How many data silos are there on average in companies?

The number of data silos varies depending on company size and industry. Studies show that large companies often operate several dozen to over 100 isolated data systems. Even in medium-sized companies, 10 to 20 silos are not uncommon. These are the result of different software solutions, departmental structures and inadequate data integration strategies.

What are the hidden costs of data silos?

In addition to inefficient workflows, data silos lead to higher IT costs for maintenance, storage space and redundant systems. They also tie up valuable human resources, as employees have to merge data manually. Security risks also increase, as fragmented data is more difficult to protect. Energy consumption also increases due to inefficient storage structures.

How does breaking down data silos affect sustainability?

By merging data, redundant storage solutions can be reduced, which lowers energy consumption. More efficient processes mean less paper consumption and optimized use of IT resources. In addition, companies can make data-based decisions to develop more sustainable business models.

What role does artificial intelligence play in breaking down data silos?

AI can help to harmonize data from different sources and identify patterns. Automated data cleansing and integration make it easier to link isolated information and make it usable. AI thus improves data quality and enables more efficient analyzes.

Which departments are most affected by data silos?

Sales, marketing and customer service are particularly affected, as they often work with inconsistent customer data. Data silos also arise in logistics and production due to different ERP and planning systems. The more interdependent the departments are, the greater the negative impact of fragmented data.

Why do data silos keep reappearing, even once they have been dissolved?

Data silos are often created by the use of new software solutions that are not integrated into existing systems. Organizational changes, such as mergers or departmental restructuring, can also create new silos. Without a long-term data strategy and clear governance rules, the risk remains that isolated data will re-emerge.

What legal risks arise from data silos?

Data silos make it difficult to comply with data protection regulations such as the GDPR, as companies often do not have a complete overview of personal data. This can lead to compliance violations, especially if data is stored unsecured or without authorization. Transparency and erasure obligations are also more difficult to implement.

How does the dissolution of data silos affect customer satisfaction?

A uniform database enables companies to offer personalized and consistent customer experiences. Customers do not have to enter their information multiple times, receive faster responses from support and benefit from customized offers.

Resolve data silos efficiently

Without data silos, companies benefit from reliable, correct and unambiguous master data at a central point

Customer master data is very often spread across the entire company in data silos. Departments or newly developed business areas cannot access all master data. The game changer is a holistic view of customers and business partners.

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Where do data silos come from in companies?

Nowadays, companies and their customers and prospects are usually active in both the digital and analogue worlds. This results in many online and offline touchpoints. The data from customers and prospects that is collected via these interfaces in a company inevitably ends up in different systems. These data silos can be CRM, ERP or customer experience management systems, or even simple Excel lists.

And then it happens: data about a person is scattered across the entire company, across departments and divisions; in a global enterprise context, even across national borders. There is no central data storage. In addition, there are usually different data quality standards because definitions are missing. There is also often no uniform understanding of how the data should be maintained.

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This leads to data silos

Data silos due to departmental thinking and lack of collaboration

Companies are often divided into different departments each of which has its own processes and systems. Without a common understanding of data, each department sticks to its own data maintenance and use, creating silos.

Data silos due to different IT systems and incompatibility

Different departments often use completely different software solutions that are not compatible with each other, or only with difficulty. If there are no interfaces or integrations, the data inevitably remains isolated in its data silos.

Data silos due to a lack of central data strategy

Without a clear strategy for data management, teams collect data independently without sharing or consolidating it with other areas of the company. This also has a negative impact on the efficiency of processes.

Data silos due to data protection and security concerns

Certain data may only be made accessible to certain departments for legal reasons. These restrictions can unintentionally lead to data silos. This applies, for example, to data that is particularly worthy of protection, such as health and patient data.

Data silos due to technical and organizational legacy issues

Historically grown structures, old systems and legacy software often make it difficult to exchange data between different systems and departments. Modernization is expensive and complex, so old silos remain.