One of the biggest challenges organizations face when it comes to their analytics efforts is adoption. In fact, our 2015 State of Self-Service BI Report revealed that adoption of self-service analytics has remained stagnant at only 22% for the past two years. In a world that is largely driven by technology and data, this is a difficult stat to grasp. So how can BI and analytics be a top priority for most competitive businesses, yet the adoption of these tools remains so low?
The more important question is: how can we fix this?
The answer lies in embedded analytics: the integration of analytic content and capabilities within applications.
When your analytics apps and business process apps (e.g. CRM apps, Finance apps, etc.) are separate interfaces, users are forced to switch between multiple applications to derive insights and take action. On the other hand, embedding analytics puts intelligence inside the applications people use every day – improving the analytics experience and allowing users to be more productive by combining insight and action in the same application.
Take Amazon, Kayak, and the increasingly popular FitBit, for example. Each has successfully combined a useful service with analytics: Amazon offers product ratings, reviews, and suggestions to online shoppers, Kayak presents its customers with an assortment of relevant flight data to aid in their decision, and Fitbit performs a detailed analysis of physical performance. All three of these companies effectively provide customers with actionable insight – within a single application. By embedding analytics within the actual application, users are able to take advantage of analytics without having to go out of their way to do so (some people may not even realize they are being fed data to make an analytical decision). Moreover, they are more likely to use these tools over others that don’t provide the same sort of analytical insight.
The overarching theme of embedded analytics (if you haven’t figure it out already) is that it makes analyzing data a part of the users’ workflow. We’ll never see growth in analytics adoption if users are required to leave an application in order to gain insights from their data. The key to solving this BI adoption problem is to leverage embedded analytics, ultimately empowering users to be as educated as possible when making a business decision.