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Despite millions of dollars of investments, in 64% of organization, only 10% of enterprise employees are using Business Intelligence today according to Forrester. This is even more disturbing given projections by Gartner that by 2014, 50% of enterprise employees will need analytics, and that by 2020, the need will rise to 75%. So if analytics are so critical to business decisions, what’s holding employees back and what can organizations do increase adoption?

The causes for low adoption are myriad but three rise to top of mind. The first is the proliferation of technologies; all too often this means not enabling the user with the right technology. A second is that end users may not have the requisite analytic skills, which can be addressed through tool training. Yet a third one which is more pervasive, is not thinking about analytics in the right way, e.g., a lack of an analytic mindset. Many employees are stuck in a “reporting” paradigm instead of a true discovery, exploration and analysis one. This challenge can also be addressed through training but a cultural shift and change management are also needed, which are more difficult to effect.

Here are a few guerilla tactics to address these needed changes. Setting a corporate example is one way to drive culture change. SAP was one of the earliest adopters of IPads to manage our own internal sales pipeline, but a valuable secondary effect is that our sales professionals can do their own demos using our mobile visualization tools because they use these apps every day. Often the early adopters for mobile applications are corporate boards and senior management teams; this executive adoption drives momentum throughout the organization. It's a form of peer pressure that trickes down through all levels of management to use these technologies and drives analytic vocabularies and awareness.

BI Competency Centers can also drive adoption. Training and driving adoption are key mandate for BICCs.  They can create analytic sandboxes, posting initial releases or trial versions of new software engaging users in the evaluation process and gathering feedback. Get around infrastructure hurdles by using Cloud environments to test new capabilities like text mining or sentiment analysis. 

Lastly, don’t overlook making analytics fun and interactive. We’ve created various internal and customer campaigns and contests that drive the use of new applications, create demos and garner product feedback. See the Data Geek 2.0 website which we created for our visualization and predictive products as an example. We created or provided access data sets that appeal to every hobby or interest, be it fantasy football, UFOs, crosswords and more to encourage people to engage. Complement your campaign with videos, spoofs, t-shirts and more!  Check out the Ultimate Data Geek 2.0 Challenge at