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1486 Labs Research Highlights External Data Inefficiencies

For the past eight years I have been teaching and lecturing on the subject of data and advanced analytics – specifically as they relate to the application to business problems and opportunities. The mantra is consistent – analytics is the engine to high performance and disruption and data is the fuel for that engine. The better turned the engine and high quality, on-spec fuel optimizes the performance.

Data – the fuel – comes from many sources. But to keep it simple, let’s say there are two primary sources: the data that we mine, curate, refine from our own repositories and the data that we purchase. That external data often augments and enables our internal data so that the analytics run at their highest performance – and sometimes provide prescriptive actions so that we can maximize the probability that the outcome matches our highest expectation.

Over the past year, a group of my students and I have been conducting research – interviews, group discussions, conferences, and secondary research. The high-level issues continue to focus on familiar issues:

  • Lack of pricing transparency,

  • Purchased data not matching quality expectations,

  • Lack of choice – “where are my alternatives to existing vendors?”, and

  • Friction in the buying process – both internally and transactionally with the vendor.

We will continue to forge ahead with additional research. However, we will start to focus our discussions on solutions to these inefficiencies. We welcome your thoughts or if you would like to contribute some thoughts or suggestions, we would love to interview you. Message us back!

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