Assessing the ‘Employee Experience’ through targeted listening and research   

Written by Peter Foley and Kelly A. Blue


Organizations continually evaluate and evolve their employee value propositions (EVPs) to ensure they are offering a compelling employee experience (EX).  While economic cycles and demographic changes have played a role in this, more recent shifts – discussed below – are forcing organizations to re-think their EVP strategies to adapt to a ‘new normal’.

Listening techniques such as conjoint analysis or ‘maxdiff’ (best-worst scaling) have long been deployed by market researchers to better understand consumer preferences.   These methodologies present consumers with different product attributes (e.g., brand, price, product features), and ask the respondent to choose among different combinations of attributes.  The pattern of choices they make are then analyzed to determine the specific attributes (or combination of attributes) that are likely to drive consumer purchasing decisions.

While management consultants have used these same tools for well over two decades now, the level of organizational interest in this type of employee listening has grown exponentially over the past 15 years. 

Similar to consumer research, organizations are seeking to better understand how their employees ‘consume’ different elements (e.g., benefits) that are offered as part of their employment package, as well as assess, more broadly, which aspects of working for the organization are the most/least attractive.  This includes ‘softer’ elements such as work-life balance, diversity & inclusion, wellbeing and purpose, as organizations seek to provide a more human-centered employment experience.


We believe the rapid expansion in the use of “employee preference research” is the result of multiple factors:

  • The 2008 economic crisis
  • Significant, and rapid, demographic change1
  • Progressive ‘shifting of risk’ from employer to employee2
  • Uncertainty across the U.S. healthcare landscape3
  • Important shifts in the traditional employer-employee relationship4

We believe the current environment will only accelerate the need for organizations to measure and assess their overall EVPs.  While we have been living with the Coronavirus pandemic for months now, organizations are just beginning to think through returning to work and what the ‘new normal’ will look like.

As these changes unfold and become the ‘new normal’, organizations will need to assess how effectively they are optimizing their overall spend (measuring the ROI of investments in rewards, benefits and other people programs), as well as monitor how employees are modifying their behaviors (e.g., telecommuting, benefits choices and coverage levels) in the face of new choices. 


In our experience, an effective preferences survey must be customized to each organization’s unique EVP, and be grounded in a thorough understanding not only of their current offering, but also potential future changes that the organization is contemplating.  Any number of factors such as cost, the competitive landscape, or an anticipated shift in the skill sets required to realize the company’s business strategy, might drive these potential changes.

For organizations with operations in multiple countries, this necessitates a unique survey design for each country or region, as the overall EVP varies significantly across geographical boundaries due to statutory and cultural differences.

As stated above, an employee preference survey presents the respondent with sets of alternatives from which the employee must pick.  For example, we might ask if the company match on the 401(k) is more valuable than the ability to telecommute 1-2 days a week.  Typically, the respondent sees 3-4 choices at once, and must select the most valuable and least valuable elements, then move on to the next set.  These comparisons are repeated in a ‘balanced design’ to ensure that all alternatives are compared to one another. 

The resulting analysis generates what is known as a ‘utility score’.  A higher utility score means that a given EVP element has higher utility – or usefulness – to that respondent.  Sticking with our example, if an employee picked the opportunity to telecommute over the 401(k) match, telecommuting has higher utility, meaning it is more valued by that employee.

While an employee preference survey is a critical piece in helping organizations evaluate and evolve their EVP, several other key elements, if added, will greatly enhance the organization’s ability to assess this proposition more holistically.

  • Cost analysis:  Understanding the overall cost of individual programs/benefits, as well as testing scenarios for change based on preference survey responses .
  • Market competitiveness:  Evaluating how well the current pay and benefits compare to the broader labor market and/or a specific peer group with which the organization competes for talent.
  • Personas research:  Leveraging employee demographic and other data to group employees into personas based on life stage and individual needs.
  • Program utilization:  Assessing the choices that employees are making (e.g., healthcare plan choice, retirement deferral rates) and how effective those choices are.

The first two elements, while important, are self-explanatory and commonly incorporated into the overall strategic analysis.  The second two, however, are more recent tools, particularly in how they can intersect with the employee preference data.

Personas Research & Program Utilization

Personas research is an excellent complement to any employee preference survey.  Most organizations do some regular form of employee sensing that yields insights regarding how employees feel about the overall work experience (type of work, supervisor relationship, culture, career opportunity, engagement, etc.). 

These data points tell us how people feel while they are at work.  Our research has taught us, however, that it is equally important to understand who people are more holistically, including their lives outside of work.  Personas research fills that gap and paints a picture of your workforce based on a multi-dimensional view of their life stage, socioeconomic conditions, and behavioral trends.

This data-driven approach allows personas to be derived from a few key demographic characteristics such as age, income, and company tenure.  Additional layers of data are then added such as socioeconomic status (e.g., median family income, median home value), as well as consumer behavioral data (spending trends, lifestyle traits, decision-making mindset).  The resulting personas provide the organization with a much richer understanding of who their employees are as distinct individuals, and not just the job they perform at work.  The mosaic of data for each persona enables the organization to better empathize with employees’ perspectives and needs.

A simple example will illustrate:

Let us take two Millennials, both 38 years old.   With the insights provided by personas, we can surface details that show one employee is single, without children and renting in a downtown/urban setting, having just joined the organization 3 years ago.  The other employee lives in a suburban setting, with a mortgage, three children, and has been with the organization for 17 years.  While both belong to the same generational group, these very different life situations directly influence not only benefits needs and choices, but also expectations about the overall employment relationship.  Simply looking at Millennials as a monolithic group would miss this critical perspective.

Once personas are defined, an in-depth analysis of benefits elections can be undertaken, summarized by persona group.  Examining health, wellbeing, retirement, and voluntary programs provides a rare opportunity to view usage trends across the spectrum of benefits offered.  This analysis yields tremendous insights around overall program usage, often illuminating behaviors that are not in the employee’s long-term best interests.  Examples might be over-insuring through their healthcare plan selection, failing to take full advantage of a company 401(k) match, or not leveraging an FSA/HSA to lower the employee’s overall tax rate.  This view of benefits utilization provides a dramatic underscore to survey results, bridging what employees say about benefits to what they do with their benefit elections.


Employee preference research is a highly effective approach to understanding the degree of alignment between employees’ expectations and the organization’s overall EVP.  It can also be used to test alternative scenarios before changes are implemented.

When combined with other techniques such as personas development and program utilization, organizations can build a holistic view of the overall competitiveness of their EVP strategy.

For more information contact Rhonda Gettelman at 312  852 6339 or

About the Authors

  Pete Foley, Ph.D.

Pete Foley is a Senior Principal within Mercer’s Career segment, based in Atlanta.  Pete works with Mercer clients around the globe to improve their bottom-line performance through more effective management of their talent.  Pete’s work has covered all aspects of talent management including employee research, talent strategy, internal / external labor market analysis, workforce analytics, and total rewards effectiveness.

Prior to joining Mercer, Pete worked for a leading global research firm as director of their Southeastern U.S. and Latin American practices. He has 30 years of experience in the design and implementation of employee research platforms – particularly for multinational organizations operating in diverse cultural settings.

Pete’s industry experience includes financial services, government, healthcare, higher education, manufacturing, non-profit organizations, pharmaceuticals, professional services, retail, telecommunications and utility/energy, among others. Having worked extensively overseas Pete is fluent in both Spanish and French and conversant in several other languages.

Pete holds a BA in Psychology from the University of Michigan and MS and PhD degrees in Applied Psychology from the University of Georgia.

  Kelly A. Blue

Kelly is a Principal in Mercer’s Health business and a member of the Data, Technology, and Analytics (DTA) team. Kelly employs data to derive insights and surface stories, providing employers with actionable recommendations to accomplish specific strategies. In recent years, her focus has included persona development for use in program design, targeted communications, and measuring outcomes. Kelly has provided analytics to more than a dozen Fortune 100 employers and has consulted to countless other organizations across a variety of industries. While her responsibilities for Mercer are national, Kelly is based in Indianapolis and brings 20 years of consulting experience to her role.

Prior to her current role, Kelly helped to establish Mercer’s US Financial Wellness consulting business. For more than 6 years, she has worked with employers incorporating data analytics and behavioral economics to inform the design and delivery of financial wellness programs customized to meet employees where they are in their financial journey.

Earlier in her career, Kelly was a lead actuarial consultant who specialized in defined benefit retirement plan consulting including:

  • Development of funding strategy and contribution planning,
  • Financial accounting and impact of statutory change
  • Plan design incorporating organizational goals, and
  • Benefits administration and government reporting requirements.

Kelly has a Bachelor of Science degree from Indiana University Bloomington in Mathematics, received with general and departmental honors. She also holds a Master of Arts in Actuarial Science from Ball State University with perfect academic record. Kelly was formerly an Enrolled Actuary and a Member of the American Academy of Actuaries.

1 The oldest Baby Boomers turned 62 in 2008, the first year of eligibility for Social Security benefits in the U.S.  As of 2017, just nine years later, Millennials represented the largest segment of the U.S. workforce and still do today.

2 For example, the replacement of defined benefit plans with defined contribution plans, or the progressive shifting of the overall cost share for healthcare.

3The passing of ACA/Obamacare, and the specter of a single-payer healthcare system have raised uncertainty among the U.S. labor force.

4 Factors here would include AI, automation/robotics, digitalization, the rise of the gig economy, and the Coronavirus pandemic.