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Article | Beyond Data

Shifting to a skill-based reward strategy

A challenge facing reward professionals is how to determine the market value of certain skills.

By Laurent Grimal and Michiel Klompen | March 30, 2020

Given the changing nature of work and ever-shifting skill requirements, HR and reward professionals are increasingly looking to move beyond role-based compensation frameworks
Compensation Strategy & Design|Work Transformation|Ukupne nagrade
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WorkVue and SkillsVue

Companies cannot be expected to solve tomorrow’s problems using yesterday’s tools. That’s why Willis Towers Watson developed WorkVue and SkillsVue – two, first-of-their-kind, interactive analytical platforms enabling companies to deconstruct jobs to analyze the underlying tasks, identify how automation can be used to achieve the optimal combinations of humans and machines, predict shifting skill requirements, and see the impact of skills on pay.

In a workplace disrupted by automation and digitalization, skills are becoming the new currency, prompting employers to rethink how they reward their employees. As the nature of work changes, so too do skills and skill requirements. The need to attract and retain employees with critical skills — in particular “hot” digital skills — is motivating organizations to shift from role-based compensation to a reward strategy that accounts for skills.

A new focus on work and skills

The supply and demand for critical talent today is driving a new focus on work and skills. In the past, organizations met their demand for talent primarily by hiring full-time employees from a pool of candidates trained for highly structured jobs. Many people were employed in similar types of jobs where there was limited variation in the tasks to be accomplished and the skills required to do the work. Employees worked in a single job often for their lifetime or followed a prescribed linear career path. Technology was used largely to support employees in their jobs.

Technology is fueling agile ways of working, changing how, where and by whom work gets done.

In today’s workplace, however, technology is fueling agile ways of working, changing how, where and by whom work gets done. The one-to-one relationship between a person and a job is increasingly being replaced by a many-to-many relationship between skills and the different ways work can be completed. Technology such as robotic process automation (RPA) becomes a work “partner” as parts of a job (e.g., repetitive tasks) can be automated. The remaining work can then be completed in discrete projects or assignments, with employers relying on a talent pool comprised of employees as well as a range of contingent workers.

The projects to be completed can require a wide range of ever-changing skills and experiences driven by the rapid pace of technological innovation. There is a strong demand for specialized digital skills (ranging from data science to blockchain development), which increases the likelihood that organizations may face skill deficits. At the same time, more workers are making their own decisions about the types of work and work relationships they want to pursue depending on their interests and experiences. These individuals seek to build their own portfolio of skills and shape their own unique career experiences.

This shift in focus from a fixed job to a more agile approach of work and skills impacts how organizations reward their employees and meet their expectations. As a result, organizations are increasingly moving away from the conventional one-size-fits-all role-based approach to a more future-focused skills-based approach that includes greater flexibility in the compensation package at a talent segment or individual level.

Identifying the challenges

Organizations must address a set of internal and external challenges to lay the groundwork for a more flexible, skill-based approach to rewarding talent. The internal challenge is two-fold. First, it is vital to understand the current state of skills within the organization. Learning about employees’ skills, even those not currently used on the job, is critical, as it allows the organization to foster talent mobility, develop data-driven succession planning models and maximize learning opportunities. Next, because of the fast pace at which new skills emerge, it is also important to identify the skills needed to support the future work of the organization. However, predicting future skill requirements is no small task as the number of variables can be staggering.

A key external challenge facing reward professionals is how to determine the market value of certain skills. The following considerations can help organizations understand the scope of this challenge:

  • Making sense of market pay data can prove difficult for organizations seeking to reward for skills and work as opposed to discrete jobs. Most organizations indicate that they pay premiums in the base salary for specific skills. However, some organizations have introduced separate skill allowances, while others make use of hiring / retention bonuses or long-term incentives to attract and retain talent with specific skills.
  • Capturing skill diversity as jobs become more agile can be daunting. As jobs become increasingly fluid and agile, the skills needed to do the work are increasingly multi-faceted. But traditional compensation surveys may make it difficult to define benchmark jobs that capture the diversity of these skill configurations.
  • Adding more skills to a job does not necessarily equate to a higher salary. In some cases, adding skills may lower the salary market value due to a lack of specialization in more focused domains, or simply due to a low demand for the added skills.

Finally, in a rapidly changing market, compensation data must keep up with shifts in supply and demand for different skills. In programming, for example, some skills have become so common that supply has caught up with demand unlike skills in newer, more niche programming areas where demand exceeds supply . Without an accurate understanding of supply and demand, employers risk overpaying for certain skills and underpaying for others, resulting in challenges attracting or retaining talent.

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A roadmap for a skill-based compensation strategy

Today’s skills economy calls for an innovative approach to rewards that goes beyond role-based compensation frameworks. The following levers can help organizations on their journey to a skill-based reward strategy.

  1. 01

    Define your organization’s current and future skill requirements.

    This involves understanding your organization’s business strategy and identifying the skills your organization needs to drive business results today and over the long term. To identify these skills, it’s critical to understand the work required by the organization. In particular, special attention should be paid to the skills required to power innovation.

  2. 02

    Implement a career framework

    that accounts for skills (i.e., a knowledge architecture) and allows you to map employees based on predefined skill sets crucial to your organization’s success.

  3. 03

    Assess the skills of your workforce to identify gaps.

    To effectively evaluate employee skills, it’s essential to stay up-to-date with applications that can help you establish a skills inventory while also keeping an eye out for emerging industry-wide standards for skill badging/skill assessments.

  4. 04

    Ensure that your skills assessment is used to inform upskilling and reskilling, talent mobility and talent sourcing initiatives.

    Non-monetary rewards such as continuous learning and reskilling, and skill-building work experiences are highly valued in a workplace where sought-after skills are constantly changing.

  5. 05

    Use market pay data solutions

    that deliver skill premium valuations based on actual pay data submitted by HR professionals and job descriptions, and ensure there is a solid governance that allows you to repeat year-over-year your potential differentiated approach for skill-based benchmarking.

  6. 06

    Determine your strategy for paying for skills

    Consider the range of approaches to differentiating rewards for the specific skills your organization requires.

  7. 07

    Avoid the risks of mass customization of rewards.

    Data science and machine learning are opening up opportunities for the mass customization of rewards, enabling employers to reward top talent based on individual characteristics, needs and preferences. However, reward professionals need to be mindful of the risks associated with this approach. First, mass customization initiatives need to be aligned with your fair pay agenda to ensure that such an approach does not create unfair differences in pay or unexplained differences in pay that could be perceived as unfair. Second, such initiatives risk failing without robust internal and external market data to help predict the value of skills. For example, our SkillsVue application uses proprietary machine learning algorithms to analyze real-time skills data, calculating the value of skills on a granular level and the resulting impact on pay.

  8. 08

    Last but not least

    Last but not least; skills are only of value if your organization can fully utilize them to complete work projects and make it worth the effort for your talent to acquire them.

How are employers compensating critical skills?

75%
Anchor employees at the higher end of the salary band
65%
Anchor job base salary at a higher market percentile
45%
Providing a hiring and/or retention bonus.
35%
Provide an additional equity grant
30%
Skill premium on top of base salary

Source: Willis Towers Watson 2019 Artificial Intelligence and Digital Talent compensation survey

This shift requires a new approach that includes a focus on the skills required to get the work done

Given the changing nature of work and ever-shifting skill requirements, HR and reward professionals are increasingly looking to move beyond role-based compensation frameworks. This shift requires a new approach that includes a focus on the skills required to get the work done, and accurately market pricing a set of skills. Our roadmap helps chart a path to this new reward strategy that accounts for skills.

Authors


Senior Director, Innovation and Digital Transformation
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Global Product Lead SkillsVue and Artificial Intelligence and Digital Talent Survey
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