We do a lot of work helping clients deliver marketing reporting and analytics and spend a lot of time trying to make the delivery of related insights faster and more impactful. In trying to quantify what makes insight delivery successful I have identified a few key elements that work in concert to create an “ecosystem” of sorts:

  • Analysts that can not only report on data but can also consolidate, massage, and transform information through an iterative data discovery and analysis process; this iterative discovery process may include statistical modeling and more formal analytics where appropriate, but this is not always required
  • Upstream data consolidation (i.e., data stores and marts) with conformed data sets and flexible aggregations (i.e., cubes, aggregated tables)
  • Big data solutions including appliances and Hadoop (depends on the scale of the data set)
  • Strong Analytic, Reporting, and Visualization tools
  • An inquisitive team that is curious and passionate about the stories told by the data
  • A culture that is focused on asking questions and delivering insights versus just delivering reporting data and technology

I call out the fact that you need to develop this “ecosystem” because there seems to be this notion that insights are fueled exclusively by technology. The industry has been fueling notions of “ad hoc analytics,” “analytics for the masses,” and frictionless reporting through the deployment of specific tools. There are a number of tools on the market that do, in fact, make these things more achievable, but the tools are not a silver bullet. Part of the challenge is that true insight delivery involves asking new questions that were not previously thought about. Newer generations of reporting solutions deliver reporting and visuals without a semantic layer which adds flexibility and agility to the process, but inevitably there may be data heavy-lifting required that isn’t suited for the reporting layer because it requires some pre-calculation and/or analytic modeling.

The industry will continue to evolve and come up with ways to make insight delivery more natural, but ultimately success is driven by asking the right questions, selecting the right visuals, and understanding how the data is structured. All of these things require some level of expertise and typically require some restructuring, merging, and manipulation of the data before the final insights can be delivered.

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