The inaugural X Change Europe is just a little less than two months away, and we've just announced the Keynote. We're going to try something a little different that I think is very much in the spirit of the Conference. Four top practitioners - all with deep experience in digital big data analytics projects - are going to join me in a conversation. We'll have David McBride of Comcast, Tom Betts of the Financial Times, Ulla Kruhse-Lehtonen of Nokia, and Peter Pletsch of Meinestadt.de. We're going to focus on a couple big questions around digital and big data that I think will be of deep interest to our audience of enterprise Web and digital analytics managers.
I'm not planning on running this like a panel at all. Instead, I want to create a kind of "mini-huddle" - a small group of experts exploring a single topic and I hope to drive to some pretty clear and useful takeaway's for attendees.
In particular, I want to explore where on the maturity curve an organization should be before jumping into big data analytics and warehousing. There's a prevailing assumption that analytics warehousing is the appropriate domain of highly-sophisticated organizations with a mature and successful Web analytics program that's bumping up against the limits of a tool. Frankly, that's largely the view I've held.
But I'm wondering if it's true. We have several clients who - having struggled to get much value from Web analytics tools - are hoping to "leapfrog" to the next generation. I think that's interesting. I think it's especially interesting in the context of EU-based enterprises who may feel like they haven't achieved the same level of maturity in Web analytics as some of their counterparts in the U.S.
After all, the two efforts are pretty fundamentally different. Why should success in traditional SaaS Web analytics be a prerequisite for success in analytics warehousing? And how much sense does it make to invest heavily in an analytics direction you think is interim at best?
If analytics warehousing is the direction of your future, should you continue to invest heavily in a traditional Web analytics effort to try and raise your maturity before you make that jump? What if you've repeatedly failed with those tools? Does that mean you can't or won't succeed in analytics warehousing? Does it matter (I think it does) if you've got significant expertise in traditional BI, statistical analysis, and warehousing? On the other hand, what kind of failures in traditional Web analytics are good evidence that you aren't ready for analytics warehousing?
Every member of our Keynote has led a successful analytics warehousing effort. I'll be curious to find out how mature their traditional Web analytics effort is/was and how they see the relationship between the two.
What I'm looking to get from the conversation is a blueprint for thinking about how organizations transition between traditional Web analytics and big data analytics warehousing and whether or not there is a "leapfrog" strategy that can work.
If you're in Europe, I hope you'll join us at X Change Berlin to enjoy what I think will be an extraordinary and illuminating discussion. If you're not able to make it, I hope to bring back plenty of new insights to share!