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The State of the CIO

Jonah Kowall

Today’s CIOs face a daunting task: They must move their enterprises from a traditional organization, with some degree of optimization and automation, into the digital business age. Digital businesses are software-defined — dependent on or driven by software, and leveraging software-derived data to drive decision-making. In order to move businesses into the digital age, much needs to evolve, including innovation, leadership, organization, and culture within IT.

These changes often are driven by a chief digital officer or a digitally savvy CIO. There is no doubt that CIOs and CEOs have a close relationship, which is bound to become closer as businesses digitize. According to Gartner’s CIO survey data, 41 percent of CIOs are reporting to their CEO. This is a return to one of the highest levels recorded by Gartner CIO surveys, a result of the digital narrative gaining prominence in the boardroom and on the executive committee. Even stronger evidence of opportunity for CIOs is the fact that the survey reveals that CEOs expect them to lead the digital charge during this critical transition period.

Tenure for CIOs is normally short due to high expectations from CEOs and demands from business unit leadership for IT execution. There does seem to be a disconnect between CEO expectation and what the CIO is executing upon. The level of communication and trust between executives must improve. What this indicates is that higher prioritization is required not only for digitizing the business, but for creating business transaction and impact visibility through data collection and analytics.

These business model transformations require a much greater degree of experimentation and agility, and the understanding and meaning of failure must be re-examined. Although human nature makes us fear failure, some degree of failure should be accepted, especially when experimenting with new capabilities that must be learned. Experimentation should take the form of smaller bets, which can be adjusted and changed quickly, without stringent processes inhibiting the experimentation. If these experiments are successful, they may become strategic initiatives.

Metrics are critical to measuring the success of IT. In the Gartner 2015 CIO Agenda, the following indicators are most often used:


The top IT performance metric is cost, which shows the need to constrict IT spend. Normally this takes the form of data center efficiency gains and running as lean and automated as possible. This frees up dollars for innovative experiments, versus day-to-day operational work. The use of better data and advanced analytics will create new cost savings and opportunities. IT operations analytics will play a big part in this, as the ability for people to manage operational efficiency is becoming too difficult with the complexity in environments today.

The number two metric is service levels, which are a constant struggle due to the way service levels have been measured. In Accenture’s Business Technology Trends Report 2015, experience matters most: 89 percent of business leaders surveyed by Accenture believe that customer experience will be their primary basis for competition by 2016. In my regular discussions with CIOs, ensuring service levels is an issue. Before undergoing any kind of change or improvement, the quality of IT services must be measured properly. Most CIOs have been trying to understand why IT isn’t the first to know when there is a system degradation or outage. This can be most often attributed to two things, one being a focus on infrastructure instead of applications, and the second being a limited view of the end-user experience. End-user focus is key in order to measure business differentiators. Users do not exercise infrastructure specifically; instead, they conduct transactions which traverse infrastructure components. The transaction should be the unit of measure of business, and employees should be bonused and tied to those measures. These issues most often lead towards APM discussions to help solve both of these service level gaps.

I hope this post was helpful and thought-provoking. Future blog topics for the CIO include driving business decisions off data, changing sourcing strategies, innovation and bimodal IT, mobile-first, and a focus on some high growth geographies.

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The State of the CIO

Jonah Kowall

Today’s CIOs face a daunting task: They must move their enterprises from a traditional organization, with some degree of optimization and automation, into the digital business age. Digital businesses are software-defined — dependent on or driven by software, and leveraging software-derived data to drive decision-making. In order to move businesses into the digital age, much needs to evolve, including innovation, leadership, organization, and culture within IT.

These changes often are driven by a chief digital officer or a digitally savvy CIO. There is no doubt that CIOs and CEOs have a close relationship, which is bound to become closer as businesses digitize. According to Gartner’s CIO survey data, 41 percent of CIOs are reporting to their CEO. This is a return to one of the highest levels recorded by Gartner CIO surveys, a result of the digital narrative gaining prominence in the boardroom and on the executive committee. Even stronger evidence of opportunity for CIOs is the fact that the survey reveals that CEOs expect them to lead the digital charge during this critical transition period.

Tenure for CIOs is normally short due to high expectations from CEOs and demands from business unit leadership for IT execution. There does seem to be a disconnect between CEO expectation and what the CIO is executing upon. The level of communication and trust between executives must improve. What this indicates is that higher prioritization is required not only for digitizing the business, but for creating business transaction and impact visibility through data collection and analytics.

These business model transformations require a much greater degree of experimentation and agility, and the understanding and meaning of failure must be re-examined. Although human nature makes us fear failure, some degree of failure should be accepted, especially when experimenting with new capabilities that must be learned. Experimentation should take the form of smaller bets, which can be adjusted and changed quickly, without stringent processes inhibiting the experimentation. If these experiments are successful, they may become strategic initiatives.

Metrics are critical to measuring the success of IT. In the Gartner 2015 CIO Agenda, the following indicators are most often used:


The top IT performance metric is cost, which shows the need to constrict IT spend. Normally this takes the form of data center efficiency gains and running as lean and automated as possible. This frees up dollars for innovative experiments, versus day-to-day operational work. The use of better data and advanced analytics will create new cost savings and opportunities. IT operations analytics will play a big part in this, as the ability for people to manage operational efficiency is becoming too difficult with the complexity in environments today.

The number two metric is service levels, which are a constant struggle due to the way service levels have been measured. In Accenture’s Business Technology Trends Report 2015, experience matters most: 89 percent of business leaders surveyed by Accenture believe that customer experience will be their primary basis for competition by 2016. In my regular discussions with CIOs, ensuring service levels is an issue. Before undergoing any kind of change or improvement, the quality of IT services must be measured properly. Most CIOs have been trying to understand why IT isn’t the first to know when there is a system degradation or outage. This can be most often attributed to two things, one being a focus on infrastructure instead of applications, and the second being a limited view of the end-user experience. End-user focus is key in order to measure business differentiators. Users do not exercise infrastructure specifically; instead, they conduct transactions which traverse infrastructure components. The transaction should be the unit of measure of business, and employees should be bonused and tied to those measures. These issues most often lead towards APM discussions to help solve both of these service level gaps.

I hope this post was helpful and thought-provoking. Future blog topics for the CIO include driving business decisions off data, changing sourcing strategies, innovation and bimodal IT, mobile-first, and a focus on some high growth geographies.

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

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 ...