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Compensation -�Essentials and Practical Tools�

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Claude Diwouta

September 16, 2025

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Let’s Connect

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Where are you joining from today?

And what’s one word to describe how you feel about compensation reviews?

(Type your answers in the chat )

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The Real-World Challenges We Face

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Before we dive in, let’s name the main concerns about compensation that you shared.

Equity and fairness across countries and roles
Access to reliable and localized salary data
Compliance with legal requirements across geographies
Staying competitive to attract and retain top talent
Achieving transparency, understanding, and staff acceptance
Others?

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Agenda & Learning Objectives

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Organizational Structure, Job Descriptions & Evaluation

Compensation Philosophy

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Develop Job Descriptions

Create a Grading Structure

Model Salary Ranges

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Strategies and Practices

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Foundations

Leverage AI

Managing

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Core Components of a Compensation Strategy

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Compensation Philosophy: Organizational stance on fairness, competitiveness, and pay transparency

Market Positioning: Choice of market percentile to target (e.g., 25th, 50th, 75th)

Job Evaluation & Grading: Framework to assess job size and align to pay levels

Pay Structures: Salary bands and ranges across grades and families

Performance & Talent Management Linkage: Alignment of compensation with results and behaviors

Benefits & Total Rewards: Health, retirement, paid time off, recognition, and development

Management & Compliance: Policies, controls, and legal adherence across geographies

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Foundations

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Key Pillars

Ensure clear coles and responsabilities

Provide the foundation for fair comparison and internal equity

1. Organizational Structure

Clarity of roles and levels across departments

Consistency across geographies

2. Accurate, up-to-date job descriptions

3. Standardized job evaluation methodology,

Internal comparison and job grading criteria

Organizational Culture

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Compensation Philosophy

What to Consider:

Principles such as equity internal & across geographies, transparency, competitiveness
Total Rewards: non-monetary elements
Global vs Local alignment including managing expatriates
Positioning against the market (e.g., 25th, 50th percentile)
Adaptation to funding realities and mission-driven goals
Performance management linkage (merit increase, bonus…)

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Aligns pay strategy with organizational values, culture, and goals. Is the basis of your compensation strategy.

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Let’s Pause – Quick Check-In

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What’s the most time-consuming or challenging part of managing compensation in your organization?

(Feel free to drop it in the chat or share out loud if you’d like)

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Leverage AI

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I. How can AI help ?

1. Develop Job Descriptions: generate, refine, and standardize job descriptions.

• Analyze existing job content for consistency

• Use AI assistants to draft new JDs based on job families

• Benchmark job content with market/industry standards

• Ensure inclusive language using AI-based bias detectors

2. Create a Grading Structure: analyze and cluster roles into logical job levels.

• Align evaluation criteria across roles using AI pattern analysis

• Automate grading matrix creation using AI clustering models

• Use AI tools to visualize grade dispersion and overlaps

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Here’s where AI really shines. Gathering salary data manually across countries is hard. AI tools can scrape, clean, and normalize market data across multiple sources. This means you can compare internal pay to market benchmarks, account for local cost of living, and ensure legal alignment.

First, AI can help you generate, refine, and standardize job descriptions—quickly and consistently. It ensures roles are described in inclusive language, aligned to your job families, and benchmarked against market data. For NGOs building capacity in new countries, this is a game-changer.

Second, AI can help build your grading structure. By clustering similar roles and visualizing overlaps, it ensures logical leveling across departments and countries. This is critical to achieving internal equity—especially when local norms vary significantly.

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Example: Job Description Creation

Scenario: You need to create a job description for a new Program Manager role.

How ChatGPT helps:

• Draft a first version based on provided responsibilities and level

• Suggest standardized language for job family and grade, delete redundant, or biased phrasing

• Compare the draft with external job market benchmarks

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Example: Build a Grading Structure

Scenario: You want to create a logical grading structure for 100+ roles across regions.

How AI supports you to:

• Analyze job descriptions to extract required skills and responsibilities

• Group roles with similar complexity, scope, and qualifications, identify job families

• Identifie overlaps or inconsistencies across job families

• Suggest logical grade levels and pay bands based (step approach, Tier approach…)

• Visualize results to support calibration across departments

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II. How can AI help ?��

1. Benchmarking: collect, normalize, and analyze salary data from diverse sources.

• Pull salary/benefit data from reliable online sources using AI

• Use predictive models to estimate compensation for rare roles

• Compare internal vs. market rates using AI dashboards

2. Model Salary Structures: simulate and optimize compensation bands across levels.

• Use models to define salary progression within grades

• Simulate different scenarios (e.g., positioning at 25th/50th percentile)

• Apply AI to visualize compression, gaps, and pay equity

• Automate the calculation of tiered salary bands with embedded rules

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Managing

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Compensation Strategies in Practice

• Written policies for salary reviews, Cost of Living or Cost of Labor increases, and bonuses, inflation management

Benefits standardization & flexibility
Local labor law compliance and global consistency
Communication and transparency mechanisms
Placement of new hires and employees on the salary bands
Performance-based increases and talent management

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Translating philosophy into actionable and consistent, practices. Build trust.

Policies make things predictable. Clear salary review cycles, documented increase guidelines, and communication tools help staff know what to expect—and reduce perception of favoritism or opacity. They also ensure legal compliance, especially when you operate in multiple jurisdictions.

Should you do this work internally or with external help?�Internal reviews are fast and cost-effective. But external reviews bring benchmarking tools, neutrality, and credibility.�If you use AI, a consultant can help interpret results, ensure equity, and coach your internal team.

Should you do this work internally or with external help?

Internal reviews are fast and cost-effective. But external reviews bring benchmarking tools, neutrality, and credibility.

If you use AI, you can interpret yourself or get external help interpret results, ensure equity, and coach your internal team.

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How Today’s Session Addressed your Concerns

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Equity: Role clarity, job evaluation, and salary bands

Local data: Market benchmarking using AI and external support

Legal: Policies that align global consistency with local compliance

Competitiveness: Strategic positioning and structure modeling

Staff acceptance: Transparent philosophy, tools, and communication

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Closing Reflection

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What’s one word that describes how you feel after this session?

(Type your word in the chat )

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Thank you!