For continuous digital experience across expanding set of endpoints, traditional IT won’t work. It warrants a new architecture and supporting infrastructure for data, applications, systems, platforms, and security. How are leaders getting their IT ready to support the digital mesh?

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• • Chris Zissis, Chief Information Officer, EMEA – Head of Technology, Data and Information Management, JLL

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Transcript

Sanjog Aul [00:00:23]:

Hello, and welcome to this segment on CTN. To learn more, please visit ciotalknetwork.com. The topic for today is getting IT ready for the digital mesh, and I have Chris Zissis, who is the chief information officer for EMEA, head of technology, data and information management for Jones Lang LaSalle, JLL. Hey, Chris. How are you?

Chris Zissis [00:00:46]:

I’m well. Thanks, Sanjog Aul. How are you today?

Sanjog Aul [00:00:48]:

Very good. Very good. It’s a beautiful day in Chicago here, and where are you based right now?

Chris Zissis [00:00:55]:

I’m in London today, so it’s an overcast, rather windy afternoon for us in London, but the sun is not shining, but it is fairly bright. So happy it’s still daytime.

Sanjog Aul [00:01:10]:

Oh, that’s great. So the reason we got together here because, of course, we are looking in this, living in this digital era, and besides the new way of thinking of business, what’s also coming are, the variety of devices that we have to deal with and not just the regular mobile devices, but even IoT came into play, and then there are many other flavors, of sensors being introduced. So all of this coming together is being given this umbrella term called digital mesh, and while we are getting used to dealing with different devices, but that doesn’t mean that it takes away the complexity it may create in terms of the data, the variety of security issues, and many others. So we thought why not actually take a closer look. What does this do in terms of the value it creates for the business just because you have a device mesh? And then what challenges does it pose? How do we get IT ready so we harness the most value out of it? So let’s talk about maybe you can give your perspective on what’s the novelty and the cool things these devices attached to the device mesh are bringing, and then what is the dark side of the complexity?

Chris Zissis [00:02:29]:

Sure. Thank you for having me on the show. Let’s answer your question directly and do so by thinking about what digital mesh is in its simplest terms. So if you think about what is digital mesh, it’s basically a simple way of referring to how multiple connections between devices, people who wear these devices, applications, services such as IoT come together and generate content and data, to create digital outcomes, to create new digital views or perceptions of the world, and so what’s the novelty? The novelty is, with the huge amount of information and content available, we are starting to see things in a very different perspective. So one of the latest I saw was, one of the airlines I fly with, who was able to, over a period of 10 years, tracking my lounge access, tracking my bookings, tracking what I’ve ordered on the airplane in business class to eat, give me a dashboard and a summary of what I’ve been doing for the last couple of years, and, I mean, the headline message is I was advised by the dashboard that I have flown to the moon and back 4 times. Yeah. So that’s kind of a novel way of looking at the digital mesh, but if you want to think about the mesh in a way of creating business value and creating growth, which is ultimately what businesses are trying to do, then the digital mesh is about creating a foundation for a new and improved digital business, either by helping us improve through these devices and the data they generate or through the applications and the data they generate, improved customer engagement, helping us drive a better understanding of production and sales cycles, undertaking risk management through having a better insight into identity management, and then also, something close to my heart because JLL is all about real estate, is helping us kind of predict what the workplace of the future will look like and what smart cities we’d like to be living, working, and developing in. So the digital mesh is all about how do we bring data together and make informed decisions, but more importantly, create new business outcomes, and that’s the complexity of it because it’s not traditional IT. It’s a completely new value chain for businesses that aren’t digital and innovative and are learning to do so.

Sanjog Aul [00:05:29]:

So, of course, what you just mentioned, so anything which we try to do in terms of technology adoption, we try to make the lives of the people who we serve interesting, engaging, simplified, but should it always be at the cost of complicating and making it unnerving for the people who deal with it? Is there a way when we are saying we will introduce this digital mesh, it’s gonna be creating a lot of value for the customer. When we say the word that complexity will get introduced, is that the very at the onset and then we can work towards simplifying, or should we almost accept the fact that when we make things better for the customer, it’s gonna get worse for the people who manage it?

Chris Zissis [00:06:19]:

Oh, that’s an interesting question. I think, like all things technology, we go through a learning curve. Right? So if you think about digital mesh, 1 year or 2 years ago, it was all about how do we connect these devices? How do we connect wearables, traditional laptops and iPads and IoT together so that we can have a seamless view of the information that’s created. Fast forward two years from there, it’s all about the data and having an information architecture that ultimately is adaptable and scalable to create this new digital view of the world that we may not have in our heads or in the way we manage our businesses today. So I don’t think it’s as binary as it’s easier for the consumer and more and more difficult for the creator or the architect or the solution as I bring it together. I think it’s more about we will go through that learning curve, and IT teams and IT leadership and technology and data leaders will just have to simply become better at predicting disruption, being more agile in how this mesh creates an ongoing dynamic interaction with the world and then being able to respond to it, but to be able to respond to it with new skills and a cost to serve that’s much lower than it was 2 years before that and 2 years prior to that, etcetera. So it’s not about constantly living in complexity. It’s being able to solution for that complexity and being able to go up the learning curve so that things get better and we can do more things with the insights we get from the mesh, i.e., leveraging artificial intelligence, leveraging machine learning, being able to merge the physical and the digital information to create new realities such as augmented reality. All of that was really hard two years ago. It’s getting easier today.

Sanjog Aul [00:08:37]:

So would you say from a maturity standpoint, are we at a point where the architectures that we have created, whether to handle the connectivity and compatibility and integration with these different devices or the way you take the data out of it and make sense of it and create value from it, is that become like a mothership where you say, okay. Bring it on. So it’s not that we will stop creating the different new variety of devices, but are we at a point where we say, okay, life is good. You bring anything new, it’ll follow a certain standard and we will get the data from it, make sense of it, and life will keep getting better.

Chris Zissis [00:09:17]:

I think, if you think of the maturity curve, we are not past the precipice of the maturity curve, right? And the reason why I say that is traditionally, technology teams have thought about enterprise architecture. They’ve thought about, to use your term, bringing data and knowledge back to the mothership and then growing that understanding to serve very, very predictable actions, processes, interpretations of markets, interpretation of our customers in the geographies and in the markets we serve. What this interconnectedness has brought is a real challenge to the teams because it’s about data coming back to the mothership, and that is only the data you need to inform the business outcomes that help you grow the business in the traditional way, and it’s also about keeping data and understanding and insight at the edge of the mothership, which is very dynamic. There, to respond to your maturity question, I think we are still learning. What data do we keep? How scalable should the architectures be? Should the engineering be real time? How secure should it be? Are we going to take some risks because there’s low material risk on data leakage? And so it’s, again, not a binary thing. I think what we’re doing is we’re seeing lots of focus on information architecture and data architecture today than we did before. We’re seeing a lot of focus on the application architecture being agnostic of technologies and platforms and being more focused on securing the data and helping the applications learn and grow as they become more engaged with the mesh, and I think, at the same time, the skill debate on do we have the right skills to learn and build upon this kind of world that is in flux is probably the biggest challenge on the maturity basis because depending on the markets and depending on which leaders you talk to, the skills required today are buyers of good technology, people who understand data and have insights into data, but people who can leverage automation, artificial intelligence, machine learning at an application level, at a data level and at a business engagement level. So that, I think, is where the maturity is still lacking and where we have a lot more focus that’s needed.

Sanjog Aul [00:12:24]:

Let’s take a quick break, listeners. We’ll be right back, and let’s look at or maybe rather split this whole ecosystem, which is being created through digital mesh as Upstream where is, like, you’ve got different devices, what you have today and what will come in future. Are we still in the land grab stage or, market grab stage where we are saying our device will follow our standards, and it may not work with your other devices you may have in the mesh that you’re dealing with, or even we are talking about the way the data is being made available. Is that going to come in one standard format? Are we in it together? So if digital mesh is going to be multiple devices for multiple people, for multiple value chain partners in our ecosystem, is everyone on the same page in terms of standards, in terms of how data will be exchanged, how you will authenticate a device, how will you basically make sense of it? If we don’t do it, we are leaving so much more opportunity on the table. Where are we with it? So let’s talk that upstream part, and then we can go to, okay, life is good in the upstream. What are we gonna do to create business value, and where are we with it? So please stay tuned listeners. We’ll be right back.

Speaker 0 [00:13:49]:

Predict your company’s future by creating it. Is your workforce able to connect, exchange ideas, and share brilliance simply and securely? Create tomorrow, today. Empower your people to innovate anytime and anywhere with secured BlackBerry Enterprise Mobility Management and document sharing solutions. To learn more, visit blackberry.com/enterprise.

Speaker 0 [00:14:17]:

Patient centered care requires a connected enterprise. Are you ready? If you’re looking to scale your health care IT efforts, visit redmane.com/health today. Whether it’s to connect data from multiple partner solutions or developing software for unique needs, RedMane can help. To find out how RedMane can help your company deliver on the patient centered care promise, visit redmane.com/health or call (773) 693-3919. Visit today.

Speaker 0 [00:14:50]:

Your growing business needs a highly productive workforce, effectively communicating and collaborating without exposing corporate data to cyber attacks. Are you looking to balance security and workforce productivity? Move beyond short term measures and securely scale your business with BlackBerry Enterprise Mobility Management Solutions. To learn more, please visit blackberry.com/enterprise. You are listening to CTN CIO Talk Network with Sanjog Aul. To learn more about our program, please visit ciotalknetwork.com. Now back to the show.

Sanjog Aul [00:15:39]:

Welcome back. So, Chris, let’s look at the upstream side where we are bringing these pieces together, and you mentioned, like, two years ago, we had that challenge how we will connect these devices. Agreed, but then new forms and flavors of devices are coming, new ways of taking data out of it or messing with it to come up with some values also evolving. Are we still in that competitive mindset or we are together, vendors, customers, partners, all coming together to make this as an opportunity for all involved?

Chris Zissis [00:16:13]:

Yeah. That’s really, really good question and the answer is yes and no. I would say if you think about IoT as a good example, if you think about IoT a few years back when it was still very much the flavor of the month, vendors would be talking about you have to use my device to be able to generate predictability, whether it’s asset failure rates, whether it is footfall and trying to predict the utilization, whether it’s trying to understand who’s walking past your retail store using mobile device triggers. That has changed. I think ultimately with cloud computing and a lot of these cloud providers truly being quite agnostic on how they ingest the data, we are seeing that a lot of the IoT solutions, workplace strategy solutions, again, close to home, are incredibly device agnostic. That doesn’t mean, though, that there are some big players out there that are obviously wanting to dominate the market as much as possible because there’s a novelty and a value to be had from there. So the most relevant consumer example I can give, if you are an Amazon Alexa disciple as my family and I are, it switches on our lights. It reads our calendars to us, and it’s quite a novel way of taking the tension out of a household when you’ve got multiple people doing multiple things because it’s quite predictable and helps you manage your day. Alexa does not allow for integration with Apple Music, which if you’ve made an investment many, many years ago in Apple Music and are a big follower of Apple, you can’t listen to your music on the one sort of digital sort of enabler that makes your life easier. So I think you have some of that, but if I could sort of reflect on the question, I don’t think it’s about data standards and device standards. It’s about open and leverageable open source endpoints, APIs, and an ability to mesh devices with other devices in an ecosystem, and I think there’s many partners out there that do this for a living. We build some of these ourselves. So in short, I think the whole notion of my device is better than yours will very, very, very quickly dissipate on the consumer side. Clearly, when you think about autonomous vehicles, when you think about key machinery that is used in mining or construction, there I think there will be a more closed nature as far as the devices are concerned because it poses security challenges. It poses certain risks, which you don’t want someone to instantly hack into your vehicle and then push your brakes while you’re driving 100 miles an hour. So I think it’s variable. It depends on the use case, but today, I don’t think the vendors are against working with one another, but the use case, be it surgery, be it vehicles, be it mining, be it flight management systems and how the mesh helps to predict failure rates, behaviors of pilots, etcetera, I think that’s going to be a bit closed and rightfully so. So more open on the consumer side, less open on the, let’s say, specialized side, but again, the ability to access data for business outcomes and particularly digital business outcomes is becoming more open.

Sanjog Aul [00:20:34]:

And when we talk about the architecture itself and any good architecture, it should be agnostic of a technology or a specific device, etcetera. So are we at a point where the newer device manufacturers, the old ones who were going for the land grab, have recognized that their existence would be dependent on making it that open system or open stack centric? Has that gone?

Chris Zissis [00:20:58]:

Yes, I think that’s really, really important point to highlight. Yes, if you look at some of the big software houses in the past, very much even the IBMs of this world very much started with a journey. The Microsofts of this world closed. You have to use us. We are able to enable you to scale today if you break architecture into three components: application and services architecture organizations that are living and breathing the digital mesh given the huge availability of data sources, through wearables, through sensors in buildings, through mobile devices, you have to focus on microservices. You have to focus on service orientated components that basically help you address the what if questions, help you address the new business opportunities you need to exploit given all this data you have. Where it becomes a little bit more complicated is if you then go beyond that into the information architecture and being able to blend information needs, all this data. What data do I need? How do I store it? What do I keep, and for how long? What do I delete? What do I send back to the mothership? What do I retain just to address a particular use case? With that, I think it becomes more complicated because in the past, it was only about storage and analytics. Now it’s about real time fulfillment through data, and there, the architectures are all about real time engineering, which gives you the velocity and throughput to be able to exploit the mesh, and so there, the big players, you’ll see they are moving more and more away from it’s closed, it’s mine, I have the IP to being able to exploit velocity, a real time access, ability to bring things back to the mothership but also keep them on the edge where the data is needed to drive customer engagement, to drive predictable, artificially intelligently driven analytics, and there, I think we’re seeing the shift. We’re seeing the shift from mine to how do I beat the engineering race, and then finally, I think the biggest opportunity yet challenge is with so much computing power in the hardware today and with the access to rather cheap cloud services is how do you secure all of this? And I’ll give you an example. I recently was speaking to a colleague of mine who was saying, in the past, when you were thinking about cybersecurity or information security, you had to create a firewall. You needed to prevent people from coming in, and if they did, you had some remediation steps by that you take to clean yourself of any risks. With a huge focus on hacking, I think what we need to understand is the mesh creates some vulnerabilities. So the example I’ll give is, this colleague of mine was saying to me that someone was using their mass compute power and engineering capability to do some cryptocurrency mining on their cloud environment. Not there to destabilize the business, not there to try and propagate some form of a cyber attack purely to use their compute power, and it took them two weeks to realize that was the case because they were losing service. They were losing throughput, and those are some of the risks that the mesh brings. It brings risks that you would not necessarily anticipate because everything is so interconnected.

Sanjog Aul [00:25:24]:

And so you bring up this cloud infrastructure, and there are a lot of organizations because of I’m not saying maturity, but the resistance to go to cloud because of this untold fear with respect to security challenges, or there are regulatory issues which would prevent them. So would you say there is a way out for all companies in some form of fashion to be able to leverage this digital mesh by doing something to their infrastructure so that that computing power or their connectivity and distributable, that global distribution related issue which is very, very much required for a digital mesh to exist is no longer an issue. Because this is the foundation without having that, god bless, I’m not sure if we can really get to fully harnessing the value of digital mesh.

Chris Zissis [00:26:19]:

Yeah. I think the challenge around cloud and the historical challenges we’ve all faced — are we meeting regulatory requirements, are we meeting global data protection requirements, are we able to secure the hardware and the servers in a way that they are hardened, that we don’t create risk for enterprise — is very much still there, but I think the reality is cloud environments, particularly some of the big cloud providers, if you think of Amazon, Amazon today is not only Amazon as we know. It has the largest distributor and logistics company that allows us to buy stuff without going into stores. They are a cloud provider and a very good one at that. They’ve hardened and they’ve catered through their architecture for a lot of these challenges around regulation, data protection and enabling CIOs and CEOs and management boards to feel comfortable in creating risk, and if you think about it one step further, if you think about how start ups start, start ups ultimately start with cloud services, and then ultimately, they have the challenge of scaling, and over time, the successful ones scale appropriately through partnerships or through additional investment, but they never really move away from the cloud ethos. So Uber is a cloud-run business. Microsoft, 2 or 3 years ago declared that they will become a huge provider of cloud services by eating their own medicine, and so if you think about today, email is cloud hosted. If you think about content management, it’s cloud hosted. If you think about what we do in our daily lives, through banking, all the applications we use for online banking, I’m sure in The States as well as in Europe, are cloud hosted. So we’ve overcome that challenge. I think the digital mesh brings on a different dimension and that is how do you move from cloud computing as a style of computing to create service orientated models for hosting things to cloud computing and edge computing. So as I said earlier, engineering where the application is in your face. It’s available to you either through a wearable or through a mobile phone and how cloud and that edge computing allows for constant connectivity in a distributed way, but then also allows the cloud services to prevent security breaches, prevent leakage, and that is, I think, kind of the flavor of the day and that’s where the key skills that I spoke about earlier in terms of having the right skill to understand how this architecture all hangs together and can bulletproof any risks is probably the bigger focus rather than on premise versus cloud as it was in the past.

Sanjog Aul [00:29:56]:

Let’s take a quick break, listeners. We’ll be right back. So it was a great discussion on the upstream part, which is setting up your plumbing, the architecture, the infrastructure if you will, at least on the connectivity side and the core computing power. Now, once we come back from the break, let’s talk about downstream. So, okay, you got your pieces together. They’re hanging on well together. Now you got the data being exchanged, being processed, being acted upon for you to essentially create that experience in the first place while you started this. What does it take given most organizations, large and small enterprises dealing with this glut of data? Everyone says I want to make a data lake, but what then? How do you make sense of it? Problems with data enablement as a culture, that’s a big problem. Data management is a big problem. So how are digital mesh related investments ever going to pay off without us having a good handle on data management and building a culture of data enablement? Let’s discuss that. Please stay tuned listeners. We’ll be right back.

Speaker 0 [00:31:15]:

Your growing business needs a highly productive workforce, effectively communicating and collaborating without exposing corporate data to cyber attacks. Are you looking to balance security and workforce productivity? Move beyond short term measures and securely scale your business with BlackBerry Enterprise Mobility Management Solutions. To learn more, please visit blackberry.com/enterprise.

Speaker 0 [00:31:46]:

Patient centered care requires a connected enterprise. Are you ready? If you’re looking to scale your health care IT efforts, visit redmane.com/health today. Whether it’s to connect data from multiple partner solutions or developing software for unique needs, RedMane can help. To find out how RedMane can help your company deliver on the patient centered care promise, visit redmane.com/health or call (773) 693-3919. Visit today.

Speaker 0 [00:32:19]:

Predict your company’s future by creating it. Is your workforce able to connect, exchange ideas, and share brilliance simply and securely? Create tomorrow, today. Empower your people to innovate anytime and anywhere with secured BlackBerry Enterprise Mobility Management and document sharing solutions. To learn more, visit blackberry.com/enterprise. You are listening to CTN CIO Talk Network with Sanjog Aul. Now back to the show.

Sanjog Aul [00:33:00]:

Welcome back. So we did talk about upstream infrastructure, architecture, plumbing, which will keep the pieces together, and now let’s talk about the downstream, which is, okay, you got all data coming from different directions. How do you handle it? How do you make sense of it? How do you find something actionable? And then give that what I call a continuous digital experience to the parties who you are aiming to serve?

Chris Zissis [00:33:29]:

Yes, thank you. I think if you think about what we discussed earlier, one of the most telling things about the digital mesh is the fact that data is everything, right? Data content is everything. It’s the foundation upon which we can create new businesses, be they digital or challenge some of the notions of how we do business today. So data through the digital mesh poses a unique opportunity for us to challenge the way we’ve captured and leveraged data, but also how to better store and then exploit the storage of that data for future use. So what does that mean in real terms? It means that the skills of the organization very quickly shift from process automation, very quickly shift from a sales orientation, being able to cobble together applications that help for more efficiency and productivity to skills that are all about data and how we exploit the data to ultimately create new insights in what we do. Data scientists is the flavor of the month, has been for many months and years in our profession, but employing good data scientists that have the ability to learn as the mesh creates more dynamic views of information, evaluate the accuracy of those and then use those to create new insights, and coupling that capability with algorithms, artificial intelligence, ultimately is what the business of technology and data is in the new digital world, and so ultimately, I see a shift in how organizations will leverage IT departments, technology departments, more focus on application engineering, more focus on acquiring or buying new technologies that can help exploit the mesh and then more importantly more focus on data scientists to create a more systemic and dynamic view of all this data that is coming into the enterprise to ultimately create new things. So an example I’ll give is, if you think about valuations of real estate, it’s a very simple thing. You have a workflow, you get a whole bunch of data that is traditionally based on your understanding of corporate real estate and the market. You give it to some very clever people, actuaries, valuers and they determine over a period of time, based on supply, demand, transactions, what ultimately the potential value of real estate could be today and possibly in the very near future, but not in the distant future. If you then think about the digital mesh, it’s providing information of where people want to entertain themselves, where they commute from, where they do their shopping, and ultimately, how they get to a destination, and that starts to add a lot more insight and a lot more information on some other parameters that can determine value, and that’s where data science comes in. You then start shifting the paradigm from I can predict valuations based purely on what I know to I can start thinking about valuations in the context of information I never had, which the mesh is providing, and then going forward, not only can I predict valuations, but I can ultimately start to influence valuations by ensuring that the construction of buildings or the refurbishment of buildings is in line with the insight I’m getting from the mesh. So data science, ability to exploit data, ability for data scientists and application developers to work together to create new outcomes is key, which then brings me to the whole idea of how IT departments or technology leaders respond to this. I must say it’s a world of two polarities. I think some are basically saying, this is not me. Let the data guys deal with it. They have more skill and capability, and we will just do what we do, which is protect the perimeter, make sure the cloud environments are strong, make sure our end users have the right devices. Others, as is the case in our organization, we’ve combined the two capabilities, and slowly and incrementally, we are changing our skill base to be more responsive to generic technologies the way digital natives think by coming into the enterprise. They know what they want. They know how to leverage the technology. They don’t need to be educated. They don’t need to be spoon fed and we are moving our skill more towards leveraging automation, leveraging the intelligence that the digital mesh brings, bringing in data skills, bringing in solution experts so that we can create real outcomes from what’s coming downstream.

Sanjog Aul [00:39:34]:

So traditionally and even going forward, would you agree that IT would really do the job at its very best when it is invisible? I mean the device mesh would exist, but it would be more of an experience versus us literally taking notice of the devices that exist or they work any differently, etcetera. So is there any effort being made to make it as an experience versus IT tinkering with a bunch of different architecture devices and data?

Chris Zissis [00:40:05]:

Yeah. I think that’s a really good question. If you think about the mesh today, it is both visible and invisible. IT in the past, and even in many cases today, was all about how do I improve functionality? How do I constantly through my experience of the organization and its needs predict what I need to invest in to improve what the organization needs because I have an understanding of the strategy, the process flows, the way we go to market today, and with this constant need for people to have access to data — I mean, how many times some of my colleagues check their LinkedIn profiles and their Instagrams and their Facebooks — this constant need for data is actually challenging our ability to predict what organizations want and what the digital natives need. They need something real time and they need something on a whim because that’s how we are growing up as consumers. The iPhone has kind of changed the way we calculate things, the way we determine how we go from point a to b, the way we order things, and so IT departments are no longer about predictable industrial planning where investments, be it CapEx or OpEx, are predictable and able to deliver good ROI if done right. IT departments today, given the fact that the mesh has challenged some of the thinking, are about trying to respond to the opportunities that all this information and content brings, truly responding to partnerships out there that do it better and faster than traditional enterprise technologists would do, and then more importantly, using that to have a conversation with the business or the fee earners or the product colleagues on how we can change the business from just doing what we did well to doing things that are very different that we’ve never dreamt or thought of before. So I’ll use a good example. If you think about Blockchain, for example, as a distributed concept, the computer is the mesh, right? And it’s still trusted because people understand that it’s got certain criteria whereby you cannot dispute the record. You can have a record of what’s been agreed in a dynamic way. So if you think about organizations and enterprises, we have to become more blockchain-esque. We have to not try and have a point to point transaction between what we do. We’re going to have to figure out ways and are figuring out ways where all this information will lead to new business outcomes, and those business outcomes will challenge the traditional way we’ve invested, hired, and more importantly with who we’ve partnered.

Sanjog Aul [00:43:58]:

Now here when we are going through this journey and, yeah, we talk about technology, we talk about data and analytics, people — and I say quote unquote people — are becoming issues, and that’s if you were to ask people in the room and say raise your hands how many people have issues with people as part of the foundational elements which will make device mesh more manageable or making the digital successful, most hands go up. What do we do on that front? What do we do in terms of the training? So we’ll take a quick break right now, and that’s something we should cover as well because that becomes the most important thing. So you’ll have some changes in the processes, but eventually it comes down to people because this is a never ending race or an exercise because today you have one experience to deliver to your customers. That would morph, and new technologies, new devices, new architectures, it keeps happening. How do you keep these people to have the juices flowing at the best possible manner and get them to deliver exceeding expectations of the ones who you serve? What does it take? Please stay tuned listeners. We’ll be right back.

Speaker 0 [00:45:25]:

Predict your company’s future by creating it. Is your workforce able to connect, exchange ideas, and share brilliance simply and securely? Create tomorrow, today. Empower your people to innovate anytime and anywhere with secured BlackBerry Enterprise Mobility Management and document sharing solutions. To learn more, visit blackberry.com/enterprise.

Speaker 0 [00:45:52]:

Patient centered care requires a connected enterprise. Are you ready? If you’re looking to scale your health care IT efforts, visit redmane.com/health today. Whether it’s to connect data from multiple partner solutions or developing software for unique needs, RedMane can help. To find out how RedMane can help your company deliver on the patient centered care promise, visit redmane.com/health or call (773) 693-3919. Visit today.

Speaker 0 [00:46:25]:

Your growing business needs a highly productive workforce, effectively communicating and collaborating without exposing corporate data to cyber attacks. Are you looking to balance security and workforce productivity? Move beyond short term measures and securely scale your business with BlackBerry Enterprise Mobility Management Solutions. To learn more, please visit blackberry.com/enterprise. You are listening to CTN CIO Talk Network with Sanjog Aul. Now back to the show.

Sanjog Aul [00:47:11]:

Welcome back. So, Chris, when you are looking at different aspects of digital mesh, we did talk about the upstream, the downstream in terms of what you do with data, but then all of that comes down to the people who are creating things, managing it, and serving the very people who you intend to serve. That means your internal business users. That means your internal technology workers who are coming together to make it happen. What would you change or what would you do new, more, or different with them? So that you truly get to maximize the value of working and supporting the digital mesh.

Chris Zissis [00:47:50]:

Yeah. I think there’s a couple of thoughts that come to mind. If you think about people first of all and skill sets, I think the two truly important skills that any organization that’s going through this journey needs are data scientists and digitally focused software engineers who are able to interpret all this capability across architectures, across engineering requirements and make something of that, and yes, I think a lot of organizations talk about project managers and program managers and trainers, but for me software engineers and data scientists are very key, and you have to invest and you have to continuously invest in their higher development and challenging them. So that’s one facet. The other facet is any organization that’s going through so much dynamicism and so much change because of the information available, the vendors coming through with a clear review of what’s better as opposed to something that’s not as good, is having a truly open and trusted dialogue across the enterprise on what you’re trying to achieve. So seeing — I mean, we call it digital watch — it’s understanding what everybody else is doing, what’s out in the market, who’s offering what, and the reason why that’s important is with the digital mesh, with the fact that so many devices, so many endpoints, so many applications are viable today, you don’t have to build them. You don’t have to spend months creating them. It’s really important that you have people to understand what’s happening out there and what you can leverage. So that’s the second piece. The third piece, which is less about skills and having an understanding of what’s out there and having a common understanding of what’s out there in the technology teams and the business teams, is you can only be successful if you are clearly defining the outcomes you want to achieve with the data, with the information you are receiving through the mesh. So the one phrase I like to use, and I’ve heard this from some very clever people who’ve been successful in exploiting the mesh is maniacal focus on scope. So what am I trying to achieve? Why am I trying to achieve it? What value will it give me? So if you think about the people context in relation to these three themes, it’s have the right skills, understand what’s out there because in many cases today, you don’t have to start from scratch. You can start with the foundation that you can buy or you can learn and then build, and then number three is the outcomes need to be very clear from how much time I’m going to put in, what I’m trying to achieve and then ultimately how much am I going to get in return for that, and that has changed the paradigm of what technology teams have done, right? If you think about traditionally, it was all about big projects, very, very specific business cases to implement an ERP over a period of time. Now we’re talking about doing those as well because enterprises need them, but to exploit the mesh, it’s all about small proof of concepts, light touch applications, pivot, pivot, fail or proceed, and you need the skill base to evolve in that way of thinking, and that’s ultimately a big differentiator. The final point I’ll make about people is they are hard to come by because software engineers, good software engineers, the ones that ultimately are are very good and will be successful want to work for the Googles of this world, want to work for the Apples of this world. They don’t ultimately want to work for every other enterprise. So investment in people, paying good money but then really, really pushing the ante on making sure that they’re working on challenging things and not just maintaining the status quo is a commitment an organization has to make strategically. So not a cost center. These are people who are driving value, leveraging the mesh, leveraging the data that comes from it. They are driving new business outcomes and they have to be rewarded and remunerated in the same way that people who actually sell products and services grow market share are rewarded and, ultimately, remunerated, and then finally, training is important. I think you earlier said not even the trainers ultimately are able to embrace some of this. So it becomes really important that you’re constantly building a bench of new partners, new colleagues and employees, new alliances that will ultimately help you move through the uncertainty that this constantly changing world of technology brings to the fore.

Sanjog Aul [00:53:44]:

On behalf of the show and our listeners, I’d really like to thank you so much, Chris, for sharing your views on how IT leaders can get ready to support and harness most value from this digital mesh.

Chris Zissis [00:53:58]:

Well, it’s just very good to be in. I thank you for your time. Really enjoyed it.

Sanjog Aul [00:54:02]:

Thank you so much again, Chris. Please like us on Facebook listeners, search for CTN, that is CIO Talk Network. Be sure to follow us on Twitter. Join us on LinkedIn community, and then find our podcast on a variety of platforms including iTunes, TuneIn, Stitcher, iHeartRadio, Spotify. We are there everywhere you are. So hope you will join, subscribe, and rate our podcast. Thank you again for listening to this segment on CTN. This is Sanjog Aul, your talk show host. Till next week, take care, and God bless.