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How Well Do You Know Your Leave Data?

Are you able to determine what number of employees are absent from your organization each day? Do you know who’s out, why they are out, and how long their leave duration is anticipated to be? Managing this information on a daily basis sounds overwhelming. But there are solutions in the marketplace today that can help you manage this information while staying compliant, reducing costs, and identifying key trends for business decisions.

A business intelligence solution which includes an integrated leave of absence data warehouse could be the first step toward better understanding your leave incidence, duration and cost. Having the ability to look at trends over time is crucial in maximizing your management efforts of both paid and unpaid leave benefits. In addition, this will give you the knowledge of which locations or departments in your organization are experiencing the highest absence rates or which job types or job schedules are linked with the highest duration.

Do you know which employees are most likely to be out an extended length of time? Of those employees, do you know which ones have the greatest opportunity for early intervention and management?

A daily disability feed from your vendor can be utilized to identify employee absences most likely associated with lengthy absence and/or high cost. But absence length and cost alone aren’t the only factors associated with which absences are the ones presenting the best opportunity for savings. Numerous characteristics of the absence have interplay into the length of the leave. Establishing a high risk score algorithm based on a daily disability feed is a great first step towards best managing those complex claims which are intricate but yet potentially shortened because of improved focus and care.

Do you know the differences in benefits consumption and which benefit plan design changes would be most beneficial to your organization?

An analysis of current disability expenditures might reveal gaps in current disability plan design or provide enlightenment as to which conditions are truly the most costly. Instituting a 90-day eligibility waiting period for new hires has the potential to reduce initial disability incidence if your current plan design offers employee enrollment in disability plans at an earlier day of employment. Furthermore, it might appear that mental health claims are the most prevalent and most costly, when in reality, based on the data, musculoskeletal claims are associated with the largest amount of your disability spend.

Having information, say from pivot tables or disparate spreadsheets only tells you what’s happened in the past. You need to be able to predict what will happen in the future.

Knowing the past is only part of the information you’ll need going forward. You must have a toolset which allows you to forecast the future. A business intelligence solution with an integrated data warehouse can be that predictor which will give you knowledge of your data.