Thursday, December 12, 2019

How Work Experience for Many is a Dumpster Fire and Why it’s Time for Something Completely Different

Transcript of a discussion on the future of work and the new ways of exploiting what technology does best to deliver intelligent workspaces that prioritize and personalize tasks.

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.

Worker productivity gains -- despite 30 years of computing technology roll outs -- remain hard to define by economists. Ask a worker, however, and you are increasingly likely to get a hard, cold assessment.

A huge amount of time these days, they say, is wasted on the inefficiencies of technology run amok. Only a sliver of time is going to the creative and innovative types of work that employees crave -- and employers gain the most value from.

Stay with us now as we explore the future of work and the new ways of exploiting what technology does best to deliver intelligent workspaces that prioritize and personalize tasks.

To learn how the newest digital work strategies help unburden those saddled with deflating productivity, please join me in welcoming Fouad ElNaggar, Vice President of Future of Work Products at Citrix. Welcome, Fouad.

ElNaggar: Hey, Dana. Thanks for having me.

Gardner: Fouad, why, when we walk through the front door of our office buildings are we being teleported back 20 years?

ElNaggar: Well, it’s kind of crazy when you think about it. Every one of us has this nice black rectangle that sits in our pocket, and when you think about what that rectangle enables us to do, it’s crazy.

In the world we live in today, I can push a button and a car shows up and takes me wherever I want to go. I can swipe right and I am on a date. I am old. I remember when you had to go up and talk to people at a bar or restaurant or at a concert and do this big dance to get them to go out with you for a meal. Now I am swiping right.

Life is great; work is a grind

When I started working, I used to memorize five different routes to work. I would get together with my friends and we would share secret shortcuts on how to save two or three minutes off of our commute. Now I hit a button on Waze, type in my address, and I am getting to work and back home in the fastest way possible.

I can push a button on my phone and a pint of ice cream comes to my house so I can eat away the disappointment of another Philadelphia Eagles loss. This is magical. The world that we are living in today is magical.

If I had to explain this to a young Fouad in the mid-1990s and say, “Imagine this. Imagine this world.” … When I started working, I remember showing up to my office the first day and laughing at people still using typewriters, okay?

The world we live in today is so insane and amazing. But then you walk into the front door of your office, guess what? That Fouad from the mid-1990s, starting out in New York, would 100 percent recognize that office: Bad guest Wi-Fi; signing in on a clipboard where people are writing Mickey Mouse and Donald Duck; plugging a laptop into one of those light bulb and fan projectors that’s got a VGA adapter on the end of it, and working on some horrible, crappy laptop that takes two minutes to open a big Excel file. It’s crazy. It’s crazy.

The Fouad from 20 years ago could not have imagined the consumer world we are living in today, but he was actually working in the same work world we are in today. It’s amazing, every one of as a consumer has these amazing experiences with our devices. But then you walk through the front door of work and it’s like taking a wormhole back to the 1990s. It’s insane.

Gardner: It’s like we took what used to be client-server business applications, put a web interface on them, and gave up. Not much has happened since then.

So what’s the solution? How do we move from this inertia of workplace innovation? Do we just keep adding on more old stuff, or do we reinvent?

ElNaggar: You bring up an incredible point. I live in Silicon Valley, so it’s probably the worst year -- where people are bringing out medieval bugles and blowing the horns to celebrate the wonderful world of software as a service (SaaS) software. And the crazy thing is, they think that because they took Siebel Systems and put it into a web browser and called it Salesforce, and they took PeopleSoft and put it into a web browser and called it Workday, that they are somehow dramatically changing how work happens.

When you actually look at those systems side by side, it’s the same tabs, menus, and workflows. Salesforce is celebrating their 20th anniversary this year, and literally nothing has changed. The way you use those systems is the same way you used those systems in the 1990s. Like you said, they just took client-server apps but put them on the web.

It’s sad when you think about it, because for the first 30 years of enterprise software -- the investments that went into digitizing the back office, of giving people personal computers, connecting those computers to the Internet so we had email and could communicate with people in our companies or around the world any time of the day -- those investments changed the way we worked.

Those investments drove huge changes in the employee experience, in employee engagement, and in employee productivity. You could do so much more. We were doubling individual productivity every 20 years. Think about that. It used to take two Fouads to do what one Fouad can do today.

And so we had all of this incredible investment and innovation -- and then all of a sudden we hit a roadblock. Look at the last 15 years of enterprise software, and what’s really changed? Again, it was taking a client-server system and putting it into a browser, and then taking some crappy, over-bloated implementation of those same systems to a mobile device that nobody wants to use. That’s not really innovation, right? That’s not changing how we work.

And so when I think about the future of work, I think we are going to have to attack that fundamental problem -- our processes and workflows haven’t really changed. That’s where you have to start.

Gardner: What’s changed for me is instead of spending just two hours a day on email, I am spending five hours a day on texts, chat, Slack, Teams, and email. But I don’t seem to be getting anything more for it. Am I unusual?

Interruptions disrupt productivity 

ElNaggar: That’s exactly right. Collaboration is a big part of work. When you think about the whole premise of a corporation, and about why corporations were even formed, the idea was that if we put specialists in different functions together as a group we could achieve more than we could as individuals.

Yes, collaboration is important, but also being able to deliver on your special skill is important. And as we keep layering on more “collaboration tools,” we have ended up in a world where there is just a ton of noise.

To your point, it’s … “Great, I have an email notification. Great, I have a Slack notification. Great, I have a Teams notification. Great, my salesperson just texted my phone.”

There was some research that came out earlier this year. We are interrupted 1,100 times a day at work -- 1,100 times. Think about that for a second, it’s insane. How can we even get any work done? To your point, you used to do email for two hours a day. Now, the typical person does about 17 hours of email a week, okay?

And then on top of that, we have all of these other systems and vectors for people to interrupt us, to try and communicate with us, try and collaborate, and a lot of times it’s just noise.

I don’t know if your email inbox looks like mine, but mine is like a dumpster. It’s an unprotected place where people can sit there and buy my email address off of Rainking and Discover , right? Or they can just guess it and try one of those ways to get to me.

And so what does my inbox end up looking like? Well, I have random vendors and people that have my email and are spamming it. I have Groupon in there. I have Nigerian prince scams. My wife maybe auto-fills an email and it goes to my work email instead of my personal email. And in the sea of all that noise and distraction I am expected to get my work done?
I have talked with CIOs at some of the biggest companies in the world and they measure what happens in Slack and Teams -- and it's a bunch noise. It really hurts the employee experience, and it kills employee productivity.

And these chat clients? I have talked with CIOs at some of the biggest companies in the world and they measure what happens in Slack and Teams -- and it’s a bunch of noise. It’s like, “Hey, guys, there is a cake in the kitchen. Hey, guys, here is a funny new animated GIF, here is a meme.”

It’s a bunch of noise. And so we are adding a lot to the noise and distraction levels. What’s been lost in the mix? It really hurts the employee experience, employee engagement, and it really kills employee productivity.

Gardner: Sadly, my solution was to work on Saturdays so that I wouldn’t be interrupted.  I would wait and do all my creative work -- and actually get something done. It allowed me to concentrate on the same subject for more than 20 or 25 minutes. But that’s not good because now I’m working six days a week.

How else do we let workers be creative and exploit what their brains were designed to do? How do we get out of this interruptions rut?

Going through the motions

ElNaggar: It’s a great point. What I will add to it is that you are actually engaged in your work. You love what you do. You want to work on your skills to be successful, so you work on the weekends to get your stuff done.

But what I should frame this whole discussion with is two-thirds to 80 percent of employees are not engaged with their work. They are not emotionally aligned with the mission or goals of the company. Whereas you will sit there and say, “Okay, I have to get my job done. I want to be great at this. I want to be exceptional at this. I am going to sit there and work afterhours and on the weekend to get things done.” A lot of people don’t. They are punching the clock. They are not engaged with work. They are disengaged with work. And that’s a huge problem.

Part of the reason they get disengaged with work, where they hate how they work, is because a lot of these systems we have put in place create friction for them. They increasingly create busy work and the kind of work that they did not sign up to do.

We talked earlier about people being specialists in corporations. Each one of us has a special unique skill, what we put on our résumés, and we put in our LinkedIn profiles.

If you go and look at my LinkedIn, you can check it out, what you are not going to see are any merit badges on there because I often use Concur. You are not going to see any credentials that say, “Fouad is really good at finding information on Tableau.” You are not going to see anything in there that says I am “unbelievable at using the procurement system to make things happen.” None of those things are my core skills. None of those things differentiate me in the marketplace.

But that’s how are people spending their time today. They are spending more than half of their time on what they consider busy work. There is BS stuff like expense reports, performance reports, and finding information across different systems and from meetings that don’t matter to them.
They are doing a bunch of copy-and-paste work. I saw some data about two months ago that says at work on average we copy and paste 134 times a day. I saw this and I said, “That can’t be true, that can’t be true.” And so I started to actually track myself and you know what I discovered? I copy and paste like 180 times a day at work. And that was frightening to me. But you realize these things and it’s like, “Oh my God, how many times am I in one system and I copy a piece of data and put it into an email or I copy something out of an email and put it into a form field on another system?”

All day long we are sitting shuffling information between different systems – even though each of us has a unique, special skill. You know what human beings want to do when they work? They want to develop that skill, to hone their craft, and to get better at what differentiates them, because that’s what’s going to allow them to create more value for their organization. And it also set them up for a promotion, a new job, and to make more money. And these are the things that excite people at work.

Employees prize purpose, potential, and play

There is a lot of research out there around total motivation and what really drives engagement. What they have found is that people want to have a feeling of play at work. They want to feel like they are using their adaptive brains to be creative and solve problems. They want to have a sense of purpose. They want to know why they are at their companies and why are they doing their jobs.

There was some research that came out recently that said more than 70 percent of people don’t know why their jobs even exist. Think about how frightening that is. Like why does my job even exist?

So again, they want some kind of purpose. They want to know the work that they do contributes to their organizations and how.
More than 70 percent of people don't know why their jobs even exist. Think about how frightening that is. Like, why does my job even exist?

And the other thing they want is potential. They want to know that there is a pathway for them to develop their skills. People want to spend their time working on their skills sets and on individual projects in unstructured time.

If that’s a developer, they want to work and have a nice big block of time to code. If you are a writer, you want a big block of time to focus on research and crafting beautiful documents. If it’s a salesperson, they want to spend their time in front of customers evangelizing their vision of the product and evangelizing how they can help the customers achieve their goals.

Every one of us has our skills that we want to work on. Working with a team to achieve something greater -- that’s where people want to spend their time, because that’s where they get a sense of purpose for their work. They get a sense of play in their work because they are being creative and solving problems. They are setting themselves up for reaching their potential, and so to move up the wage pyramid, get a promotion, and get that next job.

Gardner: Well, the good news is those types of creative functions are exactly what artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) can’t do. So it’s good that people want to do that. The problem is there is no one app that allows me to do that. I still have 45 apps that I have to cut and paste from. So how do we bridge this, of going from umpteen apps to having more of what’s a creative and appropriate environment for people to be creative in?

App overload 

ElNaggar: It’s a great question, and it’s the question that we had six-plus years ago when we started my company, Sapho, which Citrix acquired about a year ago. And we were looking at this landscape -- the number of applications -- when I was the chief strategy officer at CBS Interactive. And my co-founder, he was the chief technology and information officer there, and we were looking at our universe as a Fortune 100 company. We looked at the reality of our day-to-day jobs and we said, “Oh my God, we have all these incredible apps installed.”

I think Symantec just released a report saying that the typical enterprise is managing 928 applications. Some of the banks that we work with have 8,000 applications. So there is this incredible set of application programming interfaces (APIs). And by the way, the Symantec report says the number of apps has grown by 60 percent in just the last three years. We are not deprecating these old workloads, we are keeping them, and we are adding more cloud-based point solutions on top of it all.

So clearly work is becoming more complex. The typical person is using 42 apps to do their job, and it’s growing. It’s becoming more complex.

We looked at that. And, to your point, we said, “Well, okay, how do we stop the context switching? How do we stop the copy and paste, and how do we shift time away from busy work and toward value creation?” And what we came upon was this idea that -- because of the evolution of APIs, of ML, and of identity access -- there is an opportunity to build a system of engagement and intelligence that sits horizontally and plugs into all of those systems to create a single, harmonious experience for the end users.

And that was our big “aha” moment and that translated over to Citrix and the Workspace product. The idea is that for 30 years in the enterprise there has been the concept that the front end and the back end of the systems that you buy have to be stuck together.

So, for example, as an enterprise I go and I buy an SAP enterprise resource planning (ERP) system, and I get this incredible backend, it’s amazing. It solves all these problems, like two-phase commit. But guess what? You are stuck with that SAP front end, the best that German engineering can imagine, which of course is not necessarily like a modern user experience.

How to cut through the noise 

And so, for 30 years in the enterprise there was the view that if you have a system, you have to take the good and the bad. And what we came along and said is, “No, no, no. Keep the good, the backend, but let’s also take advantage of the API economy and what we are seeing with that level of integration. Let’s connect into these things, abstract them into their tasks, and then create a harmonious experience, a beautiful engagement layer that allows anybody to do their work from many systems from a single point.”

They can live in Messenger, in email, in the Workspace app -- but there is one chokepoint that delivers your work to you, that delivers you your information. It will help you make better decisions.

Step one, we shift the amount of time you are spending on busy work and non-value-creating work, which today, by the way, is 80 percent-plus of your time. We can we flip the script on that so that people are spending less than 20 percent of their time doing that stuff, and now spending 80 percent-plus of their time creating value, being creative, and using their adaptive minds to solve problems and create value for their organizations. That’s step one in the journey. That’s what we are doing with the Citrix Workspace now.

The next step is actually even cooler. It addresses how to supercharge the worker so they are even better on the value-creating stuff. But those are two steps in a journey that we are helping some very large customers through right now.

Gardner: I understand what you need to do. But why is Citrix the right organization to help do it?

Right time, right place for Citrix 

ElNaggar: It’s a great question, and I have spent a lot of time with customers. I think I have met about 250 customers in 2019, and they ask the same question, “Why Citrix?” They know Citrix and they go, “Oh, yeah, the gold standard in virtualization. That’s what you guys are known for.” And what I tell them is, if you think about it, Citrix has actually always been on the forefront of the future work because we have always sat between the end user and their systems of record.

As we talked about developing a system of engagement and intelligence -- of being that layer that sits between the end user and all very different systems -- guess what? Citrix has been doing that for 30 years. Whether you are talking about multiuser, MetaFrame, WinView, or any of these products that Citrix has rolled out for 30 years; whether it was remote desktop access or virtualization, Citrix has always been the engagement layer between the end user and those backend systems of record.

People know Citrix as the place to go to do their work. And now we are saying, “Guess what? The whole conduct of an application has changed. The whole concept of work has changed. And we are sitting in that beautiful position between the end user and their symptoms already, so why not bring the value that we are talking about to that layer?”

Can we be something more than just a thin client that sits between you so that you can access your desktop remotely? Can we be something more than the same client that sits between you and your virtual apps and virtual desktops?

Those things are still important. People are still going to need to access virtual apps and virtual desktops in a secure way. But, we are sitting there right now, ingrained with these systems already. We are trusted by 99 percent of the Fortune 500 already. Why not use this position to help shepherd businesses through their journey? And it’s always a journey. I laugh when I see people out there selling silver bullets or magical switches where they are going to solve the employee experience with the snap of a finger.

It is journey. We have that engagement layer already to help our customers through that journey of organizing work more effectively. Can we drive people through their work more effectively and automate their work more effectively? We can drive this needed shift and value-creation so that people aren’t spending 85 percent of their time doing busy work and garbage and can start spending 85 percent of the time creating value.

That’s Citrix, and hopefully it makes sense because there are a lot of people really interested in the Workspace. They look at this and say, “Oh, my God, this is the future.” Our employees have already been trained by consumer applications on what they can expect. They want a hub, a place that brings them stuff from all across the Internet to a single location so that they can consume it effectively.

They want AI to disappear into the background of the system and yet still make them better off. I talked earlier about Waze. I don’t think about Waze as consumer AI. I don’t want people to think about Workspace as enterprise AI. Waze just weaves into my natural experiences and makes them better and makes me better. It gives me minutes back in my life. I get somewhere faster.

That’s what we think about with Workspace, of weaving experiences right into the solution so it can empower people, help them focus on creating value, and help them do the work they really want to do.

Gardner: Okay, Fouad, give me the elevator pitch, in three minutes. Tell me what Citrix Workspace is, what it does, and why I should want it.

Workspace works for your work experience 

ElNaggar: Citrix Workspace is an experience-driven platform for work. We have done all of the work to make it easy for people to integrate into all of their different systems of record and unbundle those systems of records into micro flows and micro applications. We have done all the work building the intelligence at the user level so that people can build ML and AI to make work better. We have built the infrastructure to enable micro-automation from the ground up, not from the top down like RPA.

We have done all that so we can again organize, guide, and automate people to work. With the Workspace, when I can go there, it feeds me all of my different tasks and the insights and information I need to make choices. It allows me to work at the edge. I don’t have to log into 50 different apps to get my work done. My work comes to me. That’s the key. Bringing work to the individual, assisting them through their work, guiding them through their work, organizing their work, and reducing the amount of time that you have spent having to find stuff. Then you can spend your time doing stuff. That’s what we are about now. That’s the product that’s gone into general availability in November 2019.

And again, it’s a journey. It’s a journey for every customer because you have to really think about, “Hey, what’s our workflow and process today? How can we make it better? How can we unbundle it?”
That's what we are delivering, a chance for people to unbundle and rethink how work is done, to rethink how workflows are done, and to automate non-value-creating repetitive tasks and busy work to ultimately deliver intelligence augmentation to the end user.

That’s what we are delivering, a chance for people to unbundle and rethink how work is done, to rethink how workflows are done, and to automate non-value-creating repetitive tasks and busy work to ultimately deliver intelligence augmentation to the end user.

It’s a platform for work, a place where people can get their work done quickly so that they are not spending 20 percent of their time finding information or 50 percent of their time filling out testing procedure specification (TPS) reports. We want to minimize all that stuff so you can focus on your special skill, focus on your unique craft, and get better at your job so you can create value for both yourself and your employer.

Gardner: Thanks. If I want to customize my Workspace, but not to the point being an application developer, how do I address customization?

ElNaggar: It’s a great question. Being able to customize without being a developer or investing in a bunch of spaghetti code is something that we spend a lot of time thinking about. When we were at Sapho, and we [were] brought over to Citrix, we spent four-and-a-half years and spent $30 million building an incredible integration hub.

For a person who can at least use a business intelligence (BI) tool to develop a report, so maybe a business analyst, somebody who can build something in Tableau, for example, that level of person; we’ve made it really easy for that type of person. They can, number one, integrate into their systems -- whether that’s a software as a service (SaaS) system, an on-prem, off-the-shelf system, or a homegrown system. Incidentally, that’s where a lot of value is, in these wacky homegrown systems that have been around for 20 years but are still running critical workflows that you want to modernize or enable people to access on different devices and via different channels. We made it really easy to integrate those things, and to build in and inherit any business logic that you have to understand, “Hey, here’s the event that should drive a workflow.”

We made it really easy for people to unbundle the micro flow, build little micro apps, and get them into any of these different channels. We said, “Okay, every time we build an integration we want to make sure that we’ve got a bunch of build-out-of-the-box micro apps that are ready to go.”
These are things we see at lots of different customers. We say, “Here you go, customer. You now have a bunch of things that you can start using on day one. We already know they create value, that they hit use cases that a lot of people have.” But then on top of that we made it really simple with drag-and-drop tooling for people to go in and actually build a custom micro flow and micro app that they need on another system. Because a lot of times these are user-initiated workflows that people want to build easily. We have built the tooling -- and this is a new thing for Citrix -- but we’ve built this awesome tooling that makes it really easy for people to do that.

To build a better interface for engagement intelligence -- that sits horizontally across these systems -- you have to make sure you can get into all of those systems. And every organization is going to have their little skeletons in the closet. They are going to have Workday, or Concur, or Microsoft Power BI, right? Sure, they are also going to have Salesforce, and that’s great.

We make sure we have the stuff ready for them for those. But they are also going to have something gnarly, like BMC Remedy or PeopleSoft, or some homegrown system that’s still running on an AS400. And so you have to be able to empower those customers, too, to build better experiences on top of those things. That’s what we do with the tooling, the integration layer, and event tracking, along with the micro-flow builder and orchestration layers.

All of these things are designed to make it easy to not have to sit there and write code to deliver these things, but to drag and drop components into place and that makes it possible.

Gardner: You mentioned that the latest Citrix Workspace becomes generally available in November, but you also mentioned that there is another shoe to drop around intelligence augmentation. Where does this all go next when it comes to augmenting the worker?

Intelligent augmentation in three steps

ElNaggar: Intelligent augmentation is the guiding North Star for Citrix. We want to have intelligence-assisted workers. I’m sure you have seen the research out there about AI in chess, for example. It was really hard for grandmasters to be AI-driven in chess against things like IBM Watson until they started working in conjunction with AI. Now they can use an average Elo-score chess player to beat a Watson because they are working in parallel with AI -- and that’s the world that we are trying to build.

By abstracting workflows out of these monolithic systems and turning them into simple micro flows and micro apps at the individual level, we are also building datasets around what happens at work. Because we are tied into the systems of record -- it’s not like RPA where we are screen-scraping and guessing at stuff -- we are actually connected into the system. So we can say, “Okay, this event is happening 1,000 times, this action is being taken 1,000 times. Okay, great, let’s hotspot that and get rid of that repetitive task.” That’s step one.

Then step two is saying, “Okay, what are these stacked actions that we see? What are the things that we know every time your vacation is approved, for example? What are the next four things that will usually happen?”

Well, for most people, number one they go to their calendar and they mark the days that they are going to be on personal time off (PTO). Then when they go on PTO, they change their away message to say, “I am on PTO, if you have an emergency, text me at this number.” Maybe a week before PTO, they will email their team and say, “Hey, I’m gone for the next week, if you have anything critical, let me know, so I can do it now.”

Maybe they will go into their Outlook app and create like a VIP escalation rule for an email from a customer so that it also goes to their boss. Now, because we have broken things down to that micro flow, micro app level, we can automate all of that. Once your PTO gets approved, we will do those next four steps on your behalf.

Now we have taken that customary workflow away from you via automation. But there is a next phase of automation that we call system-learned. System-learned says, “Hey, every time Dana gets an expense report under $50, he approves it without even looking at the receipts.” Because, guess what? You are busy, Dana, you want to work on creating great content, you don’t care about the time that you are spending doing expense reports.

So now the system says, “Okay, 50 times out of 50, Dana approves an expense report under $40 without looking at it. Why do I need to send him 50 notifications about expense reports under $40? Let me approve them on his behalf, and here are just the two that look riskiest.”

Now the system has automatically approved 40 expense reports on your behalf, and you get only the two that are potentially risky. Guess what? I have taken 40 notifications and approvals out of your life and made work easier. That’s system-learned.

Now, there is going to be another step, a third tier. Those first two tiers are like using an autopilot. But the next level is what we call co-pilot. These things help you become a better pilot, a better driver. At this point, the augmentation capability notices something across these two systems that you should know about that might be able to help in your decisions.

The system determines, “Oh, I have seen another group that’s worked on a problem like this, and here was the output. Let me serve that up to you in context.” That’s that next level of ML and AI that we have weaved into the Workspace because we have integrated at such a deep, personal level, at the task level, at the atomic unit of work level, so that we can see all of these things going back and forth. We can then build some really cool algorithms across a truly unique dataset.

If you think about it, nobody in the world has the dataset that we have. It’s a horizontal, cross-system-of-record view of what’s happening in an organization yet tied to an individual. That’s really cool and gives a lot of flexibility to shoot for the moon on what’s possible with new types of work.

Gardner: We are just about out of time, but how should businesses and individual workers prepare themselves for the future of work that you just described?

From book value to people value

ElNaggar: Number one, as an organization, you need to be committed to delivering an incredible employee experience.

For 100 years companies have been valued based on book value. They took the value of all the property, plants, and equipment – from photo copiers to the company jet -- and said, “Okay, that’s the replacement cost of your organization. Let me multiply it by five or six, and that’s what your company is worth.”

If you look at the S&P 500 in 1975, 80 percent of the market cap was tied to such tangible book values. But the world now is more about intangible values. It’s about human equity. The people who work for you are worth a huge value within your organization.

In the S&P today, for example, 80 percent of the market cap is now not based on physical assets, but people and the intangible assets. It’s about the knowledge that’s in the brains of people that work for us.

If you are an organization thinking about the future, it’s time to correctly value the people. I often hear people saying, “Oh, people are most valuable assets.” But I still don’t see a lot of these organizations actually treating people as assets, treating them as their most valuable assets.

But some organizations are having a cultural switch, where they say, “Shoot, human equity is what matters. I need to figure out how I invest in human equity. I need to figure out not just how to attract the best talent, but how to power that talent to be the best version of themselves -- and then keep them so that they are not turning over after just 22 months like many Millennials do.”
It's more important than ever for people to understand what their skills are, their craft, and get themselves mentally prepared to be adaptive.

That’s what organizations need to do. For individuals, it’s more important than ever for people to understand what their skills are, their craft, and then get themselves mentally prepared to be adaptive. They have to do adaptive problem-solving because that’s a value they can best create. The busy work and the other stuff that eats up 80 percent of people’s time today is going to disappear or be diminished.

Where you are going to shine and demonstrate your value to an organization over time is focused on: Here is my skill, here is my craft, how do I hone it, how do I get better? That’s what the individual needs to be thinking about over the next few years as the future of work becomes more relevant.

Gardner: I’m afraid we’ll have to leave it there. You have been listening to a sponsored BriefingsDirect discussion on new ways of exploiting what technology does best to deliver intelligent workspaces that prioritize and personalize tasks.

And we’ve learned how the newest workspace advances are helping unburden those saddled with deflated worker productivity. So, a big thank you to our guest, Fouad ElNaggar, Vice President of Future of Work Products at Citrix.

Also, a big thank you to our audience for joining this BriefingsDirect intelligent workspaces 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 the future of work and the new ways of exploiting what technology does best to deliver intelligent workspaces that prioritize and personalize tasks. Copyright Interarbor Solutions, LLC, 2005-2019. All rights reserved.

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Thursday, December 05, 2019

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).

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: 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: 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: 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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