I recently read an insightful piece originally published on Senior Housing News that explored how dining programs in senior living communities influence move-ins, particularly within memory care. What stood out most was the article’s emphasis on generational differences in how people rely on data when choosing senior living options.
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Senior living decision-maker vs. senior living resident
The article highlights an important distinction between the “senior living decision-maker” and the “senior living resident.” Sometimes these roles are held by the same person: an older adult proactively choosing to move into a continuing care retirement community (CCRC), a life plan community, or another type of retirement residence. Other times, the decision-maker is an adult child or another family member who steps in when an older relative needs more support.
Common scenarios in which an adult child becomes the decision-maker include:
- An older person experiences age-related decline and needs help with activities of daily living (ADLs). Care may come from unpaid family caregivers, paid in-home aides, or an assisted living community.
- A senior develops a progressive memory condition such as dementia and can no longer remain safely at home, creating the need for a memory care community.
- An acute health event, like a stroke, leaves someone requiring extensive or full-time nursing care. Families may attempt to provide care themselves, hire in-home nursing, or place their loved one in a skilled nursing facility.
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Data-driven senior living programs
The original article argues that younger generations—Gen X, Gen Y, and Millennials—tend to rely on objective, quantitative data when making significant life choices, including decisions about senior living. Older generations, such as Baby Boomers and the Silent Generation, are more likely to accept anecdotal evidence or recommendations from friends and family.
Because many adult children now drive senior living decisions, communities—especially memory care providers—need to rethink how they design and market programs like dining and resident activities. Applying measurable metrics to culinary offerings, program participation, and operational aspects can help communities demonstrate the value and suitability of their services to data-oriented decision-makers.
As an example, Morrison Living, a food service provider for numerous senior living communities, has formed an internal data analytics team. They analyze information gathered from communities to craft culinary experiences tailored to resident preferences and needs, and to inform choices about facility layout and staffing.
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Gathering and sharing more data
The use of quantitative analysis can extend well beyond dining. Younger decision-makers will likely expect transparent, measurable information across many aspects of community life when evaluating options for their loved ones or for themselves in the future.
Consider the types of metrics that could be collected and shared: program participation rates for social and educational events, community demographics, percentages or average ages of residents who transition to higher levels of care, fitness facility utilization, or anonymized health statistics such as prevalence of hypertension. These kinds of data points can speak to a community’s wellness programs, menu planning, staffing adequacy, and overall engagement.
Providing clear, aggregated, and anonymized data may give families the confidence they need to choose a community, and will align with the way many younger decision-makers evaluate services.
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The data trend of the future
Generations that prioritize measurable evidence in decision-making are nearing retirement and are already guiding choices for older relatives. This raises two key questions for CCRCs and other senior living providers: are they systematically collecting the hard data that future consumers will demand, and are they using that data to inform business and operational decisions rather than relying on anecdote or inertia?
Shifting toward a fact-based model of operations and management—where communities collect, analyze, and transparently share meaningful metrics—may be essential to meeting the expectations of data-driven decision-makers and securing the future success of the senior living industry.