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The Age of the Customer Requires a Shift in Monitoring Focus

J. Rakowski

In my February 2014 report Left–Shift Technology Monitoring For Success In The Age Of The Customer, I explore what the near future will bring for technology monitoring approaches and solutions. Today, for the typical I&O organization, successful technology or service delivery monitoring focuses on two main areas. Firstly, availability, so ensuring the technology underpinning business services is up and available when needed. And secondly, performance, so making sure that technology utilized (applications and associated workloads) is fast enough for the business service it supports.

There is a major problem with this approach though. As the famous author Harper Lee stated “We know all men are not created equal” and the same can be said about your customers and employees – they are not all equal and the rapid pace of consumer technology innovation in areas such as mobile means that they will utilize technology in different ways to support productivity or to engage with your enterprise as a customer.

Our relationship with technology is changing rapidly. It is becoming more intimate and personal, meaning that datacenter centric monitoring approaches that focus on availability and performance alone, while still essential, are only the beginning of what is required for a holistic technology monitoring strategy.

In the age of the customer, it’s increasingly easy for your customers and even employees to switch to another technology provider. They will do this if they feel their experience needs are not being met from the technology based services provided.

Experience can be broken down into three simple facets:

1. Does the technology based service meet needs?

2. Is it easy to use?

3. Is it enjoyable?

The technology monitoring market in recent years has evolved from a focus on infrastructure monitoring, to application monitoring and the emergence of End User Experience Monitoring/Management (EUEM). EUEM looks to understand technology based business service performance from an employee or increasingly a customer perspective. However, many methods that I see in the market today are still application-centric in their monitoring approach e.g. the operator configures monitoring based on specified applications.

This means that many EUEM implementations fail to understand the full employee or customer journey. This includes how they use technology in in order to be productive within the enterprise or how they engage with enterprises, externally as customers. To understand the full technology interaction journey requires a more detailed form of end user monitoring which we define as End User Behavior Monitoring.

End User Behavior Monitoring has the capability of monitoring all interactions or activity between employees/customers and the technology they use, i.e consumer devices and applications. The aim here is not to alert, but to build up a detailed understanding of how the various types of business users or personas interact with business services so as to ensure that experience is tailored appropriately.

The following graphic summarizes this form of monitoring and its relation to other monitoring approaches on the market today:

Image removed.

Of course, end user behavior monitoring may ring alarm bells in regards to data privacy, but as our relationship with technology becomes increasingly more personal then I expect some of these concerns to fade away along with associated legislation.

If you are a Forrester client then my report highlights the concepts of End User Behavior Monitoring in detail. I also have an associated report coming out in Q2 2014 which looks at solutions on the market today which are capable of doing this form of monitoring within the enterprise.

John Rakowski is Analyst, Infrastructure and Operations, at Forrester.

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The Age of the Customer Requires a Shift in Monitoring Focus

J. Rakowski

In my February 2014 report Left–Shift Technology Monitoring For Success In The Age Of The Customer, I explore what the near future will bring for technology monitoring approaches and solutions. Today, for the typical I&O organization, successful technology or service delivery monitoring focuses on two main areas. Firstly, availability, so ensuring the technology underpinning business services is up and available when needed. And secondly, performance, so making sure that technology utilized (applications and associated workloads) is fast enough for the business service it supports.

There is a major problem with this approach though. As the famous author Harper Lee stated “We know all men are not created equal” and the same can be said about your customers and employees – they are not all equal and the rapid pace of consumer technology innovation in areas such as mobile means that they will utilize technology in different ways to support productivity or to engage with your enterprise as a customer.

Our relationship with technology is changing rapidly. It is becoming more intimate and personal, meaning that datacenter centric monitoring approaches that focus on availability and performance alone, while still essential, are only the beginning of what is required for a holistic technology monitoring strategy.

In the age of the customer, it’s increasingly easy for your customers and even employees to switch to another technology provider. They will do this if they feel their experience needs are not being met from the technology based services provided.

Experience can be broken down into three simple facets:

1. Does the technology based service meet needs?

2. Is it easy to use?

3. Is it enjoyable?

The technology monitoring market in recent years has evolved from a focus on infrastructure monitoring, to application monitoring and the emergence of End User Experience Monitoring/Management (EUEM). EUEM looks to understand technology based business service performance from an employee or increasingly a customer perspective. However, many methods that I see in the market today are still application-centric in their monitoring approach e.g. the operator configures monitoring based on specified applications.

This means that many EUEM implementations fail to understand the full employee or customer journey. This includes how they use technology in in order to be productive within the enterprise or how they engage with enterprises, externally as customers. To understand the full technology interaction journey requires a more detailed form of end user monitoring which we define as End User Behavior Monitoring.

End User Behavior Monitoring has the capability of monitoring all interactions or activity between employees/customers and the technology they use, i.e consumer devices and applications. The aim here is not to alert, but to build up a detailed understanding of how the various types of business users or personas interact with business services so as to ensure that experience is tailored appropriately.

The following graphic summarizes this form of monitoring and its relation to other monitoring approaches on the market today:

Image removed.

Of course, end user behavior monitoring may ring alarm bells in regards to data privacy, but as our relationship with technology becomes increasingly more personal then I expect some of these concerns to fade away along with associated legislation.

If you are a Forrester client then my report highlights the concepts of End User Behavior Monitoring in detail. I also have an associated report coming out in Q2 2014 which looks at solutions on the market today which are capable of doing this form of monitoring within the enterprise.

John Rakowski is Analyst, Infrastructure and Operations, at Forrester.

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...