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Fairy-tale Castles, Mad Kings and Business Analytics: the Gartner BI Summit

by Alan D. Duncan  |  October 20, 2014  |  Submit a Comment

Those of you who have been follow me for a while will know that  my blogging can sometimes be as much travelogue as it is about data and analytics. (“Holding the Law In Our Hearts”“Winning With Big Data” and “Context is Crucial, but People are Paramount” are all such examples.) This week has seen me back on my travels, this time to Munich for Gartner’s European Business Intelligence Summit (and my first official event as a fully-fledged Gartnerist.)

Ahead of the conference, I had the chance to meet up with a few of my Gartner colleagues (including Ian Bertram, Tom Austin, Joe Bugajski, Frank Buytendijk, Mark Beyer and Thomas Oestreich) as we headed out of the city and drive to the village of Hohenschwangau in the Alpine foothills, where sit the fairy-tale castles of Schloss Hohenschwangau  (“High Swan County Palace”) and Schloss Neuschwanstein (“New Swan Stone”), best-known for being the inspiration behind Disney’s Sleeping Beauty Castle.

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Either of these edifices would serve as a perfect setting for a fairy story (take your pick as to whether you prefer dark morality tales like those by the  Brothers Grimm, the hopeful and whistful fables of Hans Christian Andersen, or re-worked, high-gloss musical froth from Disney).

There is no doubting the beauty of there glorious royal follies. Both castle-come-palaces are works of art, both outside and in, and the majesty of the German Alps serves as a perfect backdrop. However, in considering these two magnificent works, the creations of King Maximillian II of Baviaria and his son Ludwig II respectively, it struck me that I was looking at an architectural analogy to what we do in business analytics.

The  castles are beautiful, accessible, represent a hundred different and interlinked stories that connect with the Bavarian psyche, and are what draw in the paying public. The village of Hohenschwangau has plenty of restaurants, bars and entertainment too, so overal it’s a fun place to be.  That’s exactly what want your analytic output to be like – beautiful, accessible, connectable and fun.

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But pretty, engaging and user-friendly doesn’t add up to much if the castles were likely to fall down at any moment – notwithstanding the potential waste of investment, you’ve also got a significant safety and security problem to deal with. So strong foundations, robust underpinning ground and high quality construction are a must. The two castles in Hohenschwangau are built respectively on the former sites of twin medieval strongholds, which were constructed for defence, not enjoyment. And the whole site is built into the side of an Alp. So all-in-all plenty of strength and solidity there. The workmanship is exquisite, yet the process was lengthy and involved huge amounts of work – for two decades, the construction of Neuschwanstein castle was the major employer of the region.

So it is with Analytics; we need a strong foundation of good data upon which to build, and there is likely a lot of hard work involved before we can have any form of outcome, let alone anything robust and resilient. (Cue discussions about the trade-offs between time-to-value/responsiveness and integrity/maintainability).

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Finally, let’s consider the roles of the kings, Maximillian and Ludwig. Both had a strong vision of what they wanted to achieve and were aspirational in their desires to see their castles come to fruition. Both were committed to seeing their respective projects through to completion. As king, of course both had the power and authority to enact their plans. Ludwig in particular was visionary in his aspirations for his fairy-tale castle masterpiece as well as in his care for the welfare of his subjects, setting up insurance and welfare services for the construction workers. Realising this vision came at a huge cost however, both financial and personal, and Ludwig was ultimately declared insane and deposed by government commission, before then dying in mysterious circumstances.

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Do you have a strong sponsor for your analytics project? Is the sposor truly committed, both in terms of financial investment and emotional involvement? Or should they be committed?! Is their vision shared by those around them, or are their plans viewed with “it’ll never work” cynicism by others? Just because everyone else thinks you’re crazy doesn’t mean it’s really so.

Analytics. The fairy tale can be made reality. Just don’t let the process drive you mad. See you at the BI Summit…

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Category: analytics  big-data  business-analysis  business-intelligence  data-governance  data-quality  data-science  information-management  

Alan Duncan
Research Director
1 years at Gartner
22 years IT Industry

Alan Duncan is a Research Director within Gartner's Analytics and Business Intelligence research team. Major areas of interest include: the business value of analytics solutions and architectures, data governance and quality, culture of evidence-based decision making, and data-led organizational change. Read Full Bio




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