Embedded Analytics Defined

Embedded analytics is the integration of analytic content and capabilities within applications, such as business process applications (e.g. CRM, ERP, EHR/EMR) or portals (e.g. intranets or extranets).

The goal is to help users work smarter by incorporating relevant data and analytics to solve high-value business problems and work more efficiently as these capabilities are available inside the applications used every day. This is in contrast to traditional business intelligence, which focuses on extracting insight from data within the silo of analysis.

Common Analytics Capabilities within Software Applications

  • Dashboards and data visualizations: charts and graphs that display performance metrics
  • Static and interactive reports: tabular views of data with or without parameters and scheduling capabilities
  • Self-service analytics and ad hoc querying: enables users to ask their own questions about the data by exploring a set of data to create their dashboards and reports
  • Benchmarking: comparing performance metrics against best practices from external data
  • Mobile reporting: ensures interactive functionality on mobile devices and takes advantage of capabilities specific to mobile devices
  • Visual workflows: incorporating transactional capabilities directly within the analytic user interface, sometimes referred to as write-back.

How Is Embedded Analytics Different From Business Intelligence?

It’s all about context.

Business intelligence is a set of independent systems (technologies, processes, people, etc.) that aggregate data from multiple sources, prepare the data for analysis, and then provide reporting and analysis on that data from a central view point. It is most optimized for supporting management-level decisions that require highly aggregated views of information from across a department, function, or entire organization. These systems are specifically designed for people whose sole responsibility is to perform data analysis.

Embedded analytics is a set of capabilities that are tightly integrated into existing applications (like your CRM, ERP, financial systems, and/or information portals) that bring additional awareness, context, or analytic capability to support decision-making related to a variety of tasks. These tasks may require data from multiple systems or aggregated views, but the output is more than a centralized overview of information. It is targeted information to support a decision or action in the context in which that decision or action takes place.

While traditional BI has its place, the fact that BI applications and business process applications have entirely separate interfaces forces users to switch between multiple applications to derive insights and take action. Instead, embedded analytics puts intelligence inside the applications people use every day to improve the analytics experience and make users more productive by combining insight and action in the same application.

Said another way, business intelligence is a map that you utilize to plan your route before a long road trip.

Embedded analytics is the GPS navigation inside your car that guides your path in real time.
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Embedded Analytics Maturity Model

Embedded analytics strives to bring together insight and action into the same context by integrating analytics deeper and deeper within business applications and workflows. Analytics is embedded within applications in one or more of the following ways.
 

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An application can begin at any point along the embedded analytics maturity model and move over time. We have found that Inline Analytics is the most popular form of embedding today, and Infused Analytics is the stage which is increasing the most in popularity. As we see in later parts, deeper integration of analytics within applications is correlated to improving the user experience, increasing end user adoption, and differentiating the product.

Who Uses Embedded Analytics?

By Industry
Organizations across all industries and departmental functions utilize embedded analytics to make sense of their data so they can make better, more informed decisions. In a recent study conducted with application providers, financial services, technology, and manufacturing led the adoption of embedded analytics among the top ten industries surveyed.

Adoption of Embedded Analytics by Industry

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Commercial vs. Internal Apps
Any organization that develops or deploys a software application often has a need to embed analytics inside their application. This includes commercial software and SaaS providers who are serving the analytical needs of their paying customers. This also includes IT departments who develop and manage applications used by internal stakeholders and partners. Even though this second group may not have a revenue-driving “product,” they still need to meet “customer” demand for analytics and drive user adoption of their application. In our surveys, we have found that commercial software providers lead in their adoption of embedded analytics over their non-commercial peers.

Adoption of Embedded Analytics
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Are You Ready For Embedded Analytics?

Take this quiz to determine if your company is ready for embedded analytics.

Please rate your level of agreement with each of the following statements (5=strongly agree, 1=strongly disagree).

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