Transforming Healthcare Costs with AI (ft. Jeff Heenan-Jalil)

Thanks for tuning to Digital Voices podcast, where we chat digital transformation challenges and opportunities across healthcare and life sciences. And now, your host, Ed Marx. Hey, it's Ed. Welcome to another edition of Digital Voices. And we have a return guest, which we haven't had too many. So Jeff, you're in a rarefied space. We maybe have had 2 or 3, and I think they were related to me. So welcome again to Digital Voices.

Thank you very much, Ed. Fantastic to be here.

So just to level set with everyone, Jeff was on episode 43. We are now in the 250s. So you were 200 episodes ago. So if you do the math, because it's one a week, it was a couple years ago when we spoke. And you're the CEO of Hunter AI. And it's really about supply chain optimization, things like that. We'll talk a little bit about it. Uh, but before we get there, always like to know something personal since we already asked you about music and everything like that. Uh, the other sort of common thread that you and I have is triathlons. Tell us about, uh, your triathlon experience and why you got into it.

Um, well, yeah, Ed, you know, as they say, health and fitness is, uh, the number one key thing to, let's say, keep you on this earth. The great thing about, uh, getting into triathlons, never ever got into it before until my brother actually passed away. And I wanted to try and challenge myself and I just jumped in boots and all and did a half Ironman from about 4 months when he passed. So barely could swim, barely could run. Yes, I could cycle, but boy, that was some time back now. And now I'm still keeping up on that journey. Just completed an Olympic triathlon in the sea. The training here in the United Kingdom is a little bit different, I think, in the US, but I was training in the wintertime. And I was out on a beach and I think it was about 5 degrees centigrade. It was freezing. And you know it, right, Ed? Once you actually get into that mode, you keep on swimming. And I just went from the beginning of one part of the beach to the other end of the part of the beach, and I was literally frozen, but I was in that zone. And by the time I came back and I started running back down to the beach, my wife got So mad at me because she thought I'd drowned out there because it was so cold. And obviously she was actually having a cup of coffee inside.

Yeah.

Things are going well with regards to that side.

Yeah, no, that's good. And I know, cause we've met up a few times, uh, you really take care of yourself, which is, uh, so important. And I forgot to mention at the top, uh, so Mike, I have a conflict here. So I want everyone to know about it. I am on the advisory board of Hunter AI. That's when we first, Jeff and I first met was probably 4 or 5 years ago. And a friend of mine was like, Hey, there's a, you know, this was before AI was cool, Jeff. A friend of mine was like, hey, there's this startup, you know, there's a great guy that has all this experience with, we'll talk about in a second, in supply chain with some major, you know, companies. And he started his own thing, you know, this AI thing, you want to be on the advisory board? And I was like, yeah, that sounds super interesting. Cause, you know, again, AI was not in vogue yet. And so I wanted to learn as much as I could. And so, so that's how we met up. So I just want to be straight with my audience about that. But yeah. So before we go into sort of some of the strategic issues that a lot of health systems are dealing with, and I will share my point of view as a board member of a couple, uh, health systems, tell us a little bit about your background, like, you know, your, your career, like in 60 seconds.

60 seconds. Born in a, I suppose, a call center in New Zealand in a healthcare organization and rose up through the ranks, uh, representing the sales part of, um, Southern Cross Healthcare. Then took a quick switch into procurement, headed up procurement for electronic data systems and Unisys for the Asia Pacific region, and then really transferred into business management and managed a lot of high-tech organizations and departments and divisions and geographies for Wipro Technologies and also latter part IPsoft and also Cognizant. So full raft, but close to 16 years in the healthcare industry sector.

Yeah. And if people want to dive deeper again, Jeff, they can go back to episode 43 and where we go a little bit deeper into that. But I just want to make sure I level set for the audience that has not heard you before or heard of Hunter AI. So from a strategic point of view, we just want to talk about how do you take cost out of a health system? Because again, that's one of the top 3 or 4 priorities of every health system is cost takeout. It is so expensive. Everyone's working on their Their margins, you know, at the time of this recording, which is late 2024, Q4 2024, the margins for the average hospital is positive now, which is good as opposed to when we recorded 2 years ago, but barely positive. So, you know, about 1% average of averages. Of course, there's outliers or some that are doing really well, 8%, 9%, 10%. And there's, of course, others that are doing the negative of that. So. Uh, it's still a tough place out there and we're always like looking for how to take out costs and then how to optimize supply chain. So supply chain's a pretty obvious place because the biggest cost in most health systems, right? One is, uh, labor. Um, and, uh, 2 is definitely cost of supplies. So it's definitely something important. So Jeff, what, what has changed? Has the market changed much in the last couple years since we spoke? What, what do you, what's your perspective?

No, I don't think the market's really changed, you know, a lot with regards to the problem statement. The problem statement is always there inside, you know, US hospital systems and inside US healthcare. So I don't think the problem statement's changed. It is always the question, do I attack direct costs or indirect costs first? And to your point, do I attack labor or do I actually go for supplies? And, you know, there's, you know, various degrees of complexity in both. Be it in direct, you know, people say we've got direct totally under control. It's been under management for many, many years, lots of investments placed inside managing the data of all clinical supplies and services. And then you've got the other flip side of it where you have all the purchase services in direct spend where it is uncategorized, unruly, difficult to manage, really difficult to commoditize. But what's changed for us? Still no different. We still believe that both sides of the equation, direct and indirect, have got still tons of opportunity available.

Yeah. Well, so when we first met up 4 or 5 years ago, when Hunter AI was first developing, of course, then you advanced quite a bit since the last time we spoke, you know, 2 years ago, you already had a working model and you were already doing things. And I know in the last 2 years that has advanced even more. Can you share for the audience that might not know a little bit about Hunter.ai? And then I want to talk about any sort of examples that you can give us, because I think the theory all sounds good, but people always want to know, wow, does this really work?

Yeah. So for those that don't know, Hunter.ai is really focused on spend transparency of all of the financial data inside a hospital system, direct and indirect. You know, effectively we look to truly understand the granular level of detail of the finance data So that you can look at cost recovery, cost reduction exercises, and process efficiencies. And like you say, Ed, 4 and a half years ago, wow, it seems a long time ago that we started. And tens of hospital systems data has actually been placed, you know, through our system and the savings have been quite evident. I suppose what's actually changed in the last 2 years since I last spoke on this podcast. Is that we believe that a lot of the problems that were already solved didn't require our technology. And I'll give you an example. Where our base data actually starts from is from item description of everything that's been purchased inside the invoice. So there might be multiple items on an invoice. So the key question comes back is, if you've got that level of granularity of detail, and we were just focusing on spend transparency, We figured many of the other problem statements would've already been solved. For example, supplier duplication on invoices. Let's say detail on working capital that everyone had working capital under control for suppliers. So for example, were they paying their suppliers on the due date that they were contracted for? Or, you know, what's another example of You know, some of the costs that were under control because they were so big, for example, in clinical, that everything was totally analyzed and that there was no gaps in the data. And what we've literally found is those problem statements haven't been solved universally. The reality is a lot of those gaps are still available in those hospital systems. And don't get me wrong, every hospital system actually has great processes, great IT and systems. in place, but obviously AI provides a deeper granular view of the data and provides scope to find millions of dollars of savings out of that data over and above what has already been retained, controlled, or recovered.

Yeah, it's pretty amazing to me. It seems like, oh, low-hanging fruit, you know, but there's still this in general, not Just talking about spend analytics, but in general, there always seems to be a little bit of a defensiveness amongst a variety of leaders in terms of really taking a close look and pulling out costs. What do you think are the one or two reasons that health systems or someone who'd be interested in purchasing this sort of capability is a little bit resistant?

You know, and we'll get into examples of this, but I'll just give you the 3 that I see. Very simple. People believe that it is a punitive, let's say, technology and, you know, whatever you find is going to harm the people that are originally responsible to control it and manage it, which it purely isn't because, you know, how can you manage tens of millions of data points manually or through legacy systems? You can't. It's not a punitive action. Second component is they believe the cost part. Of implementing a new system inside their current environment will take too long. And another change request to an existing system is just going to be too prohibitive. And then the third is, is this going to be really disruptive to my existing processes and my people? Because I really don't have time to think about this. And, you know, come on, Ed, everyone's saying great AI this, great AI that, and then expecting all of these great results and they actually haven't delivered the results. So now people are a little bit scared of saying, well, I'm going to deploy AI into my environment, but knowing that it might have those 3 knock-on effects inside an organization.

Yeah. And I think a 4th one, it's kind of written in maybe all 3 that you already spoke about is skepticism, right? It's like, oh yeah, we've heard this AI story. And we tried some AI and it didn't work. And here's going to be another example. But I think your first and third one are probably the biggest issues in general when I see new technologies come into healthcare. And the first one, you know, that you mentioned is the punitive one. And we actually saw that one time where, you know, we were able to show, well, we can, we can take out all of these savings. You know, I was working with, I'll be very generic, working with a supply chain. Leader. And we found that indeed we could make all these savings. And, and the person, again, even though we tried really hard to make sure they realized it was not a punitive action, they, you could, by the way they acted, they, they definitely took it that way and took it very personal. And, you know, pride is good and pride in what you do and being the best. But, you know, you don't want to get to the point that you harm your organization by not saying, hey, I learned something new. There's nothing wrong with that. Saying I learned something new. And then the other thing that I remember happening. And again, this is unrelated to Hunter AI, but the general same concepts is, you know, where we found this opportunity. And then they went back to the original vendor to say, look what we found through this analytics. And that vendor was like, we'll just cut a check for $1 million and let's keep going. And, you know, let's keep going in the same direction. And so it's weird that way that there's these opportunities to really pull out costs, but for these human reasons, we're kind of reluctant to do so. So that's another topic perhaps for another episode is like, you know, how do you overcome this resistance in the marketplace? Not again, we're not talking Hunter AI specifically or anything like that, but just new technologies that you bring in and some of the skepticism. And, you know, and I don't want to downplay the third one that you had, which is, hey, I'm pretty busy already. And it's true, right? You know, the average person in healthcare and probably any industry is super busy. You got all these things going on. So it's hard to carve out any sort of time to think about, hey, maybe there's a better way of doing it. Let's analyze this. And so I get all that. So.

Absolutely. You know, because it, you know, 100% as an ex-CIO, right? You've already made out your plans. Your programs of work are already in place. Your budget's been allocated. Your people are there, are already stretched to 100%. 10%. And, you know, I was speaking to a, you know, another member of our advisory board, Sean Lennon, you know, ex-CIO of Medtronic. And he said, you know, Geoff, um, you know, in that instance where they're running SAP, there might be something like 5,000 different points of customization in their system across multiple, let's say, organizations. Trying to add another customization or another implementation on top of that is just, you know, crazy to actually think that it's actually going to happen, and especially perhaps in that budget cycle. So all of these things were, you know, top of mind to actually make sure that when you're looking at AI, you've got to have all of those sorts of considerations under control. Otherwise it's a no-brainer. It will never happen.

Yeah.

Right. Just purely just won't, even though that you might come up and say, oh, I can save you millions of dollars. And I think you would have actually heard this multiple times over. If every supplier came in that I heard that said, I can save you millions of dollars, you know, that CIO would probably have about $10 million in his back pocket. Right.

Right. So yeah, that's completely true. Yeah. I, I am going to put it out there in the show notes and stuff. How do people get ahold of you? I, cause I want to ask you some more questions, Jeff, but I also at the same time, Don't want to come across as infomercial because we don't do infomercials, but if someone is interested in learning more about Hunter AI and is this real or not, how can they find more information about you?

Just simply go to hunterai.com or look at me, Jeff Ahin and Jalil on LinkedIn. And, you know, I want to just press something very, you know, key, right? We've been in now the business for 4 and a half years and On my LinkedIn, and this is not an info commercial from that viewpoint, but you can see that we just presented with Ernst& Young and Christiana Care. You'll see, you know, that we posted $100 million worth of savings plus another $40 million that's actually being planned for this year. And really pleased that we presented this in front of a whole bunch of chief executives and CFOs and chief operating officers. The results were real. And so we presented, didn't actually have to say too much because Bonnie and Jason did a fantastic job. But the feedback was, Jeff, we want to speak to you, not because of what you said, because I hardly spoke. It's because Bonnie went up and said, this is how AI was put into our organization. It did not touch our existing processes. It was based on a full contingency basis. So it didn't cost her anything. Only from a viewpoint, from our viewpoint, that whatever we delivered, we got compensated for. And so the implementation was within days and weeks. So, you know, when someone says it's not real, and then you've got a senior vice president of a health plan that's actually, you know, close to $3 billion in revenue, and they're going up there and saying that, you know, this is what they have achieved. You know, the door is being knocked on on quite a regular basis now. And it is a situation of why don't people do it when they're making people redundant or, you know, not getting the best patient care to the individuals that they serve. So I do find it a challenge. And the question comes back to you, Ed. You speak on the speaking circuit so often. How would someone address this when the reality is staring you in the face?

Yeah. Well, it's great that you have customer testimonial and yeah, people can look on your LinkedIn and find that and see, see real data. So that, I think that's definitely a key. And, and the other thing is, and I think you've done this with, uh, in your business model and the Christiana Care is an example, is there's no upfront cost. You are basically, uh, showing the results and taking part of that result. So, so that was the other thing that I, that I've run into a lot. Is, and I was the same way as CIO. I was like, yeah, I love to do this. How can we do it without being cost neutral or taking cost out and self-funding the particular project? And this is a good example. I think to answer your question, you know, I think it's addressing the 3 or 4 things we talked about a little bit earlier about why are we so defensive, uh, in these things? Because I mean, think about it. I, if I was responsible, so I'm responsible for IT and let's just say I discover that I've been overpaying for my networking, uh, by, let's just say X, it's all a matter of scale. So the dollar amount doesn't matter. It's going to be, let's just say it's a lot of money. It's, it's, uh, overpaying by 25%. And to go back and say to my CFO, hey, I found a way to reduce 25%. And they're going to be like, well, how come we haven't been doing this forever? All right. So that's, again, my natural self is going to be, well, I don't want to show that. But if you think about the greater good of the organization, so I think from a vendor perspective, a partner perspective, you have to help them get through that and tell the story of why it was the way it was. And it's like that everywhere. And thankfully, we're one of the first ones to discover this new way of doing things and leveraging AI. The second, you know, yeah, how do you help someone get through with their pride issue? Again, because, you know, I run the best IT shop in the world or supply chain in the world. And, you know, this is going to make me look bad. But on the other hand, it's like, No, we're continuously improving. We do it on the do it on the care quality side as well. We have you know X percent of a sepsis. We don't do the sepsis bundle. It's fifty percent, and we do some changes in our process, and now it's seventy percent of the times we do our sepsis bundles when required. That's great. Don't look at it as a negative like we were only fifty percent, but look like you've improved twenty percent. So I think it's Jeff. It's just helping people get through this the mindset. And then in terms of the difficulty right now, this is the third thing you had mentioned. Yeah, now it's so hard. I already got my plan. I, you know, now it's just another thing and my team is overworked. Um, but in this case, it may not always be in this case, but in this case, it's rather simple to implement and it's, and it's days, not, not weeks type of thing. And it's not like a year-long project or anything like that. So, so there's opportunity. So you have to think strategically. So I would help people think strategically, like, All right, you already have your set plan. But if you maybe move something out a month, you're gonna do this thing that's gonna give back a ton of money to the organization. I know now I'm sounding like a commercial, but I'm really, Jeff, just answering your question. This is how I've been on both sides. That's how I would work with the customers, like how to help them through that. It's like, yes, you've got a plan. Awesome. But what if you delayed something one month? And as a result, you know, you, you brought back, you took out You know, tens of millions of dollars in costs, then you could have more money to hire more people to do more things that are important and strategic to the organization. And the skepticism, that was sort of the 4th thing. I think you go at risk and in your model, you, it basically is at risk model because you don't pull out any savings. You're not, you don't get any money. So I think that helps get over the skepticism. It's like, yeah, I know you hear AI from everyone and it really doesn't always work quite the way everyone thought. But we're going to go at risk with you. If it doesn't work, you know, it's no, it's, you know, there's no cost to you or whatever it might be. So I think it's just helping people through the mind. It's a mind thing. It's a mind shift. So I talk too much from my own podcast. I want to hear from the guests, but you asked the question. So.

No, no, no, that's fine. Because, you know, all I got to just say is I think it is the pathway to implementation, which I think is critical, right? And it's a learning after 4 and a half years of what was so different from our model. We were jumping in to actually solve the big problem. Actually, we actually jump in now to solve the small problem that delivers big results. And to your point, a non-punitive action is if we can find, you know, a billion out of a billion dollars spend, we can find a million dollars that can be recovered in cash back into the organization's back pocket. Through duplicate supplier invoices or anomalies or fraud detection, even though that they might actually have those systems already in place, but we can actually still find more over and above, why wouldn't you do it? So that's your quick entry point because literally if I can say I can process your data in 24 hours and then within the first week I can actually detect for you, let's say $1 million that you can actually go and look and knock on the door of the supplier. And then I can actually pick up the phone on your behalf and say, hey, this is what we've actually done. This is what we've actually located. This is the invoice. Yes or no? It's a pretty easy discussion to actually have because it's very factual, evidence-based, and it's all on this, on the client's data. And so that's something very small, but I'm just giving you a bad example, right? We've found something for every billion. We've got 1.7 is the lowest. The highest is 3.2 million per billion. So that's duplicate invoices. All of a sudden, you know, it might be managed by another API tool or it might be managed by another financial services organization. What have you got to lose?

Really?

And so that's your, that's your entry point to get over that skepticism because if you can prove it in a week. then all of a sudden what we've found is, wow, if you can do that, can you go back 2 years? Can you go back 3 years? And literally that's what we've been asked to do, right? Go in with the first financial year of data and then all of a sudden peel back 2 years, 3 years. And then all of a sudden you've now got all this data that you can present back to the client of other savings opportunities, which is where we wanted to start at.

Yeah.

But the reality is Perhaps solve the problem, you know, unseen and the easiest first.

Yeah, I have one other comment to make before I get there. Hopefully the last 5, 10 minutes, and not specific about Hunter AI, although that's a great use case. All the things we're talking about right now are things that you should consider for any sort of technology where you think it's going to really move the needle, help transform your organization. We're just talking about really Ways that you could overcome the typical defensive barriers. The last thing I would say, and that's been helpful to me, is make sure you partner with someone because like in this case, this heavy on supply chain, you better be like, don't say if you're the CIO, don't be surprising your supply chain head or your CFO, whoever supply chain might report to. Don't be surprising them or ambushing them or making them feel like putting them in that defensive posture. But basically partnering with them. And similarly, if you're the supply chain person, you know, be working with IT or whoever the important people are and do this together. And I think that way you're going to overcome the punitive, the, the pride, all that kind of stuff. Because you can say, look, we formed this, this, I don't want anyone to form a committee, but we formed this little group, this little short-term team. We did this quick analysis and together we discovered opportunities for savings. And then when the CEO or someone says, or the CFO or whoever, If they're not part of the team directly and they say, how come we didn't know this, you know, years ago? You say, we finally have the technology to do it.

Yeah, exactly.

There are definite ways of overcoming. And that's really my heart, Jeff. And I know because of the experience with your brother, and this is what drives you as well, is like, this is what we need in healthcare is to take out all these costs so we can reinvest in different areas. that actually helps save people's lives. So that's why I, I'm a big believer in it. I'm happy to be on the, on the advisory board. And, you know, I have episodes like this where it just like gets super practical. Like this is how you overcome resistance to technology. Yeah.

And, you know, as always, you know, I would actually just say that my learnings over the last 4 and a half years is sometimes when you're looking to solve the big problem, that's perhaps not the problem that you should be solving. You know, take the sports analogy. You know, you're a semi-professional. I would say obviously you're not professional, but you represent USA, right? Which is of an extremely high standard and kudos to you. But the reality is you don't get out and start racing after 12 months, um, you know, from a rest perspective. Every day you're out there training, you know, whether or not I speak to you sometime, you're either climbing a mountain, you're on a bike, you're running this way. You know, running that way. And it's that 1%, 2% improvement over time. I know it's been done to death with regards to all these sports, you know, psychologists and great sports people that have actually said, you know, it's not a 10% improvement. It's not a 100% improvement. But the big difference that I have with AI, really simple, you can have a 1% improvement on productivity and efficiency, but the value that you would get from an ROI perspective, can be in 100 to 200 to 1,000% value back. That's the big difference from a sports analogy perspective. Yes, I will solve my efficiency by 1 to 2%, but the value from a dollar perspective may be huge. I honestly don't know why people aren't trying to chase this down a little bit more efficiently.

I think we answered that question earlier and it came up with a lot of great ways of overcoming Why that, that why people aren't willing to do it. But anyways, Jeff, always great catching up to you. I love what you're doing, helping these organizations, uh, take out costs and do the things that you do and very mission-driven. So thank you for being a guest the second time on Digital Voices.

Thank you very much, Ed. And I love your podcast and obviously follow you religiously. So thank you for, let's say, your inspiration that you provide your listeners, because it is truly inspirational.

Well, it's, it's my honor and it's only because of guests like you. Hey, that wraps up another edition of Digital Voices. Thanks for listening.

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