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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

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...