Quiet Exiting

Looking back, there was a real hopefulness to it. Big data, cloud and analytics were creating genuinely powerful opportunities, and tech leaders were still selling a vision that we trusted. It feels like forever ago.

It was around this time that my team was called into a project for one of our clients, a large, national health insurance company. It was one of those projects that had a secret code-name and required an extra NDA on top of the one already in place. I’m going into the kickoff meeting with some excitement. Maybe we had something to talk about that matched the transform-everything vibes of the time. Healthcare needed it, and this organization had the scale to do it.

We walk into the room greeted with the code word on corporate PowerPoint cover slide, settle into seats and get ready for the payoff. The next slide says four words: “100% population health engagement.” Eyebrows in the room raise. That’s a big promise. Then text animates in: “driven by our proprietary advanced analytics platform.”

The analytics platform was legitimately impressive. It took massive amounts of health data, augmented it with massive amount of non-traditional data which were fed algorithms that generated multi-dimensional engagement pathways. The health plan theoretically could reach every single covered member.

What happened when big data hit health insurance?

Since 2001, Gallup has been tracking how Americans rate the quality of health care in the US. When I was in that clandestine meeting, a majority of Americans said that it was good or excellent. In the most recent edition of the study, around ten years after that meeting, American’s views of healthcare quality has hit the lowest in history of the study, with 70% of Americans saying the system has major problems.

KFF data shows that nearly 6 in 10 insured Americans have experienced problems with their health insurance in a year, and of those, 54% gave up trying to find fixes for the problems.

I hear similar themes all the time when I’m talking to consumers. They’re no longer seeking those long-term relationships with providers and plans, they’re delaying care until something is urgent, trying out alternatives (that may or may not be endorsed by traditional healthcare), and they’re opting out of engaging all together unless they have to. But they’re not announcing their exit, they’re quietly exiting out the side door.

From inside the house, it’s easy to read this as a temporary thing. They’ll be back. Afterall, this is health care and health needs are inevitable. When they’re back, be prepared with an improved experience along with the right set of nudges and touchpoints that will win them over.

People, however, are not treating this as a temporary disconnection. It’s more like a relationship that is drifting. They’ve moved on emotionally and are accumulating personal practices, sources of information and workarounds. They’ve stopped believing that they healthcare system is where health happens at the same time as new options are exploding onto the scene. 

This drift, left alone long enough, starts to become a norm.

The instinct from inside the system is to respond with better outreach. It’s almost prescribed: better data leads to better segmentation, which leads to better targeting, which leads to more relevant touchpoints. When this chain of tools operates further downstream from the consumer drift, the touchpoints become less signal and more noise.

How do you become closer to people who are learning to live without you?

If a decade ago, the gravitational pull was in building a data analytics infrastructure, the infrastructure that is needed most in this moment is brand.

There’s a technology company that, in the middle of this drift, successfully convinced many millions of people to share some of their most intimate health data. Information about what’s happening with their heart, skin temperature, sleep cycles, reproductive health. They weren’t incentivized to do it through the promise of a Starbucks or Amazon gift card in return. They volunteered it over.

That company was Apple. They obviously had the data infrastructure that you’d expect from one of the most thoughtful technology companies ever. But the infrastructure that made their health play possible was brand. Not just the years of brand promise around privacy and security, but a visible commitment to it in product decisions and publicized fights with the federal government around user privacy. By the time Apple asked for health data, permission had already been earned.

Brand is the upstream infrastructure that changes the effectiveness of the downstream tools. It opens up outreach by changing whether people want to be reached. One organization built a data platform that could reach every covered member but couldn’t connect. Another had people volunteering health information to a company outside of the healthcare category.
 

The next version of this story is already underway.

AI is bringing about a new wave of possibility into healthcare engagement that we couldn’t imagined in that conference room a decade ago. The temptation is the same: dive into the capability and assume the relationship will follow. But when it’s built on permission, it brings them closer.

The reverse of quiet exiting isn’t precise marketing, it’s restored confidence.