How Data and Analytics Can Optimize HR Programs

How Data and Analytics Can Optimize HR Programs
How Data and Analytics Can Optimize HR Programs
Human Capital Analytics

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This insight is part 09 of 09 in this Collection.

Insights for HR

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This insight is part 03 of 10 in this Collection.

May 9, 2023 10 mins

How Data and Analytics Can Optimize HR Programs

How Data and Analytics Can Optimize HR Programs Hero Image

Pressure to reduce costs in response to a challenging economic environment highlights the pivotal role data and analytics can play in optimizing business investment in talent and future growth.

Key Takeaways
  1. Use data to determine where the biggest impact can be made with your workforce, including location strategy, headcount and compensation and benefits.
  2. Assess employees for future skills and potential — then invest in these individuals through total rewards and career development.
  3. Leverage existing data such as employees’ usage of paid time off in new ways to determine how to make total rewards more impactful.

With costs continuing to rise amid ongoing economic headwinds, organizations are struggling to keep compensation and benefit programs affordable. For example, the cost of healthcare is rising globally, and many employers are dealing with higher compensation costs from paying above average new-hire salaries during a tight labor market. This creates a delicate balance: Companies want to continue to attract and retain talent through robust total rewards while maximizing their investment and making programs cost effective.

Through data and analytics, organizations can optimize their spending to achieve the best possible outcomes. But finding the right data, contextualizing it properly and using it to make better decisions about spending is easier said than done.

There are several types of data that can be used to drive decision making.

  • Descriptive and Contextualized — Identify the facts of the current situation and what has already happened within the context of the broader competitive landscape (e.g., benchmarking).
  • Predictive or Scenario-Based — Identify what could happen in the future or modeled against certain criteria.
  • Prescriptive — Recommend the optimal course of action or strategy moving forward.

When deployed thoughtfully, data and analytics can contribute to better decisions about large-scale structural issues like overall talent strategy, location strategy, reward and benefit programs, organizational design, and diversity, equity and inclusion (DE&I) initiatives. Here are some ways organizations can use internal and external data to gather insights and make more informed decisions that generate significant return on investment.

Determine the Most Impactful Ways to Optimize Your Workforce

Before making any major changes to your total rewards, assess current and future workforce needs to optimize spend. Protecting critical capabilities should be the most important goal. Benchmarking in areas like headcount, location strategy, compensation and benefits can identify where costs are higher than your peers and if you’re achieving target return on investment for the spend.

Using Data and Benchmarking to Inform Location Strategy Decisions

Benchmarking across multiple data points is critical to making informed decisions with optimal impact. We worked with a technology firm on location strategy for skilled technology specialists. In determining the client’s optimal site to hire and retain talent, we assessed several of their active working locations. By scoring five different markets (two different cities in the U.S., two in the UK and Tokyo, Japan) on six different categories, including labor supply, labor cost, expected employee growth and others, the recommendations were narrowed down. The resulting scores showed that Tokyo was the clear choice. This underscores the need to look at multiple data points. Focusing only on the general cost of living may have resulted in the incorrect conclusion that Tokyo would be a less attractive option.

Use Talent Assessments and Market Data to Learn More About Current Talent

Workforce agility is a major component of building a sustainable working life for employees. Part of that agility is knowing what skills employees have or need to do the job you want them to — both now and in the future. While many companies use talent assessments to hire candidates, also using them to inform your decision-making process adds great value. The data from assessments can be reviewed to understand key insights, such as:

  • Critical talent for targeted retention programs
  • Future skills (both softer skills and technical ones) you may already have within your organization that can be leveraged for new types of jobs to drive growth
  • The resiliency of your organization overall and through different population segments

For example, based on an analysis of 15 million assessment participants taken by Aon clients annually, we found that individual resilience increases with people’s age over the past four years. Those aged 60 years and above are the most resilient; the under-20 group is the least resilient. Senior managers and customer service jobs tend to have the most resilient employees, with apprentices and recent graduates the least. Taken together, this data suggests that age is an important factor in building resilience. Data like this provides insights for employers to assess existing HR programs and target them to certain employee groups. It can also be used to measure the effectiveness of building resilience over time.

45%

Companies that are assessing employees for agility, adaptability and digital skills.

Source: Aon Global HR Pulse Survey, 2021

Agility Leads to Savings in Reskilling and Upskilling Workers

An investment bank in the U.S. assessed its skill base by using market data to better understand what new skills it needed to execute technology products and which jobs were at risk of automation. Rather than mass layoffs followed by hiring new workers with the desired skills, the bank created a program to engage, understand and reskill more than 1,000 workers over a few months. Based on organizational data, we found that the cost of hiring new employees would be 10 percent higher than industry estimates due to recruiting costs, severance packages and the detrimental impact on staff morale.

People data was used to quantify the opportunity, redeploy affected employees into new roles and determine how many would be prepared to successfully reskill. The resulting savings were significant, estimated at $150 million. Additionally, the bank was able to preserve its company culture, values and reputation by keeping employees’ jobs.

Leverage Tools to Reduce Costs that Also Support Your People

Supporting your existing employees by optimizing total rewards and benefits is valuable for a few reasons. Cost savings are an obvious benefit, but there’s more: A resilient workforce means employees’ needs are being met by the benefits offered.

When looking at health benefits, data can play a huge role in program optimization. And much of that data is readily available. Insurance claims data, the number of days off employees take and workplace safety data are just a few things companies can look at to see which programs are working and which can be improved. These are all cost optimization tools that can also support talent development. For example, utilization data may show that an expensive benefit program is not providing the impact it should, allowing you to replace it with something more appropriate. Or, if a program meets identified employee needs but is still underutilized, the company can improve its communications around the program.

Using Data to Inform Benefit Decisions

Benefits are most effective when the design and messaging are aligned with employee priorities. This involves a degree of personalization since not all employees value or want the same things. Collecting data on employee preferences and needs and then leveraging that data for customization purposes can help maximize the employee value proposition (EVP).

Traditional approaches to benefit customization typically group employees by generation (e.g., people in their 20s value gym memberships, while people in their 30s and 40s value childcare). But while there may be some variations by age, there is far more knowledge to be gained by surveying employees’ preferences and categorizing lifestyles.

The result is data-led personas. These guide organizations by standardizing and categorizing employee lifestyles so that the company can tailor its benefits and perhaps just as importantly, its benefit communications.

Health, Equity and Affordability

Another area where data and analytics can play a role in optimizing spend is around health, equity and affordability. Health outcomes and costs differ depending on where employees live. These social determinants of health (SDOH) can affect a population’s health, ranging from access to primary care services and pharmacies to the availability of transportation and healthy food options.

With a few key data points from a company’s census, predictive analytics can be used to create insights related to SDOH, which can pinpoint the greatest health disparities leading to higher costs. This allows an employer to target preventative and other lower-cost solutions toward the portions of their workforce who need it the most. Doing so can not only help optimize healthcare spend, but it can also help organizations meet their DE&I goals (read more about DE&I trends in Aon’s 2022 Global DE&I Survey).

Refine and Integrate Your Wellbeing Strategy

Data has become a major factor in wellbeing strategies. We know that allocating funding to wellbeing programs, once seen as a perk, directly affects company performance. Improving your employees’ sustainable working life has the potential to increase company performance by between 11 and 55 percent, according to Aon’s 2022-2023 Global Wellbeing.

Connecting Wellbeing to Cost and Performance

Aon’s Wellbeing and Business Performance Dashboard allows companies to quantify their progress in five key areas of organizational resilience. The dashboard tracks from the organizational level down to the individual level. It tracks progress across key metrics and uses predictive analytics to show how those metrics will affect costs and performance. HR leaders can see at a glance the resilience of their organization and what can be done to improve it.

By using data to take an all-encompassing perspective on performance and wellbeing, companies can offer a richer colleague and client experience. They will also be able to design better ways for their workforces to bounce back, innovate and sustain themselves over time.

In practice this may mean committing to new ways of measuring wellbeing, such as the Human Sustainability Index, and educating and empowering people to make meaningful changes for themselves, their teams and ultimately their organizations.

As we saw during the pandemic, workforce resilience is key to how a company performs during times of volatility. The same is true during uncertain economic conditions, where resilience remains critical. Only about half of companies rate their employees’ resilience as “excellent” or “very good.”1 But that number is rising, in part because of the investment companies have made in wellbeing.

Using Data to Make Better Decisions

Having the right data and analytics won’t make difficult decisions for you — a big part of the process is knowing what and how much data to collect and analyze. But it will give leaders the confidence and clarity to make decisions and communicate them more clearly to others. Managing through difficult economic times means making better decisions. Having an advisor that can help separate the signal from the noise will make the data more useful, and lead companies to be better informed and better advised.

1 https://www.aon.com/global-wellbeing-survey

General Disclaimer

The information contained herein and the statements expressed are of a general nature and are not intended to address the circumstances of any particular individual or entity. Although we endeavor to provide accurate and timely information and use sources we consider reliable, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the future. No one should act on such information without appropriate professional advice after a thorough examination of the particular situation.

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