonqualified deferred-compensation amounts are not separately available but Total Compensation is reported, retain the reported total and note the component limitation rather than treating the total as incomplete.


Do not treat an unavailable individual component as zero unless the source explicitly reports zero.


2. Annual income statements for fiscal years 2023, 2024, and 2025 containing:


- Fiscal-year end date

- Revenue

- Operating income


3. Annual key metrics for fiscal years 2023, 2024, and 2025 containing:


- Fiscal-year end date

- ROIC


Do not retrieve:


- Market prices or market capitalization

- Quarterly or TTM financial data

- Company profiles

- News

- Proxy-statement narrative

- Shareholder-voting recommendations

- ESG scores

- Insider-trading records

- Board-composition data

- Stock-performance data

- Earnings estimates

- Additional financial ratios

- Additional executives

- Additional companies


Do not search for substitute non-FMP sources, expand the peer group, or replace a missing fiscal year with another period.


EXECUTIVE SELECTION AND CONTINUITY


For each company, use only the executive identified as:


- Chief Executive Officer

- CEO

- Principal Executive Officer


Do not combine CEO compensation with CFO, chair-only, president-only, former executive, or other officer records.


Require the same individual to be the comparable CEO across fiscal years 2023, 2024, and 2025.


If the executive changes, the title is unclear, a year represents partial-year service, or current and former CEO records overlap:


- Mark the company Review required

- Set the governance review flag to Data validation

- Set confidence to Low

- State the exact continuity issue

- Do not combine compensation belonging to different executives


If several records exist for the same CEO and year, use the consolidated total compensation record only when duplicates can be resolved confidently. Otherwise, mark Review required.


REQUEST LIMIT


Use no more than 12 primary FMP requests:


- Four executive-compensation requests

- Four annual income-statement requests

- Four annual key-metrics requests


Permit no more than one additional retry across the entire run, and only for a failed executive-compensation, income-statement, or key-metrics request.


If the permitted retry fails:


- Mark the affected company Review required

- Do not infer or substitute the missing field

- Continue with the other companies unless the failure is an explicit data-family access restriction


Do not include step-by-step request logs.


PERIOD AND COMPARABILITY RULES


Use fiscal-year labels 2023, 2024, and 2025 for every company.


Report each company's exact fiscal-year end dates.


Align the compensation year with the corresponding company fiscal-year label.


Do not silently combine compensation and financial records carrying different year labels.


If compensation and financial periods cannot be aligned reliably:


- Mark the company Review required

- Set confidence to Low

- State the mismatch in the methodology note


OPERATING-INCOME COMPARABILITY


When operating-income growth changes sharply while revenue growth is substantially smaller, keep the calculated operating-income growth visible but review whether the prior-year operating-income base is comparable.


If the retrieved FMP data does not provide enough evidence to establish that the operating-income comparison is free from a material base effect, remeasurement, restructuring item, or other non-recurring distortion:


- Label the operating-income indicator Review required

- Do not count that indicator as confirmed Positive or Negative performance evidence

- Retain the numerical operating-income growth rate

- Use the remaining valid performance indicators to determine Performance Support

- If fewer than two valid indicators remain, set Performance Support to Review required

- State the operating-income comparability issue in the methodology note or Data Caveat field


Before the tables, provide one compact methodology note stating:


- Analysis run date

- Peer group

- Fiscal years used

- Annual reporting basis

- CEO or principal-executive-officer basis

- Exact fiscal-year end dates for each company

- Leave-one-out peer-median methodology

- Any CEO transition, duplicate record, missing component, or period-alignment caveat


CALCULATIONS


Use unrounded source values for all calculations. Round only displayed results.


1. Year-over-year compensation change


FY2025 total compensation divided by FY2024 total compensation minus 1


2. FY2025 revenue growth


FY2025 revenue divided by FY2024 revenue minus 1


3. FY2025 operating-income growth


FY2025 operating income divided by FY2024 operating income minus 1


4. Three-year ROIC change


FY2025 ROIC minus FY2023 ROIC


Express the change in percentage points.


5. Leave-one-out peer compensation median


For each company, calculate the median FY2025 total compensation of the other three companies.


6. Pay-to-peer ratio


Company FY2025 total compensation divided by its leave-one-out peer compensation median


7. Leave-one-out peer revenue median


For each company, calculate the median FY2025 revenue of the other three companies.


8. Relative company size


Company FY2025 revenue divided by its leave-one-out peer revenue median


9. Equity-award share


FY2025 stock awards plus FY2025 option awards divided by FY2025 total compensation


DENOMINATOR AND MISSING-VALUE RULES


Do not calculate a growth rate when the prior-year denominator is zero, negative, or missing.


If FY2024 operating income is zero or negative:


- Show operating-income growth as Not meaningful

- Do not classify that indicator as Positive or Negative


If fewer than two valid performance indicators remain:


- Mark Performance Support as Review required

- Mark the final classification Review required


If FY2024 total compensation is zero or missing:


- Do not calculate compensation growth

- Mark the company Review required


If ROIC is supplied as a decimal, convert it consistently to a percentage before calculating the percentage-point change.


Do not calculate missing compensation components as zero unless the source explicitly reports zero.


DISPLAY RULES


- Show compensation in USD millions with two decimal places

- Show revenue and operating income in USD billions with two decimal places

- Show growth rates and ratios with two decimal places

- Show ROIC values and changes in percentage points with two decimal places

- Display negative values with a minus sign

- Do not round inputs before completing calculations

- Keep table cells concise


PERFORMANCE-INDICATOR CLASSIFICATION


Classify FY2025 revenue growth as:


- Positive: greater than 0%

- Stable: exactly 0%

- Negative: less than 0%


Classify FY2025 operating-income growth as:


- Review required: the numerical growth rate is available, but prior-year operating-income comparability cannot be established under the OPERATING-INCOME COMPARABILITY rules

- Positive: greater than 0% and no comparability review is required

- Stable: exactly 0% and no comparability review is required

- Negative: less than 0% and no comparability review is required

- Not meaningful: the prior-year denominator is zero, negative, or missing


Classify the three-year ROIC change as:


- Positive: greater than +0.50 percentage points

- Stable: from -0.50 to +0.50 percentage points, inclusive

- Negative: less than -0.50 percentage points


PERFORMANCE-SUPPORT CLASSIFICATION


Use the three indicators:


- Revenue growth

- Operating-income growth

- Three-year ROIC change


Classify performance support as:


- Strong support: at least two valid indicators are Positive

- Weak support: at least two valid indicators are Negative

- Mixed support: any other combination when at least two valid indicators are available

- Review required: fewer than two valid indicators are available


COMPENSATION-CHANGE CONTEXT


Classify FY2025 year-over-year compensation change as:


- Material reduction: -10% or lower

- Stable or moderate: above -10% through +10%

- Moderate increase: above +10% through +20%

- High increase: above +20%


PEER COMPENSATION CONTEXT


Classify the pay-to-peer ratio as:


- Below peer range: below 0.75x

- Within peer range: 0.75x through 1.25x

- Above peer range: above 1.25x


COMPANY-SIZE CONTEXT


Classify relative company size as:


- Smaller than peers: below 0.75x

- In line with peers: 0.75x through 1.25x

- Larger than peers: above 1.25x


PAY-FOR-PERFORMANCE CLASSIFICATION


Apply the following rules in this order.


1. REVIEW REQUIRED


Assign Review required when:


- CEO continuity is not established across all three years

- A required total-compensation value is missing or duplicated

- Compensation and financial years cannot be aligned

- Performance Support is Review required

- FY2025 or FY2024 revenue is missing

- FY2025 or FY2024 operating income is missing

- FY2025 or FY2023 ROIC is missing

- A core calculation cannot be completed


2. DECOUPLED


Assign Decoupled when at least one condition applies:


- Performance Support is Weak and compensation increased by more than 10%

- Performance Support is Mixed and compensation increased by more than 20%

- Compensation is Above peer range, company size is not Larger than peers, Performance Support is not Strong, and compensation increased above 0%


3. ALIGNED


Assign Aligned when at least one condition applies and no Decoupled rule applies:


- Performance Support is Strong, compensation increased by no more than 20%, and either compensation is not Above peer range or company size is Larger than peers

- Performance Support is Weak and compensation declined by at least 10%

- Performance Support is Mixed, compensation did not increase, and compensation is not Above peer range


4. PARTIALLY ALIGNED


Assign Partially aligned to every complete case that is not classified as Aligned or Decoupled.


These are fixed analytical rules for this demonstration. They are not universal governance standards.


GOVERNANCE REVIEW FLAG


Map the final classification as follows:


- Aligned: No current flag

- Partially aligned: Monitor

- Decoupled: Governance review

- Review required: Data validation


When FY2025 compensation increased by more than 50% and equity awards represent at least 60% of FY2025 total compensation, append: Equity-award structure review.


Do not describe the award as one-time or excessive unless the retrieved data explicitly establishes that fact.


CONFIDENCE


Assign confidence according to evidence quality:


- High: CEO identity is consistent across all three years; compensation components and totals are complete; annual financial periods are aligned; and all three performance indicators are valid

- Medium: Core calculations are complete, but a large equity-award concentration, minor date-alignment caveat, disclosed compensation-component issue, or operating-income base/comparability review requires interpretation

- Low: CEO continuity, compensation completeness, period alignment, or a core performance input requires manual validation


A Review required classification must have Low confidence.


Confidence must reflect evidence quality rather than whether compensation is high or whether performance is weak.


RESULT FORMAT


Return exactly two tables with exactly four company rows in each table.


TABLE 1: COMPENSATION AND PERFORMANCE EVIDENCE


Use exactly these columns:


1. Company / CEO

2. Total Compensation FY2023 / FY2024 / FY2025 / FY2025 YoY Change

3. FY2025 Revenue Growth / Operating-Income Growth

4. ROIC FY2023 / FY2025 / Three-Year Change

5. Leave-One-Out Peer Median / Pay-to-Peer Ratio

6. Relative Company Size / Data Caveat


TABLE 2: PAY-FOR-PERFORMANCE ASSESSMENT


Use exactly these columns:


1. Company

2. Performance Support

3. Compensation and Peer Context

4. Pay-for-Performance Classification

5. Governance Review Flag

6. Confidence / Analyst Follow-Up Action


Keep every table cell concise.


After the two tables, provide exactly three brief peer-group observations:


1. Identify the strongest pay-for-performance alignment and state the primary evidence.

2. Identify the clearest potential decoupling or review case and state the primary driver.

3. State the most important peer-wide governance follow-up.


Do not provide:


- Additional tables

- CEO rankings

- Statements that an executive is overpaid or underpaid

- Shareholder-voting recommendations

- Investment conclusions

- Assertions about whether compensation is good or bad

- Extended company-by-company commentary

- Extra calculations

This prompt keeps the comparison limited to four companies, three completed fiscal years, and three required data families. It also applies the formulas and classifications described earlier in the final evidence and assessment tables.

Compensation, Performance, And Peer Alignment Results

The analysis was run on August 7, 2026 using annual data for fiscal years 2023 through 2025. The fixed peer group included Coca-Cola, PepsiCo, Mondelez International, and Colgate-Palmolive.

The assessment followed the same CEO or principal executive officer across all three fiscal years: James Quincey at Coca-Cola, Ramon L. Laguarta at PepsiCo, Dirk Van de Put at Mondelez, and Noel R. Wallace at Colgate-Palmolive. Executive continuity was confirmed across the full comparison period.

Coca-Cola, Mondelez, and Colgate-Palmolive used December 31 fiscal year-end dates. PepsiCo's FY2025 period ended on December 27, 2025 under its 52/53-week fiscal calendar, while the compensation and financial-year labels remained aligned.

Reported Total Compensation was used as the authoritative annual compensation figure rather than reconstructed from individual components. The retrieved compensation records did not separately break out pension-value or nonqualified deferred-compensation amounts for the four CEOs, so those components were not inferred or treated as zero.

Operating-income comparability required additional review for Coca-Cola and Mondelez. In both cases, FY2025 operating-income growth moved much more sharply than revenue growth, while the retrieved FMP data was not sufficient to establish whether the prior-year base was fully comparable. The numerical growth rates therefore remain visible, but the operating-income indicators are marked Review required and are not counted as confirmed positive or negative performance evidence.

Compensation And Performance Evidence

Company / CEO

Total Compensation FY2023 / FY2024 / FY2025 / YoY Change

FY2025 Revenue Growth / Operating-Income Growth

ROIC FY2023 / FY2025 / Three-Year Change

Peer Median / Pay-to-Peer Ratio

Relative Size / Data Caveat

KO / J. Quincey

$24.74M / $28.00M / $31.21M / +11.45%

+1.87% / +37.73% (Review required)

11.54% / 13.00% / +1.47pp

$23.90M / 1.31x

1.24x / Operating-income comparability review

PEP / R. Laguarta

$33.91M / $28.81M / $23.90M / -17.04%

+2.25% / +4.69%

12.66% / 13.29% / +0.63pp

$24.52M / 0.98x

2.44x / FY2025 ends 12/27

MDLZ / D. Van de Put

$21.02M / $22.30M / $24.52M / +9.91%

+5.75% / -42.95% (Review required)

7.65% / 5.13% / -2.53pp

$23.90M / 1.03x

0.80x / Operating-income comparability review

CL / N. Wallace

$17.12M / $18.23M / $16.48M / -9.63%

+1.40% / -0.80%

24.76% / 30.34% / +5.58pp

$24.52M / 0.67x

0.43x / None

Coca-Cola: Revenue increased by 1.87% and ROIC improved by 1.47 percentage points, providing two confirmed positive performance indicators. Operating income increased by 37.73%, but that result is marked Review required because the retrieved data does not establish whether the prior-year operating-income base is fully comparable. Coca-Cola therefore retains Strong performance support based on the two valid indicators, but confidence is reduced to Medium. CEO compensation increased by 11.45%, while pay was 1.31x the leave-one-out peer median and relative company size was 1.24x, resulting in a Partially aligned classification.

PepsiCo: Revenue increased by 2.25%, operating income increased by 4.69%, and ROIC improved by 0.63 percentage points. All three performance indicators were positive. At the same time, CEO compensation declined by 17.04% and remained within the peer range at 0.98x the leave-one-out median. PepsiCo was also materially larger than peers based on revenue, supporting an Aligned classification with High confidence.

Mondelez: Revenue increased by 5.75%, while ROIC declined by 2.53 percentage points. Operating income declined by 42.95%, but the magnitude of the change requires a comparability review and is therefore not counted as confirmed negative performance evidence. With one valid positive indicator and one valid negative indicator, performance support is Mixed. CEO compensation increased by 9.91% and remained within the peer range, resulting in a Partially aligned classification with Medium confidence.

Colgate-Palmolive: Revenue increased by 1.40% and ROIC improved by 5.58 percentage points, while operating income declined slightly by 0.80%. Two of the three valid performance indicators were positive, producing Strong performance support. CEO compensation declined by 9.63% and remained below the peer range at 0.67x the leave-one-out median. The result is classified as Aligned with High confidence.

Pay-For-Performance Assessment

Company

Performance Support

Compensation And Peer Context

Pay-For-Performance Classification

Governance Review Flag

Confidence / Analyst Follow-Up Action

KO

Strong support — 2 valid Positive indicators; operating income Review required

Moderate increase (+11.45%); Above peer range; In line with peers

Partially aligned

Monitor

Medium / Confirm operating-income base comparability before treating the +37.73% increase as performance evidence

PEP

Strong support — 3/3 Positive

Material reduction (-17.04%); Within peer range; Larger than peers

Aligned

No current flag

High / Continue routine monitoring

MDLZ

Mixed support — revenue Positive; ROIC Negative; operating income Review required

Stable or moderate (+9.91%); Within peer range; In line with peers

Partially aligned

Monitor

Medium / Review operating-income comparability and monitor the ROIC decline

CL

Strong support — 2/3 Positive

Stable or moderate (-9.63%); Below peer range; Smaller than peers

Aligned

No current flag

High / Continue routine monitoring

PepsiCo shows the strongest pay-for-performance alignment in the peer group. Revenue, operating income, and ROIC were all positive, while CEO compensation declined by 17.04% and remained within the peer range. The combination supports an Aligned classification with High confidence.

Colgate-Palmolive is also classified as Aligned. Revenue growth and ROIC improvement provided two positive performance indicators, while operating income declined only slightly. CEO compensation fell by 9.63% and remained below the peer range, supporting the classification without requiring a governance flag.

Coca-Cola remains Partially aligned, but the evidence should be interpreted more carefully than in the earlier version. Revenue growth and ROIC improvement provide two confirmed positive indicators, while the 37.73% operating-income increase is marked Review required because the prior-year base has not been fully validated for comparability. Compensation increased by 11.45% and remained above the peer range at 1.31x, while relative company size was still within the in-line range. The result therefore remains Partially aligned with Medium confidence.

Mondelez is the clearest review case. Revenue growth was positive and ROIC declined by 2.53 percentage points, while the 42.95% operating-income decline is marked Review required rather than counted as confirmed negative evidence. Performance support is therefore Mixed rather than Weak. CEO compensation increased by 9.91% and remained within the peer range, leading to a Partially aligned classification with Medium confidence.

Across the peer group, the most important follow-up is the comparability of unusually large operating-income movements. For Coca-Cola and Mondelez, the numerical changes remain visible, but they should not be treated as confirmed performance evidence until the prior-year operating-income base and any material non-recurring effects are reviewed.

Where Pay-For-Performance Alignment Needs Analyst Review

The framework provides a consistent way to compare executive pay with operating performance and peer context, but compensation data can contain structural features that are not visible in a simple year-over-year comparison. High-quality governance and financial data still needs review before the classification is treated as decision-ready.

One-Time And Multi-Year Equity Awards

Stock and option awards may cover several future service or performance periods. Recording the full grant-date value in one fiscal year can create a sharp increase in reported compensation even when the award is intended to span multiple years.

A large equity component should therefore be reviewed separately when compensation growth appears unusually high. Analysts should confirm whether the award is recurring, performance-based, retention-related, or part of a longer-term incentive cycle.

Reported Compensation May Differ From Realized Pay

Reported total compensation combines components measured on different bases. Stock and option awards are generally reported using grant-date fair values, while salary, bonus, and non-equity incentive compensation reflect amounts earned for the applicable year. Reported totals may also include changes in pension value and above-market earnings on nonqualified deferred compensation when applicable.

The ultimate realized value of equity awards may differ materially from the grant-date amount because of:

  • vesting conditions
  • share-price performance
  • performance targets
  • option exercise timing
  • award forfeitures

Reported total compensation remains appropriate for standardized peer comparison, but the equity-award components should not be interpreted as cash already received or value already realized by the executive.

CEO Transitions Can Distort Annual Comparisons

Sign-on awards, severance payments, interim appointments, partial-year service, and overlapping former and current CEO records can make compensation trends non-comparable.

The analysis should not combine compensation belonging to different executives simply to preserve a three-year series. When continuity cannot be established, Review required is more reliable than a forced pay-growth calculation.

Compensation And Financial Periods May Not Align Perfectly

Compensation-year labels and company fiscal years do not always cover identical dates. PepsiCo's 52-week fiscal calendar illustrates this issue: the FY2025 period ended on December 27 rather than December 31.

Minor differences may not invalidate the assessment, but they should be disclosed. Larger mismatches, partial-year periods, or overlapping records require manual validation before compensation and performance are compared.

Operating Results May Reflect External Or Non-Recurring Factors

Revenue and operating income can be affected by acquisitions, restructuring charges, commodity costs, currency movements, remeasurements, litigation, impairments, and other items that make year-over-year comparisons less representative of underlying operating performance.

This matters when operating income moves far more sharply than revenue. In the current results, Coca-Cola reported 1.87% revenue growth alongside a 37.73% increase in operating income, while Mondelez reported 5.75% revenue growth alongside a 42.95% decline in operating income. Both operating-income indicators are therefore marked Review required rather than automatically treated as confirmed performance evidence.

For Coca-Cola, analysts should review whether the FY2024 comparison base was affected by material items, including whether the fairlife contingent-consideration remeasurement contributed to the apparent year-over-year swing. For Mondelez, analysts should similarly determine whether the decline reflects underlying operating deterioration, temporary charges, commodity-cost pressure, or another comparability effect.

Until those drivers are confirmed, the numerical operating-income growth rates remain visible but should not independently strengthen or weaken the pay-for-performance classification.

This directly addresses the editor's concern about applying the same skepticism to both KO and MDLZ.

ROIC Requires Consistent Definitions

ROIC can vary depending on how taxes, goodwill, excess cash, leases, acquisition accounting, and invested capital are treated.

The assessment should use the same FMP definition across all companies and fiscal years. A sudden ROIC change should still be reviewed when major acquisitions, divestitures, or balance-sheet changes may have affected comparability.

Peer Benchmarks Depend On Peer-Group Quality

A fixed peer group improves reproducibility, but it does not guarantee that every company is perfectly comparable.

Differences in business mix, geography, revenue scale, operating complexity, and executive responsibilities may affect compensation levels. A pay premium should therefore be interpreted alongside company size and operating structure rather than treated as evidence of misalignment by itself.

Coca-Cola illustrates this limitation. Its compensation was above the leave-one-out peer range, while its revenue scale remained within the framework's in-line range. That result warrants monitoring, but it does not establish that the compensation level is inappropriate.

Threshold Effects Can Change The Classification

The framework uses fixed demonstration thresholds. Small differences around those boundaries can change the final result.

Mondelez increased compensation by 9.91%. Under the defined rules, that remains within the stable-or-moderate range. A slightly larger increase above 10% would have moved the case closer to the Decoupled criteria because performance support was Weak.

Analysts should therefore review cases near classification boundaries rather than treating the label as an absolute conclusion.

These review triggers define where a standardized pay-for-performance screen ends and governance judgment begins. Combining compensation trends, operating performance, ROIC, company size, and peer benchmarks helps identify cases that appear aligned, partially supported, or potentially decoupled, while deeper review determines whether the result reflects incentive design, temporary accounting effects, or a genuine governance concern.

Turning Pay-For-Performance Evidence Into A Governance Decision

Executive compensation becomes more meaningful when it is evaluated alongside operating results, capital efficiency, peer pay, and company scale. Total compensation alone may attract attention, but it does not show whether pay changed in line with performance or whether the level remains reasonable within a comparable peer group.

The framework in this article connects those inputs through a consistent set of rules. Compensation growth is assessed against revenue, operating income, and ROIC, while leave-one-out peer medians provide context without allowing a company's own pay or revenue to influence its benchmark.

The peer results show why no single metric should determine the conclusion. PepsiCo and Colgate-Palmolive received Aligned classifications through different combinations of performance and compensation change. Coca-Cola remained Partially aligned because compensation was above the peer range while company size remained within the framework's in-line range. Its revenue growth and ROIC improvement provided Strong performance support, although the large operating-income increase remains subject to comparability review. Mondelez was also Partially aligned, with Mixed performance support based on positive revenue growth and declining ROIC while its operating-income decline remained Review required.

These classifications are not conclusions about whether an executive deserves a particular level of pay. They are governance escalation signals that help research and stewardship teams distinguish cases with validated performance support from those requiring closer examination of operating-income comparability, compensation components, equity-award structure, fiscal-year alignment, peer comparability, or incentive design.

Used within those limits, FMP compensation and financial data can support a repeatable pay-for-performance review across a defined peer group. The analytical value lies in identifying where compensation broadly tracks results and market context, and where the relationship between pay, performance, and company scale warrants deeper governance review.

About the Author

Pranjal Saxena
Pranjal Saxena

Financial APIs, Claude MCP, and AI-driven research workflows

Pranjal Saxena writes technical content focused on financial data APIs, Claude MCP workflows, AI-driven research systems, and Python-based market analysis. For FMP, his work centers on turning structured financial data into practical, workflow-driven content for developers, analysts, and fintech teams. He combines experience in data science, NLP, generative AI, and financial API workflows to show how APIs, automation, and AI-assisted systems can support modern financial research and analysis.

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