Success Factors for Self-Service BI

What is self-service business intelligence?

As it’s quite late I’ll make it easy for me and just cite the definition of one of the big players in the self-service BI space:

Self-service business intelligence (SSBI) empowers teams such as product developers, sales, finance, marketing, operations, and more to answer data questions, with governance supported by IT and business intelligence (BI) analysts. BI is the strategic process of using data insights to make decisions that help organizations reach their goals. Instead of using gut instinct, precedents, and traditional mindsets, self-service BI helps to create a new culture around using data every day.

Success factors for self-service BI initiatives

Why am I writing about these success factors for SSBI initiatives?

I recently had a project where we developed a new data platform and therefore needed exactly these success factors to answer our underlying question: how do we motivate the business users to use self-service capabilities (pull) instead of waiting for pre-made reports/ dashboards from the BI department (push)?

The (beneficial) implications of this switch from push to pull are tremendous:

• Business users get curious about the data and dig themselves for new insights.
• Business users querying the data themselves saves time from the BI developers. Not short-term, but long-term. The saved time can be used instead to e.g. enhance the data platform per se, enrich additional data sets, or improve the overall data quality.
• The BI department/ developers are not the bottleneck anymore and thus scaling becomes possible.
• Data literacy within the organization is increased.

What are the success factors for SSBI initiatives?

The following list is based on my work experience and also inspired by the Core Capabilities of Data-Driven Organizations which is part of the Tableau blueprint. I really like the approach of Tableau for self-service business intelligence as they are focusing primarily on the business users and their day-to-day problems.

There are three success factors - the 3Cs (or my German translation: “die drei Gs”)

• Changeability (originally called Agility, my German translation: Geschwindigkeit)
  The new SSBI initiative needs to adapt quickly to the needs of the users to create added value for them.

  • Provide the data platform in-time
  • Data and pre-made dashboards need to be available from the beginning
  • (Viable) Change requests need to be fulfilled swift
  • Performance of the technical environment needs to be ensured

• Competency (originally called Proficiency, my German translation: Geübtheit)
  Users of self-service BI tools need to be confident using it.

  • Future (power) users need to be trained (initial & ongoing training)
  • User behavior should be measured (e.g. who is creating and consuming content, which content is popular, who is active)
  • Enhancing data literacy overall within an organization should always be an objective, not solely for such an initiative

• Community (originally called Community, my German translation: Gemeinsamkeit)
  A network of users exchanging ideas will drive the adoption.

  • Establish an internal business intelligence community (with members from in- and outside the BI department)
  • Foster exchange and communication between the users
  • A thriving community will help the users get excited and learn from each other
  • Provide continuous support (e.g. FAQs, mentoring)

How did we implement them concretely in our project?

• Changeability: we initially operated the BI platform (in our case: Tableau Server and some databases) ourselves in the BI team instead of getting it done through the infrastructure department to get going quickly. We used a data warehouse automation tool (in our case: WhereScape) to get a shorter “time to market” for new data requests. We used the fallback to Excel sheets where necessary to provide the requested datasets if the “correct” paths were not usable immediately.
• Competency: there was a 3-day training conducted for all 30+ power users initially and licensed online training available for every employee. We made internal data available for the initial training to show some real-life examples. We provided weekly sessions at each employees desk to take them by the hand and showing them the potential of the self-service BI tool.
• Community: a (bi-)weekly newsletter was sent out from the data team. Including newly available data (incl. documentation - sort of a minimum viable data catalog) and notable dashboards generated. There was an “Insight of the Month” with a little prize and it was awarded during bigger company meetings to show the importance and give the winner visibility. Interested people (from in- and outside the BI department) went together to external community events (e.g. meetups, vendor sessions).