What is a data silo? How does it affect your business and how to break it down?

Businesses generate massive amounts of data through various operations, systems, and interactions. However, different teams across organizations often operate in isolation, each guarding their own systems, insights, and metrics. This results in disconnected decisions, duplicated efforts, and missed opportunities – all caused by data silos.

Data silos cost businesses an average of $3.1 trillion annually in lost revenue and productivity. – McKinsey & Company

In organizations, data hides in nooks through legacy tools, spreadsheets, and CRMs, each disconnected from the rest. Over time, they slow decision-making processes, reduce operational efficiency, and hide critical business insights. If data silos are not attended to in a timely manner, they can hold back growth and innovation.

In this blog post, we will explore what data silos are, how they hinder business performance, and why breaking them down is vital. We will also explain how data engineering and cloud-based platforms can unify your data landscape. The goal is to make your data accessible and actionable, which drives true value.

What are data silos?

Data silos refer to pockets of information stored in an isolated system, which is not designed to get integrated with other systems or tools, limiting access to data. These data silos are developed due to different goals and priorities among departments, technical issues, or individual preferences.

Various departments within organizations utilize varying platforms and tools to help facilitate their work. Due to disintegration, these legacy systems make it difficult to share information with stakeholders and other departments. Siloed data, therefore, disrupts collaboration, inhibits an integrated view of the data, and may cause inconsistencies and redundant data across departments.

For instance, the facility management team uses a particular platform to log equipment usage and maintenance activities, but the operations team uses a different system that doesn’t integrate with facility logs. Thus, maintenance schedules are missed or repeated, affecting equipment uptime or resource planning.

Signs that reflect your organization has data silos

Data silos occur naturally depending upon the organization’s structure. Each department collects data to accomplish its goals and stores it as per their feasibility, creating data silos. Here are a few signs that indicate your organization has data silos:

1. Legacy systems

If each department in an organization employs different tools and technologies like CRM, accounting software, and spreadsheets, it can be a sign of data silos. These applications may possess proprietary data formats and are not designed to share data easily. Most SaaS applications do not provide end-to-end integration, and this makes it challenging to share data across departments. Incompatible systems and decentralized IT models thus impede collaboration and efficiency.

2. Lack of cross-departmental collaboration

When there is no collaborative culture between teams, it leads to data silos. It occurs when departments incorporate their own method to gather and store data, which creates a siloed mentality, discouraging combined business goals. It may cause misuse of resources and redundant work.

3. Unclear data policies

When there is no data governance and policies, each team develops its own way to store and collect information, creating inconsistent and fragmented datasets. Thus, unclear data policies lead to the creation of micro-silos across the organization. Without clear documentation, employees lack direction in data-sharing practices. This can lead to inconsistent handling of sensitive information, raising the risk of compromised data integrity and accidental leaks.

4. Poor data quality and integrity issues

If the team is utilizing inaccurate, incomplete, and outdated information, it is a sign of data silos within an organization. These data silos lead to inconsistencies, hindering strategic decision-making. Thus, organizations need to promote data transparency and ownership that can help departments understand the value of maintaining high-quality data.

Every year, poor data quality costs organizations an average of $12.9 million. –Gartner

How do data silos disrupt your business?

Data silos can significantly hamper businesses by obstructing their ability to operate efficiently and make strategic decisions. Here are a few ways data silos are harming your business:

1. Limited data access

Data silos across organizations make it challenging to access information when it is required most. It is isolated within a specific system or department that requires additional effort and time to locate and retrieve information. Thus, a lack of access to vital data can slow down processes and productivity.

2. Duplicate data

Siloed data often results in duplication or misuse of information.  The same data can be found in different tools and platforms with different accuracy and formats. This results in data conflict, leaving the decision-makers in a dilemma about the most reliable and up-to-date data source.

3. Limited data visibility

Data silos limit people from having an overall view of an organization’s data. Disconnected information hinders decision-makers from drawing meaningful conclusions, hence informed decision making becomes an uphill task. In addition, siloed data hinders pattern, trend and opportunity identification which can lead to innovations and business expansion.

4. Increased cost

Siloed data requires additional storage, management tools, and IT resources, thus increasing operational costs. Each silo is formed on separate infrastructure and maintenance, adding financial overheads. Integrating siloed data also demands third-party tools, increasing IT costs.

5. Reduced productivity

Data silos decrease team productivity because they take time to manually collect and aggregate information. In addition, more time is wasted on finding and reconciling data from different sources instead of concentrating on insights and decision-making. This inefficiency can slow the overall workflow pace and hinder real-time decision-making.

What are the examples of siloed data?

Siloed data can exist in nearly every department, often hidden within disconnected systems and tools. The table below highlights common examples across various functions and where this data is typically stored.

How to break down data silos?

Data silos can prevent organizations from collaborating, deriving insights, making informed decisions, and gaining maximum advantage from their data assets. Here are a few strategies to break down data silos.

1. Implement a data governance strategy

Breaking down data silos starts by implementing a strong data governance strategy that ensures transparency, defines ownership, and manages data effectively. This framework offers centralized access to vital data, reducing the risk of data silo. Data engineering can support this strategy by designing scalable pipelines and integrating frameworks that enforce governance policies, unify data across all systems, and maintain proper data structure across organizations.

2. Invest in a data warehouse

Siloed information restricts departments and individuals from analyzing, accessing, and responding to information effectively. This can be addressed by developing a centralized data warehouse that integrates data, allowing secure access to critical data company wide. Data science as a service in association with data warehouse and data lake eradicates data silos through analyzing and consolidating different data sources at scale, providing an aggregated actionable view for decision-making.

3. Implement business intelligence software

Data silos can be avoided with data integration using business intelligence software such as Snowflake that breaks down and consolidates data storage. The business tool enables decision-makers to access and interpret data from different sources in order to gain insight and facilitate efficiency. Snowflake services improve data accessibility using a cloud-based data platform to consolidate data from multiple sources into one system to enable ease of analysis and collaboration.

4. Train your staff

Educating teams on data and risk management best practices can demolish data silos. The training course should encompass the use of tools and cross-functional collaboration to harmonize data management with business objectives. Data engineering specialists assist firms in safely centralizing their data on a single, scalable platform, allowing data to be shared between organizations.

Benefits of a connected data ecosystem for business

Business functions become more efficient when data and platforms are integrated across the organization, enhancing productivity and efficiency. Here are some ways a connected data ecosystem supports valuable business outcomes.

1. Improves decision-making with clear insight

When all the data is in one place, decision-makers will get clear insights and can make decisions based on true facts and not on partial reports or assumptions.

2. Eliminates duplication and confusion between teams

When individuals and departments within the same organization access the same platform and tools for data, there is less chance for back and forth. Thus, reducing errors and enabling each department to stay on the same page.

3. Makes reporting faster and more accurate

Unified data sources help teams avoid the entire steps of pulling down data from multiple sources or manually combining spreadsheets, reducing errors and saving time.

4. Supports better customer experiences

As sales, marketing, and service teams access the same unified customer information, they can offer personalized support in real time, enhancing customer experience and customer service efficiency.

5. Helps your business adapt more easily to change

Whether your organization is exploring new market opportunities or there is a sudden change in the business strategy, unified data helps your team to work swiftly by adapting to new changes. This eliminates the need to chase down missing pieces.

6. Improves cross-departmental collaboration

As data is easily accessible to every team, it enhances teamwork. Moreover, it helps everyone to understand how their efforts contribute to the overall business goals.

Cloud is the future of data storage

Cloud platforms are efficient tools that businesses can use to store and access their data, breaking down data silos. It offers scalable and flexible solutions to access data securely, supporting distributed and hybrid work environments.

Deloitte emphasizes that cloud platforms facilitate the breakdown of data silos, enabling data scientists and algorithms to get easier access to data.

Moving to the cloud enables organizations to integrate scattered systems, eliminate legacy processes, and ensure everyone has access to accurate and up-to-date information. This helps teams to collaborate efficiently and align data with business goals, even as data continues to increase. For companies looking to break down data silos to stay competitive, cloud solutions offer a clear path.

FAQs

1. What are the risks of having data silos in your business?

Data silos have significant risks such as hindering collaboration, restricting access to vital data, reducing productivity, limiting data-driven insights, and increasing IT costs.

2. Are data silos good or bad?

Data silos can negatively impact business operations by limiting data visibility and creating duplicate and inconsistent data, impacting decision-making capability.

3. What is the impact of data silos on customer experience?

Data silos can lead to missed revenue opportunities, as service teams struggle to access the insights needed to engage customers effectively and upsell relevant solutions.

4. Can cloud platforms help eliminate data silos?

Yes, cloud platforms can eliminate data silos as they offer flexible and scalable solutions to store and access data. Integrating cloud platforms like Snowflake can unify data at one source, enhancing business operations and customer experience.

5. What tools or technologies help prevent data silos?

Data engineering, data science as a service, data warehouse, and Snowflake services can prevent data silo by integrating data and tools to enhance accessibility and data visibility.

6. What is the difference between a data warehouse and a data silo?

A data warehouse is a system where data is easily stored and managed to offer quick access to data when needed. Data silos refer to pockets of information stored in an isolated system, which is not designed to integrate with other systems or tools, limiting access to data.