A little over two years ago I wrote a series of blogs introducing Insight-as-a-Service.  My idea on how companies can provide insight as a service started by observing my SaaS portfolio companies.  In addition to each customer’s operational data used by their SaaS applications, like all SaaS companies, these companies collect and store application usage data.  As a result, they have the capacity to benchmark the performance of their customers and help them improve their corporate and application performance.  I had then determined that insight delivered as a service can be applied not only for benchmarking but to other analytic- and data-driven systems.  Over the intervening time I came across several companies that started developing products and services that were building upon the idea of insight generation and providing insight as a service.  However, the more I thought about insight-as-a-service, the more I came to understand that we didn’t really have a good enough understanding of what constitutes insight.  In today’s environment where corporate marketing overhypes everything associated with big data and analytics, the word “insight” is being used very loosely, most of the times in order to indicate any type of data analysis or prediction.  For this reason, I felt it was important to attempt defining the concept of insight.  Once we define it we can then determine if we can deliver it as a service.  During the past several months I have been interacting with colleagues such as Nikos Anerousis of IBM, Bill Mark of SRI, Ashok Srivastava of Verizon and Ben Lorica of O’Reilly in an effort to try to define “insight.”

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