WEBVTT - AI for Nursing Jobs, Right Kind of Wrong Book

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<v Speaker 1>You're listening to Bloomberg Business Week with Krol mess Here

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<v Speaker 1>and Tim Stenebek on Bloomberg Radio.

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<v Speaker 2>Mike, you know there's a nursing shortage in the US,

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<v Speaker 2>and our next guest may have a solution. A doctor

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<v Speaker 2>Emon Abbozaid is co founder and chief executive officer of

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<v Speaker 2>Incredible Health, and she's joining us now from where are you, Austin?

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<v Speaker 2>I'm looking at the background. That doesn't look like Austin,

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<v Speaker 2>not that I've really that's the.

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<v Speaker 1>Nicest soum background I think we've seen today. It's pretty bank.

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<v Speaker 3>Thank you, Austin. It's pretty green, all right.

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<v Speaker 2>So what is what is Incredible Health and how are

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<v Speaker 2>you going to solve the nursing crisis in the US.

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<v Speaker 3>So, Incredible Health is the fastest growing venture backed healthcare

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<v Speaker 3>career marketplace hospitals and health systems. They use our software

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<v Speaker 3>to hire nurses and permanent roles in less than twenty days.

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<v Speaker 3>Our mission is to help healthcare professionals live better lives

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<v Speaker 3>and to help them find and do their best work.

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<v Speaker 2>Oh and wait for it, Michael, they use artificial intelligence, so,

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<v Speaker 2>which means if this were a publicly traded stock, could

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<v Speaker 2>be like through the roof right, yeah, right, So well

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<v Speaker 2>how does AI? What's what's the intersection of what you

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<v Speaker 2>do and artificial intelligence.

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<v Speaker 3>So this week we announce the implementation of generative AI

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<v Speaker 3>across our platform, which we're really excited to do and

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<v Speaker 3>we're also the first in our industry, right in our

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<v Speaker 3>part of the industry to do that. There's these features

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<v Speaker 3>really aim to just expand opportunities for nurses and to

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<v Speaker 3>help further streamline the hiring process too. I will say

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<v Speaker 3>that even beyond the generative AI, we do use machine learning,

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<v Speaker 3>we also use algorithms to drive the value here. First

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<v Speaker 3>first area I just want to share is just our

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<v Speaker 3>resume wizard that allows nurses to instantly create resumes in

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<v Speaker 3>a high quality resume and seconds in our mobile app.

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<v Speaker 3>Thirty percent of nurses start the job search process without

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<v Speaker 3>a resume for a variety of reasons, you know, including

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<v Speaker 3>socioeconomic reasons like not having access to a computer laptop,

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<v Speaker 3>or not simply not knowing what a high quality resume

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<v Speaker 3>is what's needed. And so thousands of nurses have already

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<v Speaker 3>used this, and so that's thousands of nurses that are

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<v Speaker 3>no longer left behind in the job search process.

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<v Speaker 1>And doctor how are you utilizing the AI? Are you,

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<v Speaker 1>you know, is it a chat GPT thing or using

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<v Speaker 1>one of these big tech products that's already available. Did

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<v Speaker 1>you develop your own? How are you accomplishing this?

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<v Speaker 3>Yeah, so I have a fantastic product and engineering team

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<v Speaker 3>and they're using a GPT technology from open Ai specifically.

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<v Speaker 3>Another feature I wanted to mention is just our customized

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<v Speaker 3>health system outreach to nurses. So this is this is

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<v Speaker 3>an example of a feature where that health systems can

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<v Speaker 3>use to send highly customized messaging to nurses. It highlights

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<v Speaker 3>you know, hospital perks and benefits and ultimately helps hospitals

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<v Speaker 3>really differentiate themselves from the competition. And since we implemented that,

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<v Speaker 3>the interview requests accepted from nurses has gone off by

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<v Speaker 3>twenty percent, So.

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<v Speaker 2>Why limit this just to nurses and everybody use it.

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<v Speaker 3>So the nursing is one of the is the top

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<v Speaker 3>shortage in healthcare when it comes to just labor shortages,

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<v Speaker 3>it's also one of the top shortages in the country,

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<v Speaker 3>and it's definitely one of the you know, top areas

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<v Speaker 3>that are the health systems that we work with care

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<v Speaker 3>about the most. So we're very focused on nurses and

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<v Speaker 3>hospitals right now in the US, of course, you know,

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<v Speaker 3>we have plans to expand beyond nurses and beyond hospitals

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<v Speaker 3>before now that's for now, that's our.

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<v Speaker 1>Focus radio radio people. Yeah, they're gonna the chat cheep

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<v Speaker 1>PT is gonna you know.

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<v Speaker 2>The funny thing is is this, like in my career,

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<v Speaker 2>I've been doing this, like, oh my god, forty years.

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<v Speaker 2>I have never once had to give anybody a resume.

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<v Speaker 1>Really, I don't know. They hear your voice, John, and

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<v Speaker 1>then it must be they hear that Barry White voice

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<v Speaker 1>and they're they're instantly so. But doctor, I'd like to

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<v Speaker 1>step back just a little bit and talk about this

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<v Speaker 1>nursing shortage. What caused that? Is it a remnant of

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<v Speaker 1>the pandemic where you know a lot of nurses sort

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<v Speaker 1>of had to step back from their career. What's going

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<v Speaker 1>on that's driving this big shortage of nurses in your opinion?

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<v Speaker 3>Yeah, So, Look, it's a long term trend that's been

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<v Speaker 3>going on for ten years and it's projected to continue

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<v Speaker 3>for many decades to come. What's happening is that our

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<v Speaker 3>demand from patients and from Americans on the healthcare system

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<v Speaker 3>continues to increase because our population is aging, but we

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<v Speaker 3>as a country have not done a great job of

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<v Speaker 3>increasing the number of healthcare workers to meet that growing demand,

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<v Speaker 3>and so the shortage is increasingly becoming tougher and tougher. Now. COVID,

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<v Speaker 3>of course, was a demand shock, but even after COVID,

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<v Speaker 3>even now there's still a shortage. I think you all

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<v Speaker 3>mentioned the Jobs report. When you look at the detail

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<v Speaker 3>in there, the biggest increase in job gains in the

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<v Speaker 3>US is in healthcare. So this does continue, and despite

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<v Speaker 3>the job growth, we still don't have enough healthcare workers

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<v Speaker 3>to fill those roles.

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<v Speaker 2>How many hospitals are using your stuff right now to

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<v Speaker 2>end your customer base?

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<v Speaker 3>Yeah, So we work with over seven hundred and fifty

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<v Speaker 3>hospitals across the country, including large health systems like Age

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<v Speaker 3>and Kaiser, Permanente, large regional systems like Baylor, Scott and White,

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<v Speaker 3>and many academic medical centers too, like Johns, Hopkins and

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<v Speaker 3>Cedar Sinai. We also work with over eight hundred thousand nurses,

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<v Speaker 3>so one in four nurses in the US uses incredible

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<v Speaker 3>health to manage their careers.

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<v Speaker 1>And I assume to the nurses pay or is it

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<v Speaker 1>the hospital's paying, and the nurses get it for free.

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<v Speaker 1>What are the economics of the Yeah, it's.

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<v Speaker 3>One hundred percent free for nurses. They can use all

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<v Speaker 3>our tools, all our features, you know, even beyond finding

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<v Speaker 3>a job. We have continuing education and a community for

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<v Speaker 3>them to ask for advice and salary estimators and so on.

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<v Speaker 3>And it's the hospitals that pay.

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<v Speaker 2>I'm curious how you started the business and the different

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<v Speaker 2>funding rounds you had to go through. How easy or

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<v Speaker 2>difficult was that? And walk me through the steps that

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<v Speaker 2>brought you into an existence.

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<v Speaker 3>Sure, we founded the company six years ago. We've raised

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<v Speaker 3>almost one hundred million dollars for the company, and the

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<v Speaker 3>company today is valued at one point sixty five billion.

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<v Speaker 3>I myself, I'm an MD by background, I've been in healthcare.

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<v Speaker 3>I've been in technology for the last ten years of

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<v Speaker 3>my career. And ultimately myself and my co founder, my

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<v Speaker 3>CTO Rome Portlock, who's a brilliant software engineer from MIT.

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<v Speaker 3>You know, we really we knew that there was There

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<v Speaker 3>were constant complaints from members of our family. Actually, so

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<v Speaker 3>doctors in my family were often complaining about understaffing nurses,

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<v Speaker 3>and Rome's family were saying, hey, I'm experienced I'm qualified,

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<v Speaker 3>I apply to ten places I don't even hear back.

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<v Speaker 3>We started to really dig into it. We realized the tools,

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<v Speaker 3>the processes of technology in healthcare hiring, A lot of

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<v Speaker 3>it's not really changed in over twenty years. It's primarily

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<v Speaker 3>job bars. You know, post a job and hope it

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<v Speaker 3>all works out. But that's really tough and that's not

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<v Speaker 3>sufficient a in an industry that has major labor shortages.

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<v Speaker 2>Do you have additional funding rounds coming up and the

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<v Speaker 2>expansion You sort of touched on that before, But what's next?

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<v Speaker 3>So what's next for us and just looking at twenty

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<v Speaker 3>twenty four is continuing to invest in our product roadmap,

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<v Speaker 3>more extensive use of generative AI as well, to continue

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<v Speaker 3>to expand opportunities for healthcare workers, for nurses, and to

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<v Speaker 3>make and to streamline the hiring process. We want to

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<v Speaker 3>make it more and more personalized, more and more automated,

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<v Speaker 3>just make it easier for everyone to access fantastic opportunities.

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<v Speaker 1>And I always wonder with a venture capital based company,

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<v Speaker 1>h doctor sort of the long term ambitions are we

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<v Speaker 1>perhaps going to see you ringing that stock market bell

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<v Speaker 1>on I p O day someday or any any into

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<v Speaker 1>what's to come as far as the next phase for

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<v Speaker 1>Incredible Health.

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<v Speaker 3>Yeah. So, our vision and our mission is to help

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<v Speaker 3>healthcare professionals lead better lives and help them find and

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<v Speaker 3>do their best work. So, and this is a very

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<v Speaker 3>ambitious company. Our goal ultimately is to one day go public.

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<v Speaker 3>But you know, a lot of work to do between

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<v Speaker 3>now and then.

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<v Speaker 2>All right, let's leave it there. I mean anything else

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<v Speaker 2>to add? I think you've covered it all.

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<v Speaker 3>Doctor, all right, thank you so much for having me.

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<v Speaker 3>I appreciate it.

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<v Speaker 2>That was fantastic, Doctor Iman Abuse, the co founder, chief

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<v Speaker 2>executive officer of Incredible Health. Mike, you know we all

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<v Speaker 2>have failures and shortcomings.

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<v Speaker 1>Speak for yourself.

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<v Speaker 2>I was going to say, I was going to include

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<v Speaker 2>you in that list. By the way, our next guest

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<v Speaker 2>has turned her failures and shortcomings into something of a

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<v Speaker 2>science project. Amy Edmondson is author of The Right Kind

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<v Speaker 2>of Wrong, The Science of Failing Well. I think we

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<v Speaker 2>have to read this book because what it won the

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<v Speaker 2>Business Book of the Year for the FT I am

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<v Speaker 2>told that's pretty impressive. Hey, Amy, thanks for being on

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<v Speaker 2>the program. What was your science project?

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<v Speaker 4>My whole life has been the science project, I guess,

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<v Speaker 4>but indeed, failure is a central thread that runs through it.

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<v Speaker 2>And you know, we're all told in school there are

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<v Speaker 2>no dumb questions and that we advance and learn from

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<v Speaker 2>our mistakes. But do we really well.

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<v Speaker 4>Yes, we really do, although we don't do it naturally.

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<v Speaker 4>We need to be We need to learn the right

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<v Speaker 4>mindsets and skill to actually learn from failures. I do

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<v Speaker 4>make a distinction between failures and mistakes. Mistakes are by definition,

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<v Speaker 4>deviations from known best practices or protocols or recipes, whereas

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<v Speaker 4>failures can in fact be in new territory where there

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<v Speaker 4>was no recipe and amy.

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<v Speaker 1>I'm fascinated with the concept of studying a topic like

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<v Speaker 1>failure from an academic sort of scientific approach. Could you

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<v Speaker 1>could you walk us through how you did that? You know?

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<v Speaker 1>Did you did you start with the kids who flunk

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<v Speaker 1>your class and do brain scans on them? I'm kidding,

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<v Speaker 1>but how did you? How did you approach this? Actually?

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<v Speaker 4>I mean let me, let me be be more accurate.

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<v Speaker 4>I don't study failure. I study organizations, and in organizations

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<v Speaker 4>there are many failures. So I am fundamentally a management researcher,

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<v Speaker 4>and one of my core passions is management decisions. And

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<v Speaker 4>management actions that lead to preventable failures and even worse

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<v Speaker 4>at times, that inhibit the productive experimentation and innovation activities

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<v Speaker 4>that would lead to future successes.

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<v Speaker 3>So I see both kinds of errors in organizations.

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<v Speaker 4>A failure to experiment enough, necessarily incurring failures along the way,

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<v Speaker 4>and a failure to prevent some of the preventable accidents

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<v Speaker 4>and bad decisions that we see all around us.

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<v Speaker 2>So I'm guessing for all this to work in an organization,

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<v Speaker 2>you have to have a climate of openness and one

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<v Speaker 2>that where you're not getting going to get in trouble

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<v Speaker 2>if you venture out and make mistakes. And I don't know.

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<v Speaker 2>For some reason, earlier today i was reading the preface

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<v Speaker 2>to the book, and I'm thinking, like God, would this

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<v Speaker 2>any of this apply to Congress? I don't think so.

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<v Speaker 4>Well, you know, it's I think in earlier times it

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<v Speaker 4>would apply to Congress. Congress is an organization just like

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<v Speaker 4>any other. And I have to admit that most of

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<v Speaker 4>you know, the research I've done and the organizations I've

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<v Speaker 4>studied is done with an assumption of a good faith

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<v Speaker 4>effort to perform well and a good faith effort to

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<v Speaker 4>do your job, and even with a good faith effort

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<v Speaker 4>to have a really effective organization that is serving its

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<v Speaker 4>clients or serving its constituents well. Mistakes and failures still happen.

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<v Speaker 4>But when you have an organization where it no longer

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<v Speaker 4>seems clear that the goal is to perform well and

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<v Speaker 4>serve the public, then some of the basic assumptions of

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<v Speaker 4>my research and my findings may no longer hold.

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<v Speaker 1>Are there any sort of common causes of failure? Is

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<v Speaker 1>it you know? Is it simple enough to boil them

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<v Speaker 1>down to a few things I don't know, hubrius or

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<v Speaker 1>you know, too much risk taking? Are there any sort

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<v Speaker 1>of common threads that seem to appear over and over?

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<v Speaker 4>Absolutely common? See I identify three kinds of failure. Basic

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<v Speaker 4>failure is complex failures and intelligent failures. The third kind,

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<v Speaker 4>the intelligent failures, are the good kind, the kind we

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<v Speaker 4>want more of. They're essentially discoveries. There they bring new

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<v Speaker 4>knowledge in territory that we haven't plowed yet. So it's

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<v Speaker 4>it's they're invaluable.

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<v Speaker 1>Could an example.

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<v Speaker 4>Sure a scientific Let's say you're a I mean, this

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<v Speaker 4>is maybe an obvious example, but if you're a scientist

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<v Speaker 4>and you have and you're the leading edge of some

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<v Speaker 4>scientific field and you have a hypothesis that something might

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<v Speaker 4>work and be a great discovery, and then you try

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<v Speaker 4>it and it doesn't work. That is a failure, but

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<v Speaker 4>it is a discovery. It tells you that that hypothesis

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<v Speaker 4>was wrong and gives you new information that you previously

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<v Speaker 4>lacked about what to try next.

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<v Speaker 3>That that's a science example. But in our lives, you know.

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<v Speaker 4>Just let's say dating, you might have you might go

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<v Speaker 4>on a on a date and have good reason to

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<v Speaker 4>believe this could work out, but it falls short, and

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<v Speaker 4>you can't call that any thing but an intelligent failure.

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<v Speaker 4>Couldn't go in advance that it wouldn't work.

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<v Speaker 2>And I got to ask this question because it's one

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<v Speaker 2>of these market themes that we have. Where does artificial

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<v Speaker 2>intelligence then fit into what you do and what organizations

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<v Speaker 2>do well.

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<v Speaker 4>Artificial intelligence, you know, essentially works quickly with a lot

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<v Speaker 4>more data than our brains can work with. So it

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<v Speaker 4>could it could be used to help us prevent these

0:13:31.840 --> 0:13:35.040
<v Speaker 4>preventable failures that I was referring to before, the basic failures,

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<v Speaker 4>the complex failures. It could it could help us when

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<v Speaker 4>we're about to make consequential decisions that are either irreversible

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<v Speaker 4>or at least very high stakes and under conditions of uncertainty.

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<v Speaker 4>It could help us make those decisions with better data,

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<v Speaker 4>more informed by all the available data. And it could

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<v Speaker 4>also help us generate better experiments, which would lead to

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<v Speaker 4>maybe fewer intelligentailures and more discoveries.

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<v Speaker 3>But still you'd have to have some intelligent failures.

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<v Speaker 1>So you talk about failing, well, what's the opposite of that?

0:14:08.720 --> 0:14:11.600
<v Speaker 1>What's just a failure at failing so to speak?

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<v Speaker 4>Yeah, I mean, so there's two kinds of failures at failing,

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<v Speaker 4>and one is we.

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<v Speaker 2>Got to do it in a minute.

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<v Speaker 4>So the failure the failures we get from not trying

0:14:20.600 --> 0:14:23.520
<v Speaker 4>very hard, from mailing it in, you know, from sloppy work.

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<v Speaker 4>That's the wrong kind of wrong, right, That's that's not

0:14:26.560 --> 0:14:27.200
<v Speaker 4>failing well.

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<v Speaker 3>And also the.

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<v Speaker 4>Failure to experiment, to stretch, to grow, to try new

0:14:32.720 --> 0:14:36.400
<v Speaker 4>things and therefore not failing at all, that's also not

0:14:36.480 --> 0:14:37.160
<v Speaker 4>failing well.

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<v Speaker 2>Amy, thanks so much, an absolute pleasure joining us from Cambridge.

0:14:41.800 --> 0:14:45.440
<v Speaker 2>The author Amy Edmondson the right kind of wrong, and

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<v Speaker 2>we should mention again the ft in Schroeder's business book

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<v Speaker 2>of the Year.

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<v Speaker 1>I'm inspired, John, I'm going to go home and fail

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<v Speaker 1>at something. I don't know what it is.

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<v Speaker 3>But

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<v Speaker 2>Well make sure it's the right kind of that's that's

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<v Speaker 2>Michael