About 10 years ago, social media tools like Facebook, Twitter and LinkedIn introduced a wave of collaborative analytics and BI capabilities. We saw chat streams associated with specific analyses that users could like or endorse. The number of contributions a user made to the community was part of his or her profile so others could accordingly weigh the importance of the input.
However, after an initial surge of interest, these efforts failed to gain traction and waned. Collaboration requires a large community of collaborators and there simply weren’t enough people regularly engaged in using the analytic tools. Most line of business personnel use a variety of business applications and don’t spend their entire day working solely with analytics products, but early efforts at collaboration required the users to participate in the dialog from within the analytics and BI products.
Today, mobile devices provide the glue to pull a community of collaborators together. Most of today’s analytics and business intelligence products support some form of collaboration, providing capabilities that support the sharing of and communication about the output from analytical processes. This is important because analytical processes help organizations maximize the value of their analytics investments and support decision-making and those decisions typically involve multiple people.
Analytics and BI vendors have recognized the value of collaboration and have increasingly been incorporating these capabilities into their products. In particular, the significant expansion of mobile analytics and BI has made it easier for users to easily collaborate on analytic processes. In the same way social media users get notifications of activity via mobile devices, collaborative analytics and BI vendors use mobile notifications to engage their community of participants.
As a result, we see a resurgence in the use of collaborative analytics and BI. Our research shows that nearly four in 10 organizations are using collaboration to support analytics processes and more than half said they expect to use these capabilities in the future.
The analytics process typically involves multiple people with differing areas of expertise and responsibilities. Collaborative tools can enable this diverse group of participants to coordinate their activities and share knowledge. To be most effective, collaborative capabilities should cover the entire data and analytics process; only this way can participants understand the provenance of data as it is analyzed. With this approach it’s easy to identify subject matter experts to engage in the dialog. The team can discuss and document decision-making for compliance purposes and the actions resulting from those decisions can be assigned and tracked to completion. We expect that these types of capabilities soon will become a standard feature of data and analytic processes in much the same way that visualization is now.
As organizations embrace more sophisticated analytics such as artificial intelligence and machine learning and as analytics become more easily accessible via technologies such as natural language processing, collaboration capabilities will become even more important. However, strong collaboration capabilities alone are insufficient; strong analytics are required as well. Our Value Index assessment takes all these factors into account.
Ventana Research has conducted research in related areas including Data Preparation, Machine Learning, Data and Analytics in the Cloud, Next-Generation Predictive Analytics and Big Data Analytics and Integration. We have examined the expansion of business intelligence through the use of cloud computing, mobility and advanced analytics as well as how BI products use collaboration capabilities, social media techniques and location-related analytics. The findings of these research undertakings guide our comprehensive approach to our Collaborative Analytics and BI Value Index, the findings of which we will discuss in our next post.
SVP & Research Director