Unlocking Workforce Innovation Through Empowerment

All right, TGIF! We're back for In Case You Missed It, and as you can see in the bottom left-hand corner of your screen, this is our 100th official episode. With all of the other things that we've had going on, it's been a wild ride, Joe. So, uh, happy 100th episode to you.

Same to you. We had some great guests and we got another one here today.

That's right, and we actually have a two-timer here. We're bringing back Norma Patron, CEO of Empirica Lab, And, you know, as you can see by the title, we want to talk about kind of unlocking workforce innovation through empowerment. We want to talk about AI's role in that. And Norma and her company have been doing some very interesting work, and there's so much applicability into this larger market that we're going to talk a little bit about here, because workforce is really the elephant in the room for all agencies in this regulated industry that we're in. And they're struggling with how do we upskill, how do we reskill, How do we focus on enabling real collaboration? And Norma is the foremost expert on that. So let's welcome back to In Case You Missed It, Norma Padron. Norma, great to see you.

Great to see you again, Dustin. How are you today? Hey, Joe.

Doing great.

Where in the world are you today?

I know, I'm back in New York City. I was actually in Austin last week, and so I was in my old stomping grounds. Heat was, I think, 110 degrees one day or 109.

It's 103 right now, so I'm glad you're in a cooler place.

Yeah, yeah, yeah. Well, New York City, it's— but home is always where, you know, your family is. So Texas.

That's right. That's right. And I got my Texas mug to represent here.

There you go.

There you go. So, you know, I guess first question for you, you know, you've had a lot going on over the last year. It's been about a year since you've been on In Case You Missed It. Maybe bring us up to speed with everything you've been up to.

I know. And actually, I was rewatching our conversation. It was almost about a year ago. I think at the time we were really early in our MVP, really talking to, starting to talk to customers, looking at use cases and how really, how healthcare organizations, enterprise organizations were thinking about upskilling and reskilling their workers, right? So since then, as other early-stage companies, we went for capital. And so we completed the AWS Impact Accelerator for women founders, super grateful to everyone at AWS. We revamped our database architecture. We really rethink our— rethought our product. I continued having a lot of conversations which were really eye-opening across the segments. So we're not only talking to health delivery organizations, health systems, we're also talking to health plans and public health, regional public health organizations. We went through the Techstars Workforce Development Accelerator Program. I know that some of the startups were also in civic tech, and so I know that you know, some of the other founders in the program. And then we completed the incubation program with the Mount Sinai Innovation Partners. And so that's what brought me to New York. And we're super excited and happy to report that they're our first, you know, commercial partner. And so, yeah, deployed pilots, deployed a pilot with Thomas Jefferson Health. And so the— you know very well this drill of like early lifecycle of a company. And so We went through, we've been through quite a bit.

That's super exciting. Yeah, I think you look at all of that activity, you talked about the different customer segments, you know, Dustin kicked us off by talking about when we look at the public sector, workforce is the number one topic. You can't go to an event and not hear about skilling, upskilling, hiring, retention, all of these issues that everyone's facing. What are you learning across your customer segments when it comes to the the conversations around upskilling and skilling?

Yeah, so I think like 3 huge trends, and actually there's sort of like convergent dynamics that are happening. I think that on the employee side, on the workforce side, there's this huge movement towards more flexible work. And it's not only hybrid work, remote and hybrid, but it's also like flexible arrangements, the so-called gigification of work, which might've started before COVID certainly has been accelerated. This is true across the segments. So it's true across the healthcare delivery side. So you see it on the clinical and the nonclinical staffing. You see it as well on the payer side. You see a lot of teams that were historically analytics teams or data and technology teams, which felt that they might've benefited from at-home work or things like that, demanding the sort of like more flexible. So huge demand for flexible work arrangements. I think on one bucket that obviously we're very interested in, one big trend is this demand for upskilling and feeling like qualified to do not only your job today, but the job as it's changing. And so I've spoken with a lot of nurses, I've spoken with a lot of care navigators, spoken with a lot of folks on the public health realm as well. And I think that there's this sense that, you know, it might have been okay 10 years ago that whatever organization you were joining might have, you know, given you some training or optional training or reimbursement, and that was it. But now there really is this sort of like, what is the intention of my employer or this organization that I'm joining and how is it preparing me for the job as it's changing? And so we hear it a lot. I actually spoke recently with a chief nursing officer and she was telling me that younger nurses, like as they're joining the organization, a lot of the questions are around training and opportunities for career mobility. And so in this work, this is a shift that she's feeling that might've not been as salient before. And I think the last trend, of course, you know, it's the big elephant in the room, is the adoption of artificial intelligence and the different shapes and forms that we're all interested. But if we take a step back and we think about enterprise, right, these are huge organizations, high-reliability organizations. That is true in the public health realm, it is true in the delivery side, right? Very small mistakes, huge repercussions. So training is something that you need to be continuously doing. And now we have these tools that are coming into market that are, the fascinating thing I think of this wave of technology innovation is that the potential for adoption isn't at just like one tier of scale, it's across the tiers of scales, right? And so the marginal benefit for someone at an entry level for adopting artificial intelligence and the tools that are being, you know, brought to market is huge. And so there's this kind of push and pull, right? On the organizational side, how do we do this in a safe, equitable way. And on the employee side, it's like, it is now really like a, like an add-on, is sort of like a high-quality job would include access to these tools, because I can work better and faster. And so I think that is these 3 trends that we really heard loud and clear in the last year of conversations across the country.

Yeah, we're definitely hearing a lot on the AI side. So I'd love for you to maybe dig into kind of what you're seeing with ChatGPT and some of these other generative AI solutions. How should we think about AI adoption in these regulated industries? Any thoughts on how to approach that? Should these public health institutions go and deploy ChatGPT? Should they look at more responsible enterprise aspects of AI adoption across those skill lines you talked about?

Yeah, yeah. I mean, I think so first to acknowledge that there are obvious risks. It is true across every technology, right? So there are challenges in adopting machine learning, You know, except that I think that when, as machine learning has been adopted and scaled, is adopted mostly in the data analytics teams and not across the enterprise or this, or, you know, organizations at large. And so there are challenges and risks across all technologies and innovations that we have. And so I think that those need to be acknowledged and obviously continue to study it and obviously regulate it in sort of ways that are, that promote their adoption, but, you know, prevent some of the bigger risks. But I think that said, I think that the biggest opportunity here is that enterprise is sort of like truly being transformed, right? And so I think that the biggest opportunity here in my mind tends to be there's digitally enabled care, there's digitally delivered care, there is care enablement in the public health realm. There's sort of like a lot of knowledge and evidence generation that needs to happen. And so you have this sort of like objectives that can be categorized and cleared, and they all have their guardrails in some way. Safety standards when it comes to digital therapeutics will continue to sort of preempt and prevent some of the challenges and risks that we experience as we adopt these technologies. In the public health realm, I think that the biggest opportunity continues to be on evidence adoption and evidence generation that is faster. We saw it a lot during COVID with guidelines changing really quickly. And so the question became just sort of like, how do you disseminate this information faster, obviously in a safe way, but reach out to the people at the right time, at the right moment? And so I think that these tools do present huge opportunities for that.

So let's dig a little bit more into where tools like AI can have big impact. I know when we talk to our audience, they certainly have latched on to the the trendingness of this topic, right? Everyone's looking for what AI is going to mean to their organization. Where do you think some of those maybe immediate use cases may be, the low-hanging fruit? And then where do you think maybe some of the biggest impact may be?

Yeah, there's some super interesting research recently from Stanford that came out, this sort of like landscape scan about the marginal benefit across like skill-level roles, right, from adopting these tools. And there was a recently published study at the National Bureau of Economics, the NBER. And so basically my reading or my sense is that a lot of these immediate benefits can be for entry-level roles that can benefit from sort of like, imagine that you can do your onboarding supported with tools that are trained on data from existing workers, right? And so as you're asking these questions, you know, you can just go back and ask these questions from curated information from that organization that is very applicable to your role. And so you can just kind of do, do this faster. Um, there's obviously, I think, huge, huge opportunities in the care navigation space. I think huge opportunities for, for roles that, that are very, actually very human. And so that still requires someone to have curated that information or that body of knowledge to have been supervised in some way or trained in a way that is actually you know, with the empathy and the level of knowledge that is required of that role. And so for those roles, I think that there's this huge opportunity. The reality is that it's like the marginal benefit, you know, it's large across the board. And so you can think then of sort of like these jobs. I was talking recently to a doctor and he was telling me about how a lot of the fears or the challenges in adopting, you know, newer technologies in healthcare is because a lot of the technologies that have been brought to market have increase, not decrease the burden of the work, the experience of work. And so it's how, you know, he spoke a lot about, you know, before electronic health records, like, of course, I had to take notes or whatever. But, you know, now I have to spend hours and hours doing this. And so it doesn't feel like this technology helped me, it feels like this technology is a burden. And so there's some reluctance, I believe, in sort of adopting this technology. I think the last point that I would make is that it will be not only at the role level, I think that the impact, you know, we're very keen in sort of saying, like, is this for low-skilled jobs or medium-skilled jobs or high-skilled jobs. And I think there's definitely some truth. There's going to be a gradient of marginal benefit across skill levels and the skills required for those jobs and how clean and curated that information might be ready for being sort of really adapted and adopted in artificial intelligence models that we're using or large language models that we're using today. But I think it's also true that the winners are going to be organizations, enterprise organizations or large-scale agencies, you know, ONC. And, you know, I know that there's huge movement right now in the federal government to to curate use cases where AI can be adopted. I can send you a link, Dustin, to pass it to your audience.

Yeah.

And I think it's gonna be at the organizational level where these jobs are gonna be impacted, where the leadership actually of these organizations takes it upon themselves to say, we're gonna be adopting in a safe way. Here are some guardrails, but we're actually gonna be adopting. The bigger delta right now, it's whether an organization chooses to adopt it or not. And I think that is, we're too concerned about the risks. And I'm not saying, I'm not trying to minimize the risks, But it's going to be more about those that kind of have a strategy and a plan for adoption.

Yep. It's coming whether they want it to or not. So they have to be prepared. So I think that's good advice for them. So with everything going on, what are you most excited about today? Oh, projects, all the different things that you've got.

Yeah. I mean, so, okay, so space at large, I'm obviously really excited because I do talk to organization leadership across the board. And so they really do feel that training when it comes to artificial intelligence, digital literacy. Our program with Mount Sinai is on data literacy. And so I think that training, upskilling, there's a lot of these conversations that are happening today because of these trends that I told you, right? Like employees want better work experiences, are demanding better training. And so we have AI coming in and so organizations are reacting to this in ways that feel like this, this is the right time to be having a conversation about tools like ours in terms of of training and workforce development and an enterprise solution that can actually give you this knowledge base and intelligence on where your knowledge, you know, your organization is knowledge-wise. And so I think that that obviously is really— Technology-wise, I'm obviously really excited about artificial intelligence as it's coming to market. I think that, again, to me, the biggest kind of uniqueness of this wave is that it's being adopted across skill levels. I'm keeping an eye on sort of like, obviously, how is it going to transform, you know, how we think about data science, how we think about programming today, how we think about these roles that it used to be really difficult for organizations. It was a huge challenge. I mean, in the federal government or state governments, it was really, really difficult to attract and retain maybe very advanced data scientists. And so if this becomes a tool where we can provide support and actually upscale workforce that we have today into these roles and transition them into this kind of quote-unquote high-skill or high-complexity jobs, I think that that is an amazing opportunity.

And so I'm really, really interested in organizations that are developing today a strategy for using this to So what's the one piece of advice or your top piece of advice that you'd have to our audience in public health, regulated industries, healthcare, in terms of what they can do to transform their workforce skills and collaboration?

Yeah, I mean, listen, I have a ton of respect. So public health and healthcare delivery are sort of like they're cousins, but they're different. They're different things, right? I think of public health problems as wicked. I mean, every problem in healthcare, you know, as wicked problems, right? These problems that aren't— there's not an obvious solution. They're very complex. They require a lot of decision-making. They require a lot of intuition and empathy for the end users, which at the end of the day are humans, right? Both on who is providing the public health access, who works at these agencies, who's, you know, who's actually making these decisions, and then the end users, which are citizens, patients, caregivers. And sort of like, as you mentioned this question, I thought about a project that I worked with the city of Philadelphia. This was a few years ago, and it was on developing a strategy for, or, you know, hypothesizing cost-effectiveness analysis for safe injection sites. And so Philadelphia has, you know, very huge problems as other parts of the nation with the opioid crisis. And so really public health departments ask this type of questions all the time, you know, what are the best tools and resources that we can provide to ameliorate this problem, to save lives, to keep people healthy. And these are not easy problems in any way, right? And so I think that when it comes to the adoption of technology, I think there's a huge opportunity, of course, but I do think that at the end of the day, it's going to be— it's going to remain a uniquely human, wickedly human problem. And so the— again, the organizations that would make a dent into these problems and, you know, really differentiate themselves is going to be because they adopt these tools, but they keep that, you know, uniquely human perspective and empathy perspective and geography perspective. I am part of this group, this collaborative with the University of Chicago that is working on sort of like mapping social determinants of health. If anyone kind of cares to Google out, there's the SDOH Atlas, and I was part of the team working on that. And so we mapped out community resources at the neighborhood level and some characters at the neighborhood level. And it's just always astonishing to me that you know, how non-generalizable solutions can be. Because when you look at a map, it could be that one neighborhood looks one specific way and the other neighborhood looks a specific way. And so in terms of their access, in terms of resources, health outcomes, health opportunities, and so never losing that, you know, sight. I think that a lot of the fears that is coming around the sort of adoption of AI or, you know, even when it was just machine learning, right? And we were just running sophisticated logistic regressions. I think that a lot of those fears is not so much because we fear the technology, but we fear kind of forgetting that you can't blindly trust it. But public health finds itself probably at a huge opportunity right now. And I think that you might agree with climate change and many other circumstances will make the need for responsive, real-time public health information and access much more salient. And so my hope is that these organizations, and I believe from my conversations this is happening, my hope is that these organizations will adopt these technologies in very strategic ways.

Absolutely. And our audience echoes that and is loving the conversation. So thanks for sharing your insights.

Yeah, post any questions. Yeah.

Easiest question for you though is where can our audience go to keep up with the work that you're doing and to kind of follow that, plug in, maybe find out ways to partner with your organization?

Thank you so much. Well, I'm very easily findable at, you know, on LinkedIn. I gave an interview recently and I mentioned that LinkedIn is where all the cool kids are. And so you can reach out to me via message, but also at norma@empiricalab.com. Shoot me an email if you'd like to see a demo of our product, if you'd like to talk to me and learn more about the work we're doing across the segments in the healthcare industry. And so just, I'd be happy to talk to you. to you all and any public health department that is interested in partnering with us. We're very interested in emergency preparedness and guidelines. And so anyone that is interested in talking with us, I'll be happy to talk to them.

Well, Norma, thanks so much for joining us again on our 100th episode.

I know, I'm so excited. Congratulations, guys. I feel so honored to be the 100th episode guest and double, double, you know, timer. So thank you so much for having me.

Well, thanks for what you do. And thanks for joining us. And until we see you again, Have a wonderful weekend.

Thank you so much, everyone. Happy Friday.