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Use Big Data to Improve Your Benefits Program


Big data relates to the massive amount of information that businesses come across every day. In the past, employers were hard-pressed to keep up with and properly analyze copious amounts of data. Now, with the advancement of technology, data can be collected and processed at a much higher velocity. After the data has been gathered by a system, it can be used to identify trends, forecast outcomes and formulate business decisions.

In the context of employee benefits, employers need to know whether the programs being offered are effective — and what to do if they are not. Companies can reach conclusions by collecting, mining and analyzing large sets of data.

Below is an example of how big data and metrics can be used to better understand benefits usage and costs for health and wellness plans.

Metric: Cost drivers

Determine the main employee health conditions driving employer cost. For instance, do you have employees who smoke and would like to quit? If so, what is the cost of implementing a smoking cessation program? Studies show that other leading conditions impacting employer cost include diabetes, cancer, arthritis, obesity, heart disease, hypertension and depression.

Metric: Participation rate

Determine how many employees are participating in your health and wellness plan. Also identify whether any programs are being underutilized and whether they should be scrapped. A potential solution would be to communicate underutilized programs more aggressively to employees and then check to see whether an increase in utilization follows. If there's no increase, you may want to reinvest the money into other benefits that are more valued.

Metric: Satisfaction level

Determine how employees feel about the program. Are they happy with it? Are they complaining about it? Based on the results, you may or may not need to make changes to the program.

No boilerplate formulas

Every benefit is unique, so you'll need to adjust the metrics to fit the benefit in question. For example, when analyzing big data for your 401(k) plan, be sure to evaluate not only demographics and participation rate but also deferral rates. Assessing deferral rates will reveal how much money employees are contributing to their 401(k)s and whether there are employees who aren't taking advantage of the full company match.

Working with big data requires wading through the noise to get to the stuff that truly counts: the meaningful data that will help you make the decisions that are right for you and your employees. The breadth of this endeavor is voluminous, often consisting of several moving parts — such as the payroll provider, the benefits carriers, the third-party administrator, and the on-site HR and payroll teams. A collaborative approach will help ensure reliable, data-driven decisions.


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Our firm provides the information in this e-newsletter for general guidance only, and does not constitute the provision of legal advice, tax advice, accounting services, investment advice, or professional consulting of any kind. The information provided herein should not be used as a substitute for consultation with professional tax, accounting, legal, or other competent advisers. Before making any decision or taking any action, you should consult a professional adviser who has been provided with all pertinent facts relevant to your particular situation.The information is provided "as is," with no assurance or guarantee of completeness, accuracy, or timeliness of the information, and without warranty of any kind, express or implied, including but not limited to warranties of performance, merchantability, and fitness for a particular purpose.
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