Measured Matters: The Use of 'Big Data' in Employee Benefits. Blakely, S. Technical Report ID 2599767, Social Science Research Network, Rochester, NY, April, 2015.
Paper abstract bibtex Since “big data” is changing so many aspects of the business world, how is it affecting the way health and retirement benefits are provided to private-sector workers? This paper summarizes the presentations and discussion at the Dec. 11, 2014, EBRI policy forum held in Washington, DC, on the topic, “Measured Matters: The Use of ‘Big Data’ in Employee Benefits:” the use of massive amounts of data and computer-driven data analytics to determine how people behave when it comes to health and retirement plans, which programs work or do not, and how to get better results at lower cost. EBRI’s 75th biannual policy forum last December delved into both the status and promise of this trend before an audience of about a hundred benefits professionals and policymakers. Two panels of experts -- one focusing on health and the other on retirement -- provided an overview of what employers, researchers, and data analysts are currently doing, what they hope to be doing, and what seems to be working so far. Speakers included employers, research and analytic experts, health and retirement plan executives, and consultants. Among the broad areas of agreement: Employers and researchers are making a major commitment to capturing and analyzing the vast amount of health and retirement data in their benefit plans; the health sector is considerably farther down the road than the retirement sector in using data analytics in benefits plan design and management, but both fields are in the very early stages of using big data; many workers are already seeing the results of this trend, such as the rapidly growing use of electronic medical records and their ability to access their own health records online; the science of applied mathematics seems destined to dominate the art of employee benefits.
@techreport{blakely_measured_2015,
address = {Rochester, NY},
type = {{SSRN} {Scholarly} {Paper}},
title = {Measured {Matters}: {The} {Use} of '{Big} {Data}' in {Employee} {Benefits}},
shorttitle = {Measured {Matters}},
url = {http://papers.ssrn.com/abstract=2599767},
abstract = {Since “big data” is changing so many aspects of the business world, how is it affecting the way health and retirement benefits are provided to private-sector workers? This paper summarizes the presentations and discussion at the Dec. 11, 2014, EBRI policy forum held in Washington, DC, on the topic, “Measured Matters: The Use of ‘Big Data’ in Employee Benefits:” the use of massive amounts of data and computer-driven data analytics to determine how people behave when it comes to health and retirement plans, which programs work or do not, and how to get better results at lower cost. EBRI’s 75th biannual policy forum last December delved into both the status and promise of this trend before an audience of about a hundred benefits professionals and policymakers. Two panels of experts -- one focusing on health and the other on retirement -- provided an overview of what employers, researchers, and data analysts are currently doing, what they hope to be doing, and what seems to be working so far. Speakers included employers, research and analytic experts, health and retirement plan executives, and consultants. Among the broad areas of agreement: Employers and researchers are making a major commitment to capturing and analyzing the vast amount of health and retirement data in their benefit plans; the health sector is considerably farther down the road than the retirement sector in using data analytics in benefits plan design and management, but both fields are in the very early stages of using big data; many workers are already seeing the results of this trend, such as the rapidly growing use of electronic medical records and their ability to access their own health records online; the science of applied mathematics seems destined to dominate the art of employee benefits.},
number = {ID 2599767},
urldate = {2015-05-11},
institution = {Social Science Research Network},
author = {Blakely, Stephen},
month = apr,
year = {2015},
keywords = {Behavioral research, Data analysis, Employee benefit costs, Employee benefit design, Employment-based benefits, Health benefit design, Retirement income adequacy, Retirement plan participation},
file = {Snapshot:files/51371/papers.html:text/html}
}
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