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Why Data Silos Kill Collaboration

Chris Cooney
Head of Developer Advocacy
Coralogix

A silo is, by definition, an isolated component of an organization that doesn't interact with those around it in any meaningful way. This is the antithesis of collaboration, but its effects are even more insidious than the shutting down of effective conversation. To paraphrase Wittgenstein, in the modern economy, "The limits of data are the limits of my world."

Removing these limits is an essential step in maximizing the value of your data. In a world where 60% of organizations report over half of their data is considered "dark data," this is a huge challenge.

Why Do Silos Form?

There are a number of situations that drive the creation of a data silo, but the most common are:

■ Departments acting in isolation, hoarding data in pursuit of their own local optimizations.

■ Mergers and acquisitions, poorly stitching together two organizations with separate tools and systems.

■ Inter-departmental politics, driven by a pathological culture that doesn't favor collaboration (more on this later).

These are just a few of the many scenarios that drive the growth of data silos, but why are data silos so bad, and what do they have to do with collaboration?

The Traditional Arguments Against Data Silos

When writing about data silos and their associated impact, we almost always discuss things like server costs, wasteful licenses, a lack of economy of scale and more. These are very real, serious problems that are directly linked with the growth of silos, but the cost to collaboration is far more insidious.

The Hidden Impact to Collaboration

Collaboration requires a few things to really flourish:

■ Free movement of information between teams.

■ A culture of psychological safety, that won't punish people for surfacing their mistakes.

■ An environment free of the often political impulse to prioritize personal objectives over organizational outcomes.

Without all 3 of these components, honest collaboration is going to struggle. Silos directly attack point 1, free movement of information, and indirectly encourage the sorts of suboptimal behaviors that prevent the realization of 3, an environment free of political impulse. How does this happen?

The Impact to the Free Movement of Information

Silos are the obvious antithesis of the free movement of information. This is often driven by a technological barrier. For example, a large volume of valuable information is stored in an unparseable format, or is held in a legacy database without an easy querying mechanism, but it's also a collaboration barrier.

Teams develop habits. If they grow accustomed to their own data, in their own infrastructure, with all of the flexibility and freedom that entails, the idea of sharing, or indeed the idea of using another data format that is managed by another team, will require a lot more effort for initially small gains. As this vicious circle repeats, teams become more tribal, more entrenched in their own processes and techniques.

The Growth of a Culture of Confrontation

As teams become more tribal, trust disappears. In larger organizations, this manifests itself in "othering", where teams begin to treat colleagues as enemies, with uncertain ambitions. They begin to view the organization as a battleground. Every visitor from outside their team is treated as potentially hostile. This culture, identified by Westrum as Pathological, is self-fulfilling and, without strong and enlightened leadership, will continue to feed itself to catastrophic effect.

All of this, by hiding data and not encouraging cross-team pollination. It's that serious.

How to Break Down the Walls

Attacking this problem takes time, persistence and effort, but it is undoubtedly worth it.

Cross-Departmental Dialogues

Initiate open discussions among teams to share data needs and challenges, fostering trust and understanding. This step is essential to identify existing data silos and understand the barriers to collaboration.

API Standardization

Develop a standardized API framework to enable seamless data integration and interoperability across different systems. This allows for efficient data sharing and reduces fragmentation.

Data Governance Policies

Implement clear data governance policies that promote data sharing while ensuring security and compliance. Define data ownership, access rights, and quality standards to maintain consistency and trust in the shared data.

Foster Collaborative Culture

Cultivate a culture that values collaboration over competition. Recognize and reward efforts to break down silos and encourage data sharing. Leadership should exemplify collaborative behavior and emphasize the importance of working together to achieve common goals.

By implementing these strategies, organizations can dismantle data silos, enhance collaboration, and fully leverage the value of their data.

Let Your Data Roam Free

Free, accessible data can be correlated, compared, explored and refined. Teams can make data driven decisions, even if the data is halfway across the company. These internal API calls turn into collaboration sessions that form teams and steering groups and shared ambitions and goals which are the bedrock of a learning organization and, undoubtedly, some very long lasting friendships.

The elimination of silos is not just a cost optimization exercise. It is a cultural imperative, to ensure that you're not falling victim to an accidental Inverse Conway Maneuver and building a culture, and software, that will stand the test of time.

Chris Cooney is Head of Developer Advocacy at Coralogix

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Why Data Silos Kill Collaboration

Chris Cooney
Head of Developer Advocacy
Coralogix

A silo is, by definition, an isolated component of an organization that doesn't interact with those around it in any meaningful way. This is the antithesis of collaboration, but its effects are even more insidious than the shutting down of effective conversation. To paraphrase Wittgenstein, in the modern economy, "The limits of data are the limits of my world."

Removing these limits is an essential step in maximizing the value of your data. In a world where 60% of organizations report over half of their data is considered "dark data," this is a huge challenge.

Why Do Silos Form?

There are a number of situations that drive the creation of a data silo, but the most common are:

■ Departments acting in isolation, hoarding data in pursuit of their own local optimizations.

■ Mergers and acquisitions, poorly stitching together two organizations with separate tools and systems.

■ Inter-departmental politics, driven by a pathological culture that doesn't favor collaboration (more on this later).

These are just a few of the many scenarios that drive the growth of data silos, but why are data silos so bad, and what do they have to do with collaboration?

The Traditional Arguments Against Data Silos

When writing about data silos and their associated impact, we almost always discuss things like server costs, wasteful licenses, a lack of economy of scale and more. These are very real, serious problems that are directly linked with the growth of silos, but the cost to collaboration is far more insidious.

The Hidden Impact to Collaboration

Collaboration requires a few things to really flourish:

■ Free movement of information between teams.

■ A culture of psychological safety, that won't punish people for surfacing their mistakes.

■ An environment free of the often political impulse to prioritize personal objectives over organizational outcomes.

Without all 3 of these components, honest collaboration is going to struggle. Silos directly attack point 1, free movement of information, and indirectly encourage the sorts of suboptimal behaviors that prevent the realization of 3, an environment free of political impulse. How does this happen?

The Impact to the Free Movement of Information

Silos are the obvious antithesis of the free movement of information. This is often driven by a technological barrier. For example, a large volume of valuable information is stored in an unparseable format, or is held in a legacy database without an easy querying mechanism, but it's also a collaboration barrier.

Teams develop habits. If they grow accustomed to their own data, in their own infrastructure, with all of the flexibility and freedom that entails, the idea of sharing, or indeed the idea of using another data format that is managed by another team, will require a lot more effort for initially small gains. As this vicious circle repeats, teams become more tribal, more entrenched in their own processes and techniques.

The Growth of a Culture of Confrontation

As teams become more tribal, trust disappears. In larger organizations, this manifests itself in "othering", where teams begin to treat colleagues as enemies, with uncertain ambitions. They begin to view the organization as a battleground. Every visitor from outside their team is treated as potentially hostile. This culture, identified by Westrum as Pathological, is self-fulfilling and, without strong and enlightened leadership, will continue to feed itself to catastrophic effect.

All of this, by hiding data and not encouraging cross-team pollination. It's that serious.

How to Break Down the Walls

Attacking this problem takes time, persistence and effort, but it is undoubtedly worth it.

Cross-Departmental Dialogues

Initiate open discussions among teams to share data needs and challenges, fostering trust and understanding. This step is essential to identify existing data silos and understand the barriers to collaboration.

API Standardization

Develop a standardized API framework to enable seamless data integration and interoperability across different systems. This allows for efficient data sharing and reduces fragmentation.

Data Governance Policies

Implement clear data governance policies that promote data sharing while ensuring security and compliance. Define data ownership, access rights, and quality standards to maintain consistency and trust in the shared data.

Foster Collaborative Culture

Cultivate a culture that values collaboration over competition. Recognize and reward efforts to break down silos and encourage data sharing. Leadership should exemplify collaborative behavior and emphasize the importance of working together to achieve common goals.

By implementing these strategies, organizations can dismantle data silos, enhance collaboration, and fully leverage the value of their data.

Let Your Data Roam Free

Free, accessible data can be correlated, compared, explored and refined. Teams can make data driven decisions, even if the data is halfway across the company. These internal API calls turn into collaboration sessions that form teams and steering groups and shared ambitions and goals which are the bedrock of a learning organization and, undoubtedly, some very long lasting friendships.

The elimination of silos is not just a cost optimization exercise. It is a cultural imperative, to ensure that you're not falling victim to an accidental Inverse Conway Maneuver and building a culture, and software, that will stand the test of time.

Chris Cooney is Head of Developer Advocacy at Coralogix

Hot Topics

The Latest

In MEAN TIME TO INSIGHT Episode 12, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses purchasing new network observability solutions.... 

There's an image problem with mobile app security. While it's critical for highly regulated industries like financial services, it is often overlooked in others. This usually comes down to development priorities, which typically fall into three categories: user experience, app performance, and app security. When dealing with finite resources such as time, shifting priorities, and team skill sets, engineering teams often have to prioritize one over the others. Usually, security is the odd man out ...

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Guardsquare

IT outages, caused by poor-quality software updates, are no longer rare incidents but rather frequent occurrences, directly impacting over half of US consumers. According to the 2024 Software Failure Sentiment Report from Harness, many now equate these failures to critical public health crises ...

In just a few months, Google will again head to Washington DC and meet with the government for a two-week remedy trial to cement the fate of what happens to Chrome and its search business in the face of ongoing antitrust court case(s). Or, Google may proactively decide to make changes, putting the power in its hands to outline a suitable remedy. Regardless of the outcome, one thing is sure: there will be far more implications for AI than just a shift in Google's Search business ... 

Image
Chrome

In today's fast-paced digital world, Application Performance Monitoring (APM) is crucial for maintaining the health of an organization's digital ecosystem. However, the complexities of modern IT environments, including distributed architectures, hybrid clouds, and dynamic workloads, present significant challenges ... This blog explores the challenges of implementing application performance monitoring (APM) and offers strategies for overcoming them ...

Service disruptions remain a critical concern for IT and business executives, with 88% of respondents saying they believe another major incident will occur in the next 12 months, according to a study from PagerDuty ...

IT infrastructure (on-premises, cloud, or hybrid) is becoming larger and more complex. IT management tools need data to drive better decision making and more process automation to complement manual intervention by IT staff. That is why smart organizations invest in the systems and strategies needed to make their IT infrastructure more resilient in the event of disruption, and why many are turning to application performance monitoring (APM) in conjunction with high availability (HA) clusters ...

In today's data-driven world, the management of databases has become increasingly complex and critical. The following are findings from Redgate's 2025 The State of the Database Landscape report ...

With the 2027 deadline for SAP S/4HANA migrations fast approaching, organizations are accelerating their transition plans ... For organizations that intend to remain on SAP ECC in the near-term, the focus has shifted to improving operational efficiencies and meeting demands for faster cycle times ...

As applications expand and systems intertwine, performance bottlenecks, quality lapses, and disjointed pipelines threaten progress. To stay ahead, leading organizations are turning to three foundational strategies: developer-first observability, API platform adoption, and sustainable test growth ...