Tim Panagos, CTO of Microshare

IoT Applications for Contact Tracing, Predictive Cleaning, and Occupancy Monitoring with Tim Panagos, CTO of Microshare transcript powered by Sonix—easily convert your audio to text with Sonix.

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Saul Marquez:
Welcome back to the Outcomes Rocket podcast, Saul Marquez here, and today I have the privilege of hosting Tim Panagos. He’s the co-founder and Chief Technology Officer at Microshare.io. Tim is an entrepreneur, philosopher, engineer, Co-founder and Chief Technology Officer at Microshare.io, which combines wireless data sources to allow better decision making while respecting the privacy of the individual. Microshares universal contact tracing solution has been adopted globally as the centerpiece of comprehensive COVID-19 responses. Tim is an industry veteran with more than twenty five years of developing data driven applications for banking, health care, retail and manufacturing companies. He studied Computer Science at the University of New Hampshire and holds a master’s in Management of technology from MIT. Tim’s been working on how organizations could be data driven while allowing individuals to maintain agency and privacy in the face of high resolution digital twins’ created by online and offline digital measurements. I am really privileged to have him here to talk to us about the really interesting work that they’re doing at Microshare. And so with that, Tim, I want to give you a warm welcome.

Tim Panagos:
Saul, very much thank you. And thank you for working your way around that mouthful.

Saul Marquez:
Now, man, you’re up to some really neat things, specifically around COVID-19. But but overall, you know how we’re doing the best things to engage with the people we want to engage with and influence behaviors. And so talk to us a little bit about you and what got you involved in health care to begin with.

Tim Panagos:
Yeah, so I’m a technologist, obviously. And for most of my career, I’ve been thinking about sort of data in general and how it can be used to make better business decisions right. so writ large. But I got involved in more of the health care space when I went back to school to get my master’s degree. I actually spent a lot of time looking at how we could use these kind of technologies to improve the way we manage elderly specifically with kind of supported aging in place. And this is going back now 20 years. But it was really very interesting to me because I had aging parents very early. My father particularly was was was on the older side for a young technologist. And I really wanted to explore a more compassionate mechanism to support his aging. And so really did a deep dive into how all that work. And it led me into really the sort of medical or at least quasi medical area to kind of think about this ecosystem of aging in place and and over time came to realize that there’s nothing necessarily specific about aging in place as much as being well in place. And what does that mean? What places and what kind of wellness? Well, there’s some details there, but it just became clear to me that everybody needs to do to have a more supportive environment to help them live the best lives they can.

Saul Marquez:
That’s super interesting. And I always find inspiring how entrepreneurs get into health care. For you it was your dad and just kind of wanting something to make sense. There’s so many things in our buildings. There’s so many things that are oftentimes connected that we’re not leveraging, oftentimes not connected that should be connected. And so what you’re doing is helping make facilities smarter so we can be safer. And so I’ll be honest, this concept of contact tracing is new to me. I love if you could level set there. Tell us a little bit about what exactly that is. And then we could dive into some of the ways that you guys are offering value to the health care ecosystem.

Tim Panagos:
For sure. Well, you can be forgiven for contact tracing being new to you because it’s new to everybody ourselves, including if I couldn’t have predicted as we entered 2020 that this would be the biggest part of our business. But now, many months into twenty twenty, looking at twenty one point twenty twenty one, we find ourselves in a strange spot of being a market leader in a thing that didn’t exist nine months ago, really. And it ultimately is important to the moment and I think will be ongoing importance as people think about whatever the new normal is to returning returning to their workplaces in a more safe way. But contact tracing to put simply, is really the process that allows people to backtrack from an infection, to look at once we have a confirmed case of COVID-19 or really any infectious disease, how do we go back in time and analyze the sort of social network of who that person has been in the presence of and interacted with in a way that might increase the risk of those folks to also contract the disease, in this case, the COVID-19 disease? And it’s really a process more than it is a technology. Some people are doing this manually.

Tim Panagos:
You see, people in the state specifically have implemented this as let me call you if you’ve got a positive diagnosis and then ask you, who have you talked to in the last two weeks, who’ve you had contact with? And in other words, have you come within six feet of of different people? And what I think universally is being experienced is not everybody remembers who they had contact with over. Just think back two weeks and that seems like forever to me. Who might I have interactions with, particularly if you’re not already in quarantine? Right. if you’re back in a work environment, maybe it’s a hospital environment or a manufacturing environment, you’re going to interact with a lot of people through the course of your day. How can you conclusively say you’ve remembered them all? And so what’s developed around that process are supportive technologies, right. things that will help record those contact events so that you can either support the human memory, jogged memory, or provide another way of sort of providing a more holistic view of that overarching risk. And so that really, what contact tracing the technology space has come to me.

Saul Marquez:
Thank you. Thank you. I appreciate you level setting there. And I would imagine it’s a process designed to limit the spread of disease. You have to understand where it’s coming from and how to avoid it.

Tim Panagos:
It’s sort of optimizing the well-being across the population right.. And we do most of our work within the context of a particular commercial environment Right.. So it might be an airport, a hospital or an office building, a factory. So we’re not generally doing it for a government or a jurisdiction, which means that fundamentally the employer is worried about what’s happening in their envelope. But at the same time, the people who are transiting that space right. be the customers, employees, patients, vendors. What they care about is what’s the impact on my coworkers, my family and my friends right.. So it gets really personal to them. But from the employer’s perspective, they’re looking to provide a optimized environment for people right. the balance as well, being with productivity and returns people to a zone where they can be effective at work as much as they possibly can in these times. So it’s a bit of a balance between that individual mandate and the overarching company’s mandate.

Saul Marquez:
That’s pretty cool. That’s pretty cool. And so I think this pandemic and really the way that health care is evolving, more and more employers and also thought leaders are pointing to the importance of health begins outside of the hospital. And this movement that you’re you and your team are spearheading, Tim, is fascinating to me and I’m sure to a lot of the listeners. And so talk to us about how you guys are doing it. And examples work best here. You have an example of how you’ve been able to deploy a solution like this, how it’s improved outcomes. What exactly came out of it that be great?

Tim Panagos:
Absolutely. I think that’s right. So, you know, we hear stories and see see video coming out of health care environments around COVID. And it’s heartbreaking what happens at the tail end of this right. the the overarching outcomes when it gets that far are not great, or even though we’re doing a lot better, obviously. And many thanks to all the listeners for as much work as they put in and as much expertise as they have acquired in a short amount of time. It’s impressive, but I think we can all agree the best the best scenario is keep people out of the intensive care units, right.. And so we really are kind of trying to shift our mission to be oriented towards extending the insights that we might be developing in a scientific or clinical setting and then washing those best practices back in a way that can support the the behavioral changes of the individuals and the organizations that would minimize the impact of the spread and the maybe flattening the curve of controlling the the potential deluge into the health care environment. And I think that’s really important. And again, it follows the theme of using data to kind of break down where human intuition fails us and support human behavioral change and ultimately, hopefully have everybody be able to make the decisions that optimize the health of themselves, their family and their coworkers.

Saul Marquez:
Yeah, and so how does it work?

Tim Panagos:
Like an example?

Saul Marquez:
Yeah. Yeah, no, that’s OK. And I just I’m just wanting to put some handles on this right..

Tim Panagos:
Yeah. Yeah, yeah. So we’ve had maybe a manufacturing environment is is a good angle to start with. We have had some really fantastic early adopters of this technology in the biotech and pharmaceutical space and manufacturers, and they’re presented with a unique challenge, particularly early on, which is they are manufacturing the very medicines and treatments that are necessary to help the globe adapt to this health care problem. So it was really important early on to allow their employees to get back to creating those life saving medicines to ensure that we have an ongoing supply that’s robust. So this was maybe, not surprisingly, the very first wave that was interested in any solution that would balance that employee wellness with the truly critical nature of the work that they were doing. And so, by way of example, we’ve got some of these manufacturers who have global manufacturing for their pharmaceuticals. And in often cases, we’re talking about less developed areas. So Southeast Asia would be a good example of where they actually do manufacturing for maybe some of the more developed areas. What we find is that they’ve got highly trained staff, but often those staff either don’t have cell phones or they’re not allowed to bring their cell phones into their hospital a lot into the manufacturing environment because these are clean environments. Right. So a very restricted into. The things they can wear and carry into those environments so they couldn’t count on sort of cell phone contact tracing, which has been maybe the default that people have put forward.

Tim Panagos:
Certainly Google and Apple have made great strides to allowing their smartphones to be used for this purpose. But we find that there’s plenty of environments where you can assume people have those kind of devices or can take them with them. So what we went to was really a wearable strategy where you can have a device that you can carry that’s very unobtrusive. It often takes the form of a bracelet or a small medallion that you can put on a keychain or a lanyard. And some cases we’ve we’ve had manufacturing clients have put them into washable wristbands or armbands that they could wear on their uniforms, but basically allows them to ignore the need for a smartphone and still have high resolution contact. Basically, what it does is these devices will sense the presence of another device and give you a sense of the duration of a contact and the distance of the contact. So it can tell roughly whether we’re six feet apart for five minutes or three feet apart for 60 minutes. And that information then can be consolidated using some AI tools in the cloud to give you a risk score so that if you happen to be tested positive at some stage, you may have interacted casually with a thousand people in a factory floor.

Tim Panagos:
Over time, a different shift changes and interactions with supervisors, interactions with machines that you might have touched and left fomites behind. It’s actually a fairly complex question, but we can use A.I. tools in this data to give administrators a way to prioritize their response because they don’t want to shut the whole factory down. It’s important that the business remains functional, but they want to sort of direct to the most likely areas to either encourage more quarantine of people to provide additional testing or whatever the resources that they have available generally or scarce resources they want to give them to the people who are most likely impacted. So what we will do is from the thousand potential people that you might have contacted on the factory floor, we’ll narrow it down to some number of of really high risk contacts. And they might be high risk because you’ve had multiple contacts throughout the period. It might be duration of a single contact. It might be proximity. But we’ve actually been working with some universities and pharmaceutical folks who have some some really important models that help us to really define that risk. And it’s about putting that back into the hands of the individuals and the human resources typically department whose job it is to really to care for those folks and limit the spread.

Saul Marquez:
Man. That is interesting and seems difficult. It feels like it’s one of those things where why there’s a lot involved, you know, and but when you’re dealing with so many people moving around in an environment, you’ve got to have a way to do it. Right. And do you find that this is typically in larger environments with masses of people?

Tim Panagos:
I think that’s right Saul. We are kind of specializing in wireless sensing in general Right.. So even before contact tracing in 2020. It’s about doing this at scale. If you just think about a normal building Right. if I have one doctor’s office that I manage and it’s got four exam rooms, a waiting room and an administrative area, that’s complex enough. But the chances are I understand my building fairly well. I will see where it’s too cold or too warm. I’ll notice that there’s leaks and it might still be a challenge to to trace contact. But I’ve got lists of patients and I know what my staff are. It’s manageable Right. so a human can get away with that. But when you start scaling that up right now, it’s not just one practice area, it’s 10. And it’s not just five thousand square feet, it’s five hundred thousand square feet. These are environments that you just can’t expect the human mind to be able to balance the complexity of managing it the way we we generally do by walking around. It’s now at the scale where you really need support, particularly when you throw everything out the window like we have with something unprecedented, like COVID-19, where there isn’t a well-worn path for how to handle this stuff. So you really need to give people the tools that will allow them to keep doing what they need to do without expecting to already understand it, because it’s just it’s it’s it’s beyond experience. So I do think it’s at scale where this really comes to play primarily. And and I think that’s what we’ve really focused on, people with with larger, more complex organizations. And I think that’s that’s been bearing fruit for people.

Saul Marquez:
Fascinating. And I’m curious. So. Two of the things we like to focus on here on the podcast are outcomes improvement and business innovation like business model innovation. Can you point to either of those two items and maybe talk to how you guys have been able to improve one or the other or both?

Saul Marquez:
Yeah, sure. So I think the ink is not at all dry yet on our current crisis and how contact tracing will play into it. So from an outcomes, the early experience that we have is less on the efficacy of preventing transmission, because ultimately we we do hope that’s what we’re getting to, is making better decisions. So we limit transmission and the data just isn’t really available yet at the scale necessary to know. But what we can tell really early on is that humans will show up to work reluctantly with something like this. And it really depends on the trust level they have for their environment, whether that’s the employer or the jurisdiction or the building manager. The people who transmit a space have different ways of thinking about why and who they trust in that. But it does end up being a human problem. Do I trust my my janitorial staff to be clean and do I trust the hospital administrator to have my my back, or do I trust my coworkers to be helping me protect myself and my family? What we do see really early on is by putting some of these supportive solutions in place and making it clear to the people who are working in or transiting the space because the customers are patients, that the effort of showing them that we’re that the organizations are going to the trouble to manage this and that they care enough to be investing this way does at least give people more comfort.

Tim Panagos:
That leads to better productivity. Right. that you can share, at least for a moment, parties this to decide and say I can trust this organization to at least be thinking about the problem. But they’re not all seeing, all knowing, but at least they’re worried about it. At least they’re taking steps. And then I think when you fold in other things, not just contact tracing but visible cleaning and employee feedback and air quality measurement. And our ideal is that this is not even done from on high Right. it’s not Big Brother managing all this data on your behalf. Ideally, we’re pushing that data in real time out to the people who are actually on the floor so that they can make their own decisions. They can say, oh, Saul has been really dutiful and his contact regime, so his risk is really low. I’m more likely to say, yeah, let’s go, let’s go grab a cup of coffee and talk about a work problem. But if I see that that Saul has been exposed in a potentially risky way, then he and I might mutually decide, you know what? This is not a good week. Let’s do this by Zoom or whatever right. we want ultimately to give the power of all this information. We’ve got to simplify it because like I said, there’s a lot of moving parts. And that’s one thing we’ve learned is it’s too easy to overwhelm humans by trying to do the right thing and giving them too much because they’ve got day jobs, they’ve got complicated day jobs.

Tim Panagos:
You don’t want to be like requiring all that mental effort because that itself is a drain. We want to try to make it easy. So we’re trying to boil things down. You think about a credit score, Right.. Everybody’s got a FICO score and it folds together a lot of complex information and even a bank, it’s too complex for a bank to use all the detailed information. So folding it into a single number is really helpful to drive business decisions. That’s kind of what we’re trying to do with this greater wellness perspective, is to say this space has to score, this person has to score. This asset has a score so that you can kind of quickly look, is this a red, yellow, green, move on with my job. Right. But I could I could make in the moment decisions based on that that wouldn’t be taxing, hopefully would be reassuring. And we do think over time will improve outcomes. But in the end, where we may have to wait a couple of years to see enough data to really be able to conclude that. So we’re we’re kind of we’re kind of working on the best information we can see from other epidemiological studies in this area and trying to bring the best experience we can to say we think this is what will do the job.

Saul Marquez:
Yeah, that’s really interesting. Tim, your example of the credit score paints a good picture. And I also think about just the competition in right. competition for employees. Yes, Right.. And if you could somehow make this like one like the Leapfrog rating for hospitals Right., does this fold into like a lead certification in how are how should people be thinking about this?

Tim Panagos:
That’s a fantastic insight. Good on you, man. You’re absolutely right. Right. in environments where people are competing for the best employees, I think whether covid is done magically this November or whether we live with it for another five years, which every year can, I think one of the things that’s going to be clear is people will know forever now that this is possible and that there are employees, employers that worry about employee wellness and those that don’t. And so I think this is a watershed moment where and I think it’s I think it’s a part and parcel of sustainability, which has been an increasing employee value as well. Is this becomes a part of this? Has my employer shown that they are taking positive steps to address my ongoing wellness and that impacts not just me, but my family and friends. So it’s really important. When you begin to compete with retention and attraction of the best people. I think that’s exactly what’s going to happen, is there will be a way to show off that I’m collecting the data on open and visible with the data. I’m transparent with what I do. I care. And I should also be able to show where I fit in the ecosystem Right. because a credit score is useful to know that I’ve got a 350.

Tim Panagos:
But it’s even better when I know that Sol has a seven fifty because now, now I have context where do I fit in? So that benchmarking is really important and will allow people to compete on an entirely new dimension to get the best people. And that could be a specific employer. It could be a region. It could be a jurisdictional regime. Which country is best at managing pandemics? I think we know which countries are lagging. But, you know, over time, I do think that a score will be something that people will be interested in showing off when they’re doing really well, being ashamed of when they’re not. But ultimately, what I really hope is that the social pressure increases to the point where nobody can afford to ignore.

Saul Marquez:
That’s what it is.

Tim Panagos:
It brings it to the fore. So if we if the tide rises, all boats, some will be higher than others, perhaps. But we want just the stance globally to be doing better with these kind of interventions over time. And there’s no way to do that, in my mind, without clear, concise and consistent data that you can actually put into people’s hands.

Saul Marquez:
Yeah, that’s powerful, man. I am. I had an interview with the Leapfrog Group leader and she was talking about how she pulled from the it was a story the New York Health and Sanitation Department and how they went from not really getting results to assigning basic letters A B. Yeah. And and just posting it right in the front. Wow. That could destroy your business if you are not up with it. And so very cool stuff, Tim. I love it. And as you’ve been building your business model, delivering on this ask contact tracing health of the facility and the people within the facility, what have you noticed has been one thing that like maybe your biggest challenge and what have you learned from that, from that challenge?

Tim Panagos:
Yeah, I think the the most important thing that we’ve learned is, is that sort of cognitive load lesson of more data doesn’t necessarily lead to better outcomes.

Saul Marquez:
Yeah, you alluded to that earlier.

Tim Panagos:
But to underscore, it’s worth saying twice, really, you have to contextualize the information in a way that’s trustworthy. You’re not trying to hide information. So you always want to be able to allow people to drill in and get the nitty gritty detail as they want to be. But once you’ve done that and earn some basic trust, you’ve got to be able to elevate the information so that people can just weave it into what they do now, particularly in a health care environment. You know, you don’t want to give a busy nurse another thing, but they have to go out of their way to understand. It should just be easy letter, grade color, you know, a notification when something is wrong rather than make it another paperwork task or another overwhelming technical thing. That’s really been our job as we’ve gone through it is ultimately that’s what our customers pay us for, is to take the complexity out of all this Right. so you don’t choosing a wireless network in a security model, in a cloud provider and all the things that, let’s say, five years ago, if you wanted to do this, you’d have to choose to make all of that simple so the buyers can just buy it, that there’s a simple way to consume it and that the end users can just kind of adopt it naturally to make their lives better. And ideally, they pull that information because they want it. You’re not forcing it down their throats. That’s been the lesson is really kind of meet the customers where they are and bring them up the educational ladder in terms of using data to make better decisions because, you know, it’s not the world most of us live in on a daily basis, although everybody wants more information, more insight, they want to do things better. So how do you make it possible without getting a PhD and and wireless data Right.? So that’s really been the lesson is, is really focus, focus, focus, simplify, simplify and bury the complexity, but and deliver the insight, but try to do it in a transparent way as well.

Saul Marquez:
Man, that’s insightful for sure. And and bringing up some good points for all of us to consider around how we manage our workplace, how we present information if we consider something like contact tracing. As you reflect on what has happened, this new focus, relatively new focus that you guys are on, what are you most excited about today, Tim?

Tim Panagos:
Well, you know, like I said Saul I couldn’t have envisioned that this is what we’d be up to this year.

Saul Marquez:
Crazy right.

Tim Panagos:
It’s crazy and it’s gratifying. It’s exciting to be able to do well while doing good is, that’s the pinnacle, I think, of any entrepreneurs wish list. And this is presented, I think, an opportunity to be really impactful, both on really individual well-being, which I just how could you not? I think your audience that’s probably what attracted all of us to that. And at the same time, having these societal and economic benefits that are hard to dispose of as well, and particularly where people working in health care, they understand that it’s important for them to be effective at work, even while I’m nervous about what this is going to do to their own personal lives. And I’m just excited that I was able to to bring some of these nutty technologies in a way that makes it possible for people to keep doing the good work they need to do while watching our backs for them, because ultimately, that’s what I feel like we all should be doing, supporting the hard work to get through this and then over time, building up the awareness that this data is available and it’s helpful and you don’t need a quarantine to be able to make better decisions. So it’s also kind of cool that this is a compelling event that as dire as it is, it will also force people to incorporate these kind of tools and technologies because I think it can improve outcomes over time, even outside of this current.

Saul Marquez:
And I think it’s awesome, man. And and, yeah, you bring out some great, great ideas, some important considerations for all of us. Now’s the time to to think ahead. And how can you use what Tim has shared today for for your own business, for your population that you’re responsible for, for your employees? Certainly something to to consider. And this has been so interesting. I really thank you for for the opportunity to to share what what you guys are up to at Micro Share folks. It’s micro share that. I know you want to learn more about what they’re up to. Tim, share with us a closing thought and then the best place where the listeners can engage with you or your team if they want to continue the conversation.

Tim Panagos:
Yeah. Saul first of all, thank you. It’s humbling and awesome to be able to speak with you and and present to your audience. I’m really interested in what your audience thinks about these ideas, what their worries and concerns are, because we’re still very much in the in the beginnings of this. We’ve deployed in some really large scale. We’ve got tens of thousands of people being protected by these technologies. But this is really just the beginning. And I think health care is an area that has been dealing with sensitive data forever in the service of improving outcomes right. So this is the audience that is likely to have insights that are applicable to people who are mining and manufacturing and things that are typically not dealing with such sensitive information. So I’d be really interested in anybody has any thoughts about what could improve or what angle or what would make it more applicable to them? I think it will help us improve the outcome for a lot of people and ultimately, hopefully keep people out of that intensive care unit and make the health care more sustainable. So I’d really you may not be a customer. You may not care about this technology, but I’m really interested in your insight, how we can make this better for everybody.

Saul Marquez:
I love it. And folks, they have it an invitation to to converse and discuss what the opportunities of this technology could be with Tim. He’s opening up his door for a conversation. And what’s the best way for folks to reach out to you if they want to?

Tim Panagos:
I think the easiest way is if you’re on Twitter, you can get me at microshare_CTO. Send me a direct message and let’s open a channel/.

Saul Marquez:
Love it. There you have it, folks. And we will provide also link to microshare.io and Tim’s Twitter handle on the website, outcomesrocket.health. Type in microshare in the search bar and you’ll find that there along with the full transcript, questions that we asked him and the full interview. Tim, this has been awesome and keep up the great work, really thankful for everything we discussed today here.

Tim Panagos:
Saul, thanks for having me.

Saul Marquez:
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