Based on our just published survey note, BI and analytics adoption has nudged up to about 32% of employees in an organization. Are you a glass-half-full person who thinks this is progress, or glass-half- empty person who sees we have so much work to do?
BI adoption is a metric I have been tracking for a decade, back to the first edition of my Successful Business Intelligence book, and frankly, progress seems slow to me. With all the efforts to modernize BI portfolios, bringing self-service and easier-to-use tools to business users, I had hoped for better results. In asking customers about specific BI tools in the Magic Quadrant, BI adoption is only at 21% of employees; basically flat for a decade.
What’s going on here? For data-driven businesses, is this progress? How can “data be the new oil” if only a minority of workers have access to it?
On twitter, one industry thought leader asked me, how much BI is enough? Maybe 21% to 32% is the total addressable market, saturated? I disagree. We have seen organizations that are truly data driven where BI and analytics adoption is well over 50% and closer to 100%. This is not to say that all employees are authoring their own queries from scratch. That is not the goal of pervasive BI. It’s really about empowering users to have data where, when, and how they need it. For some, that’s a dashboard, for others, it’s a mobile app. New technologies – whether through BI search/NLP or chat bots – also enable less sophisticated users to query data; even though it may not feel like it. (See more on these trends in the just-published Hype Cycle.)
I think part of our challenge as industry is that we keep responding to those users who shout the loudest; so we focus on enabling the power users more than empowering the masses. Also, we are absolutely drowning in data. New data sources and new storage approaches often trump the need to bring in more users. BI and analytic teams can barely keep up with the demand for, well, everything: more data, new tools, modify this report, migrate a source system … everything! We all need to work smarter, but we also need to keep the big picture in mind and focus on the highest value opportunities.
We offer more insights and recommendations on how to improve BI and analytics adoption in the full note.
Let me know what you think: how much BI is enough? Are we making progress?
Read Complimentary Relevant Research
How to Create a Data Strategy for Machine Learning-Powered Artificial Intelligence
MLpAI can help deliver systems with more automation and less human intervention, but success requires a data strategy to deal with the...
View Relevant Webinars
Big Data Architectures: Comparing Relational and NoSQL Databases
In the big data arena, few choices are more important and impactful than the persistent data store. Relational and nonrelational databases...
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.