Cerner’s Lifesaving Sepsis Control Solution Shows the Potential of Bringing More AI-Enabled IoT to the Healthcare Edge

A discussion on how near real-time analytics at the edge helps caregivers at hospitals head off sepsis episodes and reduce serious illness and deaths.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Hewlett Packard Enterprise.

Dana Gardner: Hello, and welcome to the next edition of the BriefingsDirect Voice of the Customer podcast series. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator for this ongoing discussion on the latest insights into the confluence of edge computing and artificial intelligence (AI).

Gardner

Our next intelligent edge adoption benefits discussion focuses on how hospitals are gaining proactive alerts on patients at risk for contracting serious sepsis infections. An all-too-common affliction for patients around the world, sepsis can often be controlled when confronted early.

Now, using edge sensors, Wi-Fi data networks and AI solutions that identify at-risk situations, caregivers at hospitals are rapidly alerted to susceptible patients so they can head-off sepsis episodes and reduce serious illness and deaths.

Stay with us now as we hear about a cutting-edge use case that puts near real-time AI to good use by outsmarting a deadly infectious scourge.

To learn how, please join me now in welcoming our guests, Missy Ostendorf, Global Sales and Business Development Practice Manager at Cerner Corp. Welcome to the show, Missy.

Missy Ostendorf: Thank you very much.

Gardner: We’re also here with Deirdre Stewart, Senior Director and Nursing Executive at Cerner Europe. Welcome, Deirdre.

Deirdre Stewart: Thank you very much.

Gardner: And we’re also here with Rich Bird, World Wide Industry Marketing Manager for Healthcare and Life sciences at Hewlett Packard Enterprise (HPE). Welcome, Rich.

Rich Bird: Thank you, Dana, and hello everyone.

Gardner: Missy, what are the major trends driving the need to leverage more technology and process improvements in healthcare? When we look at healthcare, what’s driving the need to leverage better technology now?

Time is of the tech essence 

Ostendorf

Ostendorf: That’s an easy question to answer. Across all industries resources always drive the need for technology to make things more efficient and cost-conservative -- and healthcare is no different.

If we tend to lead more slowly with technology in healthcare, it’s because we don’t have mission-critical risk -- we have life-critical risk. And the sepsis algorithm is a great example of that. If a patient turns septic, they have four hours and they can die. So, as you can imagine, that clock ticking is a really big deal in healthcare.

Gardner: And what has changed, Rich, in the nature of the technology that makes it so applicable now to things like this algorithm to intercept sepsis quickly?

Bird: The pace of the change in technology is quite shocking to hospitals. That’s why they can really benefit when two globally recognized organizations such as HPE and Cerner can help them address problems.

When we look at the demand-spike across the healthcare system, we see that people are living longer with complex long-term conditions. When they come into a hospital, there are points in time when they need the most help.

What [HPE and Cerner] are doing together is understanding how to use this connected technology at the bedside. We can integrate the Internet of Things (IoT) devices that the patients have on them at the bedside, medical devices traditionally not connected automatically but through the humans. The caregivers are now able to use the connected technology to take readings from all of the devices and analyze them at the speed of computers.

So we’re certainly relying on the professionalism, expertise, and the care of the team on the ground, but we’re also helping them with this new level of intelligence. It offers them and the patients more confidence in the fact that their care is being looked at from the people on the ground as well as the technology that’s reading all of their life science indicators flowing into the Cerner applications.

Win against sepsis worldwide 

Gardner: Deirdre, what is new and different about the technology and processes that makes it easier to consume intelligence at the healthcare edge? How are nurses and other caregivers reacting to these new opportunities, such as the algorithm for sepsis?

Stewart

Stewart: I have seen this growing around the world, having spent a number of years in the Middle East and looking at the sepsis algorithm gain traction in countries like Qatar, UAE, and Saudi Arabia. Now we’re seeing it deployed across Europe, in Ireland, and the UK.

Once nurses and clinicians get over the initial feeling of, “Hang on a second, why is the computer telling me my business? I should know better.” Once they understand how that all happens, they have benefited enormously.

But it’s not just the clinicians who benefit, Dana, it’s the patients. We have documented evidence now. We want to stop patients ever getting to the point of having sepsis. This algorithm and other similar algorithms alert the front-line staff earlier, and that allows us to prevent patients developing sepsis in the first place.

Some of the most impressive figures show the reduction in incidents of sepsis and the increase in the identification of the early sepsis stages, the severe inflammatory response part. When that data is fed back to the doctors and nurses, they understand the importance of such real-time documentation.

I remember in the early days of the electronic medical records; the nurses might be inclined to not do such real-time documentation. But when they understand how the algorithms work within the system to identify anything that is out of place or kilter, it really increases the adoption, and definitely the liking of the system and what it can provide for.

Gardner: Let’s dig into what this system does before we look at some of the implications. Missy, what does the Cerner’s CareAware platform approach do?

Ostendorf: The St. John Sepsis Surveillance Agent looks for early warning signs so that we can save lives. There are three pieces: monitoring, alerting, and then the prescribed intervention.

It goes to what Deirdre was speaking to about the documentation is being done in real-time instead of the previous practice, where a nurse in the intensive care unit (ICU) might have had a piece of paper in her pocket and she would write down, for instance, the patients’ vital signs.

A lot can happen in four hours in the ICU. By having all of the information flow into the electronic medical record we can now have the sepsis agent algorithm continually monitoring that data.

And maybe four hours later she would sit at a computer and put in four hours of vitals from every 15 minutes for that patient. Well, as you can imagine, a lot can happen in four hours in the ICU. By having all of the information flow into the electronic medical record we can now have the sepsis agent algorithm continually monitoring that data.

It surveys the patient’s temperature, heart rate, and glucose level -- and if those change and fall outside of safe parameters, it automatically sends alerts to the care team so they can take immediate action. And with that immediate action, they can now change how they are treating that patient. They can give them intravenous antibiotics and fluids, and there is 80 percent to 90 percent improvement in lives saved when you can take that early intervention.

So, we’re changing the game by leveraging the data that was already there, we are just taking advantage of it, and putting it into the hands of the clinicians so that action can be taken early. That’s the most important part. We have been able to actionize the data.

Gardner: Rich, this sounds straightforward, but there is a lot going on to make this happen, to make the edge of where the patient exists able to deliver data, capture data, protect it and make it secure and in compliance. What has had to come together in order to support what was just described by Missy in terms of the Cerner solution?

Healthcare tech progresses to next level 

Bird

Bird: Focusing on the outcomes is very important. It delivers confidence to the clinical team, always at the front of mind. But it provides that in a way that is secured, real-time, and available, no matter where the care team are. That’s very, very important. And the fact that all of the devices are connected poses great potential opportunities in terms of the next evolution of healthcare technology.

Until now we have been digitizing the workflows that have always existed. Now, for me, this represents the next evolution of that. It’s taking paper and turning it into digital information. But then how do we get more value from that? Having Wi-Fi connectivity across the whole of a site is not something that’s easy. It’s something that we pride ourselves on making simple for our clients, but a key thing that you mentioned was security around that.

When you have everything speaking to everything else, that also introduces the potential of a bad actor. How do we protect against that, how do we ensure that all of the data is collected, transported, and recorded in a safe way? If a bad actor were to become a part of external network and internal network, how do we identify them and close it down?

Working together with our partners, that’s something that we take great pride in doing. We spoke about mobility, and outside of healthcare, in other industries, mobility usually means people have wide access to things.

But within hospitals, of course, that mobility is about how clinicians can collect and access the data wherever they are. It’s not just one workstation in a corner that the care team uses every now and again. The technology now for the care team gives them the confidence to know the data they are taking action on is collected correctly, protected correctly, and provided to them in a timely manner.

Gardner: Missy, another part of the foundational technology here is that algorithm. How are machine learning (ML) and AI coming to bear? What is it that allowed you to create that algorithm, and why is that a step further than simple reports or alerts?

Ostendorf: This is the most exciting part of what we’re doing today at Cerner and in healthcare. While the St. John’s Sepsis Algorithm is saving lives in a large-scale way – and it’s getting most of the attention -- there are many things we have been able to do around the world.

Deirdre brought up Ireland, and even way back in 2009 one of our clients there, St. James’s Hospital in Dublin, was in the news because they made the decision to take the data and build decision-making questions into the front-end application that the clinicians use to order a CT scan. Unlike other X-rays, CT scans actually provide radiation in a way that’s really not great. So we don’t want to have a patient unnecessarily go through a CT scan. The more they have, the higher their risks go up.

They take the data and build decision-making questions into the front-end of the application the clinicians use to order a CT scan. We don't want to have a patient unnecessarily go through a CT scan. Now with ML, it can tell the clinician whether the CT scan is necessary for the treatment of that patient.

By implementing three questions, the computer looks at the trends and why the clinicians thought they needed it based on previous patients’ experiences. Did that CT scan make a difference and how they were diagnosed? And now with ML, it can tell the clinician on the front end that, “This really isn’t necessary for what you are looking for to treat this patient.”

Clinicians can always override that, they can always call the x-ray department and say, “Look, here’s why I think this one is different.” But in Ireland they were able to lower the number of CT scans that they had always automatically ordered. So with ML they are changing behaviors and making their community healthier. That’s one example.

Another example of where we are using the data and ML is with the Cerner Opioid Toolkit in the United States (US). We announced that in 2018 to help our healthcare system partners combat the opioid crisis that we’re seeing across America.

Deirdre, you could probably speak to the study as a clinician.

Algorithm assisted opioid-addiction help

Stewart: Yes, indeed. It’s interesting work being done in the US on what they call Opioid-Induced Respiratory Depression (OIRD). It looks like approximately 1 in 200 hospitalized surgical patients can end up with an opioid-induced ventilatory impairment. This results in a large cost in healthcare. In the US alone, it’s estimated in 2011 that it cost $2 billion. And the joint commission has made some recommendations on how the assessment of patients should be personalized.

It’s not just one single standardized form with a score that is generated based on questions that are answered. Instead it looks at the patients’ age, demographics, previous conditions, and any other history with opioid intake in the previous 24 hours. And according to the risks of the patient, it then recommends limiting the number of opioids they are given. They also looked at the patients who ended up in respiratory distress and they found that a drug agent to reverse that distress was being administered too many times and at too high a cost in relation to patient safety.

Now with the algorithm, they have managed to reduce the number of patients who end up in respiratory distress and limit the number of narcotics according to the specific patients. It’s no longer a generalized rule. It looks at specific patients, alerts, and intervenes. I like the way our clients worldwide work in the willingness to share this information across the world. I have been on calls recently where they voiced interest in using this in Europe or the Middle East. So it’s not just one hospital doing this and improving their outcomes -- it’s now something that could be looked at and done worldwide. That’s the same whenever our clients devise a particular outcome to improve. We have seen many examples of those around the world.

Ostendorf: It’s not just collecting data, it’s being able to actualize the data. We see how that’s creating not only great experiences for a partner but healthier communities.

Gardner: This is a great example of where we get the best of what people can do with their cognitive abilities and their ability to contextualize and the best of the machines to where they can do automation and orchestration of vast data and analytics. Rich, how do you view this balancing act between attaining the best of what people can do and machines can do? How do these medical use cases demonstrate that potential?

Machines plus, not instead of, people 

Bird: When I think about AI, I grew up in the science fiction depiction where AI is a threat. If it’s not any taking your life, it’s probably going to take your job.

But we want to be clear. We’re not replacing doctors or care teams with this technology. We’re helping them make more informed and better decisions. As Missy said, they are still in control. We are providing data to them in a way that helps them improve the outcomes for their patients and reduce the cost of the care that they deliver.

It’s all about using technology to reduce the amount of time and the amount of money care costs to increase patient outcomes – and also to enhance the clinicians’ professionalism.

Missy also talked about adding a few questions into the workflow. I used to work with a chief technology officer (CTO) of a hospital who often talked about medicine as eminence-based, which is based on the individuals that deliver it. There are numerous and different healthcare systems based on the individuals delivering them. With this digital technology, we can nudge that a little bit. In essence, it says, “Don’t just do what you’ve always done. Let’s examine what you have done and see if we can do that a little bit better.”

We know that personal healthcare data cannot be shared. But when we can show the value of the data when shared in a safe way, the clinical teams can see the value generated . It changes the conversation. It helps people provide better care.

The general topic we’re talking about here is digitization. In this context we’re talking about digitizing the analog human body’s vital signs. Any successful digitization of any industry is driven by the users. So, we see that in the entertainment industry, driven by people choosing Netflix over DVDs from the store, for example.

When we talk about delivering healthcare technology in this context, we know that personal healthcare data cannot be shared. It is the most personal data in the world; we cannot share that. But when we can show the value of data when shared in a safe way -- highly regulated but shared in a safe way -- the clinical teams can then see the value generated from using the data. It changes the conversation to how much does the technology cost. How much can we save by using this technology?

For me, the really exciting thing about this is technology that helps people provide better care and helps patients be protected while they’re in hospital, and in some cases avoid having to come into the hospital in the first place.

Gardner: Getting back to the sepsis issue as a critical proof-point of life-enhancing and life-saving benefits, Missy, tell us about the scale here. How is this paying huge dividends in terms of saved lives?

Life-saving game changer 

Ostendorf: It really is. The World Health Organization (WHO) statistics from 2018 show that 30 million people worldwide experience a sepsis event. In their classification, six million of those could lead to deaths. In 2018 in the UK, there were 150,000 annual cases, with 44 of those ending in deaths.

You can see why this sepsis algorithm is a game-changer, not just for a specific client, but for everyone around the world. It gives clinicians the information they need in a timely manner so that they can take immediate action -- and they can save lives.

Rich talked about the resources that we save, the cost that’s driven out, all those things are extremely important. When you are the patient or the patient’s family, that translates into a person who actually gets to go home from the hospital. You can’t put a dollar amount or an efficiency on that.

It’s truly saving lives and that’s just amazing to think that. We’re doing that by simply taking the data that was already being collected, running that through the St. John’s sepsis algorithm and alerting the clinicians so that they can take quick action.

Stewart: It was a profound moment for me after Hamad Medical Corp. in Qatar, where I had run the sepsis algorithm across their hospitals for about 11 months, did the data and they reckoned that they had potentially saved 64 lives.

And at the time when I was reading this, I was standing in a clinic there. I looked out at the clinic, it was a busy clinic, and I reckoned there were 60 to 70 people sitting there. And it just hit me like a bolt of lightning to think that what the sepsis algorithm had done for them could have meant the equivalent of every single person in that room being saved. Or, on the flipside, we could have lost every single person in that room.

Mothers, fathers, husbands, wives, sons, daughters, brothers, sisters -- and it just hit me so forcefully and I thought, “Oh, my gosh, we have to keep doing this.” We have to do more and find out all those different additional areas where we can help to make a difference and save lives.

Gardner: We have such a compelling rationale for employing these technologies and processes and getting people and AI to work together. In making that precedent we’re also setting up the opportunity to gather more data on a historical basis. As we know, the more data, the more opportunity for analysis. The more analysis, the more opportunity for people to use it and leverage it. We get into a virtuous, positive adoption cycle.

Rich, once we’ve established the ability to gather the data, we get a historical base of that data. Where do we go next? What are some of the opportunities to further save lives, improve patient outcomes, enhance patient experience, and reduce costs? What is the potential roadmap for the future?

Personalization improves patients, policy 

Bird: The exciting thing is, if we can take every piece of medical information about an individual and provide that in a way that the clinical team can see it from one end of the user’s life right up to the present day, we can provide medicine that’s more personalized. So, treating people specifically for the conditions that they have.

Missy was talking about evaluating more precisely whether to send a patient for a certain type of scan. There’s also another side of that. Do we give a patient a certain type of medication?

When we’re in a situation where we have the patient’s whole data profile in front of us, clinical teams can make better decisions. Are they on a certain medication already? Are they allergic to a medication that you might prescribe to them? Will their DNA, the combination of their physiology, the condition that they have, the multiple conditions that they have – then we start to see that better clinical decisions can be made. We can treat people uniquely for the specific conditions.

At Hewlett Packard Labs, I was recently talking with an individual about how big data will revolutionize healthcare. You have certain types of patients with certain conditions in a cohort of patients, but how can we make better decisions on that cohort of patients with those co-conditions? You know, with at a specific time in their life, but then also how do we do that from an individual level of individuals?

Rather than just thinking about patients as cohorts, how could policymakers and governments around the world make decisions based on impacts of preventative care, such as more health maintenance? We can give visibility into that data to make better decisions for populations over long periods of time.

It all sounds very complicated, but my hope is, as we get closer, as the power of computing improves, these insights are going to reveal themselves to the clinical team more so than ever.

There’s also the population health side. Rather than just thinking about patients as individuals, or cohorts of patients, how could policymakers and governments around the world make decisions based on impacts of preventative care, such as incentivizing populations to do more health maintenance? How can we give visibility into that data into the future to make better decisions for populations over the longer period of time?

We want to bring all of this data together in a safe way that protects the security and the anonymity of the patients. It could provide those making clinical decisions about the people that are in front of them, as well as policymakers to look over the whole population, the means to make more informed decisions. We see massive potential around prevention. It could have an impact on how much healthcare costs before the patient actually needs treatment.

It’s all very exciting. I don’t think it’s too far away. All of these data points we are collecting are in their own silos right now. There is still work to do in terms of interoperability, but soon everybody’s data could interact with everybody else’s data. Cerner, for example, is making some great strides around the population health element.

Gardner: Missy, where do you see accelerating benefits happening when we combine edge computing, healthcare requirements, and AI?

At the leading edge of disease prevention

Ostendorf: I honestly believe there are no limits. As we continue to take the data in in places like in northern England, where the healthcare system is on a peninsula, they’re treating the entire population.

Rich spoke to population health management. Well, they’re now able to look across the data and see how something that affects the population, like diabetes, specifically affects that community. Clinicians can work with their patients and treat them, and then work the actual communities to reduce the amount of type 2 diabetes. It reduces the cost of healthcare and reduces morbidity rate.

That’s the next place where AI is going to make a massive impact. It will no longer be just saving a life with the sepsis algorithm running against those patients who are in the hospital. It will change entire communities and how they approach health as a community, as well as how they fund healthcare initiatives. We’ll be able to see more proactive management of health community by community.

Gardner: Deirdre, what advice do you give to other practitioners to get them to understand the potential and what it takes to act on that now? What should people in the front lines of caregiving be thinking about on how to best utilize and exploit what can be done now with edge computing and AI services?

Stewart: Everybody should have the most basic analytical questions in their heads at all times. How can I make what I am doing better? How can I make what I am doing easier? How can I leverage the wealth of information that is available from people who have walked in my shoes and looked after patients in the same way as I’m looking after them, whether that’s in the hospital or at home in the community? How do I access that in an easier fashion, and how do I make sure that I can help to make improvements in it?

Access to information at your fingertips means not having to remember everything. It’s having it there, and having suggestions made to me. I’m always going back and reviewing what those results and analytics are to help improve the next time, the next time around.

From bedside to boardroom, everybody should be asking themselves those questions. Have I got access to the information I need? And how can I make things better? What more do I need?

Gardner: I’m afraid we’ll have to leave it there. We’ve been exploring how hospitals are gaining proactive alerts on patients at risk for contracting life-threatening sepsis infections. But we’ve also learned about a larger perspective of how edge computing and AI are enabling caregivers around the world to respond to more types of issues and become more intelligent about providing better care for people.

Please join me in thanking our guests, Missy Ostendorf, Global Sales and Business Development Practice Manager at Cerner Corp. Thank you so much, Missy.

Ostendorf: Thank you. It was fun to be here.

Gardner: We’ve also been joined by Deirdre Stewart, Senior Director and Nursing Executive at Cerner Europe. Thank you so much, Deirdre.

Stewart: It was an absolute pleasure. Thank you.

Gardner: And lastly, we’ve been here with Rich Bird, Worldwide Industry Marketing Manager for Healthcare and Life Sciences at HPE. Thank you, Rich.

Bird: Thank you.

Gardner: And lastly a thank you to our audience for joining this BriefingsDirect Voice of the Customer Internet of Things and AI strategies interview. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of HPE-sponsored discussions.

Thanks again for listening. Please pass this on to your community, and do come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Hewlett Packard Enterprise.

A discussion on how near real-time analytics at the edge helps caregivers at hospitals head off sepsis episodes and reduce serious illness and deaths. Copyright Interarbor Solutions, LLC, 2005-2019. All rights reserved.

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Three Generations of Citrix CEOs on Enabling a Better Way to Work

Transcript of a discussion on how Citrix is building on its 30-year record of success by remaking digital workplaces and redefining the very nature of applications and business intelligence.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Citrix.

Dana Gardner: Hi, this is Dana Gardner, Principal Analyst at Interarbor Solutions, and you’re listening to BriefingsDirect.

Gardner

For the past 30 years, Citrix has made a successful habit of challenging the status quo. That includes:

• Delivering applications as streaming services to multiple users
• Making the entire PC desktop into a secure service
• Enhancing networks that optimize applications delivery
• Pioneering infrastructure-as-a-service (IaaS) now known as public cloud, and
• Supplying a way to take enterprise applications and data to the mobile edge.

Now, Citrix is at it again, by creating digital workspaces and redefining the very nature of applications and business intelligence. How has one company been able to not only reinvent itself again and again, but make major and correct bets on the future direction of global information technology?

To find out, I recently sat down with three of Citrix’s chief executives from the past 30 years, Roger Roberts, Citrix CEO and Chairman from 1990 to 2002; Mark Templeton, CEO of Citrix from 2001 to 2015, and David Henshall, who became the company’s CEO in July of 2017.

So much has changed across the worker productivity environment over the past 30 years. The technology certainly has changed. What hasn’t changed as fast is the human factor, the people.

How do we keep moving the needle forward with technology and also try to attain productivity growth when we have this lump of clay that’s often hard to manage, hard to change?

Technology for humans 

Templeton

Mark Templeton: The human factor “lump of clay” is changing as rapidly as technology because of the changing demographics of the workforce. Today’s baby boomers are being followed by generations of millennials, Gen Y, Gen X and then Gen Z will be making important decisions 20 years from now.

So the human factor clay is changing rapidly and providing great opportunity for innovation and invention of new technology in the workplace.

Gardner: The trick is to be able to create technology that the human factor will adopt. It’s difficult to solve a chicken and egg relationship when you don’t know what’s going to drive the other.

What about the past 30 years at Citrix gives you an edge in finding the right formula?

David Henshall: Citrix has always had an amazing ability to stay focused on connecting people and information -- and doing it in a way that it’s secure, managed, and available so that we can abstract away a lot of the complexity that’s inherent with technology.

Because, at the end of the day, all we are really focused on is driving those outcomes and allowing people to be as productive, successful, and engaged as humanly possible by giving them the tools to -- as we frame it up -- work in a way that’s most effective for them. That’s really about creating the future of work and allowing people to be unleashed so that they can do their best working.

Gardner: Roger, when you started, so much of the IT world was focused on platforms and applications and how one drives the other. You seem to have elevated yourself above that and focused on services, on delivery of productivity – because, after all, they are supposed to be productivity applications. How were you able to see above and beyond the 1980s platform-application relationship?

Roberts

Roger Roberts: We grew up when the personal computer (PC) and local area networks (LANs) like when Novell NetWare came on the scene. Everybody wanted to use their own PC, driven primarily by things such as the Lotus applications.

So [applications like] spreadsheets, WordPerfect, dBase were the tremendous bulk of the market demand at that time. However, with the background that I shared with [Citrix Co-Founder] Ed Iacobucci, we had been in the real world working from mainframes through minicomputers and then to the PCs, and so we knew there were applications out there, where the existing model – well, it really sucked.

The trick then was to take advantage of the increasing processing power we knew the PC was going to deliver and put it in a robust environment that would have stability so we could target specific customers with specific applications. Those customers were always intrigued with our story.

Our story was not formed to meet the mass market. Things like running ads or trying to search for leads would have been a waste of time and money. It made no sense in those days because the vast majority of the world had no idea of what we were talking about.

Gardner: What turned out to be the killer application for Citrix’s rise? What were the use cases you knew would pay off even before the PC went mainstream?

The personnel touch 

Roberts: The easiest one to relate to is personnel systems. Brown and Root Construction out of Houston, Texas was a worldwide operation. Most of their offices were on construction sites and in temporary buildings. They had a great deal of difficulty managing their personnel files, including salaries, when someone was promoted, reviewed, or there was a new hire.

The only way you could do it in the client-server LAN world was to replicate the database. And let me tell you, nobody wants to replicate their human resources (HR) database across 9,000 or 10,000 sites.

The only way you could do it in the client-server-LAN world was to replicate the database. And let me tell you, nobody wants to replicate their HR database across 10,000 sites. We came in and said, "We can solve that problem for you."

So we came in and said, “We can solve that problem for you, and you can keep all of your data secure at your corporate headquarters. It will always be synchronized because there is only one copy. And we can give you the same capabilities that the LAN-based PC user experiences even over fairly slow telecommunication circuits.”

That really resonated with the people who had those HR problems. I won’t say it was an easy sell. When you are a small company, you are vulnerable. They ask, “How can we trust you to put in a major application using your technology when you don’t have a lot of business?” It was never the technology or the ability to get the job done that they questioned. It was more like having the staying power. That turned out to be the biggest obstacle.

Gardner: David, does it sound a little bit familiar? Today, 30 years later, we’re still dealing with distance, the capability of the network, deciding where the data should reside, how to manage privacy, and secure regulatory compliance. When you listen to Citrix’s use cases and requirements from 30 years ago, does it ring a bell?

Organize, guide, and predict work 

Henshall

Henshall: It absolutely resonates because a lot of what we’re doing is still dealing with the inherent complexity of enterprise IT. Some of our largest customers today are dealing with thousands and thousands of underlying applications. Those can be everything from mainframe applications that Roger talked about through the different eras of client-server -- the PC, web, and mobile. A lot of those applications are still in use today because they are adding value to the business, and they are really hard to pull out of the infrastructure.

We can now help them abstract away a lot of that complexity put in over the last 30 years. We start by helping organize IT, allowing them to manage all that complexity of the application tier, and present that out in a way that is easier to consume, easier to manage, and easier to secure.

Several years ago, we began bringing together all of these application types in a way that I would describe as helping to move from organizing IT to organizing work. That means bringing not only the apps but access to all the content and files -- whether those reside in on-premises data repositories or in any cloud -- including Citrix Cloud. We make that all accessible across universal endpoints management. Then you layer underneath that all kinds of platform capabilities such as security, access control, management, and analytics.

Where we’re taking the company in the future is one step beyond organizing work to helping to guide and predict work. That will drive more engagement and productivity by leveraging machine learning (ML), artificial intelligence (AI), and a lot of other capabilities to present work to people in real time and suggest and advise on what they need to be to be most productive.

That’s all just a natural evolution from back when the same fundamental concept was to connect people with the information they need to be productive in real time.

Gardner: One of the ways to improve on these tough problems, Mark, is being in the right place in an ecosystem. Citrix has continuously positioned itself between the data, the systems of record, and the end-user devices. You made a big bet on virtualization as a means to do that.

How do we understand the relationship between the technology and productivity? Is being in the right place and at the right time the secret sauce?

Customers first, innovation always

Templeton: Generically, right place and time is key in just about every aspect of life, but especially the timing of invention and innovation, how it’s introduced, and how to get it adopted.

Citrix adopted a philosophy from an ecosystem perspective from pretty early on. We thought of it as a Switzerland-type of mindset, where we’re willing to work with everyone in the ecosystem -- devices, networks, applications, etc. – to interoperate, even as they evolved. So we were basically device-, network-, and application-independent around the kind of the value proposition that David and Roger talked about.

We made a great reputation for ourselves by being able to provide a demilitarized zone so that customers could manage and control their own destiny. When a customer is better off, we are better off. But it starts with making the customer better off.

That type of a cooperative mindset is always in style because it is customer-centered. It’s based upon value-drivers for customers, and my experience is that when there are religious wars in the industry -- the biggest losers are customers. They pay for the fight, the incompatibilities, and obsolescence.

We made a great reputation for ourselves then by being able to provide a demilitarized zone (DMZ), or platform for détente, so that customers could manage and control their own destiny. The company has that culture and mindset and it’s always been that way. When a customer is better off, we are better off. But it starts with making the customer better off.

Gardner: Roger, we have often seen companies that had a great leap in innovation but then plateaued and got stuck in the innovator’s dilemma, as it’s been called. That hasn’t been the case with Citrix. You have been able to reinvent yourselves pretty frequently. How do you do that as a culture? How do you get people to stay innovative even when you have a very successful set of products? How do you not rest on your laurels?

Templeton: I think for the most part, people don’t change until they have to, and to actively disrupt yourself is a very unnatural act. Being aware of an innovator’s dilemma is the first step in being able to act on it. And we did have an innovator’s dilemma here on multiple occasions.

That we saw the cliff allowed us to make a turn – mostly ahead of necessity. We made a decision, we made a bet, and we made the innovator’s dilemma actually work for us. We used it as a catalyst for driving change. When you have a lot of smart engineers, if you help them see that innovator’s dilemma, they will fix it, they will innovate.

Gardner: The pace of business sure has ramped up in the last 30 years. You can go through that cycle in 9 or 10 months, never mind 9 or 10 years. David, is that something that keeps you up at night? How do you continue to be one step ahead of where the industry is going?

Embrace, empower change 

Henshall: The sine waves of business cycles are getting much more compressed and with much higher volatility. Today we simply have devices that are absolutely transient. The ways to consume technology and information are coming and going at a pace that is extraordinary. The same thing is true for applications and infrastructure, which not that many years ago involved a major project to install and manage.

Today, it’s a collection of mesh services in so many different areas. By their very nature they become transient. Instead of trying to fight these forces, we look for ways to embrace them and make them part of what we do.

When we talk about the Citrix Workspace platform, it is absolutely device- and infrastructure-independent because we recognize our customers have different choices. It’s very much like the Switzerland approach that Mark talked about. The fact that those choices change over time -- and being able to support that change -- is critical for our own staying power and stickiness. It also gives customers the level of comfort that we are going to be with them wherever they are in their journey.

But it’s the sheer laws of physics that have taken these disruptions to a place where, not that many years ago, it was about how fast physical goods could transfer across state or national boundaries. Today’s market moves on a Tweet or a notification or a new service -- something that was just not even possible a few years ago.

Roberts: At the time I retired from Citrix, we were roughly at $500 million [in annual revenue] and growing tremendously. I mean we grew a factor of 10 in four years, and that still amazes me.

Our piece of the market at that time was 100 percent Microsoft Windows-centric. At the same time, you could look at that and tell we could be a multibillion-dollar company just in that space. But then came the Internet, with web apps, web app servers, new technology, HTML, and Java and you knew the world we were in had a very lucrative and long run, but if we didn’t do something, inevitably it was going to die. I think it would have been a slow death, but it would have been death.

Gardner: The relationship with Microsoft that you brought up. It’s not out of the question to say that you were helping them avoid the innovator’s dilemma. In instances that I can recall, you were able to push Microsoft off of its safety block. You were an accelerant to Microsoft’s next future. Is that fair, Mark?

Templeton: Well, I don’t think we were an accelerant to Microsoft per se. We were helping Microsoft extend the reach of Windows into places and use cases that they weren’t providing a solution for. But the Windows brand has always been powerful, and it helped us certainly with our [1995] initial public offering (IPO). In fact, the tagline on our IPO was that “Citrix extends the reach of Microsoft Windows,” in many ways, in terms of devices, different types of connectivity, over the Internet, over dial-up and on wireless networks.

Our value to Microsoft was always around being a value-added kind of partner, even though we had a little bit of a rough spot with them. I think most people didn’t really understand it, but I think Microsoft did, and we worked out a great deal that’s been fantastic for both companies for many, many years.

Gardner: David, as we look to the future and think about the role of AI and ML, having the right data is such an important part of that. How has Citrix found itself in the catbird seat when it comes to having access to broad data? How did your predecessors help out with that?

Data drives, digests, and directs the future 

Henshall: Well, if I think about data and analytics right now, over the last couple of years we’ve spent an extraordinary amount of time building out what I call an analytics platform that sits underneath the Citrix Workspace platform.

We have enough places that we can instrument to capture information from everything, from looking backward across the network, into the application, the user, the location, the files, and all of those various attributes. We collect a rich dataset of many, many different things.

Taking it to a platform approach allows us to step back and begin introducing modules, if you will, that use this information not just in a reporting way, but in a way to actually drive enforcement across the platform. Those great data collection points are also places where we can enforce a policy.

Over the last couple of years we have spent an extraordinary amount of time building out what I call an analytics platform that sits underneath the Citrix Workspace platform.We collect a rich dataset of many, many different things.

Gardner: The metadata has become more important in many cases than the foundational database data. The metadata about what’s going on with the network, the relationship between the user and their devices, what’s going on between all the systems, and how the IT infrastructure beneath them is performing.

Did you have a clue, Mark, that the metadata about what’s going on across an IT environment would become so powerful one day?

Templeton: Absolutely. While I was at Citrix, we didn’t have the technical platform yet to handle big data the way you can handle it now. I am really thrilled to hear that under David’s leadership the company is diving into that because it’s behavioral data around how people are consuming systems -- which systems, how they’re working, how available are they, and whether they’re performing. And there are many things that data can express around security, which is a great opportunity for Citrix.

Back in my time, in one of the imagination presentations, we would show IT customers how they eventually would have the equivalent of quarterly brokerage reports. You could see all the classes of investments -- how much is invested in this type of app, that type of app, the data, where it’s residing, its performance and availability over time. Then you could make important decisions – even simple ones like when do we turn this application off. At that time, there was very little data to help IT make such hard decisions.

So that was always in the idea, but I’m really thrilled to see the company doing it now.

Gardner: So David, now that you have all of that metadata, and the big data systems to analyze it in real-time, what does that get for you?

Serving what you need, before you need it 

Henshall: The applications are pretty broad, actually. If you think about our data platform right now, we’re able to do lots of closed-loop analytics across security, operations, and performance -- and really drive all three of those different factors to improve overall performance. You can customize that in an infinite number of ways so customers can manage it in the way that’s right for their business.

But what’s really interesting now is, as you start developing a pattern of behaviors in the way people are going about work, we can predict and guide work in ways that were unavailable not that long ago. We can serve up the information before you need it based on the graph of other things that you’re doing at work.

A great example is mobile applications for airlines today. The smart ones are tied into the other things that you are doing. So an hour before your flight, it already gives you a notification that it’s time to leave for the airport. When you get to your car, you have your map of the fastest route to the airport already plotted out. As you check in, using biometrics or some other form of authentication, it simplifies these workflows in a very intuitive way.

We have amazing amounts of information that will take that example and allow us to drive it throughout a business context.

Gardner: Roger, in 30 years, we have gone from delivering a handful of applications to people in a way that’s acceptable -- given the constraints of the environment and the infrastructure -- to a point where the infrastructure data doesn’t have any constraints. We are able to refine work and tell people how they should be more productive.

Is that something you could have imagined back then?

Roberts: Quite frankly, as good as I am, no. It’s beyond my comprehension.

I have an example. I was recently in Texas, and we had an airplane that broke down. We had to get back, and using only my smartphone, I was able to charter a flight, sign a contract with DocuSign, pay for it with an automated clearing house (ACH) transfer, and track that flight on FlightAware to the nearest 15 seconds. I could determine how much time it would take us to get home, and then arrange an Uber ride. Imagine that? It still amazes me; it truly amazes me.

Gardner: You guys would know this better than I do, but it seems that you can run a multinational corporation on a device that fits in your palm. Is that an exaggeration?

Device in hand still needs hands-on help 

Templeton: In many ways, it still is an exaggeration. You can accomplish a lot with the smart device in your hand, and to the degree that leadership is largely around communications and the device in your hand gives you information and the ability to communicate, you can do a lot. But it’s not a substitute entirely for other types of tasks and work that it takes to run a big business, including the human relationships.

Gardner: David, maybe when the Citrix vision for 2030 comes out, you will be able to -- through cloud, AI, and that device -- do almost anything?

Henshall: It will be more about having the right information on demand when you need it, and that’s a trend that we’ve seen for quite some time.

The amount of information is absolutely staggering. But turning that into something that is actually useful is nearly impossible. The businesses that are going to be successful are those that can put the right information at people's fingertips at the right time to interact with different business opportunities.

If you look at the broader trends and technology, I mean, we are entering the yottabyte era now, which is one with 24 zeros after it. The amount of information is absolutely staggering. But turning that into something that is actually useful is nearly impossible.

That’s where AI and ML -- and a lot of these other advancements -- will allow you to parse through that all and give people the freedom of information that probably just never existed before. So the days of proprietary knowledge, of proprietary data, are quickly coming to an end. The businesses that are going to be successful are those that can put the right information at people’s fingertips at the right time to interact with different business opportunities.

That’s what the technology allows you to do. Advancements in network and compute are making that a very near-term reality. I think we are just on that continuum.

Goodbye digital, hello contextual era 

Templeton: You don’t realize an era is over until you’re in a new one. For example, I think the digital era is now done. It ended when people woke up every day and started to recognize that they have too many devices, too many apps that do similar things, too many social things to manage, and blah, blah, blah. How do you keep track of all that stuff in a way where you know what to look at and when?

The technologies underlying AI and ML are defining a new era that I call the “contextual era.” A contextual era works exactly how David just described it. It senses and predicts. It makes the right information available in true context. Just like Roger was saying, it brings all those the things he needs together for him, situationally. And, obviously, it could even be easier than the experience that he described.

We are in the contextual era now because the amount of data, the number of apps, and the plethora of devices that we all have access to is beyond human comprehension.

Gardner: David, how do you characterize this next era? Imagine us having a conversation in 30 years with Citrix, talking about how it was able to keep up with the times.

Henshall: Mark put it absolutely the way I would, in terms of being able to be contextual in such a way that it brings purpose through the chaos, or the volume of data, or the information that exists out there. What we are really trying to do in many dimensions is think about our technology platform as a way that creates space. Space for people to be successful, space for them to really do their best work. And you do that by removing a lot of the clutter.

You remove a lot of the extraneous things that bog people down. When we talk about it with our customers, the statistics behind-the-scenes are amazing. We are interrupted every two minutes in this world right now; a Tweet, a text, an email, a notification. And science shows that humans are not very good at multitasking. Our brains just haven’t evolved that way.

Gardner: It goes back to that lump of clay we talked about at the beginning. Some things don’t change.

Henshall: When you are interrupted, it takes you 20 minutes on average to get back to the task at hand. That’s one of the fundamental reasons why the statistics around engagement around the world are horrible.

For the average company, 85 percent of their employee base is disengaged -- 85 percent! Gallup even put a number on that -- they say it’s a $7 trillion annual problem. It’s enormous. We believe that part of that is a technology problem. We have created technologies that are no longer enhancing people’s ability to be productive and to be engaged.

If we can simplify those interactions, allow workers to engage in a way that’s more intuitive, more focused on the task at hand versus the possibility of interruption, it just helps the entire ecosystem move forward. That’s the way I think about it.

CEO staying-power strategies 

Gardner: On the subject of keeping time on your side, it’s not very often I get together with 30 years’ worth of CEOs to talk about things. For those in our audience who are leaders of companies, small or large, what advice can you give them on how to keep their companies thriving for 30 years?

Roberts: Whenever you are running a company -- you are running the company. It puts a lot of pressure on you to think about the future, when technology is going to change, and how you get ahead of the power curve before it’s too late.

There is a hell of an operational component. How do you keep the wheel turning and the current moving? How do you keep it functioning, how do you grow staff, and how do you put in systems and infrastructure?

The challenge of managing as the company grows is enormously more complicated. There is the complexity of the technology, the people, the market, and what’s going on in the ecosystem. But never lose sight of the execution component, because it can kill you quicker than losing sight of the strategy.

The challenge of managing as the company grows is enormously more complicated. But never lose sight of the execution component, because it can kill you quicker than losing sight of the strategy.

One thing I tried to do was instill a process in the company where seemingly hard questions were easy, because it was part of the fabric of how people measured and kept up with their jobs, what they were doing, and what they were forecasting. Things as simple as, “Jennifer, how many support calls are we going to get in the second quarter next year or the fourth quarter of the following year?” It’s how do you think about what you need, to be able to answer questions like those.

“How much are we going to sell?” Remember, we were selling packaged product, through a two-step distribution channel. There was no backlog. Backlog was a foreign concept, so every 30 days we had to get up and do it all over again.

It takes a lot of thought, depending on how big you want to be. If you are a CEO, the most important thing to figure out is how big you want to be. If you want to be a lifestyle, small company, then hats off; I admire you. There is nothing wrong with that.

If you want to be a big company, you need to be putting in process, systems, infrastructure, strategy, and marketing now -- even though you might not think you need it. And then the other side of that is, if you go overboard in that direction, process will kill you. Where everybody is so ingrained in the process, nobody is questioning, nobody is thinking, they are just going through the process, that is as deadly as not having one.

So process is necessary, process is not sufficient. Process will help you, and it will also kill you.

Gardner: Mark, same question, advice to keep a company 30 years’ young?

Templeton: Going after Roger is the toughest thing in the world. I’ll share where I focused at Citrix. Number one is making sure you have an opinion about the future, that you believe strongly enough to bet your career and business on it. And number two, to make sure that you are doing the things that make your business model, your products, and your services more relevant over time. That allows you to execute some of the great advice that Roger just gave, so the wind’s at your back, so you are using the normal forces of change and evolution in the world to work for you, because it’s already too hard and you need all the help you can get.

A simple example is the whole idea of consumerization of IT. Pretty early on, we had an opinion about that, so, at Citrix, we created a bring-your-own-device (BYOD) policy and an experimental program. I think we were among the first and we certainly evangelized it. We developed a lot of technology to help support it, to make it work and make it better. That BYOD idea became more and more relevant over time as the workforce got younger and younger and began bringing their own devices to the office, and Citrix had a solution.

So that’s an example. We had that opinion and we made a bet on it. And it put some wind at our back.

Gardner: David, you are going to be able to get tools that these guys couldn’t get. You are going to have AI and ML on your side. You are going to be able to get rid of some of those distractions. You are going to take advantage of the intelligence embedded in the network -- but you are still going to also have to get the best of what the human form factor, that lump of clay, that wetware, can do.

So what’s the CEO of the future going to do in terms of getting the right balance between what companies like Citrix are providing them as tools -- but not losing track of what’s the best thing that a human brain can do?

IT’s not to do and die, but to reason why

Henshall: It’s an interesting question. In a lot of ways, technology and the pace of evolution right now are breaking down the historical hierarchy that has existed in a lot of organizations. It has created the concept of a liquid enterprise, similar what we’ve talked about with those who can respond and react in different ways.

But what that doesn’t ever replace is what Roger and Mark were talking about -- the need to have a future-back methodology, one that I subscribe to a lot, where we help people understand where we’re going, but more importantly, why.

And then you operationalize that in a way that people have context, so everybody understands clarity in terms of roles and responsibilities, operational outcomes, milestones, metrics, and how we are going to measure that along the way. Then that becomes a continuous process.

There is no such thing as, “Set it and forget it.” Without a perspective and a point of view, everything else doesn’t have enough purpose. And so you have to marry those going forward. Make sure you’re empowering your teams with culture and clarity -- and then turn them loose and let them go.

Gardner: Productivity in itself isn’t necessarily a high enough motivator.

Henshall: No, productivity by itself is just a metric, and it’s going to be measured in 100 different ways. Productivity should be based on understanding clarity in terms of what the outcomes need to be and empowering that, so people can do their best work in a very individual and unique way.

The days of measuring tasks are mostly in the past. Measuring outcomes, which can be somewhat loosely defined, are really where we are going. And so, how do we enable that? That’s how I think about it.

Gardner: I’m afraid we will have to leave it there. You have been listening to a sponsored BriefingsDirect discussion on how Citrix has made a highly successful habit of challenging the status quo. And we’ve learned from chief executives over the years how Citrix made major and correct bets on the future direction of global information technology.

And they are at it again by remaking digital workplaces and redefining the very nature of applications and business intelligence. So, a big thank you to our special guests, Roger Roberts, Mark Templeton, and David Henshall. And thanks to our audience as well for joining this BriefingsDirect 30 years of CEOs innovation discussion.

I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host throughout this series of Citrix-sponsored BriefingsDirect discussions. Thanks again for listening, please pass this along to your business associates, and do come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Citrix.

Transcript of a discussion on how Citrix is building on its 30-year record of success by remaking digital workplaces and redefining the very nature of applications and business intelligence. Copyright Interarbor Solutions, LLC, 2005-2019. All rights reserved.

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