Dissolving Data Silos: Companies Need To Define a Common Data Language

BARC (Business Application Research Center) today published the results of its topical survey “Data Black Holes – Are Data Silos Undermining Digital Transformation?”. In the study, BARC analysts Jacqueline Bloemen and Timm Grosser take a close look at the implications of data silos for the data-driven enterprise and offer insights into the main challenges companies are currently facing due to data silos.

The study is available for download free of charge thanks to sponsorship by Ab Initio, Collibra, Dataiku and Denodo.

Key Findings:

• Central data provisioning is not the one and only key to success when it comes to dissolving data silos
• Having uniform business terminology helps companies to step up their game when it comes to coping with data silos
• Organizational silos have to be taken as seriously as data silos and need to be addressed by management Dieses Thema sollten Management-Teams angehen.

According to a new BARC survey, many companies are struggling with the consequences of their current data landscape. When asked about the biggest challenge in the use of data, there is a clear message from participants. 41 percent agree that having key personas tied up with elementary data problems instead of working on the digital future of the company is the most pressing issue.

This leads companies to the conclusion that action is required: 27 percent are already working on raising awareness of existing data silos and their consequences. A further 33 percent are planning to take this measure.

Centralized provisioning of data does not necessarily ensure simple and efficient data use

The central provision of data for analyses is often regarded as best practice. The majority of companies (63 percent) therefore pursue a corresponding approach. However, central data provision is neither a prerequisite nor a guarantee for a uniform and overarching business terminology for data – despite the widespread assumption.

The study results show that investments in defining uniform business terminology pay off. Companies that have not implemented such terminology have significantly more problems in using their data to address new questions. This includes companies with a central data warehouse that is undermined by individually created data sets.

But even a common data language is not the sole remedy. Companies that have implemented uniform terminology in a decentralized data landscape clearly have fewer problems using their data than those without common terminology, but not as few as companies with a centralized data landscape.

“In the future, it will become even more difficult to manage data in a centralized manner. The data landscape of the digital enterprise is highly distributed. In other words, we must live with data silos. Solution concepts must integrate data silos instead of fighting them,” said Jacqueline Bloemen, Senior Analyst Data & Analytics at BARC and co-author of this study.

This is reflected in the approaches that companies are taking to deal with their challenges (see Figure 1).

Knowledge about data, but not the data itself, should be provided centrally. The most frequently chosen approach to this is to create transparency about existing knowledge of data and foster collaboration (49 percent). This goes hand in hand with establishing a platform for collaboration and knowledge exchange, which 34 percent have chosen to do.

Another 30 percent state that they are creating a central directory for finding and understanding data sources. These approaches are mostly implemented with the help of data catalog technologies.

31 percent of companies are working to liberalize access to data and improve self-service support. This is in line with other measures to facilitate ad hoc access to data. For example, 36 percent plan to create a central platform for data shopping. Among best-in-class companies, this approach is even more common (45 percent).

One building block for this is to make physically distributed data accessible without having to copy it. This plays a greater role especially for companies with distributed data provisioning (27 percent compared to 23 percent on average). However, with the named approaches taken to deal with the challenges caused by data silos, a new set of challenges arises.

Business and cultural challenges are obstructing efforts to address data silos

In principle, all companies strive for digital transformation. However, they face several business and cultural challenges in this process (see Figure 2).

The highest rated concern, lack of communication (56 percent), is in stark contrast to another study finding with companies reporting that data and information is shared extensively between departments. The fact that this apparently does not really work in practice is also underpinned by the second-highest rated problem: a lack of motivation to share knowledge with others (42 percent).

Further challenges include a lack of clear strategic goals and a lack of understanding of what these mean in practice.

“Some learning processes can be supported bottom-up. However, when it comes to strategy and goals as well as the behavior of people in the company, it is clearly the managers who are called upon,” said Timm Grosser, Senior Analyst Data & Analytics at BARC and co-author of this study.

A lack of management support was ranked as the third most important challenge in the implementation of strategic measures at 38 percent. For companies with decentralized (42 percent) and hybrid (43 percent) data landscapes, as well as for laggards (58 percent), this applies even more frequently.