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The 7 Principles of Collaborative Intelligence

Rick Hall
April 19, 2022

Last week we held the first ever summit on Collaborative Intelligence.  We coined the term to contrast with both centralized data warehousing and the free-for-all do-it-yourself model.  Neither approach has really satisfied our customers needs. We gathered last week in Atlanta to help define a middle way.  Coming out of the event we have settled on 7 key principles which we wanted to share:

  1. Empower Business Teams –  By making data secure and accessible, focusing on data literacy, and providing tools which allow self-service, organizations can greatly enhance their ability to use data.
  2. Focus on Outcomes – The problem we are trying to solve is clear well ahead of the specific analysis which will lead to insight.  By focusing on the outcome we want to deliver and freeing analysts to explore and iterate, we can get to true insights faster.
  3. Promote Collaboration – Over 60% of analysts efforts and 80% of their results are shared.  By promoting collaboration we greatly enhance the productivity of our teams and the quality of our results.
  4. Treat Data as a Product – By focusing on providing clean, granular, and timely data, analytic teams can support analysis of all kinds.  This “data product” orientation greatly enhances the quality of analysis and saves enormous time for business teams.
  5. Embrace a Distributed Architecture – Complex organizations are well beyond the point where all data will reside in a central data platform or even using a common technology.  Organizations who embrace this environment are better able to focus on making diverse data accessible wherever it resides.
  6. Promote Common Tools – Too often our engineers and analysts work in completely different tools with no way to share results or learn from each other.  Common tools bring the entire analytic organization together – allowing insights to be shared and facilitating learning from highly skilled to less skilled team members.
  7. Curate Analysis – When every teams builds their own analysis, multiple answers proliferate for the same question.  By identifying and promoting the best analysis to standards, organizations can eliminate contradictory results and build their knowledge base over time.

Let us know what you think, and together we will redefine analytics.