Introduction:
Reward management analysis has become an increasingly important topic for organizations seeking to attract, retain, and motivate top talent in a highly competitive market. Many leading HR consulting firms, including Mercer, Aon, Willis Tower Watson, Korn Ferry, and Hay Group, have produced a range of articles and blogs on the topic, offering insights and recommendations for improving reward practices in organizations.
Mercer's article "The evolving role of rewards in talent management" (Milligan & Wilson, 2016) highlights the importance of rewards in today's talent management practices. The article identifies the latest trends and best practices in reward management and emphasizes the need for companies to adopt a strategic and multifaceted approach to rewards that aligns with business goals and values.
Aon's article "Unlocking the potential of total rewards" (Aon, n.d.) discusses the concept of total rewards and emphasizes the need for companies to create a more holistic and engaging approach to rewards that aligns with business goals and values.
Willis Tower Watson's article "Creating a reward strategy that works" (Willis Tower Watson, n.d.) provides insights into how companies can design and implement effective reward strategies that meet the needs of employees and align with business goals. The article emphasizes the need for companies to take a data-driven approach to reward management and to consider the impact of rewards on employee engagement and productivity.
Korn Ferry's article "The future of rewards" (Korn Ferry, n.d.) discusses the impact of digital technology on reward management and offers insights into how companies can use data analytics and digital tools to improve reward practices. The article emphasizes the need for companies to move away from traditional and static reward structures and adopt a more dynamic and personalized approach to rewards.
Hay Group's article "Reward strategies for the modern workforce" (Hay Group, n.d.) emphasizes the need for companies to create reward strategies that meet the needs and preferences of today's diverse and multigenerational workforce. The article provides insights into the latest trends in reward management and offers recommendations for creating a more engaging and personalized approach to rewards.
These articles provide a wealth of insights and recommendations for improving reward practices in organizations. However, in the post-COVID-19 era and with the emergence of AI and rapid edge computing, work has changed significantly. The nature of reward also includes work flexibility like remote work options, hybrid work options, and the meaning of work now includes purpose, environmental sustainability, and social responsibility. Furthermore, society is now recognizing the need for work mental wellness, work stress balance, and gender equality in pay.
CFOs and activist investors now want to know the ROI (return of investment) on the combined pay package computation across all jobs in an instant. With the proliferation of digital transformation and software as a service, workers are now also indicating if they can BYOS (bring your own stack) and BYOD (bring your own devices). These vast permutations of elements to compute a rewarding package for talent were previously a dream, but now with AI and big data, reward management analysis can make personalization of reward a reality.
This article provides a case study of a past business example and provide future directions for researchers and practitioners to stay ahead of the curve and adapt to the changing nature of work and reward practices. The key to success will be embracing new technologies and methodologies to stay competitive and attract, retain, and motivate top talent.
Background:
Few years ago, a HR consulting firm was approached by a manufacturing company to conduct a reward management analysis. The President of the company was a firm believer in pay for performance and wanted to establish a salary structure to manage rewards for employees in the organization. The company had never conducted a reward analysis before, and the new HR management team took this opportunity to start establishing this process.
The President's goal was to instill a meritocratic way of growing the business by establishing a salary structure based on pay for performance. Currently, every staff was paid on bonuses and variable salary on a homogenous scale, which did not take into account individual performance or contribution. There was also a lack of understanding about reward management practices within the organization.
To address these issues, the consulting firm proposed to identify a number of benchmarked jobs to be evaluated and compare the current pay package with the market practices from companies of similar size in the local market. This process would enable the client's Group to accurately benchmark current and proposed remuneration packages to appropriate market levels through synergies with the administration of salary bands. The client's Group would then have the necessary knowledge to manage efficiently the Compensation system and Reward policy for its operations in Eindhoven, Bangi Malaysia, Singapore and Wuxi, China.
The HR consulting firm was chosen for their expertise in reward management and their ability to provide an objective and data-driven approach to developing a salary structure based on pay for performance. With the implementation of this process, the company hoped to create a more equitable and performance-based culture, which would in turn help to attract and retain top talent and drive business growth.
Overall, the reward management analysis was a critical step for the company in establishing a more effective and strategic approach to compensation and reward management. The consulting firm's expertise and guidance played a key role in enabling the company to achieve its goals and establish a more meritocratic and performance-driven culture.
Approach:
The consulting team recommended that the client use a job evaluation methodology as the first step in establishing a salary structure based on pay for performance. The job evaluation methodology involved anchoring the core job family using the job evaluation method and then mapping out the hierarchy of job families and job size of other jobs relative to the core job family using the job mapping method. This approach would enable the client to get a robust job size of the core job family and quickly map out the other jobs, while preserving sufficient robustness to evaluate the job size across all job families.
To determine the most appropriate job evaluation methodology, the consulting team analyzed the job evaluation methods used by Hay Group, Mercer, Aon, and Towers Watson, as requested by the client. They found that these firms were using the point factor method, which involved breaking down jobs into a set of factors or criteria, assigning each factor a point value, and adding up the points to determine the job's overall value.
Based on the analysis, the consulting team recommended using the point factor method on the core job family and the job ranking method on other job families with reference to the core job family. The job ranking method involves ranking jobs in order of importance based on a set of predetermined criteria. Jobs are ranked from highest to lowest in terms of their importance to the organization. This approach would enable the client to quickly and effectively evaluate job size across all job families.
After the job evaluation methodology is established, the next step is to collect employee data and pay data to map out the salary structure. The consulting team would then perform a salary benchmarking analysis, consisting of internal equity analysis and external competitiveness analysis. This analysis would enable the client to compare their compensation practices with those of other companies in the local market and make necessary adjustments to maintain a competitive and equitable salary structure.
Overall, the job evaluation methodology was a critical step in establishing a robust and effective salary structure based on pay for performance. The consulting team's expertise in job evaluation and methodology selection played a key role in enabling the client to achieve their goals and establish a more meritocratic and performance-driven culture.
Result:
Once the job evaluation was completed and the data (pay and employee data) was fed into a database, the consulting team was able to complete the salary structure and perform internal equity and external competitiveness analysis. These analyses provided critical insights that enabled the board and management team to make necessary adjustments to their pay policies and attract, retain, and motivate top talent in a highly competitive market.
The internal equity analysis revealed areas where job families were not in alignment in terms of pay deviation. With this insight, the management team was able to make pay policy adjustments and keep their top talent motivated and engaged. The analysis enabled the company to maintain a competitive and equitable salary structure, which was critical to retaining and attracting top talent.
The external competitiveness analysis provided the management team with insights into which job families were in high demand relative to others, and how competitive their pay package was relative to the market. Armed with this knowledge, the company was able to adjust its compensation practices to remain competitive and attract top talent. By combining the internal equity and external competitiveness analyses, the management team was able to make informed decisions about pay policies and maintain a strong and engaged workforce in the age of war for talent.
Overall, the reward management analysis was a critical step for the company in establishing a more effective and strategic approach to compensation and reward management. The analysis provided the company with the necessary data and insights to make informed decisions about pay policies and attract, retain, and motivate top talent. The consulting team's expertise and guidance played a key role in enabling the company to achieve its goals and establish a more meritocratic and performance-driven culture.
Further Areas of Research and Improvement:
The emergence of the gig economy, remote work, and the increasing demand for work-life balance, gender equality in pay, mental wellness, and social responsibility have all led to significant changes in the nature of work and reward management. In addition, the proliferation of digital transformation and software as a service has resulted in workers increasingly requesting the ability to BYOS (bring your own stack) and BYOD (bring your own device).
These factors have made reward management more complex and challenging than ever before, and it is critical for reward managers, compensation and benefits specialists to stay ahead of the curve and adapt to these changes. The advent of AI and big data analytics can help make personalization of rewards a reality. However, for such computation to be a reality, reward managers and compensation and benefits specialists need to develop new skills, such as HR data science, computational economics, statistical programming, sustainability, and DEI.
There is also a need to develop new methodologies and tools to effectively evaluate and benchmark the ROI on the combined pay package computation across all jobs. The emergence of activist investors and CFOs who demand transparency in the ROI on the compensation package computation across all jobs has further increased the need for new tools and methodologies.
Moreover, with the growing importance of work flexibility and the changing nature of work, reward management needs to adapt to the new realities of work. New reward management frameworks need to be developed that take into account the flexibility of work, environmental sustainability, social responsibility, and purpose. These frameworks need to be adaptable to different forms of work, such as full-time, gig, seasonal, fractional, job share, part-time, contract, and temporary work.
In conclusion, the future of reward management analysis will require significant adaptation and new skill sets to effectively evaluate and benchmark the ROI on the combined pay package computation across all jobs. New reward management frameworks and tools need to be developed to adapt to the new realities of work and to meet the growing demand for transparency, personalization, and flexibility in rewards. The key to success will be staying ahead of the curve and embracing new technologies and methodologies to stay competitive and attract, retain, and motivate top talent.
Disclaimer
It is important to note that the quantified numbers have been masked to protect the identity of the company. However, the findings and recommendations are based on rigorous analysis and research and can be applied to other companies facing similar recruitment challenges.
References
- Milligan, G., & Wilson, D. (2016). The evolving role of rewards in talent management. Mercer. Retrieved from https://www.mercer.com/content/dam/mercer/attachments/private/gl-2016-talent-trends-talent-rewards.pdf
- Aon. (n.d.). Unlocking the potential of total rewards. Retrieved from https://www.aon.com/getmedia/4e4d880c-3c75-4ad7-b6d4-bd9d9c41df2b/Aon-Unlocking-the-potential-of-total-rewards.pdf.aspx
- Willis Tower Watson. (n.d.). Creating a reward strategy that works. Retrieved from https://www.willistowerswatson.com/-/media/WTW/PDF/Insights/2019/03/creating-a-reward-strategy-that-works.pdf
- Korn Ferry. (n.d.). The future of rewards. Retrieved from https://www.kornferry.com/content/dam/kornferry/docs/pdf/the-future-of-rewards.pdf
- Hay Group. (n.d.). Reward strategies for the modern workforce. Retrieved from https://www.kornferry.com/content/dam/kornferry/docs/pdf/the-future-of-rewards.pdf