Host Scott Heinila is joined by Bill Bonk and Evan Ehrenberg to break down a simple, repeatable four-step long-term care (LTC) planning process—Educate → Discover → Present Solutions → Execute—and why advisors need to get “upstream” before a family is forced into reactive decisions. Evan shares the origin story and mission behind Waterlily, a planning platform designed to stop LTC conversations from being generic, awkward, or product-first. Waterlily starts with a short client intake and turns it into a highly personalized care timeline, showing likely care needs, timing, duration, family caregiver burden, and projected costs by zip code. From there, the tool supports advisors in evaluating funding strategies—self-funding and insurance solutions—by modeling how a policy would actually perform during the client’s predicted claim scenario. The conversation emphasizes that LTC planning isn’t just about money—it’s about family dynamics, dignity, and reducing caregiver strain—and that having some plan is better than having none. The episode closes with a call-to-action for advisors to engage their OIP support team to learn how Waterlily can be used inside their planning workflow.
OIP’s long-term care planning framework is a simple four-step process: Educate → Discover → Present Solutions → Execute. Scott and Bill emphasize that LTC (or “elder care/aging with dignity”) planning works best when it starts early and stays plan-first, not product-first—otherwise the conversation turns into a transaction. They also stress that “self-insuring” is still a plan, but many clients underestimate the non-financial consequences (family burden, caregiver strain, and messy dynamics) that show up when there’s no proactive strategy.
Evan explains how Waterlily makes these conversations easier and more personalized: a short client intake generates an individualized care timeline (likelihood, timing, duration, care hours, and zip-code-based costs) and helps clients visualize tradeoffs like family caregiving vs. paid professional care. The platform can also model funding approaches by importing policy PDFs (or illustrations) to simulate how benefits would actually pay during a client’s predicted claim scenario, and it supports quoting/application workflows to reduce friction and improve execution.