/ Self-Service Analytics & The Illusion Of Self-Sufficiency (Part 2)

At many organizations, business teams have been forced to establish shadow IT teams to own and manage self-service analytics due to their corporate IT teams being unable or unwilling to embrace it. At other companies, more progressive IT teams have been able to partner with the business and successfully transition from a traditional BI approach to the new self-service model. Regardless of whether a business or IT team owns the self-service BI platform, I’d like to highlight three success factors for companies leveraging self-service BI platforms:

  • Training becomes more important, not less. Self service analytics is not going to magically transform all of your employees into“citizen”data scientists. Training also doesn’t go away just because the tools are more intuitive and easier to use. Less time can be spent on learning how to use the product features and more time can be spent on how to interpret and analyze data properly (e.g., causation vs. correlation). In fact, it might be beneficial to view the training responsibility more as a coaching opportunity.
  • Community facilitates greater scale. As more and more people gain access to a self-service BI platform, the team managing your tool may find it increasingly difficult to be everywhere and answer everyone’s questions. Eventually, they may become the bottleneck that impedes user adoption. A strong user community reduces the BI team’s support burden by creating a forum where users can share ideas, ask questions, collaborate and learn from each other. There’s a profound difference between having 100 users assigned access to your self-service BI tool and building a user community around your analytics tool with 100 members supporting each other.
  • Governance doesn’t go away. The g-word isn’t overly popular or sexy, but it is just as important to self-service BI as it was with traditional BI. As one analytics director told me, “[Self-service analytics] will just create a prettier mess if the underlying processes are not in place.” However, the key difference is to better balance control with flexibility. Too much control can be stifling while too much flexibility can be reckless. You want your self-service tool to provide reliable, consistent data that is relevant and accessible to business users.

BI and analytics solutions create value by putting meaningful insights into the hands of those who can act on them—business people. As we evolve from an IT-dispensed approach to a self-service model, the flow of information is widening and opening up even greater opportunities for generating business value from analytics systems.

However,there’s no “autopilot” button you press after deploying a self-service tool—someone needs to own and manage it over time.Don’t confuse “self-service” with “self-sufficiency”, or you’ll be disappointed with the return on your self-service BI investments.

**This article was originally published on Forbes.com on November 15, 2016

Tags: Analytics, data

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