A recent Gartner report confirmed that only around 30% of employees in organizations are using Business Intelligence.
For CIO's, it’s a disheartening statistic as costs for creating BI reports are anywhere in the range of 500-1000 USD and a large organization can have thousands of reports being generated regularly. So, there is certainly a large amount of money being spent on creating BI reports for various stakeholders across the organization. However, the ROI is questionable due to the poor usage evident from the Gartner report.
Lets take a deep dive on the reasons which plague the poor usage of BI within organizations.
Different business users have different needs from BI systems and a one-size-fits-all approach to BI may not work in an organization. A lot of potential BI user base are looking at efficient ways to access enterprise data - be it power users or casual business users.
However, the information technology staff usually ends up failing in delivering real time and accurate reports due to higher cost, time to market and lack of talent.
Power users usually demand robust data discovery and visualization tools for deep analysis and accuracy. Casual business users can be better served by customizable self-service BI systems which can also take the form of dashboards for executives and other stakeholders.
However, there is a steep learning curve for business users when they have to create their own custom dashboards and reports out of self service BI systems. In the current scheme of things, a lot of training time is required to cater to such a learning curve which ends up eating into business productivity.
So, the real challenge lies in the Thematic Apperception Test (TAT), which is a projective measure that seeks to assess an individual’s thought patterns, observational abilities, attitudes and emotional responses, costs and accuracy of reports and dashboards, irrespective of the creators or users of the reports themselves
Here's where new age Conversational Analytics solutions come to the rescue.
Conversational analytics platforms understand the user behavior, context and intent to deliver personalized business insights in natural human language. It uses machine learning, data science, knowledge graph and cognitive techniques to provide personalized human interaction. A conversational BI analytics platform generates charts and graphs on the fly, thus eliminating the need of manual intervention.
Conversational analytics leverage on the power of adaptive analytics which helps anticipate future behavior or estimate unknown outcomes. When BI users query adaptive platforms, data is continuously gathered during the learning process and models are trained, which improve the level of personalization and bring context into communication. This feature ensures that right from front line associates to CXO's, everyone can extract the maximum potential of BI without undergoing a steep learning curve to access it.
Such a groundbreakingly transformational approach is expected to double the BI adoption in enterprises.
Business users who were struggling with numerous reports and technology barriers to access their business insights, can now easily make insightful actions. Thousands of charts and data grids are being auto-generated and presented as on-demand voice based replies in response to targeted queries by business users across functions and organizational hierarchies. This helps in reducing BI led report generation costs to a great extent.
Conversational analytics tools like ConverSight.ai by ThickStat are already helping organizations to cut their BI costs by about 65%. They have recently helped a logistics client to cut the need of sending excel based order data to their customers through the user friendly conversational system . This is enabling them to save 200-250 hours every week.
If you'd like to learn more about how your organization can benefit from on-demand insights generated by conversational analytics, take a look at the recording of ThickStat's recent webinar here - https://www.youtube.com/watch?v=l64f5vreKCc