Business Analytics Anyone?

Today, I participated in a focus group to help start up the BCIT School of Business Business Analytics Centre of Excellence.  The room was full of Business Intelligence/Analytics/Insight leaders from around Vancouver.  We were brought together by Ed Bosman and Karen Plesner both instructors in the BCIT School of Business.  Karen facilitated a two hour discussion on a series of topics.  The group provided advice on the skills expected of graduates in the various business analytic roles – consumers, artisans/analysts and systems technicians.  The other major focus was on what a “centre of excellence” for business analytics should provide and deliver to industry.

We were provided with a definition of Business Analytics as the seed for the discussion:

Business Analytics: the skills, technologies, applications and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning (Davenport and Harris, 2007)

This definition generated a very good discussion and the consensus was that this definition was too narrow.  It failed to address real-time analytics for operational performance management and web analytics for customer behaviour management.

We had a good discussion about master data management and data standards.  One of the great quotes of the day came from an panel member.  He was referring to a discussion about how confident and accurate your numbers need to be.  I really like this pragmatic approach.

Business Analytics augments your gut

The another panel member introduced the group to a model used by Davenport and Harris.  Here is what it looks like:

Davenport and Harris Model

Information

Insight

Past
Present
Future

The model is a measure of where business analytics efforts are focused.  This would be a good model for us to look at the maturity of our Business Intelligence/Analytics practices.

This table contains the lists of topics and themes I noted during our focus group.  There are many topics and themes below that will warrant future blog posts.

Trends Tools BI/BA Type Audience
Web Analytics Excel Operational “Real time” Consumers
Mobile Access Tactical “Just in Time” Artisans
Bring Your Own Device Qlikview Strategic “Points in Time” Analysts
Security Tableau Compliance Authors
Privacy SAP Predictive Systems Technicians
Predictive IBM Cognos
MDM MS Analysis Services
Big Data SAS
Information Overload SPSS

 

I am looking forward to the next steps in the process and hope to contribute to the effort.

Davenport, Thomas H.; Harris, Jeanne G. (2007). Competing on Analytics: The New Science of Winning. Harvard Business School Press