Copyright © 2010 http://jtonedm.com James Taylor
As part of the build up to today’s tweet jam on advanced analytics, Jim Kobelius discussed some of the questions they are planning to use in a blog post – Advance your analytics strategy. There’s a lot of good stuff in the article but I do have to take issue with a few things.
Copyright © 2010 http://jtonedm.com James Taylor
As part of the build up to today’s tweet jam on advanced analytics, Jim Kobelius discussed some of the questions they are planning to use in a blog post – Advance your analytics strategy. There’s a lot of good stuff in the article but I do have to take issue with a few things.
First, the definition of advanced analytics. There’s the usual problem whether to consider advanced analytics part of BI or not. I prefer not to as I find talking about BI pushes people to immediately think about reporting and dashboards. Instead I talk about a sliding scale from BI to descriptive and predictive analytics – from descriptive knowledge about the past to increasingly prescriptive predictions about the future. I would also take issue with Jim on social media analytics – there is nothing particular about analyzing social media that makes it “advanced”. Social media is a source of data (and an under-exploited one for sure) not a style of analytics. Social network analysis is a kind of advanced analytics, however, though it often does not use social media data (see this post on social networks in telco). CEP (Complex Event Processing) is also not a form of analytics but a kind of system that uses analytics.
While I agree with Jim that next best action is a classic use of advanced analytics I am not sure I am willing to accept that it covers all uses of advanced analytics and Jim seems to imply it does. Have to think about this one more.
I am not as sure as Jim that there is a lot of overlap between advanced analytics and BI/DW/Data Governance. Sometimes there is but often the focus on reporting inherent in existing BI programs means that the infrastructure and processes don’t lend themselves to advanced analytics. I also thing there is a fundamental problem with saying there is a need for all data being used for advanced analytics to be perfect. This is simply not true – there can be no absolute measure of quality as it depends on what you are trying to do. Data quality is about being good enough to improve the quality of decision-making, nothing more.
I was also frankly irritated by this question:
Is advanced analytics ready to roll out to all information workers, or is it still the province of a priesthood of data mining specialists?
This is the wrong question. The systems that use advanced analytics are often used by people with far less skills than “information workers” and that makes them easier to push out to more people than BI systems. This idea that, because the models are built by experts that advanced analytics only impacts a small number of people is just wrong. Instead of trying to push BI to more people companies should focus on pushing decision-making systems out to them and embedding analytics into these systems. Call center reps, store clerks and other front-line folks have neither the time, the skills or the inclination to use BI tools and we should focus on helping them with decision management applications. In contrast to Jim I have seen dozens of cases where many non-information workers are using systems that EMBED advanced analytics. They don’t build the analytic models but they sure benefit from them. The systems in which they are embedded are much more broadly used than any BI tool and that’s the point.
