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Every business leader wants to be the next hero, praised for sharpening the corporate competitive edge. Business heroes are the ones who solve big problems by leveraging emerging technology to awaken new powers accelerating strategic outcomes. So, why not use artificial intelligence (AI) to step into your higher potential, automating a system that drives more dollar value out of your corporate IT investments?

It’s time to get more value out of accelerated innovation

Thanks to years of accelerated innovation, businesses of all sizes are capitalizing on the agility of digital services and remote work. But at what cost? The challenge today is: How efficient and sustainable is your IT spending when it’s gone unrestrained over the past three years? Business heroes might even be taking on the task of curing a corporate digital transformational hangover. Consider that:

While 78% of companies adopt the cloud, not all are seeing value of their investment. Cloud overspending can be as high as 70% according to Gartner.Roughly 29% of cloud investments go to waste, according to an upcoming CIO study.Shadow IT can consume 30-40% of IT budgets, and it’s not uncommon for companies to have 10-20 times more cloud applications than they anticipate—especially following panic-stricken video conferencing purchases.

Today, IT investments happen at warp speed, and afterward business leaders are expected to govern those investments, normalizing them into the company’s standards of operational excellence. That requires applying security protections to cloud investments and remote work, taking a recount of all IT resources after widespread changes, putting checks and balances in place to manage new assets, and realigning spending with business goals.

While anyone can achieve these goals, only those who can automate them will be celebrated as a hero. But as we all know, a hero can’t win the big prize without first going on a journey.

AI: the journey to intelligent IT expense optimization

AI is making intelligent automation the new business standard. In IT, machine learning and behavioral analytics are no longer used only for making sense of security threat data or predicting network service outages. They are now being applied to address the problems of IT cost control, vendor management, and administration burdens surrounding today’s highly distributed business ecosystems.

Much like a robot vacuum learns the layout of your house, AI-powered analytics can be used to study the entire IT environment alongside its associated services and expenses, correlating this information with usage data. Tracking cloud infrastructure, network connections, mobile devices, and their services generates granular data intelligence, allowing AI engines to “understand” current IT spending trends and “see” how effectively a company uses its existing investments. Let’s look at one example.

IT service sprawl: championing vendor management with AI

AI is solving the problems of vendor management and provider sprawl—issues all too familiar to IT leaders handling an ever-expanding landscape of tools, services, and dashboards. In fact, it’s assisting with some of the downsides of software-defined networks (SD-WAN) and Secure Access Service Edge (SASE) investments when companies suddenly find themselves with an overabundance of internet service providers (ISPs) to manage. AI works to eliminate the manual work of handling hundreds of ISPs and other sprawling IT service providers.

How does it work? Advanced analytics observe network services, connectivity usage, and the costs of global links across multiple vendors, allowing IT leaders to make quick sense of highly complex telecommunications environments. With a mountain of data crunched across ISPs, voice, and all fixed wireline services, companies can gain contextual clarity into how they are using their network services all in one consolidated view for elevated insights.

AI-powered telecom expense optimization can:

Eliminate the time-consuming need for administrators to collect, review, and correlate expansive datasets including inventories of services, providers, contracts, and service level agreements.Evaluate the usage activities of all network services in one dashboard, identifying unused assets, pinpointing billing inaccuracies, and streamlining the process of chasing down credits when network service providers fail to fulfill their SLA commitments.Prevent telecom service disruptions by automating complex invoice validation and approval processes to pay bills on time and accurately allocate IT costs across business units and departments.

This is one way AI automates IT expense optimization. Let’s explore the others.

Cloud optimization: awakening the powers of AI and closed-loop automation

Everyone is migrating to the cloud, and AI engines designed to automate cloud cost savings have two unique capabilities worth highlighting.

The first important distinction is AI’s ability to recommend solutions for the problems it recognizes. Big data insights and problem identification are the advantages of yesterday—actionable recommendations and automated problem solving are today’s biggest AI benefits. For example, AI can observe your corporate cloud infrastructure services and cloud application investments, essentially guiding you in how to use what you already own more efficiently.

An AI engine might recommend how to:

Optimize cloud service provider contracts, using long-term discounts to lower costs.More efficiently use the cloud storage and servers you have in place.Get more savings out of pausing features, turning off services when they aren’t needed.Reduce redundant applications, consolidating providers to lower IT expenses .Pinpoint unused application licenses, helping reallocate resources to other users.Identify security risks associated with unsanctioned cloud applications.

The second important distinction: the ability for AI to automatically act on its own recommendations. This is the signature of advanced AI capabilities known as “closed-loop automation.” Not only can AI recognize the problem alongside the solution, but it can also make that solution a reality with just the click of an approval button. Tight integration makes this possible. Only when AI engines are connected to the cloud service delivery platform can they manipulate settings and make changes to the control panel on your behalf.

Closed-loop automation marks the moment when AI advances from a data intelligence service to a virtual assistant, doing the more meaningful work of actually solving the core problem.

Using the cloud cost optimization examples from above, here’s what closed-loop automation looks like in a real-world scenario:

AI engine: Recommends using cloud infrastructure pausing features for the IT development environment because resources are only used during business hours.IT engineer: Clicks approve.AI engine: Uses API calls to implement changes inside your cloud service dashboard (inside the AWS environment).

This is the type of automation that gets business leaders crowned heroes. Automated problem solving is the true digital advantage because it literally accelerates business outcomes. Let’s face it, every business hero knows that nothing stops innovation in its tracks like the moment when a computer-automated workflow gets handed back to the human, essentially asking the employee to take it from there.

Arriving at automated IT expense optimization  

After accelerated innovation, harnessing information across the IT ecosystem is harder than it was just three years ago, and AI is the best tool for smarter resource allocation and tighter cost control.

The first step for business heroes is to apply advanced analytics to cloud and network services, so AI engines can start to understand what’s happening inside the IT environment. The key is to align AI to your strategic cost-savings initiatives, knowing which data streams coincide. After using AI to quickly recognize spending patterns and discrepancies between service usage and costs, it then becomes easier to advance into automated problem-solving using closed-loop automation.

Worried about how to get started?

Start with any functional area that is plagued by a combination of complex data with manual administrative processes and lean on IT expense management providers to usher in AI-powered platforms that simplify implementation through software and services. If you have a vast Iandscape of global IT services to cost optimize, look for a partner that can integrate with hundreds of IT service providers across the globe. The best expense optimization teams bring a library of IT spending insights, understanding the latest pricing information as well as how companies should shift their IT investments in response to economic pressures, remote work, and new technology trends.

In the end, business leaders crowned true heroes are the ones who save 15-40% of their IT costs by automating expense optimization. But in doing so, they also help their companies spend less money on the tools they need to simply run the business and more money on digital innovation.

To learn more about IT expense and asset management services, visit us here.  

Digital Transformation, Endpoint Protection, Master Data Management, Remote Access Security, Security Infrastructure

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An organization depends on its financial institution to complete a major transaction, but a glitch holds up funds, negatively impacting cash flow. Meanwhile, regulators fined a different financial institution for failing to catch fraudulent transactions.

In both situations, better business transaction monitoring could have helped prevent negative, costly outcomes. In the former, more seamless monitoring would have ensured the bank client’s transaction was completed faster, maintaining and even boosting customer satisfaction. For the latter, it could have prevented regulatory fines.

Today, especially, as modern applications and systems have become more complicated and IT infrastructure more complex, seamless business transaction monitoring is crucial. Enterprises need the proper tools to detect incidents early, automate wherever they can to make processes more efficient and free up IT workers for more complicated tasks, and be able to automatically solve any issues quickly.

“Business transaction monitoring is transitioning from a support function to a critical element in any organization’s operations,” says Digitate CEO Akhilesh Tripathi.

French utility company ENGIE, for one, needed a solution that could monitor its workload automation processes across its extensive IT infrastructure and business applications, and reduce dependency on manual issue resolution.

One of the world’s largest independent power producers, ENGIE conducts some two-million meter readings and generates over 150,000 invoices nearly every day. ENGIE approached Digitate for help to digitally transform its billing and payment process. The company wanted to move away from manual monitoring and remediation, which were both inefficient and risk-prone, increasing the operational cost and often leading to inaccuracies and delays in revenue generation.

Within 18 months, ENGIE was able to transform its workload process through a closed-loop solution that uses intelligent automation to automatically identify and solve any issues, further cementing its transformation into a digital enterprise. Digitate collaborated with ENGIE to provide a layered solution for monitoring workload processes to create a “blueprint” of the company’s entire batch system.

Now, ENGIE spends less time and effort on manual monitoring. It has reduced impacts to downstream processes like billing and payment communications by 80%, realized a 95% reduction in customer complaint tickets, and prevented €5 million per day ($4.87 million) in revenue loss. For its successful digital transformation, powered by Digitate, ENGIE was named Order-to-Cash winner in the Hackett Group’s 2022 Digital Awards.

With better business transaction monitoring as a part of their digital transformation, companies find business processes are well supported to generate cash, while transparency increases enterprise-wide. Financial institutions completing tens of millions of transactions daily can feel confident they can detect high-risk and suspicious activities.

Regardless of industry, business transaction monitoring has a critical impact on enterprises with tangible results. For instance, utility companies monitoring hundreds of thousands of bills have peace of mind that delays can be quickly remedied or prevented from happening at all. Yet, to be successful, organizations working to become digital enterprises must have the right technology.

“With the complexity of more and more systems in place, companies need tools to create visibility and confidence in IT to execute fast and protect the business,” Tripathi says.

With its closed-loop solutions, Digitate helps companies monitor all events across their IT infrastructure to create an integrated view. Tools detect anomalies, investigate, and self-heal to correct. Routine activities are automated, doing away with repetitive manual tasks and freeing up valuable IT workers’ time.

“We close the loop and we resolve problems to create value proposition for our customers,” Tripathi says. “They’re able to do this in one-tenth of the time it would otherwise take them.”

To learn more about better business transaction monitoring and how Digitate’s products can help you, visit Digitate.

IT Leadership

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When it comes to IT resourcing during tough economic times, cutting costs in the wrong places can be dangerous. Short-term money-saving steps can be counter-productive – actually damaging the brand in the long term. Smart companies, however, are building powerful third-party Technology partnerships to maximise budgets and simplify their IT operations, so they can continue to grow and innovate.

Here are five key reasons why a third-party IT partnership makes sense:

Delivering a hybrid working environment

‘Work from anywhere’ is the new mantra for all forward-thinking organisations, but delivering a hybrid working environment in-house can be risky and expensive. Partnering with a trusted third-party, however, can help you deliver the following benefits safely and without breaking the bank: 

Hybrid working significantly reduces real-estate footprint and costs. Recent research by IWG suggests that firms can save up to £8,100 per employee annually.A recent study by PWC also suggests that hybrid working can boost productivity.Hybrid working models are also an investment in the future, providing resilience against future crises, such as a spike in covid-19 infections and public transport strikes.Retaining talent with slick hybrid cloud experiences

Collaboration, effortless productivity and user-friendly workplace tools are key to ensuring employee satisfaction in the ‘work from anywhere’ era. Get this wrong and your brightest talent is likely to vote with its feet.

Seamless hybrid-cloud experiences, however, ensure staff have the information and apps they need to get their job done with minimum fuss and from any location. Cloud-powered home working can also improve employee work/life balance, save staff as much as £300 a month on travel and ultimately boost employee retention.

Cutting costs and boosting innovation

Organisations with on-prem servers might think they can’t afford cloud migration with a recession on the horizon. The fact is they can’t afford not to. With guidance from a trusted third-party IT partner, organisations can find the most cost-effective mix of private/public/hybrid cloud, simplifying their complex IT systems, delivering significant long-term savings, while also boosting innovation.

That’s because the right cloud mix reduces capital expenditure on hardware as well as ongoing maintenance. It also increases enterprise agility and innovation, because cloud apps are faster and more cost effective to spin up and down, enabling businesses to experiment with new products and services.

Ensuring systems reliability and availability

Whether you’re providing IT services to external customers or internal stakeholders, systems reliability and availability are key to building your brand. Leading public cloud providers generally offer a 99.9% systems uptime guarantee, they maintain three copies of data at all times in different data centres, provide automatic access to backup servers to minimise downtime, and host apps on at least two servers in case of hardware failure. Few, if any on-premise data centres, can offer anywhere near these levels of reliability and availability without incurring huge cost.

Maintaining and increasing cybersecurity

Working with a trusted IT partner will enable you to audit your cyber security, ensure your resources (both in-house and out-sourced) are aligned to the real-world risks and your in-house cyber security team is focused on core risk-management activity.

With a recession looming and budgets being squeezed, IT leaders face a huge challenge, and they can’t do it alone. The answer is to reach out to a third-party IT provider and explore the benefits, cost efficiencies and opportunities that a sensitive mix of out-sourcing can deliver.

Contact Intercity now to find out how they can help your IT function prepare for the recession.

Education Industry, Hybrid Laptops, IT Management

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Data-driven supply chains continues to be a hot topic, given what’s happened over the last couple of years with the pandemic, lockdowns, transportation woes, container ships held outside ports, war in Ukraine and other issues wreaking havoc. Problems caused by these events are ongoing, but if addressed from a proactive rather than reactive standpoint, there are ways to mitigate their detrimental impact, especially when the analytics and processes become clear.

“What we’re seeing with clients, as we focus on a data-driven supply chain, is enabling data-backed decisions at all levels of the organization,” says Singleton. “Historically, supply chains have been slow to adopt technologies and analytics, but great strides have been made to upgrade systems to capture critical data in the supply chain. Now the question is how to return all of the data we have into transforming and enabling our people to make decisions—backed by that data—to create a proactive supply chain versus a reactive one to market conditions.”

Anticipating supply chain issues rather than responding to them is also a principal means to give companies an advantage over their competitors in terms of not only being able to access an increased amount of data, but having the means to effectively utilize that data in a customized and targeted way.

“Data in general has been exploding for years in all facets and all verticals,” says Abel. “And in the area of supply chain in particular, given the challenges of the pandemic, wars, chipageddon and everything else, the ability to leverage that data and create transparency up and down your entire supply chain, and run analytics on it, is the game changer now occurring.”

But when such compound disruption occurs, creating a battle on many fronts, that’s when the analytics and data become even more important because managing multiple crises at different points of the supply chain requires a more refined, targeted and accurate approach than wielding a blunt object. The ultimate goal is to eliminate the climate for crises before they happen in the first place, but the common denominator is talent and getting the right people in place who are equipped to find answers.

“We tend to focus on the technology, which generally relates to databases, BI and analytic solutions,” says Patel. “All of those things are fairly mature and available, and many companies have implemented them over the years. So we have good technology available and we want to use it effectively. But when we look at supply chain, a lot of data tends to be disparate, and getting that collected in one location or connected so you can do these deeper analytics and visualization across all of those data sets is a hard problem to solve. The people side of things is the hardest element. Far too many people are used to reports, dashboards and doing the basics and I think we need to raise the level of understanding of data and then help them with experts who can answer the hard questions.”

Abel, Patel and Singleton recently spoke with Ken Mingis, executive editor of Computerworld and host of the IDG Tech(talk) podcast, about organizational advantages realized through the data-driven supply chain, and enabling the right people to interpret that data to make more informed decisions.

Here are some edited excerpts of that conversation. Watch the full video below for more insights.

John Abel

John Abel on data management: Supply chain planning has been around forever. I know my role. I’m used to the rearview-looking aspect. Some don’t know the art of the possible or the potential there is, so it’s not that they don’t know what to do with it, but there’s no one on their team with the skill set to create the art of the possible.

So it’s bringing the skill sets into the organization in order to create. That’s where most companies are currently lagging. It’s going beyond the traditional view that supply chain professionals had of just delivering outcomes based on traditional KPIs. So going beyond that and combining traditional supply chain for information with customer data or with usage, or with customer experience, that’s when you start understanding what plays into your ecosystem of delivering better outcomes that bring top-line revenue or bottom-line cost reduction.

Those are the outcomes, ultimately, that drive most organizations. The one key thing is, if you haven’t already begun on this journey, starting sooner rather than later is key. Just look at the available data and understand that. Then arm yourself with the right talent to understand your ecosystem and how you get the right outcomes.

Manesh Patel

Manesh Patel on handling expectations: One thing many companies did was manage their supply chains in a standard capability. If we think about MRP, communicating downstream to suppliers and vendors and so on, that’s a complex problem statement in the first place. And I think just doing the day-to-day, week-to-week sort of processes was onerous in the first place and a lot of companies were focused on that.

Then with the pandemic, we all started to react and handle these exceptions, which are much harder to do because they’re all different. And I think we’ve become more adept at addressing those exceptions in the last three years. We still have a long way to go though. Grasping those exceptions has become very critical and one thing we’ve realized is this is not a one-off thing. Whether for a war, climate or something else, it is a reality of our future.

Erik Singleton

Erik Singleton on data literacy: A warehouse supervisor before might have looked at a dock or floor and said, “Okay, I’m doing good for the day.” But now they can see key metrics and concrete UPHs or KPIs. But how do they action on that? Just having the data is not enough. It’s teaching your people to think with a data mindset and really get them articulate, interpret and analyze data that has a meaningful impact. So there are so many components of just integrating, but then it’s also empowering people to use the information they have.

John Abel on data volume: Data volumes are growing everywhere. The good news is the technology side can handle that. We’re able to process and select large amounts of data but the reality is that people are getting overwhelmed. So how do you turn massive recent explosions in data into value, and what are the analytics you use?

One use case is we’re helping a customer in the sporting world by outfitting stadiums with networking devices to get huge amounts of data and give analytics back, which then they can turn into more value for their customers. The people who can look at the volumes coming in, parse it down and turn it into value are a unique skill set and hard to come by. It’s really about taking large amounts of data in your ecosystem and beyond your ecosystem, and finding what value you can drive by using analytics.

Supply Chain

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The headlines read “Artificial Intelligence (AI) will completely transform your business.” But does the hype match the reality? We have been seeing these exclamations for two decades, but where are the examples? Where are the success stories? Is AI really a game changer, and does it actually apply to my business?

Every ten years it seems there is a new technology that is going to change the world, but all too often only leads to disappointment when adopting it becomes too challenging. For several decades this has been the story behind Artificial Intelligence and Machine Learning.

However, we have now reached a tipping point with AI where the compute capacity, ubiquitous connectivity, and wealth of data can match the moment and assist business leaders to create unique competitive advantages by better serving customers, improving processes, enhancing employee experience, or reducing costs. As Andy Jassy, CEO of Amazon, said, “Most applications, in the fullness of time, will be infused in some way with machine learning and artificial intelligence.”

As I advise in my presentation “Building a Smarter Organization Powered by Machine Learning” there are three key focus areas successful organizations master to get value from AI: Mindset, Skillset, Toolset. This creates a flywheel we call The Data Network Effect, where you acquire more data, which helps create better algorithms, which drives better engagement, ultimately leading to happier customers, which then generates more data, and so on, and so on. This process then repeats, improving and generating more value with each cycle.

While some companies are already benefiting from this transformative impact of AI, we see others struggling. There is often confusion at the management level about the applicability and impact of AI, leaving business leaders to struggle to find the right use cases to prioritize. Additionally, navigating existing AI resources reveals a great deal of highly technical information but little in the way of business impact examples and guidance. Until now, a comprehensive list of AI and ML use cases that serve as meaningful references for business leaders simply did not exist.

The bottom line: Most companies know they need AI but have not found the answer to “where do I start?” In this blog post, I will share five actions you can take to move beyond the buzzwords and make your AI-driven digital transformation a reality that will shape your organization’s future.

Be clear on the “why”

Do not just implement AI so you can check it off your list. AI should be used to support your business strategy not be your business strategy. Do not fall victim to the analogy of “a hammer in search of a nail, that only winds up pounding in screws everywhere.” Instead evaluate your business opportunities or problems and then determine if AI is the right tool for the job.

Get alignment from your stakeholders

I always told my team and customers that long-term success with AI solutions is driven by people, not technology. As you begin to work with various stakeholders on your initiative, ensure you are effectively and continuously collaborating with them. Structure your strategy discussions around the four key areas: business, finance, technology, and science, and encourage stakeholders in those areas to weigh in on your AI project decisions.

It is also important to develop an organizational culture that empowers people across business and technical roles to become involved with your AI. Our customers who have successfully rolled out these initiatives have one thing in common: they embraced the culture of continuous process evolution and had champions who brought teams across the organization together. Creating a culture that excels in change management, celebrates failure as learning, promotes new skills acquisition, and fosters collaboration is a great way to propel your organization in this direction.

Explore what is possible with AI and get started

To help you get started, AWS has just launched the AI Use Case Explorer, a complimentary, interactive guide for business leaders and AI practitioners to conceptualize and build their applications.

With over 100 use cases and sub use cases and 400 customer success stories, this tool can help you quickly identify the right use case to get started based on your industry, function, and desired business outcome. Once you have identified your use cases, you can read about success stories from around the world and kickstart your deployment, from proof-of-concept to full production, by following an expert-curated action plan provided for your specific use case.

Do not boil the ocean … we tried that … it did not work

As an industry, we have learned hard lessons from trying to deploy monolithic data warehouses, business intelligence implementations, and analytics solutions by gathering, cleaning, and preparing tremendous swaths of data from across the entire enterprise. This delayed value, increased cost, raised complexity, and ultimately failed to deliver. Instead, focus on gathering the data specific to the use case you are implementing, and drive quickly through proof-of-concept to production and value. Then move on to the next use case and do the same thing again, expanding your data assets as needed.

Technology is not the objective, it is the enabler

True value does not come from just using a new technology, but rather from using new technology to reimagine existing processes. As you look to implement your AI project go beyond just creating an AI-enabled twin of your existing process, and instead reimagine the process using the new capabilities of AI.

As AI transforms the way we live and work, from optimizing business processes to personalizing content for consumers, I am excited about all of the innovative and impactful AI applications that can assist businesses as well as individuals in the coming years. The possibilities are endless! I invite you to check out the AI Use Case Explorer site and explore your organization’s unique path to AI success.

ABOUT THE AUTHOR:

Tom Godden is an Enterprise Strategist and Evangelist at Amazon Web Services (AWS). Prior to AWS, Tom was the Chief Information Officer for Foundation Medicine where he helped build the world’s leading, FDA regulated, cancer genomics diagnostic, research, and patient outcomes platform to improve outcomes and inform next-generation precision medicine. Previously, Tom held multiple senior technology leadership roles at Wolters Kluwer in Alphen aan den Rijn Netherlands and has over 17 years in the healthcare and life sciences industry. Tom has a Bachelor’s degree from Arizona State University.

Artificial Intelligence

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Service level agreements (SLAs) have long been the standard operational metrics for technology services, measuring performance in areas such as systems availability or resolution time. But a new approach to gauging IT performance has begun to take hold in organizations where ensuring an optimal customer experience has become paramount.

Experience level agreements — XLAs, for short — go beyond traditional IT SLAs to focus on the end customer experience, tracking measurements such as customer or user satisfaction and sentiment. In an era marked by a laser focus on customer-centricity and increasingly digitized interactions, there is a need for key performance indicators directly correlated with the quality of the experience instead of simply the performance of the technology that underpins them.

“Organizations are increasingly using XLAs,” says Sameer Bhagwat, vice president and head of the Applications Managed Services Center of Excellence at Capgemini Americas. “The shift to the digital economy accelerated the adoption of XLAs as companies have been eager to gain better insights into the customer experience.”

IT outsourcing providers were the first to make a shift toward experience-based performance metrics, incorporating quantitative and qualitative data to measure service outcomes and user experience. But the XLA approach can be valuable for CIOs eager to communicate the business value of what IT contributes to the organization. 

“IT leaders often get consumed with details that are important, but hard to consume,” says Rahul Mahna, managing director of managed security services at EisnerAmper. Metrics such as the number of incident tickets or trends in systems alerts or alarms may be meaningful within IT, but can be largely noise to those working outside the walls of IT.

“We find it better to position IT as solutions that enable the business to operate and support the goals of the firm,” Mahna says. “Positioning an IT department as a key component of all management functions that are strategic in nature can produce far better results in maintaining the IT organization through difficult time periods.”

The evolution from SLAs to XLAs

SLAs have reigned supreme in measuring IT performance for decades. And they were largely sufficient for what was, for a period of time, a back-office function. “Historically, IT teams operated separately from business users and established their own set of SLAs primarily focused on IT metrics such as availability and resolution time,” Bhagwat explains.

With the shifts in customer and employee digital needs, attitudes, and behaviors, a siloed approach to IT performance management no longer makes sense. Traditional SLAs provide little insight into business performance or user satisfaction. With technology now intrinsic to the end user experience, IT metrics should evolve to reflect that.

“This is where XLAs come into the picture,” Bhagwat says, adding that they can be a key foundation for changing how the business value of IT is measured and reported across an organization.

In addition, XLAs “provide an incentive for all of the parties involved — internal groups and outside vendors — to cooperate and do the right thing for the business to achieve the rewards and not just suboptimize the end-to-end process to optimize the portion of the process they are responsible for,” says Andy Sealock, senior partner in the advisory and transformation practice at West Monroe.

A measured approach to customer-centricity

Knowing the value of XLAs is one thing; being able to devise, measure, and track them is another. With decades of reliance on traditional SLAs, it can be challenging to rethink IT performance in this potential abstract way.

Still, it’s very much possible to measure experience for both external customers and internal users of IT systems. And with employee experience proving to be an important driver of overall business performance, it’s fast becoming essential to do so. The vast majority (85%) of respondents to a recent IDC survey said that improved employee experience and engagement lead to a better customer experience, higher customer satisfaction, and increased revenues.

External XLAs tend to align with key business goals related to customer engagement, customer retention, and conversion rates. Internal XLAs more likely center around employee satisfaction scores, response times, adoption, or engagement. Rather than measure uptime of enterprise applications alone, an organization might track employee satisfaction with the remote work experience. Another XLA might focus on optimizing the employee onboarding process to ensure employees can hit the ground running on day one.

“Internal service management tools can be used to track XLA performance,” explains Bhagwat. “IT leaders can then use XLAs to have a pulse on the user experience and overall customer satisfaction.”

In most situations, XLAs will not replace SLAs, but complement them to provide a more complete picture of customer or user experiences — and IT’s contribution to them.

“SLAs should be retained even if XLAs are introduced, in part because without SLAs an organization will lose important visibility into operational performance and the direction that can provide towards root-causing issues,” says West Monroe’s Sealock.

XLA best practices

XLAs are, by definition, boundary crossers, cutting across functions, processes, and technologies. “Removing the siloes between business and IT is one of the challenges in implementing XLAs,” says Capgemini’s Bhagwat.

Other issues include determining who owns the XLA, defining which metrics are the most meaningful to organizational success, establishing a change management plan to ensure XLA adoption and acceptance, and creating a robust XLA enforcement plan.

To address these and other issues, organizations seeking to implement XLAs should heed the following best practices:

Establish clear responsibility and accountability. In many cases, a business function such as marketing or HR may own the metrics associated with an XLA, but IT must have a seat at the table and work closely with business stakeholders on expected outcomes and potential issues.

“These past two years have consistently proven that there’s no longer a separation between IT and the business,” Bhagwat says. “The two functions must work together for an organization to thrive in today’s evolved experience economy.

Map the user journey. By charting out user journeys through IT services and solutions, organizations can identify various user types and needs, uncover key pain points, identify gaps in services, and create a baseline for improvement and optimization.

Focus on meaningful metrics. Settling on metrics that best represent the desired outcome can be tricky. They need to both “represent tangible value generation for the business and be clearly and directly — even though not completely — driven by the performance of the parties,” Sealock says.

Be transparent. Experience data should be shared widely and often among teams, employees, and external partners. This creates greater visibility into issues and encourages greater collaboration.

Emphasize carrots, not sticks. When working with external parties in particular, it’s beneficial to set up gainsharing or other rewards for XLA achievements rather than punishment for XLAs misses.

“We have seen XLAs used most effectively when they are structured as a reward to the participating vendors for the achievement of business objectives, not as penalties for not achieving business objectives,” Sealock says. “The problem with the latter scenario is that few, if any, vendors are willing to take on the financial liability of incurring penalties for outcomes that are outside of their direct control.”

Get IT staff on board. SLAs are familiar to IT veterans. They remain the gold standard for measuring technical performance. While the IT organization should understand that SLAs are not going away, IT professionals will need to be brought up to speed and on board with XLAs. Ensuring a successful shift will require IT leaders to invest in evolving IT’s mindset toward continuously measuring and improving the user experience, in addition to ensuring availability and issue resolution.

Digital Transformation, Employee Experience, IT Leadership, ROI and Metrics