Organizations are drowning in data that isn’t aligned with business outcomes. Businesses understand the value of data analytics in identifying hidden patterns to improve customer experience and gain a competitive advantage. But, business data is often siloed and buried in different departments and systems across the organization. Therefore, business users are often unable to access the information they need, forcing them to depend on IT for their reporting needs.
What is Self-Service Analytics?
Self-service analytics is a form of business intelligence in which business users are empowered to perform queries and generate reports on their own leveraging easy-to-use BI tools, with minimal IT support. Business users can easily analyze their data, build ad hoc reports, and modify them with very little training.
Gartner estimates that by 2020, the number of data and analytics experts in the business units will grow at three times the rate of experts in IT departments, which will force companies to rethink their organizational models and skillsets. There is an increased interest in self-service analytics driven by changing business needs and roles such as the citizen data scientist. But enabling self-service analytics across the enterprise involves much more than just deploying user-friendly tools. Many organizations are unprepared for the organizational changes and resources needed to manage, scale, and maintain self-service analytics.
Self-Service Analytics Considerations
Aligning Business and IT
A major obstacle in the path of self-service analytics initiatives is a lack of understanding between business users and the IT department. Ensuring effective collaboration at the start of a self-service initiative can help both IT and business understand the value of a self-service approach, and figure out how they can assist each other to make self-service analytics a success.
Flexible Data Governance Approach
As data and analytics become increasingly accessible, agile forms of governance are important. Centralized governance hinders the adoption of self-service analytics as it discourages users who are just starting out. On the other hand, a lack of proper governance can negatively impact data hygiene, overwhelm users with irrelevant data, or lead to data security risks.
Onboarding and Training
Organizations must support business users with the right training that can help them apply analytics to solve their specific business problems. A comprehensive onboarding and training plan can help standardize this process, making it easier to scale self-service BI across the enterprise.
What are the Benefits of Self-Service Analytics?
Reduce Dependency on IT
Self-service analytics addresses the shortage of trained IT staff and puts data in the hands of the business users. Business users can handle less complex tasks like data exploration, visualization, and reporting by themselves, freeing up IT personnel, who can now focus on more value-added tasks.
Empower Business Users
Self-service BI tools enable business users to perform their own queries on the fly instead of restricting access to just IT users. Rather than spending time and resources hiring additional IT staff, self-service analytics tools empower business users with no technical knowledge, allowing them to easily create the reports they need to address business challenges.
Faster Decision Making
Self-service BI allows users to access information quickly without having to rely on information from the IT department, which could take days or even weeks. Both business users and decision-makers can easily create their own reports, dashboards, and visualizations enabling them to gain quick insights and make decisions faster.
Single Source of Truth
With self-service analytics, all types of users have access to the same, up-to-date version of the data. Unlike spreadsheets which exist in multiple versions across multiple devices, self-service analytics ensures consistent data across different departments, enabling better collaboration and improving productivity. Self-service analytics tools also combine data from disparate systems such as ERP, HCM, SCM, etc. allowing you to generate custom reports based on your unique needs.
Expenditure on BI software licenses and related hardware can easily be quantified and are the main focus for organizations evaluating the cost of their analytics solutions. However, the costs of IT staff required to support and maintain these solutions are often not taken into account. Self-service BI platforms can scale easily when there is an increase in user adoption without causing any access issues or needing much help from IT. As a result, organizations that deliver self-service reporting spend far less on internal IT support than organizations that don’t have self-service reporting capabilities.