August 3, 2021
Traditionally, almost all business intelligence and analytics solutions were designed as general-purpose platforms or desktop tools suitable for any industry, department, or use case. That does mean, of course, that the burden of developing data models, data pipelines, dashboards, and reports falls to the customer. They effectively start with a 'blank sheet of paper,' which, in theory, can be developed to fit the organization's exact needs. However, the reality is that the organization may not have either the skills, resources, or time to develop an analytics solution that quickly meets business requirements.
The answer to avoiding this overhead of entirely homegrown analytics is to use a modern analytic application that can deliver ready-to-use analytics, right "out-of-the-box." Deployment and adoption of these analytic applications are accelerated because of built-in content developed by industry domain experts that understand the industries, roles, data, business applications, and specific analytics required by typical business user personas. A significant amount of development time can be saved because this domain-expertise-driven content can replace typical internal development processes.
In Gartner's 2020 report, When to Choose a Line-of-Business Analytic Application, they note that "general-purpose BI platforms are more time- and resource-intensive than prepackaged analytic applications — both building and maintaining — to support LOB users."
Naturally, the pre-built analytics provided must be relevant to a user's specific industry and role, whether that person is a c-suite executive or frontline worker. Using consistent and centrally governed data ensures that everyone is looking at the same information, even when access profiles are used to determine that individuals can only see their "slice" of the organization. KPIs are designed to help users improve the most critical metrics that apply to their respective departments and roles; KPIs may vary from role to role, but all paths lead to the same goal.
The faster time to value delivered by using pre-built analytic applications should increase analytics adoption across the organization. A more complete set of industry and role-specific data models and analytics content, delivered in a fraction of the time it would take to develop internally, is a great way to get your organization using analytics quickly and effectively.
To learn more about how to increase analytics adoption across your organization, read our best practice guide today.