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How three years at McKinsey shaped my second startup

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Re: How three years at McKinsey shaped my second startup

#71

Post by throw10920 »

xp84 wrote: post #20
throw10920 wrote: post #6

Article is interesting on the whole (I have no experience with "professional" work, and would love for suggestions as to how to be more familiar), but I latched onto this nugget: > Our vision at Meanwhile is to build the world's largest life insurer as measured by customer count, annual premiums sold, and total assets under management. We aim to serve a billion people, using digital money to reach policyholders and a…

> dispute resolution, customer service, etc There's a huge assumption in your comment -- that having 100,000 employees necessarily guarantees (or even makes likely) that you will have some human to help you. More likely, those 100,000 humans are mostly working on sales and marketing, and the few allocated to support are all incentivized to avoid you, and to send you canned answers. A reasonably decent AI would be bet…

> There's a huge assumption in your comment -- that having 100,000 employees necessarily guarantees (or even makes likely) that you will have some human to help you.

That's not an assumption.

I know that I, and many others, have been able to get a human on the phone every time we needed one. Regardless of the number of those humans actually working claims, in the current system, it is "enough".

I also know that it's impossible to give that level of service when you have 1 employee for every 10 million customers.

That's really all that you need in order to make the judgement that you're not going to get a human.

Side-note: I did a quick search, and found that Allstate has 23k reps that actually handle claims and 55k employees total, so almost half of their workforce does claims and disputes. They also have 10% market share of the US's ~340 million people, so that's, at most, 1 rep per 1500 employees. That's much better odds than 1 for every 10 million.

> A reasonably decent A

And there's the problem - that AI doesn't exist. You're speculating about a scenario that simply hasn't been realized in the real world, and every single person that I've talked to who has interacted with an AI-based "support representative" has had a bad experience.

Re: How three years at McKinsey shaped my second startup

#72

Post by Muromec »

matwood wrote: post #49
ImPostingOnHN wrote: post #31

Earlier quoted context omitted.

> it directly causes suffering via creating a societal permission structure for politicians to protect interest groups with protectionist trade policy and internal pork barreling policy What part of that is suffering, if it enables 100k constituents to put food on the table?

The problem is that it's a misallocation of human capital which slows progress for all of society. We should be providing social safety nets for people, not fake jobs.

Or do neither of that and get a proper revolt to learn that lesson again.

Re: How three years at McKinsey shaped my second startup

#73

Post by throw10920 »

ben_w wrote: post #64
crazygringo wrote: post #48

Earlier quoted context omitted.

> that the only way to provide dispute resolution and customer service to 1B people with only 100 employees is by depriving them of any chance to interact with a human, and forcing all interaction with the company to go through AI. That, to me, is deeply disturbing, and very very difficult to justify. I don't know. Given the human beings I've interacted with in customer support, and the number of times I've had to es…

While I get the vibes, and have had experience of human customer support being very weird on a few occasions, replacing mediocre humans with mediocre AI isn't a win for customers getting actual solutions. And right now, the LLMs aren't really that smart, they're making up for low intelligence by being superhumanly fast and able to hold a lot of context at once. While this is better than every response being from a ra…

I think there's an interesting implication here: that the actually good (for the customer) support experience is a real human who has access to a RAG where they can look up company documents/policies/procedures, but still be able to use their human brain to make judgement calls (and, of course, they have to be willing to, y'know, read the notes left by the previous rep).

Re: How three years at McKinsey shaped my second startup

#74

Post by frankfrank13 »

comrade1234 wrote: post #8

My wife made a McKinsey consultant cry… she hired McKinsey for some internal project. One person on the project was a recent Harvard grad. They were in a meeting going over the deliverables along with the McKinsey partner on the project and in the meeting my wife said something to the effect that their work wasn’t up to McKinsey standards. The junior guy started crying in the meeting. Like just blubbering. My wife st…

Having worked at Mck, what I could very well imagine happened behind the scenes here was

1. This BA/Asc was on 2. They walked into that meeting thinking they had completed exactly what the client (your wife) wanted

And after the meeting (this I feel more confident about, as it happens a lot)

1. A conversation happened to see if the BA/Asc wanted to stay on the project

2. They said yes, and the leadership decided that the best way to make this person feel safe was to always have a more experienced person in the room to deal with hiccups (in this case, the perception of low quality work)

Isn't that... good? What else would you expect

Re: How three years at McKinsey shaped my second startup

#75

Post by SoftTalker »

bee_rider wrote: post #56
SoftTalker wrote: post #52

Earlier quoted context omitted.

This is life insurance specifically. It's not very hard to prove someone is dead, is there really much room for argument over paying out the policy benefit?

If the plan is to just pay out after confirming the person is dead, what’s the AI doing? It could be replaced by a “upload your death certificate here” box.

It is kind of weird. Why does a life insurer have 100,000 employees. I'm really only familiar with term life. All the "customer service" is pre-purchase. Once you buy it, you forget it other than making the annual payment. There's nothing to manage, no real customer service required until and unless you die.

I suppose whole life where there is a cash value and investments being managed might have a more ongoing service need, but I'm not familiar with that.

Re: How three years at McKinsey shaped my second startup

#76

Post by mettamage »

> I learned deeper truths about where startups can win and compete.

Now that I'm working at a big organization (a Fortune 500 company), I can relate. I'm by far the most innovative person in my team and I'm being held down because I'm not doing my role (as I'm not a dev but a data analyst at the moment).

If I'd be doing my role however, then we wouldn't be innovating and the C-suite wants us to innovate with AI. I'm the only one at my department that can create actual AI automations. And the IT department is basically stripped out by upper management.

If anyone wants an actual dev building AI automations and think how we can disrupt with the state of the art, my email is in my profile.

Re: How three years at McKinsey shaped my second startup

#77

Post by zvitiate »

xp84 wrote: post #20
throw10920 wrote: post #6

Article is interesting on the whole (I have no experience with "professional" work, and would love for suggestions as to how to be more familiar), but I latched onto this nugget: > Our vision at Meanwhile is to build the world's largest life insurer as measured by customer count, annual premiums sold, and total assets under management. We aim to serve a billion people, using digital money to reach policyholders and a…

> dispute resolution, customer service, etc There's a huge assumption in your comment -- that having 100,000 employees necessarily guarantees (or even makes likely) that you will have some human to help you. More likely, those 100,000 humans are mostly working on sales and marketing, and the few allocated to support are all incentivized to avoid you, and to send you canned answers. A reasonably decent AI would be bet…

There's a huge assumption in your comment -- that you know how insurance works. "Most" probably aren't working in sales and marketing; I'd heavily dispute anything above 50% and I feel like 33% might be pushing it? I don't want to get overconfident here, but this claim feels off-base.

Insurance isn't like a widget. People have actual legal rights that insurers must service. This involves processing clerks, adjusters, examiners, underwriters, etc. Which then requires actual humans, because AI with the pinpoint accuracy needed for these legally binding, high-stakes decisions aren't here yet.

E.g., issuing and continuing disability policies: Sifting through medical records, calling and emailing claimants and external doctors, constant follow-ups about their life and status. Sure, automate parts of it, but what happens when your AI:

a. incorrectly approves someone, then you need to kick them off the policy later?

b. incorrectly denies someone initial or continuing coverage?

Both scenarios almost guarantee legal action—multiple appeals, attorneys getting involved—especially when it's a denial of ongoing benefits.

And that's just scratching the surface. I get that many companies are bloated, and nobody loves insurance companies. No doubt, smarter regulations could probably trim headcount. But the idea that you could insure a billion people with just 100, or even 1000 (10x!), employees is just silly.

Re: How three years at McKinsey shaped my second startup

#78

Post by throw10920 »

bee_rider wrote: post #61
John23832 wrote: post #55

Earlier quoted context omitted.

You misread. The poster is speaking about the ethical handling of customer service.

This comment is replying to the sentiment: > Completely separate from the potential ethical issues and economic implications of putting 100k people out of a job, […] I’m pretty sure. Although, the original comment was basically putting that issue aside, so I’m not sure what there is to say about it.

You got that right, and yes, I was putting that issue aside, although my counterpoint to GGP argument would be "the ethical issues aren't from the competitor's perspective, it's from the perspective of the whole workforce, industry, and/or economy as a whole".

Re: How three years at McKinsey shaped my second startup

#79

Post by n_ary »

johnobrien1010 wrote: post #15

Wanted to point to the startup the author seems to be running, which is to sell insurance somehow tied to Bitcoin: https://meanwhile.bm/ For the record, that strikes me as seriously improper. Life insurance is a heavily regulated offering intended to provide security to families. It is the opposite of bitcoin, which is a highly speculative investment asset. Those two things should not be mixed. Also, the fact that th…

Did I read that right? Sam Altman is funding this? If true, I am having some new perspective him.

Re: How three years at McKinsey shaped my second startup

#80

Post by burningChrome »

throw10920 wrote: post #6

Article is interesting on the whole (I have no experience with "professional" work, and would love for suggestions as to how to be more familiar), but I latched onto this nugget: > Our vision at Meanwhile is to build the world's largest life insurer as measured by customer count, annual premiums sold, and total assets under management. We aim to serve a billion people, using digital money to reach policyholders and a…

>> that the only way to provide dispute resolution and customer service to 1B people with only 100 employees is by depriving them of any chance to interact with a human.

Real world evidence supporting your argument:

United Health Group is currently embroiled in a class action lawsuit pertaining to using AI to auto-deny health care claims and procedures:

The plaintiffs are members who were denied benefit coverage. They claim in the lawsuit that the use of AI to evaluate claims for post-acute care resulted in denials, which in turn led to worsening health for the patients and in some cases resulted in death.

They said the AI program developed by UnitedHealth subsidiary naviHealth, nH Predict, would sometimes supersede physician judgement, and has a 90% error rate, meaning nine of 10 appealed denials were ultimately reversed.

https://www.healthcarefinancenews.com/news/class-action-laws...

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