How can Strategic Defined Contribution Analytics help with your workforce planning? Sibson uses methodical diagnostics to create customized reports about your plan’s patterns that are measurable and actionable. Sibson’s strategic deeper dive into plan data helps plan sponsors:
Evaluating and analyzing your DC plan goes beyond contribution rates and account balances. “Return on investment” is for both financial and people performance.
Take our brief, confidential questionnaire to receive your customized “scorecard” that measures how strategically you are utilizing your DC plan and how effectively your DC plan is aligned with your company’s goals (and learn how you can “improve your grade”).Get your score ›
How have organizations used Defined Contribution Analytics to their advantage?
Case Study: Increasing DC Plan Participation
Defined Contribution Analytics helped an organization increase their plan participation rate from 75% to almost 90%. How did they do it? Learn more ›
Case Study: A Plan With Many Uses
A global aerospace company recognized the potential value in the defined contribution plan it offered as both a business-planning tool and a recruitment/retention tool. Management saw both high participation rates and high balances relative to an individual’s projected retirement age as measures of success in the 401(k) offering. Learn more ›
Case Study: Plan Success through Improved Communication
A mid-sized insurance company was struggling to increase participation in their 401(k) Plan, but the employee base was slow to change. Generic communications programs provided by the recordkeeper were intended to boost participation but had not improved contribution. Learn more ›
One of Sibson’s DC Analytics consultants was recently featured in PLANSPONSOR magazine:
Data analytics “can show a plan sponsor a projection of which employee groups a change in ‘auto’-features will help – not just [a projection] for the company as a whole, but for different demographic groups,” says Jonathan Price. For example, an employer that is thinking of implementing auto-escalation may want to know how that would affect employees in some age groups more than others.
Data analysis also can project how much a plan-design change would affect specific work force segments. “Let’s say a plan has 84% participation now and the employer’s target is 90%,” Price says, “An employer can look at: Working with the tools we have, how can we get to 90%?”
“Harvesting the Right Facts and Figures,” PLANSPONSOR, September 2017
Learn what your DC’s plan data reveals – and how you can use that information to plan for success.
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