What is Self-service BI, and How Can It Be Done Right?

Have you ever felt stuck waiting for some crucial reports you desperately need? Or maybe you’re not utilizing your data the right way to make quicker, more informed business decisions. If you can relate to these issues, then you might need to consider self-service BI!

How often have you come across detailed datasets and insights that you don’t know what to do about? Probably more times than you can count on your fingers!

It’s difficult to derive conclusions from data without understanding what it truly means. This is where business intelligence (BI) comes into play. BI uses your data and presents it in a simplified manner through different visualizations. It allows business leaders to organize and analyze data to make intelligent, informed decisions.

However, traditional BI approaches usually rely on centralized data teams and IT-led deployments, which have struggled to meet the increasing demand for data-driven insights from users across the organization.

According to Gartner, businesses that embrace self-service BI capabilities are 2.2 times more likely to provide users with the data they need to make informed decisions. Those who invest in business intelligence (BI) tools and strategies will be able to extract meaningful insights from raw data quickly. 

In this write-up, we will discover self-service BI, why organizations fail at it, and how to do it right.

What exactly is Self-Service Business Intelligence (BI)?

Self-service BI is often defined as a form of BI that allows business users to rapidly and easily discover, analyze, and glean insights from data without having to deal with IT or a BI expert/developer. It revolves around several key aspects:

• Data Access: Users can directly access relevant data sources or analyze the information needed to make decisions.
• Analysis and Reporting: Autonomous BI tools help users run complex data analyses, develop interactive dashboards and reports, and find meaningful insights with minimal expert assistance.
• Agility and Flexibility: It enables organization users to act fast when requirements change and fosters the capability of developing insights at their own pace instead of waiting for IT experts.
• Democratization of Data: Self-service BI provides widespread access to data within an organization, empowering all users to make better decisions.

Traditional BI vs. Self-Service BI

The traditional Business Intelligence (BI) approach involves gathering, analyzing, and presenting business data through a centralized data warehouse, with reporting processes driven by the technical team. 

In contrast, self-service BI is a more modern approach that allows business users to access and analyze data with less involvement of technical teams. Let’s discuss their fundamental differences in more detail.

Traditional BI	Self-service BI
Centralized Data Control The technical teams tightly control data access and analysis, limiting business users’ ability to explore and leverage data independently.	Decentralized Data Access Self-service BI empowers business users to gain independent access and extensively explore the relevant data sources, fostering a much more agile and actionable decision-making process.
Lengthy Reporting Process Generating reports and dashboards requires users to submit requests to the IT or BI team, delaying obtaining the necessary insights.	Rapid Insight Generation This meant that with self-service business intelligence tools, users could create their own reports and dashboards, enabling stakeholders to quickly develop insights and respond to the business’s emerging demands.
Specialized Technical Expertise Traditional BI requires specialized technical skills; hence, participation in the data-driven decision-making process may be complicated for employees who lack technical expertise.	User-Friendly Interfaces These BI solutions are designed to be user-friendly, intuitive at the user interface level, and aimed at allowing business users to work with data without requiring significant technical skills.
Rigid Processes Traditional BI is quite inflexible, so the ability to quickly adapt to changing business requirements or add a new data source was out of the question.	Agile and Adaptive Self-service BI empowers an organization to respond quickly to businesses’ evolving needs and thus incorporate new data sources into a dynamic decision-making process.
Limited Democratization In traditional business intelligence, data and insights are available only to a few stakeholders.	Democratization of Data Self-service BI democratizes access to data, empowering users across the organization to become data-driven decision-makers and contributing to a more robust data-centric culture.

Notable Benefits of Self-service BI

• Empowered Business Users: Self-service BI tools put the power of data directly into the hands of users. Instead of relying on data analysts to extract reports and perform analyses, they now access and analyze data on their own. 
• Faster Time-to-Insight: One of the standout benefits of self-service BI is how quickly it allows you to gain critical insights. Stakeholders can dive into data, test different scenarios, and uncover valuable insights without waiting for technical teams or analysts to fulfill their requests. 
• Increased Agility: Self-service BI enhances an organization’s ability to adapt swiftly to changing business needs. Users can easily create custom dashboards and reports, which means they can address new questions or shift requirements on the fly. 
• Reduced IT Backlog: Self-service BI reduces the pressure on the IT department, as users are responsible for their own data exploration and reporting. This shift allows the IT team to focus more on strategic projects and enterprise-level initiatives rather than being bogged down by routine data requests and report generation tasks.
• Improved Data Literacy: Many self-service BI tools have user-friendly interfaces and guided analytical workflows. This helps stakeholders become more comfortable and skilled in working with data. 

How to Implement Self-Service BI Within Your Organization?

Implementing self-service BI encourages everyone in your organization to discover valuable insights from data. However, Cubix specializes in making this transition seamless by helping teams turn complex data into actionable intelligence for smarter decisions and growth. 

This step-by-step approach will give you the ability to become a data champion.

1. Define Your Objectives

The process starts with the most critical step, outlining the goals you want to achieve through self-service BI implementations. Whether your objective is to reduce reporting delays or to provide organization-wide data access, it’s crucial to have clear goals. 

You have to begin with what you aim to achieve with this initiative. Because clearly stating your goals will help you guide the implementation process and set the stage for success and overarching goals. 

• Have you identified the user types for the BI project?
• Have you assessed users’ technical skills for the BI tools?
• What data sources will users need access to?
• What types of analyses will users perform?
• Have you clearly defined your project objectives?

2. Engage Stakeholders Throughout the Project

Successful self-service BI implementation involves all stakeholders throughout the execution. It includes business leaders, IT teams, end-users, and anyone else who will impact it or benefit from the BI tools. These stakeholders will allow you to input data needs, success metrics, and usability requirements. 

Additionally, engage them regularly for feedback to ensure that the self-service BI tools meet their expectations and deliver relevant insights. This will serve as a purpose for the tool’s relevance and will create ownership and commitment among the stakeholders.

3. Choose the Right BI Tool

Select a self-service BI tool that aligns with your organization’s needs and technical environment. You must evaluate different options based on features, ease of use, and integration capabilities. Ensure the tool you opt for can handle your data requirements and support the analysis users need. You can consider the following tools when evaluating your options:

• CRM Systems: Salesforce, HubSpot
• ERP Systems: SAP, Oracle
• Data Warehouses: Snowflake, BigQuery
• Accounting Software: QuickBooks, Xero
• Marketing Platforms: Marketo, Mailchimp
• Project Management Tools: Asana, Jira

4. Establish Strong Data Governance

Robust data governance policies for consistency, accuracy, and security are compulsory for a successful self-service BI execution. You can start by developing a detailed data management strategy that includes master and metadata management. This strategy should outline how data is collected, stored, processed, and accessed across the organization to maintain data integrity. 

Define business metrics and set procedures for report quality validation. Differences in key performance indicators (KPIs) reports across departments can lead to conflicting reports and confusion. By setting up a suitable approach to metrics, you can ensure that all teams consistently understand the data. This is a key step in preventing inconsistencies in data performance.

5. Provide Comprehensive User Training

The key to realizing true power in self-service BI is user education. Organize training sessions tailored to different user groups based on their roles and technical proficiency. These sessions will cover everything from data analysis and visualization basics to more advanced topics for those requiring deeper insights. It enables the users to analyze, visualize, and model data independently. 

Foster continuous learning by setting a supportive environment where users can share knowledge and best practices. Turn learning into a continuous process by setting up continuous training through a supportive community or an expert forum on Slack or Teams to fill knowledge gaps and drive collaboration.

Ready to Take Control of Your Data?

Want to convert your data into actionable, meaningful insights? Cubix’s self-service BI could be the perfect solution for your business. 

Our team of 100+ data experts delivers high-quality, user-friendly BI platforms that accommodate users all over organizations. We don’t just provide tools; we engineer solutions that help us make informed decisions. Contact us today, and let our experts provide BI solutions to help you make smarter decisions.