Guide to data silos, their effects and how to overcome them

By Indeed Editorial Team

Published 5 June 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Many modern organisations rely on data to help them make decisions and track their performance. When this data becomes fragmented and isolated within certain parts of the organisation, you get the phenomenon of data silos. If you work with data, understanding these silos and their consequences can be very useful. In this article, we explain what data silos are, how they happen, their negative consequences and how you can address them.

What are data silos?

Data silos, also known as information silos, refers to data that becomes separate from the pool of centralised data that organisations can access. This can happen when a certain unit or department within an organisation stores data in a closed or incompatible system which others within the organisation cannot access. The absence of access could be due to dataset compatibility or separate storage. A department might have its own IT budget or independent data gathering activities, in which case it may decide to start storing its data independently and without making it accessible to others within the organisation.

These silos are therefore a problem in most cases. Various professionals within the larger organisation who rely on data, such as decision makers and analysts, might therefore lack access to enough data to do their jobs properly. Their own datasets might be incomplete as a result, causing issues with their attempts at data-driven decision making. Organisational leaders might encounter similar problems, as they might rely on the findings of analysts and others to develop plans and strategies. Moreover, siloed data can be indicative of a lack of intra-company communication and collaboration.

Related: What is SQL? (With definition, benefits and comparison)

How do information silos happen?

There are various causes for this phenomenon, some of which relate to the organisation as a whole. Here are some causes of information silos which can help you to understand how they work:

Organisational structure

The structure of the organisation itself can be a cause of siloed data. A common example is when organisations adopt a decentralised approach. This can have many benefits, as departments and units that have more autonomy might be more effective in many cases. The challenge arises when each of these uses separate IT departments or infrastructure. In these scenarios, an absence of active collaboration between these decentralised units can lead to siloed data, as each unit gathers and stores its data separately.

Each department might therefore acquire its own cloud-based data storage system or even computer hardware, without ensuring that others also have access when necessary. A siloed organisational structure can therefore lead to siloed data. In addition to decentralised organisations, large internationals with multiple subsidiaries can encounter the same issues if they don't actively implement solutions. This can become more likely when a larger company acquires another, as this can introduce a new data silo due to organisational differences.

Organisational culture

One of the issues with siloed data is that it can indicate a lack of intra-organisational collaboration and communication. This is why the culture of the organisation can be a key contributor to this issue. Moreover, the wrong kind of culture can cause this to occur even if the organisation as a whole is relatively centralised. Although it can be healthy for departments to be somewhat competitive, this can lead to a lack of cooperation. When this extends to the sharing of key resources like data, the result is information silos.

The issue can also arise simply because the company has an outdated culture, rather than an non-collaborative one. Big data is a modern phenomenon and some older companies might still be adapting to take advantage of it. They may therefore lack the experience necessary to understand what's necessary to fully utilise the potential of the data they collect. In some instances, key individuals and leaders may simply be unaware of the untapped potential.

Related: Organisational culture importance: Benefits and examples

Absence of a data management strategy

When organisations have an important resource, they typically have some sort of strategy in place to manage it. For a modern company which is able to gather lots of data, this data is an important resource. Either due to the organisation's priorities, resources or available expertise, they may simply lack a cohesive, organisation-wide strategy for managing data. This can lead to various professionals trying to develop improvised solutions for managing it, with no centralised data management strategy which ensures that there's common access for those who require it. When these various improvised solutions lack coordination, the result is siloed data.

Technology

There are two ways that technology can cause siloed data. The first is when organisations don't have the necessary technology to share data easily, which can be the case with legacy systems that lack the features for centralised data sharing. The other cause is when various individuals and departments use different technological tools which aren't compatible. For example, one department might use spreadsheets to store data, another uses SQL databases, another uses accounting software and another employs something improvised. Moreover, some may store it locally on organisational hardware, whereas others might use an external cloud-based storage service.

Related: What is information technology? (With skills and careers)

Consequences of siloed data

Here are some of the consequences of siloed data for organisations:

Incomplete data

When various units within an organisation don't share data, the data sets that analysts and others use could be incomplete. When an organisation relies on data-driven decision making, the absence of complete data could undermine this process. Another job of data analysts, data architects and similar professionals can be the development and maintenance of centralised databases, which can become more difficult when a lot of the data is siloed.

Siloed mentality

A siloed mentality is when various organisational units or departments start to act independently and without regard for intra-organisational cooperation. They may become reluctant or uninterested in sharing their data, especially if they disagree on the best ways of managing and storing it. Since siloed data can result from a company culture lacking collaboration, a siloed mentality can be quite likely in many circumstances.

Inconsistency

Even if analysts can access the data of other organisational units, the lack of common technology or formatting can cause further challenges. Data analysts and data architects might spend a lot of time simply trying to clean and organise the data properly so that it's all in the same format and easily accessible. In the absence of a good data management strategy, this could regularly take up a lot of time that they could otherwise dedicate to analysing the information and deriving valuable insights.

Related: What is a data architect? (Job definition and roles)

Data security risks

When an organisation's departments or units each employ a different data storage approach, this can increase the risk of a data security breach. This can become more likely when a unit improvises a solution due to a lack of available expertise. Without a centralised system that incorporates data security measures and professionals who know how to protect it, various data silos can become vulnerable to data security risks.

How to overcome data silos

Here are some steps to consider if you want to overcome the issue of siloed data in the organisation in which you work:

1. Introduce a data management system

A good first step is to introduce or suggest a centralised data management system. This is best at the organisation-wide level, as this is the most likely way of identifying and overcoming siloed data. A key part of this data management system is integrating existing data silos, which is possible with something like ETL (extract, transform and load).

2. Address organisational culture

If the culture of the organisation is a contributor to siloed data, it can be a good idea to try and address this. Arranging meetings or workshops with departmental and team leaders can be useful in this regard, whereby you impart the importance of intra-organisational cooperation and communication. This can also help avoid any future instances of siloed data from developing.

3. Hire new talent

In many cases, an organisation may simply lack the expertise to avoid siloed data. In this case, it can be a good idea to suggest the acquisition of new talent. This could be a consultant with experience in developing and implementing data management systems or permanent staff with special responsibilities for centrally managing the organisation's data. The advice and recommendations of an experienced consultant can also help guide the hiring process for these professionals.

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