Health Care


Connecting Benefits to Employee Satisfaction Through Data-Driven Benefits Insights

Successful employee benefits programs in the modern workforce deliver personalized services, increasing employee engagement and satisfaction. It takes data and analytics to achieve outcomes through more informed decision-making.
— By Kim Persaud

Employee engagement and satisfaction has been proven many times through research that it directly influences everything from productivity to business outcomes. Employee benefits have a direct bearing on the degree of satisfaction, but it has become a complex challenge in the modern workforce.

The workforce is global, multi-generational and diverse, making it more challenging to deliver engaging benefits programs. People's preferences have changed, too, ranging from a desire for more work-life balance to financial planning assistance to improved health benefits to employer-sponsored well-being programs.

Billions are spent on benefits programs, yet employers struggle to get the data necessary to make decisions concerning benefits as engagement strategies. Benefits today must be aligned with employee preferences; leveraged to increase employee satisfaction; and designed to support all employees, not just the younger workforce.

The data is often there for the taking, but it is knowing what data can lead to the most useful insights that really matter in the end and putting the systems in place that support employee needs while generating the data.

Modern Benefits Programs for the Modern Workforce
There is a lot of talk about modernizing benefits. In fact, Willis TowersWatson researched the needs of an evolving workforce in terms of benefits for the modern workforce. Though the study involved Swiss multinationals, it is made clear the companies assessed are not unique.

The findings clearly are applicable to most companies struggling to turn their benefits programs into employee engagement and satisfaction programs. The executives named a number of items on their agenda for modernizing benefits. They include understanding what employees want; aligning benefits with employee preferences to maximize the ROI; and broadening the definition of benefits to include well-being programs, workplace amenities, and flexible work policies.

There were some issues discovered, too. For one, companies were having little discussion on the needs of the more experienced employees, like caregiving for elderly parents. Another was addressing the needs of different workforce groups across business units while simplifying benefits offered.

Achieving such a challenging agenda requires access to data and analytics, or the business risks spending money on benefits people do not care about while not providing the benefits or the services that can increase employee satisfaction and well-being. Employees today expect ease of access and services. The same report found the challenges of accessing the data included gathering it from multiple policies and programs, difficulty in getting required data from insurance companies, legal privacy requirements restricting access to data, and using data to validate hypothetical decisions for program design.

A good benefits program for the modern workforce is a stress-free experience, meets needs, offers flexibility and choice, and all without losing control of costs. Data and analytics are crucial, and they must come from internal and external sources for greatest effectiveness.

More Than Health Insurance Plan Selection
Assessing the relevance of a benefits program to employee engagement requires applying some basic principles.

One is recognizing people are emotional beings who can change, and it is important to use ideas from the science of behavior change and behavioral economics.

Another is to collect the data that makes it possible to predict outcomes in a statistically meaningful way, which includes gathering population-wide insights. Also, the data and statistics should be reviewed by experts in multiple areas of disease prevention, chronic disease avoidance, health and wellness promotion, and health benefits design.

Program design based on data collection and analyzation is only one step. Leveraging the data to drive engagement is another. Employees need personalized approaches to benefits, and data analytics can provide the information needed for good decision-making. There are multiple ways to accomplish this.

One is meeting employee communication channel preferences. For example, some employees prefer texts or emails for reminders to do some type of activity like walking.

Another strategy is to develop a data-driven Web and mobile engagement benefits program platform that serves as a central hub. Employees can use the components that best fit their needs and can engage employees in ways they prefer, like voice, texts, mobile, etc. The engagement platform can use shared data provided by the employer and the employee, i.e. claims, biometrics, etc. Targeted messaging drives employees to utilize tools that improve health, like benefit decision support, and the companies successfully using this strategy lower benefits costs, increase employee engagement, and improve outcomes. It also provides additional data for decision support.

Metrics determining program effectiveness include return on investment (ROI) and value of investment (VOI). The VOI evaluates the qualitative results like higher workplace productivity and increased employee engagement. Key data sets include cost impact, changes in health risks and program participation.

Sending Nudges
Personalization is the important attribute of a modern benefits program. It requires a wealth of data and analytics to know which benefits will deliver the most employee satisfaction without wasting money on programs or benefits employees are not fully utilizing.

Employee surveys remain an important source of feedback data, but they provide limited information. The convergence of data from multiple sources is what can lead to the most employer insights that drive employee satisfaction. In the future, more companies will use advanced technologies like artificial intelligence to improve benefits programs and deliver greater employee satisfaction.

For example, this technology will utilize data from smart wearables and employee benefits platforms to personalize benefits recommendations and generate predictive analytics. It can also deliver personalized "nudges" to help employees stay on track with health and wellness goals.

Every interaction with employees through surveys, online platforms, insurance claims, sign-ups, participation in programs, counselor contacts, text reminders, medical and professional inputs, and so on becomes data that should go into decision-making. The days of relying only on insurance claims as the primary source of benefits program information and decisions are long gone.