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“Big Brain” Software Platforms versus “Small Brain” Best-of-Breed Applications

Nate Lentz
November 3, 2021

I recently got asked if I thought there was going to be a future need or demand for proprietary software platforms or if the evolution of APIs and the ability to efficiently connect best-of-breed applications would render the concept of a platform a thing of the past.  It is a good question.  As data easily flows across applications through increasingly efficient APIs and as AI and ML enhance what used to be laborious data cleansing, deduping, and data synch challenges, the need for a platform of deeply integrated solutions is reduced.   Furthermore, a next generation of analytic and BI solutions can take data from multiple systems and generate insights and intelligence from multiple best-of-breed solutions in a manner that replicates and replaces the need for proprietary platforms to generate insights from across their varied integrated applications.  So maybe platforms are a thing of the past and best of breed to the future.  Maybe but maybe not.

AI and ML are leading to application intelligence.  Next generation applications are not just generating data, to be analyzed elsewhere, they are generating intelligence from that data to drive actions and recommendations inside of the applications.   Applications learn from the data that flows through them and learn from how users use the applications.  We are shifting from an analytic framework where the output of software is delivered to the human user acting as the analyst.  We are shifting towards fine-tuned “learned” recommendations generated by the application – or in many cases automated, self-created algorithm-driven action taken directly by the application without any human involvement.  The application function has shifted from a coded set of actions to a set of learning algorithms.  In essence – “small brains.” The use of several best of breed learning applications results in the combination of many “small brains” operating independently on small pieces of a solution.  A proprietary platform of multiple applications integrated at their data and AI and ML learning layers enables insights into a solution as a whole.  In essence, a next generation proprietary platform could offer a “big brain” solution versus many best-of-breed “small brains” working independently.

The next generation platform will differentiate on the power of its cross-application intelligence.  Best-of-breed applications will need to share knowledge across applications in order to compete with these “big brain” platforms.  The next wave of integration technologies will be those that turn independent “small brains” into integrated larger brains.  No small challenge for sure.  I’m looking for the Mulesoft of intelligence.  Until this technology emerges, I am going to be betting on business models that can evolve from one solution to an intelligence platform where there can be potential for cross-application “big brain” intelligence with a consistent stimulus driven by evolving user experience and cross-platform learning.