Breaking Data Silos: The Worst Nightmare of Any Organisation

Discovering Data Silos within enterprise’s infrastructure is not a good new for anybody. They prevent the business teams or IT workers to extract value from data.

In short, data silos occur when organisations build systems around individual applications rather than designing applications around a shared, unified data foundation. Each department adopts tools that store and manage their own data independently, creating isolated pockets of information.

Over time, this application-centric approach leads to duplication, inconsistencies, and limited visibility across the organisation.

In this article, we’ll have a look to explain why data silos are harmful?

What are the types of data silos?

Most of the time, we count 3 types of data silos that making collaboration and strongly hinder the entire process of decision-making:

• Departmental silos: This occurs when multiple departments have separate databases. This generally leads to duplicate and inconsistent data. It also creates challenges in adopting a common data governance framework, as data is used differently by each team. This makes it harder for individuals to share data for business purposes.
• System-based Silos: Data is split between CRM (Customer Relationship Management) like Salesforce and ERP (Enterprise Resource Planning)systems such as SAP  systems when there is no coordination or interaction between the teams responsible for managing the data and fostering business value.
• Geographical Silos: Offices store localised data without central visibility. For example, an international company with locations in the US and France may not share the data they create or collect.

Why it is bad for data governance?

Well, data silos are a mess for data governance as they mostly isolate departments and data they daily manage to the point it impacts the conception of data governance as each team will have their own vision and multiple definitions of data. This lead to organisational fracture and block as company lacks of cross-functional collaboration.

From a cultural point of view, data silos prevent the encouragement of teams to follow guidelines and best practices in manipulating data such as ownership, transparency and communication. It creates barriers and walls, while data should allow the opposite.

As mentioned above, they conduct to poor decision-making as these are based on conflicting metrics between departments.

Sometimes, datasets are not even properly stored in centralised repositories. Instead, they remain scattered across spreadsheets, local drives, emails and individual team tools. Without formal capture, documentation, and maintenance, data becomes difficult to track, validate, or share. Without proper repository management, the risk of data loss, inconsistencies and compliance issues increases, further deepening the problem of data silos within the organisation.

How to Break Down data silos?

Rest assured, dealing with data silos does not mean you are incompetent, or that the situation is hopeless. On the contrary, this situation may simply be the result of inadequate data flow and structural transfer inefficiency on a global scale.

In our case, the goal is reducing the risk of data silos at best possible level. For this, there are plenty of options available, starting with the creation of a data governance framework. In doing so, you establish clear data ownership and managing data policies at organisational-scale. It enables the enterprise to have a common definition of data and share it in compliance of regulations, laws and rules of the enterprise.

By doing this, you enforce data culture and promoting a cross-functional collaboration, and enhancing at the same time transparency.

Finally, one of the most recognised solutions is to build a common, centralised data platform, such as a data warehouse or data lake, where data from different systems can be integrated, standardised, and made accessible across the organisation. At last, Equally important is strong leadership support.

Overcoming Data Silos to Unlock Organisational Value

In conclusion, data silos are harmful because they prevent organisations from fully unlocking the performance improvements and return on investment that data can deliver. When information is fragmented across systems and teams, data innovation is significantly reduced.

To overcome this challenge, enterprise leadership must actively support initiatives that promote data integration, shared governance, and cross-departmental collaboration. This includes investing in modern data platforms, establishing clear data ownership and standards, and fostering a culture where data is treated as a strategic organisational asset rather than a departmental resource.

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