One significant application is automation, which IBM defines as “the use of technology to perform tasks where human input is minimized.” This is particularly appealing to IT teams and the C-suite for several reasons.

Why automate?

Automation enhances IT delivery by automating manual processes that traditionally required human input. It also enables organizations to gain observability over their infrastructure, applications, and devices, facilitating improved content processing and management; workflow streamlining; data-driven decision-making; cost optimization; network performance enhancement; and proactive incident management.

Perhaps the most desired benefit is this last one: self-healing. As IT leaders take a more prominent role in the boardroom and face increasing scrutiny around digital transformation efforts–efforts that profoundly impact how business value is created and delivered–self-healing brings countless advantages.

It can reduce unplanned outages and eliminate performance issues from user journeys, elevating the customer experience. It can help businesses overcome forecasting challenges, optimizing resources to cut software and infrastructure overcapacity. And it can drive the development of higher-quality applications, reducing testing needs so organizations can bring products to market faster.

However, the path to self-healing isn’t as simple as installing an automation solution and waiting for something to happen, as presumed by many–who are then disappointed in the process when it doesn’t work as planned. To reach an optimum level of maturity and realize their goals, companies should ensure several key elements in the automation process are secured and understood.

It starts and ends with data

Automation is not only a result of AI but also a driver. Any intelligent tech is only as smart as the data you feed it, and to maximize its potential, this data must have clarity, integrity, and fidelity. Plus, it must be fully extracted across all your domains–from your infrastructure and networks to your apps and logs–to build a complete picture and accurate machine-learning model. After all, correlation based on incorrect or fragmented data is nothing more than coincidence.

Take, for example, the financial management apps currently growing in popularity. These connect to your mobile banking accounts and give insight into what you’re spending, where and when. If, let’s say, you have a current account, savings account, and debit and credit cards, it’s critical the app pulls in data from each of these to provide the whole reality of your expenses and lifestyle. Then, you can see what can be improved upon and which spending habits need to change.

This may seem unwelcome news, as so many organizations battle legacy systems that can’t communicate with each other and disparate data stored in silos. Ironically, the ultimate outcome of automation–observability–needs to be present to begin with to unify this fragmented data and get outdated tech talking. Luckily, there are solutions on the market, like Riverbed’s unified observability portfolio, which can do exactly this while unlocking all the advantages of automation.

Building a baseline

The first step on any business’s journey to self-healing is harvesting quality data, and plenty of it. Next, it’s imperative to set a baseline to understand and record what’s usual across systems and devices, so anomalies can be identified and addressed. It’s akin to going to the doctor for a blood test; without keeping accurate and timely medical records, all they could tell you was whether they’d found anything of note in that one particular sample, regardless of how well or unwell you were feeling. By examining your record and taking samples over time, healthcare professionals can detect deviations in data points, identifying if anything is amiss based on your unique baseline. They seek out one-off or recurring problems and prescribe medication to get you back to full health.

A baseline tends to be established based on mathematical machine-learning formulas, which aren’t one-size-fits-all. Application data, network data, end-user data and infrastructure data are all different, and should be treated and tracked as such. That’s why, for over 20 years, Riverbed has carried out packet analysis that gives us the flexibility to use the best formulas and data science in the best possible places, driving the incident correlations businesses need.

Next stop: self-healing

Once an effective baseline is established, automation can finally start. But to automate the healing process, businesses must first automate the detection process, introducing scripts that alert to incidents and where they’re coming from. This helps avoid false positives and human errors while allowing for the correlation of individual issues, identifying bigger problems and their roots to accelerate mean time to detect (MTTD) or mean time to know (MTTK). Then, finally, the self-healing process can begin.

After streamlining data collection, baseline setting, and incident detection and correlation, most of the hard work is done. Now, automation scripts can be used to speed up mean time to fix (MTTF) or mean time to repair (MTTR)–addressing situations before users complain and driving ongoing optimizations.

In summary, to receive the highest quality output from any automation system, it’s vital that businesses take the time and make the investment to give AI models the greatest possible input. Businesses must prioritize comprehensive problem management and continuous system feedback to achieve reliable self-healing capabilities.

Do you have the robust data and effective machine-learning mechanism you need to achieve foolproof self-healing? If not, Riverbed can help. Get in touch with us today to learn how.

To remain relevant, win new customers, and increase revenue streams, banks must redefine all they know. That means maintaining and modernizing core internal processes, ramping up digitalization to meet changing customer expectations and increase profitability. Read on to discover how banks can combine data, insights, and actions to run operations more efficiently, enabling faster, more effective decision-making that drives transformational initiatives to improve the omni-channel experience for employees and customers—all powered by Riverbed Unified Onservability.

Reimagine your banking systems—and run your bank better

The technology that quite literally puts banking in consumers’ hands also threatens the traditional banking models. To realize the full potential of their banking systems–reducing errors, improving application performance, and making staff more effective–these firms must reinvigorate branches and refine the services they deliver.

Primarily, this involves removing barriers between tellers and customers, introducing self-service kiosks, and supercharging their online and mobile offerings. However, a reliance on tech requires systems to operate as smoothly and reliably as possible. This is challenging when faced with huge volumes of data and legacy infrastructure that anchor banks to the past instead of propelling them into the present.

Thanks to unified observability’s automated remediation and self-healing capabilities, banks can easily resolve problems across their entire architecture before customers notice a disruption, thereby safeguarding the business’s reputation and building all-important trust among consumers. In fact, one of our clients used these tools to proactively reduce their support tickets by 20-30% a month.

By detecting and fixing problems faster, banks can achieve strategic optimizations, increase efficiencies, accelerate mean time to repair, and reduce time spent on non-critical issues. What’s more, they can eliminate alert fatigue, significantly reducing the number of notifications staff must go through, thereby lowering stress levels and turnover rates. This is critical during a time of talent and skills shortages.

Banks can use unified observability to simplify their setup, streamline operations and directly cut costs, too, by identifying under-utilized tech and optimizing networks, devices, and apps that are relied on the most. Another Riverbed client saved an estimated £600,000 on each application they examined using our technology. One more bank found they could avoid a $16M upgrade by maximizing the hardware they already had.

Reimagine modernization—and change your bank faster

Today’s consumers crave convenience, generally favoring the digital banking experience only apps and online portals can provide. However, even as banks’ physical footprints shrink, the in-person experience is still crucial and shouldn’t be underestimated.

With unified observability, banks can empower the in-branch experience by providing live reporting of ATMs and colleague operations, the same automated remediation tools mentioned earlier, change validation, and more. A banking client of ours found their remaining branches were working disparately, delivering different levels of teller service in each location. Using our tools, they could identify this and stabilize the situation to offer one consistent experience. Another went from having 1,000 employees working from home to 22,000 in a mere four weeks. They used our platform to gain visibility on who was working where and when and see which offices they could close–reducing costs without losing productivity.

As consumers navigate between online, mobile banking and physical branch, contact center or ATM visits, it’s vital that banks create a tech environment where each interaction is efficient and fit for future-ready, customer-centric, omni-channel banking. Unified observability platforms ensure that every app, across every device, within every channel consistently delivers and exceeds the level of service necessary to drive business, rather than hinder it.

Reimagine the banking journey—and perfect the experience

Banks must optimize every customer touchpoint, whatever their requirement, moving from transactional to transformational and ensuring exceptional experiences. This means empowering their staff to unlock new revenue opportunities and improve customer support, with AI-driven end-to-end visibility across the omni-channel experience.

Unified observability allows organizations to transform disparate data into intelligent user insights, making these the driving force behind increased revenue streams. Many of our clients focus heavily on digital experience improvement, utilizing unified observability to identify potential upgrades to networks and devices, compare employee experiences and productivity levels, and track how satisfied each business unit is before, during, and after implementing changes, such as new software versions.

Reimagine security and sustainability—to adapt to the future

Increasing dependence on the cloud, SaaS, and shadow IT, along with the permanent shift to hybrid work, is evolving the regulatory landscape and expanding the range of security and compliance threats within the banking industry. Meanwhile, banks must meet stringent regulations to operate legally, maintain financial stability, manage risks effectively, protect their reputation, and build trust among customers and stakeholders.

We use our unified observability technology to help businesses build brand strength, underpinned by monitoring performance. They can ensure compliance and identify and address vulnerabilities simply and innovatively, by modernizing existing core banking applications with artificial intelligence and automation, transforming branch networks, adding governance and control tools, and basing decisions on essential data. Our solutions can audit app usage and even capture and store every packet and flow, aiding in threat-hunting investigations and analysis into suspicious network behavior.

As well as being security-conscious, today’s banks are increasingly focused on sustainability to stay relevant in a world where consumer loyalty is fleeting and making a difference to the planet means more than making a profit.

Unified observability can support sustainability strategies and guide banks on their path to net zero in many ways. One way it helps is by identifying devices and infrastructure with high energy consumption, alerting staff to the resource they’re using and reminding them to power down while their devices are idle. It can even remotely turn off energy-draining hardware, like laptops, when not in action.

Experience the future

By fusing data, insights, and actions, Riverbed helps banks enable faster, more effective decision-making and continuously improve the omni-channel experience for employees and customers. Get in touch today to learn more about how our unified observability solutions can empower you to unlock the future of banking, where experience is everything.

Mildly annoyed, you finish your shop and head to the checkout. It takes you three more seconds than usual to grab that barcode and complete your transaction. No big deal, right?

Wrong. As you walk away, a queue of 10 customers forms behind you, each taking those three extra seconds swiping to their barcodes. That’s 30 seconds added to the cashier’s processing time. Multiply it by the 1,000 shoppers the store might see in an hour, and an entire 50 minutes is wasted.

At head office, the IT team’s high-fiving. The update’s rolled out, the interface looks fantastic, and everything’s running as planned. If only they knew what was going on for the employees and customers actually using their app.

And they could, had they implemented XLAs.

What are XLAs?

As their name suggests, experience-level agreements (XLAs, sometimes known as ELAs) are a variation of service-level agreements (SLAs) that focus on the end-user experience. Whether that end-user is your employees, your customers, or both, the way they engage with–and feel about–your solution is critical.

And XLAs aren’t simply an exercise in gathering sentiment. The most effective agreements combine the telemetry of your service with the feedback you receive on it and the emotional impact of it.

Essentially, you must ask yourself three questions: how reliable is my service? How well does it perform? And how do my users perceive it?

Why are XLAs important?

So, you’ve got performance management software, and you’ve set telemetry SLAs that are always met. Your IT team knows what it’s doing, and it makes sure your users can access the systems they need, when they need them. But does it know what’s going wrong once those users get into those systems, and what’s going right?

You obviously can’t ask every single employee and every individual customer how they’re feeling. Still, you can give them a platform for their thoughts–then combine this with your telemetry data to find trends, remedy issues, and make the people you serve happier and more productive.

This combination is key. Because if your employees consistently and collectively rate one of your systems negatively, you may assume it’s because it isn’t working to standard–when in reality, it’s just taking everyone too long or requiring too much effort to do what they need to get done.

It’s all about shifting your IT experts’ mindsets to journey-based services rather than services that perform their function and nothing more. It’s about considering the time it takes people to access the systems they need, how the platform looks and feels to use, and what behaviors users display.

It’s about having the data-based insight to make informed decisions on prioritizing investments, identifying skills gaps, and improving policies and processes. And it’s about adding the relevant shortcut if it takes 10,000 clicks to process an order.

How can I implement XLAs?

The good news is that there are digital experience, which can gather all the information you need– qualitative and quantitative–in one easy-to-find, simple-to-interpret dashboard.

Aternity’s sentiments capability goes beyond basic surveys, allowing you to use human-defined or department-agreed thresholds to establish what a positive end-user experience looks like for your business and your service at a granular level. For example, completing a process in three seconds might feel too slow for some users, too fast for others, and perfect for a few.

Not only can tools like Aternity flag specific issues like this, but they can also measure input across every stage of the delivery chain. Think telemetry data from your entire IT platform, feedback from your employees, sentiments from your customers, and everything in between.

So, you get a complete picture of how different elements perform in different scenarios throughout different journeys for different people–and what those people would ideally like you to do about it. And sometimes, it’s an action as small as moving your loyalty app’s barcode back to where it used to be.

In today’s increasingly digital, ever-demanding world, speedy response times and slick branding aren’t enough. To achieve your goals, stay competitive, keep your employees, and satisfy your customers, you need to transform and innovate. All based on authentic user experiences rather than IT’s assumed outcomes.

XLAs are one powerful metric that can empower you to do exactly that. Get in touch with us today and discover solutions that assess not just how well your systems are working, but how well they’re working for the people that matter.

So, what does sustainability mean for your FSI business, and how can you navigate the stringent environmental, social, and governance (ESG) goals you’ve set? Riverbed Solutions Engineer, Jaspreet Sandhu, sheds light on this in our video on the topic: “Sustainability is all about balancing the needs of our people, planet, and profit to succeed both environmentally and financially.”

Sustainability is a top priority for businesses worldwide. A recent report by Forrester reveals that 51% of the Fortune Global 200 have set carbon-neutral or net-zero aims. Despite this commitment, many are struggling to get there, as data accuracy creates the biggest obstacle in ESG reporting.

To help overcome these hurdles, the suite from Riverbed empowers FSI organizations to:

• Satisfy stakeholders with exceptional digital experiences.
• Protect the planet with energy-saving functionality.
• Save money while aligning with stakeholder expectations.

Scaling hardware and software to cut e-waste (and cost)

With siloed systems and disparate data, it can be hard to get a full picture of what hardware and software are being used the most, least, and not at all within your FSI business. Industry-leading unified observability tools like the suite from Riverbed gather and correlate large amounts of granular data on machine and license usage from internal and external sources–everything from employee PCs to ATMs.

They then transform this into actionable insights and workflow automation to drive effective decision-making, allowing you to end licenses that aren’t needed and recycle or remove hardware nobody would miss. This can add up to an enormous saving in both physical and carbon footprint. After all, data centers alone account for almost 4% of the entire world’s energy usage (and no doubt cost you a fair amount to manage).

One success story comes from Tate & Lyle, realizing substantial savings by using Riverbed Aternity. By freeing up expensive, unused software licenses, the company can now allocate the correct number to its user community, delivering excellent return on investment.

Replacing machines based on performance, not time

If you have a policy of replacing hardware every two, three, four, or five years, the chances are you’re getting rid of machines that don’t need updating or upgrading yet–and dealing with lag and blue-screening from some that may be ready to retire earlier, leading to productivity losses and employee dissatisfaction. By deploying Riverbed , you can access up-to-the-minute insights and predictions on the performance of every single device in your fleet, displayed in easy-to-read dashboards–enabling you to replace hardware based on how much life it has left in it, rather than how long its life has been.

Riverbed Aternity allowed Kent Community Health NHS Foundation Trust’s IT team to make better-informed decisions about their investments in this way. “We have revised our asset refresh plan based on device performance,” says Darren Spinks, Head of IT Operations at the trust. “Aternity showed us we wouldn’t need to replace 42% of our 1784 devices aged five years or older. This has meant that we have already returned our investment in Riverbed Aternity.”

The UK team at Energy firm EDF uses Aternity in a similar way. Donna Lloyd, the company’s Senior Enterprise Manager of Platforms & Enablement, elaborates: “When we upgraded to Windows 10, we looked across our estate to see where our slowest machines were, so we could target those replacements first. When we replaced them, we used performance statistics to assess and demonstrate the positive impact.”

Resolving problems before they even begin

Another multifaceted benefit of using a platform like Riverbed is being able to proactively resolve issues, saving time, money, and a whole lot of stress.

Coming back to the Kent Community Health NHS Foundations Trust, the Aternity solution provides the organization with auto-remediation actions. These reduce service desk calls and automatically resolve IT-related problems–before users even become aware there’s an issue. What’s more, the IT team can monitor the power consumption of its endpoints and adjust energy usage accordingly to help reduce its carbon footprint. This supports the NHS’s sustainability agenda of becoming the world’s first net-zero carbon health service.

Reminding staff to power down from afar

One sneaky way energy peaks (and bills) can creep up on you is when staff spend time away from their PCs or laptops without shutting down. And one small-but-mighty way Riverbed can help is by monitoring device usage, then sending those employees alerts when it’s time to power off–for example, when they’re heading for lunch or winding down for the day. If they ignore these notifications, Riverbed can even allow you to shut their machines down remotely, so you can be a sustainability hero from afar.

Keeping a general eye on your carbon footprint

In conclusion, Riverbed has many features and functions that can help you improve sustainability by simply being more aware of what’s going on in your business, knowing what you can do about it, and having the power to take those steps.

The Princess Alexandra Hospital NHS Trust implemented Aternity with the aim of cutting costs and its carbon footprint. Not only is the organization projected to save £2.5 to £3 million over a five-year period–it’s also able to interrogate data more intelligently and see where general improvements can be made, leading to sustainability wins across the board.

Jeffrey Wood, Deputy Director of ICT at the trust, says, “We now have a single source of truth for clinician experience, improved application performance, reduced ICT spend and at the same time we have reduced our carbon footprint. Riverbed Aternity has exceeded my expectations on all fronts.”

We’ve specially collated a dedicated sustainability resource page for companies like yours, which you can visit here. Once you’ve explored it, get in touch with our team, and let’s talk about your FSI organization’s specific, unique ESG goals–as well as how we can empower you to meet and even exceed them.

It’s hardly news that AI is the hottest trend in the tech world. Most of us have dabbled with ChatGPT, become a designer for the day using Midjourney, or taken advantage of the many applications we hardly even consider artificial intelligence–from unlocking our phone with our face to performing a smart Google search.

But having just attended and exhibited at the Gartner IT Symposium in Barcelona, where there was a huge gathering of CIOs and IT executives, it’s clear that AI is revolutionizing the digital sphere in more ways than we could have imagined. And with that comes new opportunities and new risks. Here are some of the things we discovered about AI at the event.

AI is changing the game, and our everyday

If you’re familiar with Gartner, you’ll know about their Hype Cycle methodology. As it says on the Gartner website, ‘clients use Hype Cycles to get educated about the promise of an emerging technology within the context of their industry and individual appetite for risk.’ Gartner has curated several Hype Cycle iterations around AI, including generative AI: the technology that powers the likes of the aforementioned ChatGPT.

The organization’s research has shown four primary use cases for AI:

• Everyday Internal use in a company’s back office
• Everyday External use in the front office
• Game-changing External use, helping businesses become more forward-looking via innovative products and services
• Game-changing Internal use, supporting arduous regular activities and boosting core capabilities.

According to Gartner, it’s critical that companies start considering where they want to be as an organization–and, therefore, where they’d like to use AI. Because when you know the use case, or use cases, that would align with your business’s future strategy and goals, you can apply the technology more effectively and gain the biggest return on your investment.

At Riverbed, we use AI in our unified observability solutions across all four use cases. We provide our partners with scripted automation and proactive issue detection and remediation, both internally and externally, so they can have greater control and productivity in their everyday. And we offer customer and employee journey analysis, looking at behaviors and trends to drive innovation–including product releases–so they can change the game in their industry.

AI works best when you’re open

As well as AI, digital experience management (DEM) was named one of the top five areas organizations should be focusing on – and an area that AI can help accelerate and enhance. We’re an expert in this field, and as we’ve already touched upon, unified observability solutions like ours can empower companies to better understand their employees and customers, improving their experiences using data-driven insight instead of guesswork. But did you know Riverbed’s platforms are open, seamlessly integrating with any IT setup and infrastructure to complement and enhance–not replace–third-party tools a business has already deployed? Attendees who came to our stand at the Gartner Symposium were particularly impressed with this.

One visitor commented, “I’m procuring an APM solution right now. When I found out you could integrate with it, I felt relief that my decision won’t impact the results I can achieve with Riverbed.” Another added, “Riverbed can help me capitalize on and protect my investments, which is important to me and my business.” For us, offering an Open Suite means being able to leverage open APIs to collect or feed data and telemetry from/to third-party tools. This is achieved through the adept use of AI and ML capabilities, resulting in actionable insights. By integrating emerging technologies and tools, we provide our clients with the reliability, resilience, remediation, and more necessary to deliver exceptional experiences to their customers.

AI is creating regulatory conundrums

Imagine a world where you can open a bank account, claim benefits, secure a new job, or access healthcare at the swipe of a screen. Or how about a future where you go to buy an item of clothing online, and the company already knows all your measurements, so every garment you purchase is crafted to be a perfect fit? While this may sound futuristic, fun, and functional–removing the prospect of the tedious returns process–it’s terrifying to consider how much data would need to be gathered, stored, and shared about you for this to happen.

For this reason, the government will need to play a major role in operational excellence, citizen engagement, and driving outcomes. The government will need to regulate the use of AI and will have to play major roles in Identity Use Cases: Identity for Compliance, Identity for Personalization, Identity for Fraud Detection and more. Double down on some of the use cases, they must facilitate confidentiality and compliance for people to feel confident engaging with these new ways of living and working. To that point, behavioral and customer analytics solutions–like the ones Riverbed can provide will add extreme value in better understanding and benchmarking User Behaviors, Journey, Sentiment and Experience. Ultimately, we’re about to see the birth of a new era of AI data culture and security, and we’re ready for it.

AI is only as good as what it’s given (for now)

While AI is already starting to help us in our daily lives, you only have to give Midjourney or DALL·E 3 a few prompts to see that they’re not foolproof (why do the hands always look so strange?). There are many reasons these models aren’t quite clever enough to outsmart us yet – and one of those is that, for now, the tech is only as intelligent as the information it’s given.

That’s where reinforcement learning through human feedback (RLHF) comes in. The RLHF approach involves creating a machine-learning model and continuing to educate it by asking for human input. This could mean, for example, getting people to score an AI chatbot’s response using various criteria. How funny was the chatbot? How natural sounding? How informative?

The ‘reinforcement learning’ (RL) part means AI agents are trained on reward and punishment mechanisms. So, they’re rewarded for correct moves, punished for wrong ones, and therefore incentivized to hit the mark every single time.

Then, onto the ‘human feedback’ bit. This is where real-life annotators compare various outputs from the AI agent and pick those they prefer–essentially, responses that are closer to the intended goal. By combining the elements of traditional RL and plenty of input from us, AI will evolve, eventually completing tasks with perfect performance.

AI is all about the human-machine relationship

It’s a tale that’s been told in endless sci-fi movies for countless years: humans want to be more like computers, while computers want to be more human. In truth, it’s the relationship between mortal and machine we need to get right so we can both progress. Soon, for example, there’ll be a machine-customer market, where robots can purchase consumables for themselves so they can operate for us to the best of their ability. It’s vital that CIOs own these new relationships, having awareness and influence over AI-ready principles, data, and security.

At Riverbed, we like to keep things interactive–so on our stand at Gartner Symposium, we hosted two games, our own branded Pac-Man game and golf putting. One customer, while playing golf and scoring well, commented that they’d never even been on a ‘green’. They then joked that in the future, they’d likely be able to download software to their brain and learn everything they needed to achieve like this in any new sport.

But was this statement a joke, or could it be an accurate prediction?API If Gartner’s insights are anything to go by, we could be looking at the latter.

To learn more about how Riverbed’s solutions use AI to proactively predict and remedy issues, build useful shortcuts, save companies time and money, and give customers the experiences they’ve come to expect, chat to us today.