Digital Experience Monitoring for Managed Workplace Services: A Lakeside Software Webcast Featuring Gartner

Featuring David Groombridge (Research VP, Gartner) & Dan Salinas (VP of Managed Workplace Services, Lakeside Software)

Learn how you can shift from traditional SLA key performance indicators to XLAs.

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Moderator: Cloud and SaaS adoption along with the advent of digital business have introduced unprecedented complexity to the Managed Workplace Service provider market. Customers have more choices than ever over which blend of service provider offerings best serve their end users’ needs and service providers struggle to show differentiation.

Among the most difficult issues facing Manage Workplace Service providers today is the ability to properly relay the impact of the services they provide on their customers’ business. This is why an increasingly key component of Managed Workplace Services is the ability to unearth quantifiable data that both technical and business audiences can understand.

In this program, Gartner Research Vice President David Groombridge, and Lakeside Software Vice President of Managed Workplace Services, Dan Salinas, discuss how digital experience monitoring enables Managed Workplace Service providers to shift their service level agreements away from legacy uptime metrics toward more meaningful analytics that enable service providers to deliver—and enterprise customers to quantify—measurable business outcomes. First up in our program is David. David, welcome.

David: Hello, I'm very happy to be here. It used to be very easy to make money as an outsourced service provider, but client demands have evolved, and times have changed and now margin is increasingly difficult to find and perhaps nowhere more so than in Managed Workplace Services, MWS. As part of Gartner's ongoing research, we analyze different segments of the outsourcing market and you can see the results on this chart. The growth rate of each market segment is across the bottom and our estimate of the margin is on the side. Where you want to be is delivering services in the top right, but where is Managed Workplace Services? The bad news is down there in the bottom left; it's commoditized and it’s shrinking even though the number of clients outsourcing is growing. So, in this session what I want to do is show you where the opportunities for growth lie and we’ll talk about what tools are required in order to enable that growth.

First, let's start with some good news. Digital leaders are increasingly no longer buying hardware. They're not interested in services. They don't want solutions or even that nebulous thing, partnership. Instead businesses that are really looking for digital transformation are buying outcomes. So, the question for providers is how do you sell outcomes? Let’s begin by understanding the first outcome that businesses are trying to buy: Employee Engagement. Employee Engagement is vital because our research shows that it not only increases the financial performance of a business, it adds customer satisfaction and it decreases employee turnover. But most critically, high Employee Engagement is associated with strong digital dexterity: the ability to leverage the benefits of new technology models and services and use those in digital transformation. In fact, digital transformation is over three times as likely to succeed where Employee Engagement is high.

So even better news, the way that we can leverage that we can sell Digital Workplace solutions that improve the working environment for staff, things that leverage virtual personal assistants, automation and analytics to improve the working environment. That in turn drives Employee Engagement which is what businesses want. And Employee Engagement is vital because it has two key knock-on effects for clients. Firstly, research consistently shows that engaged employees deliver better customer engagement, they deliver better customer interactions, they build longer lasting relationships, they bring customers back to buy over and over again and spend more money.

Secondly, though, Employee Engagement is vital because it drives increased discretionary work from staff, they're more willing to go beyond their normal working hours to deliver for the business. And those twin pillars of customer engagement and discretionary work really drive an increase in revenue and margin for the business. Great—we can sell Digital Workplace, enable Employee Engagement deliver outcomes. But—here's the problem: technology does not equal change; there is an execution gap between the delivery of the IT hardware and enabling the outcome. And, worse than that, the old ways that we used of measuring performance where every aspect of the incident break-fix cycle was metered and measured—where all of that was subject to SLAs—those measurements are no longer fit for purpose. A measurement of response time or abandonment rate or fixed time doesn't cut it in a world where we're trying to drive Employee Engagement. Instead of that, we need to measure the overall user experience, an all-around measure of what the user is getting from their IT day-to-day in their business and their operation.

And the key takeaway from this presentation is it is one key to closing that gap between the delivery of technology and enabling those outcomes. It is digital experience monitoring: monitoring every aspect of the experience we deliver through the digital workplace. Because by monitoring it, we can manage it, we can optimize it, and we can drive the outcomes. So, let's understand the breadth of this problem. Let's look at the definition from the International Standards Organization, the ISO.

And, as you can see, this goes vastly beyond those traditional service levels. Certainly, a measurement of how quickly the phone is answered on the service desk no longer cuts it, nor even a measurement of customer satisfaction for incident resolution. Instead, the ISO is looking at a wide range of new measures that go vastly beyond those technical measurements we used to employ. It’s looking at emotions, perceptions, behaviors, and psychological responses. Our old tools are no longer going to be suitable for measuring these kinds of issues in a world of digital experience monitoring. So, the key will be to do something different, and that different points will be to use something that we call Experience Level Agreements (XLAs). XLA is a rounded measure of the entire experience that the employee has through every aspect of their interaction with IT. It measures how they work with the service desk for sure, but it also measures the sort of experience that they get out of day-to-day services by combining hard measures of the way the service works with softer measures of emotional response to that and tracking all of that as a consolidated set of data. It is going to be measuring the performance of systems, the behavior and the use of the collaboration tools, the employee's response when they try and self-service, the impact that automation has. It's even going to extend to business KPIs and all of that will wrap together to give us a measurement of Employee Engagement.

This measurement of performance and perception across all areas of IT is going to provide an essential link between IT delivery and Employee Engagement, and it closes that innovation gap that we had. If we drill down into it, what we need to actually deliver an XLA are detailed embedded analytics tools that are measuring each aspect of the interaction of the user with the IT systems. So, for example, they may be measuring the way that the user interacts with the self-help system: how much is it used? how much does it drive incident reduction? how frequently can the user find the right knowledge on the search? what is their net promoter score for the service? But that's just the self-service.

We may also be measuring application performance. We may be measuring business KPI such as the speed of business transactions. We measure these at a granular level using the embedded analytics tools to monitor and report on the outcomes. We can then wrap that data up in a weighted dashboard to provide measures in an aggregated level, then report on the experience with an individual service lines. And then, finally, we can roll that out further, we can combine multiple measures from the entire IT state into a single measurement of user experience. In that way, we can go across the measurement from operational to managerial to executive outcomes and at every level the analytics will give us information about how we are performing in order to adjust and optimize the solutions that we deliver.

We know that the XLAs are going to benefit our clients, but they can also deliver benefits for us as providers. We have multiple sources of data available to us. We have reams of instant data. We track event logs, we track processes, we record system data, we measure user sentiment through surveys and through emotion tracking tools. We can take all of that information and the information of subject matter experts heads. We can extract it, feed it into the analytics engine. The analytics engine processes the data seeking insight, looking for correlations with historical patterns and then it can make output, it can predict what's going to happen or it can even say as well as predicting what's going to happen, it can tell us what we need to do about it. The user can then apply the fix, driving down incidents before they occur. And fewer incidents are great for the client because fewer incidents lead to an increase in customer satisfaction and an increase in employee engagement. But these are also good for us because reduction in incidents means a reduction in cost, some of which we can share with the clients, some of which we can use to improve our margin. And, even better than that, this is a virtuous circle where we can take the output of the analytics, feed it back into the analytics engine, and carry on deriving increased levels of benefits.

Sounds great. But let's remember measuring user experience is not the goal here, this is just a tool. It is a tool to enable us to connect what we can deliver with what the client wants to achieve. It enables us to bridge that execution gap between the delivery of technology and the aspirations of the client, the outcome. Without these kinds of measurements, then the benefits the outcomes the client wants to get will fall squarely into that gap—however new, however shiny the infrastructure is, it won't deliver change within the business. But the XLAs, they provide a way to close that gap by linking the benefits that the technology gives directly to business outcomes. We can understand the direct connection between the technology and the way it's used and what the business wants to achieve. That means that we can optimize, and we can help that value flow through to our clients; in this way, we can move into those higher value sales and start selling outcomes.

And parts of that sale of outcomes will be allowing us to deliver contracts that actually put our revenue on the line against those XLAs. We can commit to outcome-based contracts even in infrastructure services delivery. That might be about Employee Engagement increasing over time. It might be going beyond that about measuring staff productivity and committing to increased staff working time by say 30 minutes a day across the next three years. Or it might even extend to linking the revenue that we derive from the contract to the revenue that the client makes.

And I just want to finish with one example where a provider took over service delivery in a retail environment. There was quite a legacy approach to the service delivery, it was a highly manual operation. There was very little monitoring of the environment and certainly no understanding of the experience of the users. The provider implemented analytics throughout the operation, coupled that with automation to reduce the manual effort of work and, as a result, was able to drive down the number of incidents in the estate considerably over time, while increasing the net promoter score of the staff for the IT delivery and, more importantly, increasing both their revenue and their margin. And to do that, they committed to outcome-based contracts around how quickly the store shelves were refilled in the retail outlets.

So, the opportunities are there. Clients want to buy new things, they want to buy outcomes. We have to move away from delivering technology and we have to link what we can deliver in terms of transformational digital workplace to those outcomes. And the mechanism for that is Experience Level Agreements, XLAs. Thank you.

Moderator: Thank you, David. Now we'd like to welcome Dan to the program. Dan, thank you for joining us.

Dan: Thank you for the introduction and thank you David for commentary there on XLAs and SLAs as it relates with Managed Workplace Services providers. My name is Dan Salinas, V.P. of Business Development here at Lakeside, and I'd like to add some color to David's commentary specifically around how digital experience monitoring is used to make Managed Workplace Services providers more profitable in addition to XLAs.

Specifically, we’ll focus in on the different use cases in our experience around personas using digital experience monitoring to improve customer environments, asset management, and its role with asset analytics, the shift-left initiatives, and ultimately why we believe Lakeside is a good partner for Managed Workplace Services providers.

This slide is depicting all the different use cases that we've seen with working with Managed Workplace Services providers, specifically around different methods to gain revenue, higher TCO, that sort of thing. These cases cover anything from collective intelligence benchmarking where people are aggregating across a variety of silos and customers, collective benchmarking anonymously to drive decisions to desktop transformation. We even had a provider that used that data to help a customer plan a parking garage. The variety of different use cases are broad. But what we'd like to do for today is focus in on a couple of use cases specifically that we've seen a lot of success with the Managed Workplace providers.

Now as we deep-dive into personas, we need to think about like traditionally how service providers had done in the past with a one-size-fits-all approach to services because they didn't have the data to support different targeted services to different types of users. By using the technology, we're able to partition the users into their different persona types. Out of the box, we are looking at road workers, task workers, power users etcetera and service providers use those categories to customize it for their own purposes, so they might use that to differentiate the data.

Why they're doing this is because they can properly set expectations of the different worker types, set XLAs based upon the different persona types, and in a lot of ways increase their margin because they're targeting their services better than just sort of a one-size-fits-all and be able to deliver better services based upon this approach. Once we solve for personas, then we start looking at transition and how we bring new customers into the experience. And one of the core tenets of our platform is the concept of user experience scoring.

The way this works is we basically measure, as the users using their compute environment, we're measuring all the aspects of what garners good user experience over our 20 years of existence and experience. This score is much like a credit score, in a way: it's fixed, it's understood, and it allows you to compare users with users, personas with personas, etcetera. The way it works in detail is every 15 seconds, we're measuring this on a user basis when they're logged in and actively using the machine. If they're having an impacted in 15 seconds, we mark that and then we take all that over 100% and we establish a score between 0 and 100. So, 100 means that the user has never had any impact, 0 means they always have impact.

Now the power of this number is that it's a single number that you can digest across groups, it's consistent, it's measurable and it doesn't necessarily need to be 100 but it helps you baseline. And then when you dive into the number, you can drill into “okay, this group has a poor user experience score.” I could drill into that group and I can see immediately examples of poor user experience and I can click into that and be at a root cause level diagnosing why that's the case. This is very powerful because it's a closed-loop platform. It isn't just setting a score and then you have to figure out how to drill into it.

Now the example we're showing here is a real customer that we've been working with a service provider, where they came in, deployed SysTrack, and they went through a process of baselining in the user experience score for setting XLAs. Immediately, they found a variety of different issues in the environment they weren't able to see before and the reason they weren't able to see them is because obviously they didn't have the visibility. They fixed a number of issues over the coming months as they went to go baseline the score and providing a tremendous set of value and ultimately making it a much simpler environment for the service provider to manage because a better performing environment is easier to manage.

Some of the examples of things in this particular case was they found some login processes and group policies that were taking too long; they found some machines that were being upgraded to Windows 10 that still had spinning media instead of SSD; they found issues with latency because connected home drives were pointed to the wrong space; they find a variety of things. And as they implemented those things, they saw the score go up. And this is important because this clearly shows value that the provider’s bringing and now they can establish the baseline. With this score, we can use it in a number of other ways.

So, as we talk about the digital experience score, another use case that we're seeing is around needs-based procurement. And what we mean by this is the ability to use the score, baseline when there's variance on the baseline, then we can decide when to replace people's machinery and when they need new platforms versus this cycle of every three to five years to replace equipment. Now the reason this is incredibly valuable is when it saves a lot of money.

Two, it avoids this huge run up project, RFP to replace equipment it sort of becomes part of the delivery of services and there's a value added services. In addition, this sort of concept can also be applied to software, and really when we talk about evolving and using analytics in the delivery of services asset management which is a traditional set of services that service providers provide now, can really elevate to being more asset analytics. Don't just tell me that I have an asset, tell me if I need that asset and am I getting the best use out of that asset? So, this provides a good vehicle for more value to be delivered.

This sort of use case can also be applied to software. Do they have the right level of office in the environment: E1, E3, E5, are they getting the most value that? Do they have Visio, do they need Visio? They have 13 different versions as Adobe Acrobat Reader in the environment, clean up those images. So really when we talk about a needs-based procurement model, we're talking about hardware, we're talking about software, and really elevating asset management to becoming asset analytics and then therefore ultimately more margin for the provider and better user experience for the user who's getting what they need when they need it.

As we move on to the next case, we're really talking about shift-left here. And when we talk about moving shift-left, is empowering IT support to have data on the front end and analytics to solve issues and ultimately eliminate issues from the environment. A lot of technology here has been focused on user self-help and things like that and we fundamentally believe that what we want to do is eliminate problems from the environment entirely. We want to look at common incidences, we want to use AIOps to automate the resolution of these incidences and ultimately find these things in and take recurrent incidents out.

What we've seen in environments is there is a lot of underreported issues as well, and we want to attach those as well. So, the concept here is using automation to eliminate incidences in the environment. In addition, when something enters the support process, automate what we could see Level 1 doing, we can use chatbots and SysTrack and Power data to answer those common questions and when it arrives into Level 2, and you might define as Level 1.5, Level 2, but, when it enters those organizations, the data required to troubleshoot the issues already present within the case within the ticket, because we've attached it, so we eliminate the amount of time that the Level 2 or Level 1.5 person has to reach out to the end user. They can use the Black Box technology that we have and immediately start troubleshooting and it really at lowers the cost of that. As we look at the cost, we look at the different levels here and really as we move shift-left, the economics is clear that the more it's in the environment, the more expensive it becomes and that's really the savings in terms of shift-left.

So, as we've talked about those four cases, we'd like to talk a little bit about the unique approach of SysTrack and how they support the value propositions of TCO and lower cost and improved delivery and improved user experience. Our fundamental architecture approach is an edge-based approach. So that means that the data collection and aggregation happens on the edge and the first orders of analytics happens on the edge. That enables us to scale to large deployments and it also enables us to capture without having to sacrifice the data fidelity and both broad, 10,000 data points every 15 seconds, and also the details of each individual data point being, the analytics being based upon a very small sampling size so that the averages and the deviations of that is valuable.

It enables us to do it in an efficient way with efficient resource utilization so that we don't use a lot of bandwidth, networking, works offline and those sorts of things and it's, as I mentioned, designed to work offline. We've been around for 20 years, so we have a lot of experience in what the right metrics are to collect as well and, ultimately, it's cloud-ready, so we have a whole multi-tenant platform for service providers to deploy and then aggregate their customers together.

The other benefit here is the privacy and compliance controls. So, because we capture the data, the most detailed data on the user device itself, that data does not leave the device without the user permission. So, we are able to comply with GDPR, General Data Protection Regulation, council requests and things like that easier because this data does not leave the device to the way it does. Ultimately, this approach enables service providers to aggregate and collect enormous amounts of data, create use cases, solve problems that lower TCO, that improve their own ROI, and ultimately allow them to compete and create unique solutions in their market. With that I’ll wrap up my comments and thank you very much.

Moderator: Thank you, Dan, now we have a few questions that came in for David over the course of the presentations. David, how do managed Workplace Services Providers differentiate their use cases for digital experience monitoring?

David: So, I think the first level of differentiation is to actually have some in the first place. I see a large gap in the market. I think there are providers at the moment who are still focused just on delivering very traditional deals based around traditional SLAs without any digital experience monitoring and they can absolutely compete for cost-base deals, but as we saw on the first slide, that will be a race to the bottom, that is a market segment that's going to shrink in revenue terms. If you want to compete for the higher value transformational deals, you need to have digital experience monitoring. In terms of the differentiation there, the differentiation I think is about the breadth of tooling that you can apply.

Many Managed Workplace Services providers say, “oh yeah, we use analytics, we use it considerably.” But what they really mean is that they have an analytics tool that analyzes incident data. That is not sufficient in a world where the delivery is about Employee Engagement and the user experience. It has to be a much more rounded measure of what is happening in real time. And I think that's the third level of differentiation is the time aspect and how quickly you can measure this data and act on it. There's a big difference between processing data that you gathered six months ago and then thinking about what you might do with it in six months’ time and instead being able to respond in real time not just to large groups of users but down to individuals who may be experiencing problems. So, I think the first step is to have it, the second step is to tool widely across the estate, and the third step is to drive real time monitoring.

Moderator: Next question, how does improved user experience deliver quantifiable business results?

David: I think a lot of organizations today recognize that if they're going to make digital work, they first of all have to make analog work. And what that means the analog component is the users in their organization. A lot of organizations have worked on traditional five-year refresh cycles for infrastructure, they now recognize that there is a huge potential to bring the workplace up to date with new modern ways of working and doing that provides multiple benefits in terms of users. First of all, we know of clients who, by refreshing their workplace and measuring the experience it gives, have radically driven down their employee turnover rate for new graduates who are looking for high quality technology and service delivery in the IT workplace.

Secondly, every member of staff comes with an expectation that their workplace is going to be as easy to use as their own personal IT, the consumer IT that they carry around. If they don't see that, then it will have impacts on their morale and, naturally, that will have an impact on their work with customers and the work that they're prepared to put in. So, the second level of benefit is about increasing that Employee Engagement and as we've seen then driving greater connectivity with clients and being more prepared and more able to do work in their own time, adding value to the business.

So, I think in summary there are benefits both in reducing employee turnover where employees are increasingly selecting their workplace on the quality of the IT service and solutions they get. And secondly, there are benefits about enabling staff to respond more effectively, more rapidly to clients and to changes in their own workplace, all of which adds to top-line growth and bottom-line margin.

Moderator: And here is a final question, what is the role of AIOps in Managed Workplace Services service offerings?

David: I think AIOps are a natural evolution from the analytics phase. Clearly what analytics does is it gives us a view on the state of the environment. Now it enables us to compare it to historic data, it makes predictions about what is going to happen and maybe what we need to do, but it doesn't actually take the action for us. So, as we saw on a previous slide, it still requires a member of the IT team to actually execute changes.

The natural next step is to combine that analytics with an automation of outcome so that when the analytics identifies what needs to be done, that can be applied automatically by a script, by operations management automation or by some other automation tool within the estate. That will have the impact not only of reducing the cost of delivery by reducing the need for human staff, but also it will increase the service quality because intervention will become quicker and more repeatable. And that means that we get into the point where a properly tooled AIOps-delivered Managed Workplace Service will deliver benefits both in cost reduction to the clients and in service quality improvement. That's always been the promise of outsourcing. But, for the first time, this is what we're really beginning to see delivered by the leading outsourcers: lower cost for the client, better service delivery, and, you know what else? Better margin for the provider. So, AIOps is going to be a central component of sustainability both for clients and providers in this new digital world.

Moderator: Thank you, David, that's all the time we have. I'd like to thank both David and Dan for their great insights today. A quick program note: Gartner is an impartial independent analyst of the information technology industry. All content provided by other speakers is expressly the views of those enterprises and the speakers. The information should not be construed as a Gartner endorsement of said enterprise’s products or services. That concludes our presentation.

If you would like to learn more about today's topic, please visit: www.lakesidesoftware.com. Thank you.