Business leaders today are expected to leverage data to guide decisions and improve efficiencies. However, more than pivoting a traditional BI approach to deliver insights rapidly enough is required. Bottlenecks arise at every turn — from request tickets for new reports to reliant developers constrained by a long queue of requests. Meet self-service business intelligence.
Self-service business intelligence accelerates time-to-value by empowering a decentralized analytics model across the enterprise. Rather than IT teams or data experts being the sole proprietors of insights, self-service puts practical data discovery directly in the hands of business users. Intuitive drag-and-drop interfaces can readily translate questions into interactive visuals.
It makes tapping into data for decision-making dramatically faster while nurturing a data-driven culture throughout the organization. Let’s dive in and review how to break free from centralized reporting towards agile, self-sufficient insights.
Self-service BI: Key capabilities
For business users to effectively harness insights, self-service BI platforms must be designed with intuitive interfaces promoting self-sufficiency, flexibility, and collaboration.
Intuitive interfaces are crucial for adopting BI tools across business teams. These interfaces enable users to conduct productive analysis independently without needing extensive training or constant assistance from data experts. Essential features include drag-and-drop report building, allowing users to easily create reports and customize visualizations, and interactive dashboards for dynamic insights from aggregated data, with capabilities to delve into finer details.
Another vital aspect is visual data recovery, enabling users to conduct ad hoc analysis and intuitively combine data sources for new insights. Research shows that when using data recovery tools, organizational managers are 28% more likely to find information on time, when compared to those using dashboard managers and reports.
Data preparation capabilities are also important. They allow users to blend data from varied sources like CRM, ERP, and spreadsheets into integrated views and use transformation tools to manipulate data for analysis, including joins and aggregations. Data preparation is key to improving accuracy, efficiency, and speed.
Collaboration is facilitated by allowing users to share insights and reports quickly and enhancing communication through features like annotation and storytelling, enabling users to add context to the data.
Lastly, even in decentralized models, maintaining robust governance is paramount. This includes implementing security protocols to control access and editing based on user identity and ensuring centralized data sources for consistent reporting across the organization. There four areas of good governance in BI include: tool selection, data integration, analytics, custom BI tool work, user acceptance, training.
To be truly effective, these platforms must integrate core capabilities that empower business users to access, interact with, and communicate data insights.
Why do businesses opt for self-service BI?
This approach offers numerous crucial advantages, including reducing time-to-market for analytics products, empowering users, and enhancing data literacy and culture within the organization.
Accelerated time-to-market for analytics products
A primary advantage is the significant time savings it offers. Traditional BI processes often involve a small team of specialists handling many user requests. This can lead to extended time frames for project realization – a simple request could take a month or more from initial briefing to resource allocation and development of terms of reference. In contrast, self-service BI enables users to develop a Minimum Viable Product (MVP) within as little as a week. While these MVPs may not be ideal, they can start delivering value immediately.
Empowering independent data exploration and decision-making
Self-service BI tools empower users to analyze data and make informed decisions independently. This autonomy in data exploration increases users’ awareness and understanding of data, fostering a more data-driven decision-making process within the organization.
Enhancing data culture and skills
A significant, yet often overlooked, benefit is enhancing data culture and skills among business users. Even users who may initially be reluctant to engage with traditional or cloud BI tools find themselves learning and understanding the data their company collects. This increases their competence and contributes to a broader organizational culture that effectively values and leverages data.
Benefits of self-service BI
From faster decisions to increased data literacy, self-service BI tools provide valuable benefits to companies that want to create a data-driven culture. Here are some of the major reasons why companies are adopting self-service analytics tools.
Faster Insights: When business users can access data from any source at any time, without relying on IT, the insights flow faster, and decisions can be made without delays. Freed up from defining and communicating business requirements to other teams, users can more efficiently gain insights, make faster decisions, and stay one step ahead of the competition.
Deeper Discovery: Business users shouldn’t be restricted to linear, query-based analysis. Instead, they should have the freedom to explore relevant data any which way they like. An Associative Engine lets users uncover blind spots in data that would otherwise go unnoticed with query-based tools. Analytics are recalculated after each click while highlighting associated and unrelated values, so users always have context to guide their analysis and discover unexpected insights.
Increased Data Literacy: Data literacy is the ability to read, work with, analyze and argue with data. One-third of employees believe that data literacy will help them be more productive, while 22 percent believe it can help them reduce stress. Self-service BI tools can help organizations develop a data literate culture by giving all employees the opportunity to learn the language of analytics, easily visualize and explore data and advance their analytical skills.
Less IT Burden: With traditional business intelligence solutions, IT teams spend their time clarifying business requirements and preparing reports that are surely outdated by the time they’re delivered to data consumers. A self-service solution gives users the tools to build dashboards and reports to conduct analysis on their own. That means IT has more time for high-value work such as tending to data governance, ensuring data is clean and consistent, and prioritizing mission-critical application development.
Self-Service BI Best Practices
Set your self-service business intelligence initiative up for success with these best practices:
Governed access: BI tools that enable self-service let IT govern data quality while freeing business users to easily access and analyze that data. Governed libraries of data, measures, and dimensions let everyone work from a single source of the truth.
Data integration: An organization’s data typically sits in multiple systems. But an analytics platform with a native integration layer can bring it all together, allowing IT to quickly integrate new data sources quickly, eliminating backlogs.
Collaboration: Business users should have access to pre-built, governed data models, visualizations, and analytical worksheets that allow them to easily share data. Users should also be able to add their own content to apps for use by others.
On-demand apps, dashboards, and reports: An effective self-service analytics solution allows users to quickly create and share analytics apps, dashboards and reports. It also makes it easy to integrate data analytics assets into other apps and websites.
Anytime, anywhere access: Self-service analytics solutions should support touch-enabled, responsive, and full-featured mobile interaction offering a seamless user experience across devices so a path to discovery and insight is always available.
Conclusion
Businesses looking to empower their teams and increase efficiency should consider onboarding a Business Intelligence self-service tool. With increased visibility over insights, teams are better able to make data-driven decisions. Self-service BI tools have the added benefit of allowing teams to access deep discovery without having to rely on data analysts.
Self-service BI tools are an excellent way to reduce any organizational data burden, improve efficiency, and help teams collaborate and work more effectively.
