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Article | Beyond Data

Using pay analytics to get more value from your compensation budget

By Dipti Sangolli and Kerem Tuzlaci | January 06, 2026

Managing your budget while maintaining compensation competitiveness is a delicate balance. Here’s how to achieve it.
Compensation Strategy & Design|Kariyer Analizi ve Tasarımı|Pay Equity and Pay Transparency|Total Rewards
Pay Trends

Economic pressures are making the balance between compensation budgets and maintaining competitive pay increasingly important for compensation and HR professionals. Achieving this balance requires a careful assessment of current pay structures and market positioning, as well as a deep understanding of compensation and business strategy. Through this assessment, you can identify the reward actions that are likely to have the greatest impact.

Developing an effective compensation plan requires alignment between internal organizational priorities (e.g., business strategy, compensation strategy and structure, culture) and broader market dynamics. Luckily, digital innovation is making it easier than ever to ensure this alignment through data-driven pay analytics dashboards that help you visualize pay pressure points and articulate the business case for rewards alignment projects.

Our compensation analytics tools serve as a comprehensive diagnostic to proactively address compensation challenges and optimize their strategies. Compensation and HR professionals can efficiently target their efforts with WTW’s compensation analytics that are focused on four key areas.

  1. 01

    Job-level and framework diagnostics

    The right tools reveal inconsistencies or inaccuracies in organization levels and significant overlaps between pay ranges, across levels or against market data, all based on incorrect internal levels.

    When organizations grow quickly, they may lack formal leveling structures that span regions or entities, leading to incorrect comparisons and pay gaps. Through data analysis, we have seen that, when internal levels are overly compressed with too many layers, pay differentiation may become insufficient.

    Conversely, gaps between levels can result in large pay jumps and inadequate overlap in pay ranges. Both scenarios highlight the need for a consistent leveling approach that is communicated throughout the organization.

  2. 02

    Developing an optimal pay mix

    Pay analytics tools highlight the importance of having the right pay mix. They also reflect how an organization’s performance-based elements and employee benefits are positioned against the market.

    While aligning base salary with market norms is standard practice, companies may overlook the critical role of variable pay for some job families or fixed allowances in certain markets. Ultimately, this oversight risks increased talent loss to competitors that emphasize these elements.

    From an internal perspective, organizations also need to evaluate whether their pay composition aligns with business strategy. For example, companies in growth phases may favor high-risk/reward strategies with flexible, discretionary awards that focus on individual contributions. Meanwhile, stable-growth companies may opt for formalized structures, increasingly using variable pay as employees progress in their careers.

    Depending on several factors, the “right” pay mix for your organization may change over time. This makes it important to evaluate your pay mix periodically to ensure it meets business objectives while maintaining market competitiveness.

  3. 03

    Positioning pay based on organization structure and employee population

    Strong compensation analytics dashboards evaluate employee compensation through different lenses, such as job families, levels or gender. Each of these views may help identify systemic issues with pay or the need for a differentiated pay positioning strategy.

    Job families and industry dynamics

    Evolving industry dynamics and roles that are in high demand may cause organizations to differentiate rewards and adopt different pay positioning for job families that are critical to growth. In these cases, companies need to prioritize strategic roles that are essential for growth and adapt their pay practices accordingly.

    For instance, in the technology industry this includes cybersecurity; data science and analytics; artificial intelligence and machine learning; blockchain development; user experience/user interface design, and business intelligence.

    Meanwhile, in more traditional industries like real estate, construction and engineering, it may be worth considering how the market differentiates for rewards among core roles (e.g., project management, civil engineering, architecture) vs. roles in shared services (e.g., HR, finance, administrative services).

    Organization levels and progression

    Compensation analytics also direct organizations to consider pay progression across organization levels and how it compares against the market. For example, identifying market practice for midpoint progression when transitioning from mid-management to top executive levels and if there is a need for more significant progression between certain levels.

    Gender pay equality

    Addressing gender pay equality involves multiple layers (e.g., transparency, audits, standardized offers, flexible work policies). From a workforce analytics perspective, you can use analytics to understand:

    • Workforce prevalence at different organizational levels (e.g., women in executive positions)
    • Pay disparity
    • Industry-specific market practices and norms

    These insights enable organizations that are committed to fairness and inclusivity to embed these principles into their pay strategies and decision making.

  4. 04

    Pay perception vs. actual positioning

    The right analytics and visualization dashboards also demonstrate to senior management how well pay is aligned to the organization’s stated pay positioning. In tandem with employee survey insights on pay, this information can help assess whether employees’ pay perceptions correspond to market data findings. In turn, this helps you design effective employee communication plans.

Case example: Compensation strategy in a traditional environment

WTW recently collaborated with an engineering firm with a pay strategy aimed at aligning to the market median, with most employees compensated within a competitive range of this benchmark.

Through this work, pay comparison analytics by job family and level revealed that the company was consistently underpaying engineering roles across all grades. Additionally, certain job families like customer service, IT support and finance were consistently paid above market.

These insights, combined with data on turnover and recruitment challenges, underscored the need to evaluate whether a differentiated pay positioning strategy for core functions or levels was needed to maintain a competitive edge. This analysis also helped the rewards team effectively demonstrate the need to reallocate budgets to specific areas. By doing this, the organization could address pay gaps and proactively align compensation with the organization’s stated pay strategy.

Moreover, internal levels were not being translated to the right market grades because of a lack of job evaluation systems. Some levels were being underpaid in terms of their guaranteed and variable pay. Additionally, pay gaps against the market emphasized the inconsistency between internal job levels and market grades/evaluation systems and the need for a formalized job evaluation framework.

Balancing your compensation budget with competitiveness

Effectively balancing precious compensation budgets against market and peer competitiveness requires a well-thought and considered assessment based on both internal and external data. Analytics dashboards provide a toolkit of comprehensive insights that help organizations regularly evaluate their pay strategy, making changes as needed — a critical input into developing successful rewards programs that are worth the investment.

Authors


Dipti Sangolli
Associate Director, Rewards Data Intelligence

Rewards Data Intelligence Leader, Saudi Arabia

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