Data Driven Benefits for Retention

Data-driven decision-making (DDDM) is the tactic of using relevant data to help make business decisions. In the past, particularly with regard to human resource functions (in contrast to financial, operational, or technological matters), many decisions were made based on intuition, experience, and qualitative assessments.

While these factors serve an important role, they do not offer the level of objectivity or accuracy that data can provide. The advent of today’s data-driven analytics can empower HR professionals to make evidence-based decisions for a stronger impact on business goals. In fact, a recent PwC survey of more than 1,000 senior executives concluded that data-driven companies have improved business decisions by more than threefold over companies that have not adopted data-driven analytics.

Collecting and analyzing data serves several purposes. First, it establishes a benchmark of present circumstances. In a sense, it conveys a story about your organization with an objective, unbiased look at the status quo. Next, the data may suggest changes to alter or improve a current situation that may substantiate, or dissuade, gut instincts and traditional norms.

 Employee Benefits Decisions

HR professionals can take advantage of data-driven analytics to transform ways to attract, develop, and retain employees – ranging from upper management to key talent to rank-and-file workers. For example, deploying data collection and predictive analytics can identify those who are at risk of leaving, which gives HR the opportunity to address their concerns and improve retention.

Collected data also can help determine what benefits to offer. Not only does a strong benefits package make employees feel supported, but it also creates a disincentive to leave the company. Recognition that the range of benefits enjoyed by a worker and her family may not be offered elsewhere can eclipse the lure of a higher paycheck.

To help determine which benefits have the most impact on retention, consider gathering data specific to:

• Employee demographics (age, gender, education, experience, tenure)
• Performance data (metrics related to productivity, quality/quantity of work)
• Real-time feedback (employee engagement surveys, pulse surveys, focus groups)
• Recruitment metrics (time-to-hire, cost-per-hire, candidate sources, recruitment process efficiency)
• Retention data (turnover rates - by department, location, manager; reasons for leaving; exit interview feedback; turnover costs, both collectively and by position)

Engagement Surveys: Open-Ended Questions

It is easier to offer multiple-choice questions to synthesize data, but gathering data shouldn’t be about providing predetermined answers from which to choose. Instead, by asking open-ended questions, ensuring anonymity, and offering substantial time and space to respond, an employer sends the message that it really wants to know what workers think. While it may not be as easy to compile data via pre-set answers, it is easy to detect patterns of common opinions.

In your questionnaires, ask tough questions that make it clear that the company understands what is at stake. For example, ask what types of benefits would make a worker think twice before changing jobs, and what workers believe are standard benefits they can get anywhere. Ask open-ended questions about the types of benefits they would like to see added, and what types they’ll never likely use. In addition to asking about specific benefits, consider asking the types of problems workers have in their everyday lives so that your HR department can brainstorm on what types of benefits would help alleviate those issues.

It is important to link benefits directly to retention in order to establish which ones have a real impact on their decision to stay or seek a position elsewhere. You can even ask if they are considering leaving the company and what is their timeframe for making a change. Ask if they would consider a lateral move within the company over seeking a new employer.

Surveys and focus groups can help establish patterns of contentment or dissatisfaction, and can even pinpoint specific departments, locations, or other areas of the organization that excel or perform poorly for retention.

Data Analysis

There are many types of advanced analytics tools and software available to help HR professionals interpret the data collected. For example:

• Human Capital Management (HCM) Systems (integrated platforms that provide analytics capabilities and manage HR functions)
• People Analytics Software (designed to analyze HR data and offer actionable insights)
• Business Intelligence (BI) Tools (platforms that offer data visualization, reporting and dashboard capabilities)
• Descriptive Analytics (compares current and historical data to identify trends and relationships)
• Diagnostic Analytics (examines data to determine the causes of trends and correlations between variables)
• Predictive Analytics (forecasts future trends and outcomes based on historical data)
• Prescriptive Analytics (recommends actions for desired outcomes based on predictive models)

Follow-Through

Analyzing collated data can help HR identify trends in order to improve the scope of benefits offered and consider new ones. However, one of the most difficult tasks of accumulating data is: What now? Even when problems appear to be universal and glaring, solutions are not always as obvious. The key is to do something, even if it requires incremental changes. In this scenario, it can be helpful to publish a roll-out plan and then solicit feedback as to how the incremental changes are working and being accepted by employees.

A data-driven approach also helps improve employee engagement. When employees feel that their opinions and feedback are valued, they are more likely to be engaged in their work. Using data to understand employee engagement levels and make improvements can lead to better engagement and increased productivity. When employees are satisfied with their jobs and feel engaged in their work, they are less likely to leave.

Measure Efforts

While you continue to get subjective feedback on changes made to benefits offered, it is also important to accumulate hard data, such as how many workers increase their utilization of incumbent benefits, how many are trying out new ones, and how many people have left the company since embarking on this effort. Not only should you compare these internal numbers year-to-year, also compare them to common industry benchmarks.

Look for Patterns

A big part of the data analysis process is being able to visualize the collection effort to create a tangible story. It can be challenging for decision makers to make sense of a spreadsheet full of numbers. Create meaningful charts and graphs to help others visualize the results, as well as add subsequent data over time in order to identify trends, successes, and failed efforts.

Retention Benefit Strategies

With accurate and relevant data in hand, HR can intervene with targeted retention strategies, such as address workplace issues or provide tailored benefits. For example, some workers may consider leaving if they feel they have advanced as far as they can with their current employer. By identifying high-risk employees, HR can proactively offer additional career training and development opportunities, mentorship programs, clear career paths and opportunities for advancement.

Other employees may be frustrated by an inability to balance their workload with their personal life obligations. Retention benefits can include more flexible work arrangements, such as a flexible schedule as needed, reduced hours or job sharing, or the ability to work remotely to eliminate a long commute.

Recognize that not all employees have the same appreciation of all benefits. Some may value physical/mental wellness and financial planning, others may prioritize development and advancement opportunities, while still others may insist on flexible work arrangements. It can be useful to use benefits data to segment your workforce by preferences and tailor offerings accordingly. This can help HR design segmented benefits packages to help reduce turnover.

Retention ROI

Employees today want more than just a paycheck. They seek work that is meaningful and an employer that provides for their family and lifestyle. These goals are supported by less traditional benefits, such as flexibility, wellness, and personal advancement.

Much of today’s data analytics is applied in areas such as finance and marketing. In fact, a recent Mercer report found that 80 percent of HR departments still gather and analyze data via spreadsheets. The lack of strategic, evidence-based benefits planning in HR offers a competitive opportunity for employers willing to invest in data accumulation and analytics.

Is it worth the cost? That depends on how important your employees are to your organization. Industries that thrive on human capital can save substantial time and money by retaining talented workers rather than continually recruiting and replacing them. Even those whose operations are driven by low-skilled workers can reduce turnover, training costs, and improve productivity by tracking and analyzing the impact of their benefits package.

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