Ensuring a Superior Digital Customer Experience: Using the Powerful
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A CA Technologies eBook Ensuring a Superior Digital Customer Experience Using the Powerful Combination of CA Digital Experience Insights and IBM Services 1 In this digital age, customers demand flawless digital experiences of U.S. consumers say having a positive Over the last decade or so, the digital economy has emerged and, % customer experience 83 with a brand is more in many cases, has supplanted traditional company/customer important that the interactions. This is in large part due to the explosion of the internet product itself.1 as a source for not only information, but commerce and customer engagement. Traditional brick and mortar establishments have been disrupted by digitally-born organizations that are both nimble and customer-savvy. of large companies % want to be customer 53 experience leaders Add in the proliferation of mobile and IOT devices, organizations within three years.2 are forced to be innovative and develop and deliver a richer variety of multichannel digital experiences in order to compete for market share. At the root of all of this is the customer experience. Organizations that focus on delivering flawless digital experiences will fare better in this app economy than those that don’t. of mobile site visits are % abandoned if pages 53 take longer than three seconds to load.3 2 Delivering more digital experiences drives higher use of cloud-based services Today there are over 18K public APIs—and growing annually.4 With the drive to deliver more innovative digital experiences, 18% organizations have transformed more of their customer engagement systems to the cloud—which under the covers means Microservice-based apps are widely much more distributed and modular hardware and software used today and are forecasted to architectures based on virtualized resources, containers, APIs and become the default architecture in software-defined networks (SDNs). So, what does this mean? most large enterprises by 2023.5 While these distributed application architectures are necessary to support digital transformation initiatives, they are increasingly 90% of large enterprises plan to complex to manage. More moving parts means IT operations has move to SDNs by 2021.6 more elements to monitor, with each increasing the amount of data that needs to be collected and analyzed. Distributed architectures create more touch points—increasing the opportunity for increased “noise” from alerts—which can delay root cause determination and jeopardize SLAs. 3 How do you maximize application performance? At the end of the day, it’s about application performance and availability—not just with internal systems of record applications, but also with customer engagement applications. With customers engaging digital services from a variety of channels, it’s imperative for IT operations and line of business leaders to understand how each application is delivering a flawless experience. This requires a holistic view of the whole digital delivery chain—from the user experience on the front end, as well as understanding how the application, infrastructure and supporting networks all contribute to performance and Photo ? availability. While keeping applications up and running are the key task, when an application goes down or suffers performance degradation, the priority becomes to identify the root cause of the issue as soon as possible and remediate the issue. While this is great in concept, most organizations struggle with this for many reasons. 4 Key barriers limit the ability to derive meaningful insights Volume The days of managing monolithic-style applications running on a single platform are coming to an end. Organizations are now committed to delivering their customers a far richer variety of digital services across multiple channels (mobile, Web, IOT). This means that applications are more likely to operate from the cloud via a variety of services that are interacting with virtualized resources, containers and software-defined networks. While these distributed application architectures are necessary to support digital transformation initiatives, they are increasingly complex to manage. Many more moving parts means IT operations has more systems and elements to monitor, with each increasing the amount of data that needs to be analyzed. 5 Key barriers limit the ability to derive meaningful insights Velocity Although IT operations has always collected and processed large amounts of data, the systems and applications being monitored only changed infrequently. Even though information was collected in silos, teams had more time to respond when problems occurred. And since these applications generally supported internal business processes or one channel, problems were manageable and easier to understand. Photo ? Today’s model is far different. Agile and DevOps practices now enable a continuous flow of customer value. And with businesses competing on the basis of digital dexterity, the speed at which change can be delivered becomes a critical differentiator. Also, as research indicates, high-performing organizations can deliver software 46 times more frequently than their lower performing peers.7 6 Key barriers limit the ability to derive meaningful insights Variety Modern application architectures are highly modular and dynamic, making it difficult for IT operations to establish any point from which the end-user experience can be viewed as a whole. Complicating this further is the rich and varied set of monitoring data that now needs to be processed, including millions of time-series data points, together with unstructured logs, events, topological data and qualitative metrics. 7 Key barriers limit the ability to derive meaningful insights Teams and Tools are Organized by Silos Regardless of the scale at which applications are being developed and the increasing amount of touch points within the IT stack, many organizations have not changed the way they manage their application performance and availability. Applications are typically monitored using disparate, specific-use tools that are disconnected. As new systems and technology are added, more tools are added. It’s not uncommon for IT operations to use more than 10 monitoring tools. This can include: user monitoring, server monitoring, synthetic transactions, event diagnostics and correlation, log reporting, cloud Photo ? service checking, network fault and performance monitoring. As you can see, this can become quite unwieldy when troubleshooting an issue. To identify the root cause of an issue, it’s not uncommon for a war room event to happen where different people who are responsible for each toolset sit around a table and try to agree on where the issue originates. This can take hours or days and when considering the speed of business, every minute counts toward solving the issue. 8 Key barriers limit the ability to derive meaningful insights Lack of Visibility Across Apps, Infrastructure and Networks While the various point tools that organizations use in monitoring application, infrastructure and network performance are excellent at instrumenting their specific area of focus, there is no correlation across the digital delivery chain. IT operations cannot reliably determine how an issue (network latency for example) will affect various business services and at how it affects the end-user’s digital experience. 9 Evolving beyond monitoring: Insights through advanced analytics, machine learning and artificial intelligence. Industry analysts feel Monitoring and instrumentation creates data. A lot of it. In today’s world of big data and analytics, harnessing the the same. By 2021: exponential amounts of data created by IT operations would create both efficiency and real-time insights based on context. • 90% of leading network monitoring tools will apply machine The most efficient approach would be a scenario where learning methods to simplify the task instrumentation data from the different IT domains (Applications, of defining dependencies across large Infrastructure and Networks) is captured in a common data pool, sets of metrics, up from 30% where advanced analytics and machine learning can leverage all in 2017.8 the data to identify patterns. With this learning comes predictive outcomes and well-founded recommendations to resolve the • 60% of IT monitoring issue. In addition, performance and experience feedback can investments will include a focus on be actively fed into the development cycle to help drive higher business relevant metrics, which is an quality applications and experiences. increase from less than 20% in 2017.9 10 CA Digital Experience Insights drives greater insights CA Digital Experience Insights is an AIOps-driven platform, which correlates data across users, applications, infrastructure and network services. It applies machine learning and advanced analytics to deliver a new level of visibility and actionable operational intelligence. Built on top of a powerful analytics engine, which leverages open ® technologies such as Elasticsearch, Kibana and Apache Spark™, App App CA Digital Experience Insights uniquely provides comprehensive Experience Performance monitoring and analytics and is available via public, private and hybrid cloud. Infrastructure Networking CA Digital Experience Insights helps IT and business leaders ensure great user experiences, improve application performance and monitor your infrastructure. 11 CA Digital Experience Insights: Consolidated monitoring that delivers a unified perspective CA Digital Experience Insights provides comprehensive insights