Navigating information sprawl: A guide for enterprises

Information sprawl has become one of the most pressing challenges facing modern enterprises. As organizations generate data at unprecedented rates—with the global datasphere expected to more than double from 2022 to 2026—the ability to manage, secure, and leverage this information effectively has never been more critical.

What is information sprawl?

Information sprawl is the uncontrolled expansion of data across various systems and platforms within an organization. This phenomenon leads to challenges in data management, security, and productivity as information becomes scattered and difficult to manage effectively. The global datasphere is projected to explode from 45 zettabytes in 2019 to 175 zettabytes by 2025. This represents a nearly fourfold increase in just six years, with enterprise data growing twice as fast as consumer data.

Think of it as the digital equivalent of a cluttered office that's expanded across multiple buildings. Documents exist in filing cabinets, servers, corporate intranets, emails, and countless SaaS applications. Each department might use different tools, store data in different formats, and follow different protocols—creating a labyrinth of information that's increasingly difficult to navigate.

This isn't just about volume—it's about complexity and risk. When one in five enterprise cloud environments with internet-facing databases contains sensitive data like PII, PHI, or PCI information, the stakes couldn't be higher. Organizations averaged 802,000 files at risk due to oversharing in 2022, a 60% increase from earlier in the year, and the number of at-risk files per employee jumped from 251 in 2021 to 402 in 2022.

This isn't just about volume—it's about complexity and risk. When one in five enterprise cloud environments with internet-facing databases contains sensitive data like PII, PHI, or PCI information, the stakes couldn't be higher.

How to navigate information sprawl

Understanding information sprawl requires recognizing both its causes and implications. The proliferation occurs naturally as organizations adopt new technologies, expand into cloud environments, and enable remote work. Each new SaaS application, IoT device, or collaboration tool adds another layer to the sprawl.

The foundation of managing information sprawl is centralization. This doesn't mean forcing all data into a single repository, but rather creating a unified approach to data management across your organization. This is increasingly critical given that 65% of all Software-as-a-Service applications used in organizations are unsanctioned by IT departments, and organizations maintain an average of 975 unknown cloud services compared to only 108 officially known services.

Consider how remote work amplifies this challenge. Employees generate data across personal devices, cloud storage services, and collaboration platforms. Without proper oversight, this shadow IT creates shadow data—information that exists outside organizational control and visibility.

Step 1: Centralize data management

The foundation of managing information sprawl is centralization. This doesn't mean forcing all data into a single repository, but rather creating a unified approach to data management across your organization.

Start by implementing centralized data storage solutions that can accommodate both structured and unstructured data. Cloud storage platforms offer the scalability and accessibility needed for modern enterprises, providing a single source of truth while maintaining the flexibility teams require.

Enterprise search capabilities are essential here. Modern search platforms can index content across 100+ connectors, crawling every part of your data landscape—from document titles and body copy to metadata and comments. This comprehensive indexing makes information discoverable regardless of where it lives, effectively creating a unified view of scattered data.

Data Security Posture Management (DSPM) solutions provide continuous visibility into where sensitive data lives and who can access it. DSPM is the fastest-growing security category, with 75% of organizations expected to adopt it by mid-2025; currently, 87% of enterprises find their data discovery and classification solutions lacking. These tools can automatically discover and classify data across cloud environments, tracking movement and managing access across distributed systems. When 90% of business-critical documents are shared outside the C-suite, and over 15% of critical files are at risk from oversharing, automated governance becomes essential.

Step 2: Enhance data security measures

With data scattered across multiple platforms, security becomes exponentially more complex. Each system represents a potential vulnerability, and traditional perimeter-based security models simply don't work when there's no clear perimeter to defend.

Robust data security protocols must adapt to this distributed reality. Start with the principle of least privilege—users should only access the data they need for their specific roles. Modern platforms enforce these permissions automatically, respecting the access controls of source documents without requiring manual configuration.

Data Security Posture Management (DSPM) solutions provide continuous visibility into where sensitive data lives and who can access it. These tools can automatically discover and classify data across cloud environments, tracking movement and managing access across distributed systems. When 90% of business-critical documents are shared outside the C-suite, and over 15% of critical files are at risk from oversharing, automated governance becomes essential.

Regular security updates are non-negotiable. As data sprawl expands your attack surface, staying ahead of emerging threats requires constant vigilance. Implement real-time monitoring of data flows, automated threat detection, and regular security assessments to identify vulnerabilities before they're exploited.

Step 3: Foster a culture of data responsibility

Promote efficient information discovery. When employees can quickly find what they need through enterprise search—reducing the average 2 hours per day spent looking for information—they're less likely to create duplicates or store data in unauthorized locations. In fact, 43% of employees would consider leaving their job if there wasn't an efficient way to access needed information, rising to 51% for ages 18-34 and 57% for ages 35-44. Make finding information as easy as using Google, and watch sprawl naturally decrease.

Education is the starting point. Many employees don't realize the risks their data practices create. When someone shares a spreadsheet containing client details on public cloud storage or uses an unapproved app for sensitive work, they're contributing to sprawl and creating security vulnerabilities. Regular training helps teams understand these risks and their role in preventing them.

Encourage the use of approved tools by making them easily accessible and user-friendly. The rise of shadow IT often stems from employees trying to work more efficiently. If your approved platforms don't meet their needs, they'll find alternatives. By providing comprehensive, intuitive tools and simplifying approval processes for new applications, you reduce the incentive for workarounds.

Promote efficient information discovery. When employees can quickly find what they need through enterprise search—reducing the average 2 hours per day spent looking for information—they're less likely to create duplicates or store data in unauthorized locations. On average, knowledge workers spend 1.8 hours every day (25% of their work week) searching for information rather than creating value—effectively meaning businesses hire five employees but only get productive output from four. Make finding information as easy as using Google, and watch sprawl naturally decrease.

Step 4: Leverage technology to reduce complexity

Modern AI and automation tools offer powerful capabilities for taming information sprawl. These technologies can process vast amounts of data, identify patterns, and take actions that would be impossible for human administrators to perform manually.

Automated data classification uses machine learning to scan and categorize information based on content, context, and sensitivity. AI can identify everything from financial data to personally identifiable information, applying appropriate security controls and retention policies automatically. This eliminates the error-prone manual classification process while ensuring consistent governance across all data types.

Visibility solutions, powered by a knowledge graph, provide real-time insights into your data landscape. Modern platforms create comprehensive maps of data locations, access patterns, and risk levels. They can track data lineage, showing how information moves through your organization and identifying potential exposure points. This visibility enables proactive management rather than reactive scrambling when issues arise.

Information architecture brings order to chaos. By implementing systematic organization principles—clear naming conventions, logical folder structures, standardized metadata—you make data more discoverable and manageable. Think of it as urban planning for your digital environment, creating clear pathways and zones that make navigation intuitive.

Tips on managing information sprawl

1. Regularly assess data storage practices

A systematic approach to evaluating data storage is key to managing information sprawl effectively. By implementing a routine assessment schedule for data repositories, organizations can ensure alignment with both operational objectives and security protocols. This process involves not only mapping out data locations and access permissions but also analyzing how data is archived and purged. Regular evaluations can highlight inefficiencies, such as redundant data or outdated storage methods, allowing for strategic improvements that enhance overall data management.

Moreover, these assessments should proactively identify potential security gaps within storage solutions. With regulatory requirements and technological advancements constantly evolving, it is essential to verify that storage systems adhere to the latest compliance standards. Maintaining a current and comprehensive view of data storage practices equips organizations to better protect against unauthorized access and mitigate the risk of breaches.

2. Implement flexible data solutions

Embracing flexible data solutions is crucial for keeping pace with the dynamic demands of today's data environments. As organizations expand and data requirements grow, it's important to adopt technologies that can adjust to these changes fluidly. Opting for solutions with built-in scalability ensures that enterprises can seamlessly increase capacity and capabilities without causing disruptions. This adaptability is vital for sustaining operational efficiency and ensuring data systems remain resilient in the face of evolving needs.

When selecting flexible solutions, prioritize those that offer seamless integration capabilities with existing and future technologies. This interoperability is essential for preventing the formation of new data silos and supports a unified data management strategy. Furthermore, choose solutions that offer advanced analytics and reporting features, providing valuable insights into data utilization patterns and enabling data-driven decision-making through real-time analysis.

3. Encourage interdepartmental cooperation

Promoting cooperation among departments can significantly streamline data management practices and mitigate information sprawl. By cultivating a culture of transparency and collaboration, organizations can enhance data workflows and reduce duplication of efforts. This strategy involves not only sharing successful practices but also standardizing data handling and storage procedures across teams. When departments align on data management goals, they can more effectively coordinate actions and optimize the use of resources.

Additionally, interdepartmental cooperation provides a broader perspective on the organization's data ecosystem. Collaborative efforts allow teams to identify shared challenges and develop comprehensive solutions that benefit the entire enterprise. This unified approach not only strengthens data governance but also empowers employees to actively participate in managing information sprawl, creating a more cohesive and efficient data environment.

The journey to conquering information sprawl starts with understanding that it's not just a technical challenge—it's an organizational transformation. By implementing the strategies we've outlined, you can turn your scattered data landscape into a strategic asset that drives productivity and innovation.

The path forward

Information sprawl isn't going away—if anything, it will accelerate as organizations generate more data through AI, IoT, and digital transformation initiatives. The key is transforming this challenge into an opportunity.

Organizations that successfully navigate information sprawl gain significant competitive advantages. They make better decisions based on comprehensive data insights. They respond faster to opportunities and threats. They maintain stronger security postures and ensure regulatory compliance. Most importantly, they empower employees to focus on meaningful work rather than hunting for information.

The journey from chaos to control requires commitment, investment, and cultural change. But with the right combination of centralized management, enhanced security, cultural transformation, and intelligent technology, enterprises can turn their data sprawl from a liability into an asset.

Start small, think big, and move steadily. Every step toward better data management is a step toward a more efficient, secure, and competitive organization. In the age of information, those who can navigate the sprawl will be the ones who thrive.

Ready to see how AI can help you navigate information sprawl and unlock your organization's full potential? Request a demo to explore how Glean and AI can transform your workplace.