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Shifting to Analytics Driven Management for IT Operations

Today’s market environment demands businesses to change and adapt rapidly according to market dynamics, while still remaining in control. For business, these dynamics can mean sifting through what can amount to petabytes of data to act tactically and strategically.

Business Intelligence (BI) analytics tools help companies catch what could have been missed opportunities, using robust infrastructure to sift through mountains of data, and applying intelligent analytics. This way, business can identify hidden trends, customer relationships, buying behavior, operational and financial patterns, business opportunities and other vital information allowing business to take part in the market proactively.

Through BSM initiatives, IT is charged with supporting the changing demands of business, maintaining availability and ensuring that performance remains high. Similar to the business side experience, the IT landscape has grown in complexity, supporting a wider and growing range of technologies and platforms (Virtualization, Cloud, Open Source etc.), and accelerated application release schedules. This now means IT faces near-overwhelming quantities of information.

So while business progresses via BI, adopting analytics for management decisions, ironically the organization supporting this infrastructure, IT Operations, has adhered to an older, static-process driven paradigm. By not applying the analytics-based approach (like business) for their own operations, IT jeopardizes system stability, ultimately exposing business to the risk of devastating consequences.

Mountains of Data

Mountains of dynamic information confront IT. One of the prominent areas is in the cloud scenario. Self-service provisioning has multiplied the amount of activities occurring outside of static processes. The new provisioning opportunities are beyond IT management, leaving IT with limited visibility to what happens there. For example, an organization sets up a private cloud with a dynamic management system, allowing self-service provisioning of servers for the testing team. Traditionally, testing professionals would have come to IT and request an environment, and IT would oversee and manage this entire process. Now the process is independent, when testing needs an environment, they just create it.

Today’s Approach: Static Processes Drive IT

IT Operations has been running on static processes and strict workflows. For instance, ITIL has a process for Change Management that works according to certain steps. There are also a set metrics for measuring performance, like the amount of changes that successfully went through or failed.

IT Ops can plan as much as possible, but it won’t ensure that everything will occur as planned.

For example, when IT implements an application upgrade, and makes changes to the environment, IT administration can go through an entire established process, and still the application doesn’t function as planned. IT managers check the processes that the upgrade went through, yet still performance lags. Then they need to go into the fine, granular details and see every step, identifying the make-up of even minor changes, seeing how it was deployed to all the servers, what is the consistency between servers, have there been additional interference to the servers. They need to take this enormous amount of data – configuration and granular changes – and pinpoint what was the root cause.

Workflow-driven Management Processes

Static processes operate through workflows. The workflow only supports part of the process but there are so many things surrounding the workflow, happening outside the workflow. Business demands can force shortcuts to be taken. Steps in the workflow can be skipped in order to get immediate approval, even omitting the test stage.

Workflows Create False Security

Even when processes are enforced, like having registrations as part of the workflow management, this creates the belief that everything has been solved. There is no organization that can claim they operate completely within the bounds of established processes and approvals.

This situation creates a sense of false security that IT is on top of all the changes. IT Ops can think that everything works perfect and then the organization religiously adheres to their processes, relying on CMDB systems and workflows, ultimately undermining operations.

A Shift in Paradigm to Analytics Driven Management

Neurologists will explain that the brain has two distinct hemispheres. The right side of the brain collects information, while the left side is cognitive and analyzes this information, translating all of the sensory input into usable data.

This is really the same model for today’s IT organization, where operations need to know what is happening now. IT Ops can find itself stuck, trying to adjust static processes while keeping track of and handling dynamic events, and then getting caught off-guard when issues arise. The solution is to approach this situation with dynamic analytics, for dealing with all the changing data, and to see what is really happening. This goes beyond those few designated indicators that were usually watched, rather IT Ops needs Analytic Driven Management, similar to how business has adopted BI, extracting actionable information out of mountains of data to help decision makers respond efficiently.

About Sasha Gilenson

Sasha Gilenson is Founder and CEO of Evolven. Prior to founding Evolven in 2007, he spent 13 years with Mercury Interactive (acquired by HP), managing the QA organization and participating in establishing Mercury Interactive's Software as a Service (SaaS). Sasha played a key role in the development of Mercury Interactive's worldwide Business Technology Optimization (BTO) strategy and drove field operations of the Wireless Business Unit, all while taking on the duties as the Mercury Interactive's top "guru" in quality processes and IT practices domain.

Related Links:

www.evolven.com

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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 ...

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Shifting to Analytics Driven Management for IT Operations

Today’s market environment demands businesses to change and adapt rapidly according to market dynamics, while still remaining in control. For business, these dynamics can mean sifting through what can amount to petabytes of data to act tactically and strategically.

Business Intelligence (BI) analytics tools help companies catch what could have been missed opportunities, using robust infrastructure to sift through mountains of data, and applying intelligent analytics. This way, business can identify hidden trends, customer relationships, buying behavior, operational and financial patterns, business opportunities and other vital information allowing business to take part in the market proactively.

Through BSM initiatives, IT is charged with supporting the changing demands of business, maintaining availability and ensuring that performance remains high. Similar to the business side experience, the IT landscape has grown in complexity, supporting a wider and growing range of technologies and platforms (Virtualization, Cloud, Open Source etc.), and accelerated application release schedules. This now means IT faces near-overwhelming quantities of information.

So while business progresses via BI, adopting analytics for management decisions, ironically the organization supporting this infrastructure, IT Operations, has adhered to an older, static-process driven paradigm. By not applying the analytics-based approach (like business) for their own operations, IT jeopardizes system stability, ultimately exposing business to the risk of devastating consequences.

Mountains of Data

Mountains of dynamic information confront IT. One of the prominent areas is in the cloud scenario. Self-service provisioning has multiplied the amount of activities occurring outside of static processes. The new provisioning opportunities are beyond IT management, leaving IT with limited visibility to what happens there. For example, an organization sets up a private cloud with a dynamic management system, allowing self-service provisioning of servers for the testing team. Traditionally, testing professionals would have come to IT and request an environment, and IT would oversee and manage this entire process. Now the process is independent, when testing needs an environment, they just create it.

Today’s Approach: Static Processes Drive IT

IT Operations has been running on static processes and strict workflows. For instance, ITIL has a process for Change Management that works according to certain steps. There are also a set metrics for measuring performance, like the amount of changes that successfully went through or failed.

IT Ops can plan as much as possible, but it won’t ensure that everything will occur as planned.

For example, when IT implements an application upgrade, and makes changes to the environment, IT administration can go through an entire established process, and still the application doesn’t function as planned. IT managers check the processes that the upgrade went through, yet still performance lags. Then they need to go into the fine, granular details and see every step, identifying the make-up of even minor changes, seeing how it was deployed to all the servers, what is the consistency between servers, have there been additional interference to the servers. They need to take this enormous amount of data – configuration and granular changes – and pinpoint what was the root cause.

Workflow-driven Management Processes

Static processes operate through workflows. The workflow only supports part of the process but there are so many things surrounding the workflow, happening outside the workflow. Business demands can force shortcuts to be taken. Steps in the workflow can be skipped in order to get immediate approval, even omitting the test stage.

Workflows Create False Security

Even when processes are enforced, like having registrations as part of the workflow management, this creates the belief that everything has been solved. There is no organization that can claim they operate completely within the bounds of established processes and approvals.

This situation creates a sense of false security that IT is on top of all the changes. IT Ops can think that everything works perfect and then the organization religiously adheres to their processes, relying on CMDB systems and workflows, ultimately undermining operations.

A Shift in Paradigm to Analytics Driven Management

Neurologists will explain that the brain has two distinct hemispheres. The right side of the brain collects information, while the left side is cognitive and analyzes this information, translating all of the sensory input into usable data.

This is really the same model for today’s IT organization, where operations need to know what is happening now. IT Ops can find itself stuck, trying to adjust static processes while keeping track of and handling dynamic events, and then getting caught off-guard when issues arise. The solution is to approach this situation with dynamic analytics, for dealing with all the changing data, and to see what is really happening. This goes beyond those few designated indicators that were usually watched, rather IT Ops needs Analytic Driven Management, similar to how business has adopted BI, extracting actionable information out of mountains of data to help decision makers respond efficiently.

About Sasha Gilenson

Sasha Gilenson is Founder and CEO of Evolven. Prior to founding Evolven in 2007, he spent 13 years with Mercury Interactive (acquired by HP), managing the QA organization and participating in establishing Mercury Interactive's Software as a Service (SaaS). Sasha played a key role in the development of Mercury Interactive's worldwide Business Technology Optimization (BTO) strategy and drove field operations of the Wireless Business Unit, all while taking on the duties as the Mercury Interactive's top "guru" in quality processes and IT practices domain.

Related Links:

www.evolven.com

Hot Topics

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 ...