Many companies are still in the early stages of offering end users the data and tools they need to do self-serve analytics, visualizations, and reporting. A survey revealed that 64% opens a new window for chief financial officers to need more appropriate technology and procedures to convert data into insights. This also seriously damages the desire for informed decision-making grounded on quantitative facts and analysis.
Many companies offer Level 1 capabilities to business clients: Basic reporting is provided using BI tools, and employees email each other the results. Enterprise teams who get to Level 2 provide self-service BI and analytics tools that let users access their data and reports without IT help.
They drag and drop fields to finish their reporting needs and gain a fresh view of the data. Guided analytics also display links between related data, enabling users to uncover hitherto unknown information that could lead to new opportunities.
What is self-service BI?
One trend that is difficult to define is self-service business intelligence. In general, business users handle self-service BI tasks on their own instead of sending them to IT. Concurrently, users of BI tools should be given greater autonomy and responsibility. Because of its core tenet of user autonomy and self-sufficiency in utilizing corporate data, business intelligence becomes dispersed throughout the organization.
In addition to this broad concept, self-service BI encompasses several elements. Its significance primarily depends on the unique requirements of specific user roles. With self-service BI, users can do various tasks according to their role.
For example, casual users of BI might only require the ability to filter and sort data. In the same scenario, to quickly develop or enhance current reports, business analysts or power users might need to individually aggregate local data from many sources. Therefore, in a BI system, the amount of self-service required depends on user needs.
Why Enterprise Self-Service BI Maturity Hasn’t Increased
Why then isn’t self-service the company’s main concern right now? Business teams may have up to 25% control over IT expenditure and may have alternative goals, such as AI or digital transformation initiatives, according to FLEXERA’s Tech Spend Pulse report. Besides, writing standard reports takes time. Four to six weeks are needed by IT teams to compile requirements, build capabilities, and train users on new processes.
Consequently, even while 57% of respondents to a BI industry survey said they value self-service BI, end-user self-service ranks 11th out of 59th technologies and initiatives critical to BI, according to a Dresner Advisory Services report. This shows clearly that self-service BI investment and road mapping are still insufficient.
Why is Self-Service BI Important?
Business intelligence has historically been built on centrally deployed data marts or central data warehouses in many organizations. However, the techniques, systems, and software that were formerly thought to be data warehousing best practices are no longer adequate to satisfy the expanding demands of many modern businesses.
The need for business departments to have access to data and information at all times and locations is one of the reasons why businesses are using self-service solutions more and more. To stay ahead of the competition, businesses must take immediate action on fresh insights obtained through analytics.
Though they are still appropriate in many cases, traditional BI delivery approaches are unable to provide the agility and efficiency that rapidly evolving requirements require. An iterative approach (i.e., trial and error) to analysis is necessary to uncover new, potential business use cases and to fully utilize the economic worth of the available data because data volumes and sources are constantly expanding.
Because of this, there has been a growing need for straightforward, efficient, and user-friendly BI software solutions for some time now. Businesses want to give business users the ability to create or develop their own interfaces, reports, queries, and even data models. Even more advanced users are creating their own dashboards by assembling and modifying layout components from many sources for their individual needs and, increasingly, the needs of their teams.
But chief data officers know that teams have a great opportunity to quicken business momentum inside their companies if they can make better decisions faster. In business intelligence, self-service:
Utilizes standard metrics:
other business sectors use other metrics. When these many standards function properly, the decisions that result are more erratic. Still, they could, in the worst instance, lead to project failure or unanticipated financial losses. When business teams agree on key performance indicators (KPIs) and plan and operate using the same scorecard, more people can access new KPIs.
Produce a single data view:
Many companies employ reporting tools like Cognos, MicroStrategy, PowerBI, Tableau, and others that can be pointed at different data sources. Firms can consolidate tools, cut expenses, and simplify reporting processes. All chosen tools can also be made available via BI portal tools or a shared graphical user interface. Business users may make more consistent judgments when they have quicker access to their preferred tools and use the same data resources.
Facilitates quicker insight acquisition by teams:
Business users across finance, marketing, strategy, IT, and human resources can ask more focused questions, draw stronger conclusions, and get to market faster with self-service BI. More is accomplished by generative AI tools than just directing teams to the data that requires their attention. Before their competitors can, teams are able to spot and seize business opportunities.
More effective use of BI and IT resources:
Because business users can do their own impromptu analysis, self-service BI relieves BI and IT personnel of most of the design work for queries, visualizations, dashboards, and reports. They can then focus on higher-value projects and tasks requiring more technical know-how, such as creating complex queries and choosing data sets for corporate clients.
Speedier data analysis and decision-making:
Self-service capabilities help to reduce bottlenecks in BI initiatives by moving analytical work from a limited group of BI experts to business users. Company operations are accelerated by the ability of users to assess data, form opinions, and act more quickly.
A data-driven company:
More managers, staff, and business executives using BI tools mean that self-service solutions can help create a totally data-driven culture in the C-suite and corporate operations. It’s important to understand before starting that often this calls for a change in the culture of the company. The possibilities offered by self-service business intelligence and data analytics must be understood by both managers and employees, along with how to apply the new tools at their disposal and apply these concepts to their day-to-day jobs.
One and only source of truth:
Do-it-yourself data analysis at many companies leads to spreadsheet wars because there are several answers to the same or similar questions and no easy way to determine which is right. When verified source data is integrated with widely recognized standards for analysis and self-service BI tools are available to implement them, the results are more coherent.
Advantages over Alternatives:
By applying data more widely and making choices faster, a business can be able to create or maintain a competitive advantage in the market. This holds particularly true if the company uses self-service tools more widely and effectively than its rivals.
Increases operational efficiency:
Self-service BI allows users to create reports at any time, saving time and money on IT and data analytics assistance for specialized projects that only benefit a small number of users and have a limited return on investment. More time to work on more significant projects benefits teams that work in IT and data as well.
Reduces operating expenditure:
Companies that employ self-service BI and generative AI technologies must spend money up front for capital and personnel to build new features and secure virtual private clouds (VPCs). By using a platform that satisfies all use cases and corporate requirements, they do, however, save money on OpEx (operating expenses or expenditures).
How challenging is BI self-service?
There are also a lot of organizational problems with self-service BI implementations. A number of challenges and impediments impede the effectiveness of a self-service program:
Users in business are ignorant.
Similar to conventional business intelligence systems, self-service ones could be hindered by managers and corporate leaders who would rather continue basing decisions only on their personal intuition and experience. Furthermore, deterring user adoption might be self-service BI solutions with complicated user interfaces.
Inaccurate analytics-derived results.
Undiscovered and unrepaired data defects or missing data sets might cause self-service queries to provide incorrect results. Inconsistent information can be produced when multiple individuals work with different versions of the same material or prepare it for analysis in various ways through filtering and preparation. These issues may lead to a misinterpretation of BI findings and, therefore, subpar decision-making.
Data security, ethics, and privacy.
If self-service BI is used without strong data security controls and a functional data governance framework, problems could arise from the additional data access it provides. For example, sensitive information may be accessed by unauthorized individuals or utilized in ways that are prohibited by data protection regulations and business ethics.
Uncontrolled implementations.
Self-service BI systems run the risk of becoming disorganized in the absence of some level of centralized BI team monitoring and management. If business units adopt BI systems independently, inconsistent data silos, several BI tools, and unreasonably high costs may hinder the effective and efficient growth of self-service capabilities.
Self-Service Road Map
Self-service business intelligence (BI) should be mastered, according to several advancements. Businesses are decentralized; thus, users make decisions. Changes in the market are being accelerated by digital transformation and artificial intelligence (AI). Businesses also use the vast quantity of structured and unstructured data at their disposal to try and better understand consumer behavior and industry trends. To start using self-service BI, teams should:
1. Make a discovery:
A partner can help you to pinpoint your needs, information, resources, and user profiles. Part of this process is end-user interviews, functional and non-functional requirements development, and company KPI identification. One partner might offer an accelerator to speed up the process of determining your KPIs.
2. Analyze tools:
Together with your partner, you can next ascertain whether and how well the current tools—which include a metrics tool, a semantic layer, and self-service BI capabilities—perform. A partner can provide an accelerator so one can study the characteristics of modern reporting tools at their own speed. Most likely, you will be able to improve reporting capabilities and use fewer tools overall.
3. A proof of concept (POC) should be implemented:
Discover corner use cases, set up the chosen tool or tools in a sandbox, create use cases, document implementation simplicity, investigate the tool’s capabilities to make sure it fits, and do security checks. Finally, using this information, select the proper tool.
4. Install and integrate:
Should the Proof of Concept (POC) prove successful, you will purchase, set up, and configure one or more tools (metric store, BI portal, and/or semantic layer) in your environment. You’ll also connect the tools with other BI solutions, provide more reporting features, and ensure the semantic layer communicates with databases.
5. Call for a KPI buffet:
Finally, create as many often-used KPIs and metrics in advance as you can and train people on new processes and tools. One approach to support and maintain adoption is to provide users with more access to data and metrics.
Using this method, a large hotel chain updated to Level 2 self-service BI, cutting the number of BI tools from six to two and providing users with more features, improved data access, and a wider selection of KPIs.
Motivations to Offer Users Better BI Functions of Self-Service
Business teams and corporate data can progress since the market is slowly embracing self-service BI. Modern technologies and the potential of generative AI can help people learn new skills, make better decisions, and democratize access to data and analytics. Those who succeed can benefit from new business opportunities, including spotting white-space markets to enter, figuring out what kinds of customers to target with creative products, or finding other anomalies to capitalize on.
Conclusion
Recall that digital transformation has accelerated by 87%. sets up a new area on the agendas of corporate leaders for the time after COVID. Nevertheless, the BCG study finds that up to 70% of these changes fall short even with the greatest of intentions. A basic cause discovered was the inability to change the data- and insight-driven culture.
Moreover, according to McKinsey research, data-driven companies are 23 times more likely to beat their competitors in terms of acquiring new clients, 19 times more likely to sustain profitability, and over seven times more likely to keep customers.
The use of self-service business intelligence in enterprises has completely changed how they handle data analysis and make decisions. By giving business users, the freedom to freely examine data, organizations can achieve new heights of flexibility, creativity, and competitiveness.
However, meticulous preparation, strong data governance, and a dedication to promoting a data-driven culture are necessary for successful deployment. Organizations that use this strategy will have a major edge in utilizing their data to its fullest potential as Self-Service BI develops and helps them prosper in the ever-changing business environment.
