Self-service BI tools are quickly becoming the pillars of success in companies across the world. In today’s competitive environment, putting the analytical power into the hands of business users, who can make fast data-driven decisions, could be the difference between winning and losing.
The deployment of self-service BI gives business users opportunities to run their own queries, analyze data, build reports, and focus on insights that are most relevant to their lines of business. The best part is that business users can do all these things with minimal efforts from IT departments.
This sounds great and promising; however, before companies rush into BI deployment projects, they need to make sure that a few important requirements are met.
Most companies are not ready for BI deployment
The biggest challenges in the deployment of self-service BI are organizational readiness, data quality and governance.
“Most organizations are not ready for it,” said Brian Moffo, a project director at the software vendor IPipeline Inc., as cited by TechTarget.
Prior to deployment, companies need to establish right processes that enable proper training, good data governance, a scalable infrastructure that could then be upgraded to a full-scale enterprise-level BI program.
Simply introducing and turning on the data valve in an unprepared environment could be an unwise decision. For example, different versions of data might appear, or exploratory version of data could be incorrectly marked as “truth” and then published as facts, leading to misinformation and potential trouble.
Best practices in BI deployment
Below are some key best practices for self-service BI deployment projects that will help your company to go through the process without major issues.
- Different companies have different needs and objectives, and as a result, there are different ways to deliver BI projects to them. What will work for a medium-sized company with strong data culture may not be suitable for a large enterprise. That is why knowing your objectives and creating a clear plan of action are the important first steps.
- Before deployment, critically assess the maturity of your business and most importantly the maturity of your IT department. Some self-service concepts can be quite challenging for IT departments. It is essential to know beforehand that IT specialists understand what exactly is expected from them and how they are going to deliver it. This idea was shared by Isabelle Van Campenhoudt, managing partner at ShareQL, during her presentation at the Community Summit Europe earlier this month.
- Although the key idea behind self-service BI is autonomy of users, self-service “is not anarchy and it must be controlled,” said Isabelle. Monitoring and controlling is an essential part of the deployment process, as things can quickly get out of hand, if not carefully managed. Self-service does not mean managing data without the IT department, but rather freeing them from doing tasks, such as changing the colors and types of visuals and allowing them to focus on more complex data governance, security, and architecture processes.
- Cultivating data culture within an organization is a must. If there are users who are not familiar with BI, providing diverse trainings and creating a learning environment for everyone is a key. At the end of the day, if users do not feel comfortable using new software, even best tools will not be adopted. No training, no adoption.
- To follow on the previous note, it is important to constantly provide support and develop “champions” and power-user culture within departments. Analysts from functional department know their data best. That is why they should take the lead in building visualizations and data models, while IT staff can handle the back end and overall infrastructure. From there, one should identify power users within each business unit, who can then help to develop tools, models and visualizations that serve the needs of each department’s daily workflow.