Skip to main content

The Disconnect Between IT and the Business

Shayde Christian
Cloudera

IT and the business are disconnected. Ask the business what IT does and you might hear "they implement infrastructure, write software, and migrate things to cloud," and for some that might be the extent of their knowledge of IT. Similarly, IT might know that the business "markets and sells and develops product," but they may not know what those functions entail beyond the unit they serve the most.

The disconnect is understandable because individuals in IT and the business have different skills, training, education, and focus, but it is also surprising in that IT and the business are beyond symbiotic, they are inextricably interdependent. Both teams can take strategic steps to bridge the divide. The first step is atop the building block on which their relationship was founded: data.

Siloed Data and Communication

The common language spoken by IT and the business is data. If data is fragmented, there isn't much to say because departments will only be able to form an isolated, incomplete picture of the business landscape and marketplace. As organizations fail to share data, its value diminishes: valuable insights are difficult to generate and decision-making fails to advance business aims.

Centralizing data ecosystems is critical to break down the silo between IT and the business.

The business must survey a holistic view if they are to accelerate corporate performance, advance strategic goals, and improve customer experience; therefore, IT must aggregate and consolidate disparate data stores onto centralized data platforms, the first step to envision future success through the elusive "single pane of glass."

Industry leading companies leverage modern data architectures to affiliate data silos: data lakehouse, data fabric, and data mesh. Such designs facilitate the effective democratization of data for enterprise-grade insight generation while securing data and appropriately restricting its access. Enterprise data platforms also facilitate proper data governance and improvements in data availability, quality, and integrity. Better data means better decision making.

Disparate Systems and Tools

With aggregated, secure, governed data, IT and the business can foster a culture of collaboration.

Implementation of common systems and tools promotes real-time sharing of information and ideas. Digital transformation initiatives streamline business workflows and multiply actionable data. Investments in intuitive visualization and analytics tools make insights easier to spot.

In addition to fostering collaboration, silo busting, and improving business outcomes, the rallying of IT and the business around digital transformation will cultivate common ground. IT will develop business literacy, and they may feel less like order takers if they are offered a seat at the table. The business will increase data literacy, and they may develop an appreciation for technical complexities and thankless back-office demands.

Misaligned Goals and Objectives

Strong leadership is essential to establish and sustain effective collaboration. Of paramount importance is shared vision. Cross-functional leadership must communicate and align around corporate strategic goals. Everything IT does and delivers should be aligned to established business objectives, and IT should be empowered to decline any requests that are not.

As the business, IT effectiveness should be measured by their contribution to top line and bottom line growth and customer experience. Attribution can be difficult but not impossible. Such tight-knit alignment also strengthens accountability within the business as more effort is applied to estimating the ROI of technology requests before they are submitted to IT. Consequently, innovation will become more intentional, and the business will get more benefit from their shared services organizations.

Objectives alignment is a powerful way to repair the disconnect because it gets IT and the business speaking the same language.

What does the business do?

"They're improving customer experience and efficiency to increase top line growth 15% and profit margins 7%."

What is IT doing?

"Same thing."

Shayde Christian is Chief Data and Analytics Officer at Cloudera

Hot Topics

The Latest

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

The Disconnect Between IT and the Business

Shayde Christian
Cloudera

IT and the business are disconnected. Ask the business what IT does and you might hear "they implement infrastructure, write software, and migrate things to cloud," and for some that might be the extent of their knowledge of IT. Similarly, IT might know that the business "markets and sells and develops product," but they may not know what those functions entail beyond the unit they serve the most.

The disconnect is understandable because individuals in IT and the business have different skills, training, education, and focus, but it is also surprising in that IT and the business are beyond symbiotic, they are inextricably interdependent. Both teams can take strategic steps to bridge the divide. The first step is atop the building block on which their relationship was founded: data.

Siloed Data and Communication

The common language spoken by IT and the business is data. If data is fragmented, there isn't much to say because departments will only be able to form an isolated, incomplete picture of the business landscape and marketplace. As organizations fail to share data, its value diminishes: valuable insights are difficult to generate and decision-making fails to advance business aims.

Centralizing data ecosystems is critical to break down the silo between IT and the business.

The business must survey a holistic view if they are to accelerate corporate performance, advance strategic goals, and improve customer experience; therefore, IT must aggregate and consolidate disparate data stores onto centralized data platforms, the first step to envision future success through the elusive "single pane of glass."

Industry leading companies leverage modern data architectures to affiliate data silos: data lakehouse, data fabric, and data mesh. Such designs facilitate the effective democratization of data for enterprise-grade insight generation while securing data and appropriately restricting its access. Enterprise data platforms also facilitate proper data governance and improvements in data availability, quality, and integrity. Better data means better decision making.

Disparate Systems and Tools

With aggregated, secure, governed data, IT and the business can foster a culture of collaboration.

Implementation of common systems and tools promotes real-time sharing of information and ideas. Digital transformation initiatives streamline business workflows and multiply actionable data. Investments in intuitive visualization and analytics tools make insights easier to spot.

In addition to fostering collaboration, silo busting, and improving business outcomes, the rallying of IT and the business around digital transformation will cultivate common ground. IT will develop business literacy, and they may feel less like order takers if they are offered a seat at the table. The business will increase data literacy, and they may develop an appreciation for technical complexities and thankless back-office demands.

Misaligned Goals and Objectives

Strong leadership is essential to establish and sustain effective collaboration. Of paramount importance is shared vision. Cross-functional leadership must communicate and align around corporate strategic goals. Everything IT does and delivers should be aligned to established business objectives, and IT should be empowered to decline any requests that are not.

As the business, IT effectiveness should be measured by their contribution to top line and bottom line growth and customer experience. Attribution can be difficult but not impossible. Such tight-knit alignment also strengthens accountability within the business as more effort is applied to estimating the ROI of technology requests before they are submitted to IT. Consequently, innovation will become more intentional, and the business will get more benefit from their shared services organizations.

Objectives alignment is a powerful way to repair the disconnect because it gets IT and the business speaking the same language.

What does the business do?

"They're improving customer experience and efficiency to increase top line growth 15% and profit margins 7%."

What is IT doing?

"Same thing."

Shayde Christian is Chief Data and Analytics Officer at Cloudera

Hot Topics

The Latest

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ...