In today's insight-driven business climate, companies of all sizes are struggling to compete and turning to self-service BI tools for productivity benefits.
Some of them have sophisticated data teams in place, while others are relying on BI tools to show them the way. The latter group often makes the mistake of focusing on immediate needs, which can make scalability an issue down the road.
The organizations with sophisticated data teams and tech structures are constantly looking forward because they realize that business requirements and tech capabilities are always evolving.
"There is an increased interest in self-service analytics, driven by the changing business needs, but enabling self-service across the enterprise requires much more than just deploying user-friendly tools," said Lakshmanan Chidambaram, president of Americas Strategic Verticals at multinational information technology services company Tech Mahindra. "It involves the availability of clean and ready-to-consume data across the enterprise, which can serve as a single version of the truth."
Organizations implementing analytics and BI tools can take advantage of the following self-service BI benefits.
1. Improve decision-making
The main reason businesses first invest in BI and analytics is to improve decision-making. Self-service BI democratizes that, but the data must be easily accessible and its quality appropriate for the use case -- hence, the rise of data engineers who are creating data pipelines that feed BI and analytics platforms.
"COEs [centers of excellence] can stand up dedicated discovery environments for each business group to enable end-to-end discovery of BI capabilities or data analysis," said Sree Majji, senior vice president at Apexon, a Silicon Valley data engineering professional services company (formerly Infostretch). "Also, purpose-built platforms can be instantiated for fully governed versus loosely governed BI environments."
All this can come at unexpected costs, though -- up to five or 10 times the cost of initial procurement is due to software licensing, hardware, development and maintenance costs, Majji said.
2. Boost efficiency and flexibility
Both the business and IT welcome self-service because business professionals tire of waiting for IT to produce new reports or dashboards. Conversely, IT has its hands full keeping the lights on and grappling with increasingly complex IT stacks, while data teams would prefer to work on difficult problems.
Self-service BI benefits organizational efficiency by giving more people access to data through easy-to-use visual tools and AI-enabled search capabilities that provide information fast.
Reaping these benefits is a matter of technology, processes and people, though it's easy to assume a self-service BI tool will affect change without considering how.
"Whether your teams will adjust to evaluating their own data and running their own reports is heavily influenced by culture," said Joseph Harisson, co-founder of IT services company IT Companies. "Many seasoned firms' usual work approach may not be compatible with a self-service method."
3. Enable collaboration
Different people interpret analytical outcomes differently, which is why augmented analytics platforms "narrate" data visualizations using AI. Seasoned data professionals value some level of data literacy throughout the organization because it helps facilitate more effective collaboration between data professionals and non-data professionals.
The reality is the average business professional doesn't think like a data analyst, though they quickly discover, when using a BI platform, better queries enable better answers. This is why augmented analytics platforms suggest popular searches, and yet tools are not a complete substitute for thinking. Over time, non-data professionals improve their skills just using self-service BI, assuming the interface is simple enough.
Lakshmanan ChidambaramPresident, Americas Strategic Verticals at Tech Mahindra
One of the reasons some vendors, like Sisense, encourage data teams to enable the masses is because it facilitates bimodal data analysis. Business users can do simple analyses, while data professionals can tackle the difficult ones.
"The best approach is to establish a BI COE that defines self-service BI capabilities and tools," Majji said.
4. Reduce costs and provide financial benefits
The traditional BI model of requesting one-off reports is expensive and inefficient. Quite often, business professionals will ask IT for a report that isn't ultimately what they want, either because the business did a poor job of outlining its needs or IT misinterpreted what the business wanted.
Then, weeks or months may pass before IT delivers the report. Requests for other reports follow. In the meantime, everyone is anxious about time. The business wants answers now, and IT is too busy to be a real-time report or dashboard generation service.
Self-service analytics speeds decision-making at the business level, which reduces the traditional overhead associated with BI. Quite often, the queries have to do with some types of business performance, such as why a certain product is selling better in one location than another or why so much merchandise must liquidate at a low margin or below margin. Self-service BI helps individual departments optimize costs and outcomes.
If companies find themselves in a recession, cost-cutting and efficiency gain importance, Chidambaram said.
"Self-service analytics tools can be a great way to improve user data analysis, while keeping costs low and easily showing ROI," Chidambaram said. "We expect this category to continue to grow with more offerings and innovations in the coming years: self-service analytics, AI and ultimately fusing AI into processes to achieve operational excellence."