Self-Service BI: Blessing or Burden? Dive into Benefits, Challenges, and Solutions

For many organizations, Business Intelligence (BI) is the core for making data-driven decisions. Although BI has been around for a long time, it continues to evolve and initiate revolutions. Thanks to tools and platforms such as Power BI, Tableau and Qlik Sense. An approach that has been around for a while, but has really been booming lately, is self-service BI. Self-service BI allows business users to independently access, visualize, and analyse data. The thinking behind it, is that it increases agility, reduces IT dependency, accelerates decision-making and promotes a data-driven culture and data democratization.

Although this sounds very promising for organizations, it also introduces challenges and potential pitfalls. This blog examines the benefits and drawbacks of self-service BI and offers strategies to mitigate the associated risks.

Why does self-service BI sound promising?

Self-service BI tools are designed with user-friendly interfaces, such as intuitive dashboards and drag-and-drop functionality, making data analysis accessible to non-technical users. Think about reports and dashboards in Power BI, Tableau and Qlik Sense. These tools integrate seamlessly with various data sources and display your data in an incredibly attractive and interactive way. The customization and flexibility offered by self-service BI enable users to create tailored reports and perform advanced analytics without extensive technical expertise. That sounds great! But there is more ...

The collaboration features in these tools improve teamwork by making it easy to share insights and annotations directly in reports. Of course, it also makes it quite easy to share your report with a colleague. And today we also have AI (Artificial Intelligence) features that allows you to generate datasets, reports, and insights, such as with Copilot in Power BI. By empowering business users with these capabilities, self-service BI reduces dependence on IT departments, speeding up the decision-making process and promoting a more efficient, data-driven environment.

This approach can also lead to cost savings, as it optimizes resource use and lowers operational costs. The licensing models of these tools are quite specific and different from traditional BI tools, as they are usually offered as 'Software-as-a-Service'. Moreover, self-service BI tools often come with educational resources that help improve data literacy across the organization, promoting a democratized access to data.

Translating this information into a tool like Power BI as an example: It is accessible (MS Office look and feel), Power BI Desktop is free to download, easy to integrate within other Microsoft products, it is not expensive (or it is already part of your O365 license), easy to collaborate and share reports with colleagues, and very flexible as it can easily connect and combine many different data sources. And it only costs approximately €9,40/user (Pro license) to get started.

If you’re thinking, this is what we need! Let us get started right away! ... Hold your horses, do not get too excited yet, we need to elaborate more on this in the next topic. 🙂 This seems promising, but we also notice challenges with our customers at Datashift.

The challenges of self-service BI

Despite the benefits, self-service BI is not without challenges. Data governance issues are a primary concern because the democratization of data access can lead to inconsistencies in data interpretation and potential security risks. As more users interact with data, ensuring compliance with regulatory requirements becomes more complex. Furthermore, the ease of access to copious amounts of data can overwhelm users, leading to data misinterpretation and information overload.

Getting self-service BI of the ground

There are also technical challenges, especially in integrating self-service BI tools with existing systems and managing performance bottlenecks as user numbers and data volumes grow. The user's skillset is another major obstacle; Many business users may not have the necessary skills to use these tools effectively, leading to underutilization or errors.

The initial investment in self-service BI can be significant, including costs related to licensing, user adoption and roadmap, and fundamental data models. In addition, ongoing maintenance and support contribute to the total expenditure. It is important as an organization to define a roadmap and assess the as/is and to/be to define the foundations before implementation. By doing this exercise you will be better prepared in areas such as investments, maintenance, and support.

One single version of truth

Self-service BI tools are very flexible and can easily connect different data sources. This may seem like a great advantage, but it also brings problems. Such as BI tools that are used as 'data export' tools for carrying out operational tasks (instead of solving the problem in the source application). Some organizations are also considering a 'real-time' data connection for 'live' reporting. This sounds like a game changer, but it is only valuable with the right use cases. The line between operational analytics and executing operational tasks is very thin. The ability to connect many different data sources to export data, and misunderstanding real-time data, poses enormous risks when trying to maintain the ‘single version of truth’ as an organization. And this is also a risk of putting too much strain on the operational systems if this is not considered.

The rise of data silos is another potential challenge, with different departments maintaining separate data sets, hindering a unified view of the organization's data landscape. Again, as an organization you want to secure the ‘single version of truth.’ This already feels like a recurring concern.

Finally, cultural and organizational challenges also play a role in the adoption of self-service BI. Employees accustomed to traditional BI methods may resist the change, and fostering effective collaboration between IT and business users can be difficult, especially when there are differing priorities or communication gaps.

Stay balanced while walking the ‘self-service slackline’ with managed self-service BI

Adopting a balanced approach that combines self-service BI with managed BI, as ‘managed self-service BI’, can be a viable solution. This hybrid model balances the autonomy of business users with the oversight of IT departments, ensuring data accuracy, the ‘single version of truth’, security, and consistency. Centralized data management and governance frameworks help maintain data quality and compliance, while controlled access and guided self-service features empower users without compromising security. The 'Center of Excellence' (CoE) plays a crucial role in this approach and determines and monitors the implementation of self-service BI, and then onboards and supports the self-service users within the organization. It is the beating heart where both business and IT people come together and build a data community within the organization.

Microsoft Fabric Adoption Framework

To be able to find a balance between business-led self-service and enterprise BI, frameworks such as the ‘Microsoft Fabric Adoption Framework’ can help determine the strategy. This framework provides a structured approach to implementing self-service BI solutions, emphasizing governance, security, and best practices. By following such a framework, organizations can better align their BI initiatives with overall business goals, allowing both business users and IT departments to collaborate and use data effectively. The result is a self-service BI implementation, balanced and tailored to the needs of your organization and users. And as already mentioned, it is important to define a roadmap and assess the as/is and to/be to define the foundations before implementation.

By implementing these strategies, organizations can leverage the advantages of self-service BI while minimizing the risks. Embracing self-service BI with a well-thought-out strategy ensures that the benefits outweigh the challenges, leading to a more agile, informed, and data-driven organization.

Are you looking for support in implementing (managed) self-service BI in your organization? Do not hesitate to contact Datashift! We would be happy to discuss how we can help you further and tell you how we have applied this to our customers.