Convergence

In the 1990s there was a lot of buzz around "Convergence" in the Telecom/Internet space. This referred to the merging of technologies used for textual Internet data, telephone/voice calls, and video conferencing. The ambition was to have one unified communications network for all types of media. A lot of technologies (e.g. Asynchronous Transfer Mode) were specifically developed for that purpose. Yet, ultimately things simply converged into an already existing protocol, TCP/IP. As systems became faster, production cheaper, and the necessary support maturity for the established network infrastructure became common place, it was pragmatic to have the communication need merge into existing technologies. 

Consider the following evolutionary timeline between the dawn of computing and modern applications, starting from the bottom of the stack. Notice the tilting from "Technically focused" into the "User oriented" space over time. Early in the evolutionary cycle development was driven by what was technically possible, progress was largely limited by technology constraints at the time. Higher up in the evolutionary time line, we notice the shift more toward optimization for user value. The development goals are driven by the business goal, not the technical feasibility.

If we consider the evolution "through the ages" among interrelated aspects, we get a better sense for the concept of convergence:

If we follow the trajectory of what has become Business Intelligence, we see a similar trend to innovation not being so much in the individual functional tool or technical infrastructure space, but in the maturity of their integration. Along those lines, we can project where Business Intelligence may go.

What is today commonly referred to as "Business Intelligence" will eventually evolve into the following concepts:

Cloud Services
Abstraction of the underlying Information Technology & Software infrastructure from the user.

Semantic Web
Smart tagging of content, more meaningful search results, sets the stage for collective intelligence.

Social Media
Collaboration portals & market places for dynamic interaction and trade. Exchange of knowledge, virtual goods, services.

Crowd Sourcing
The effect of dynamic and self-motivated work distribution based on individual interest, capability and availability.

Collective Intelligence
The iterative, incremental and recursive knowledge evolution as a result of crowd sourcing. More powerful than any algorithmic search engine.


Also, notice the evolution of the network effect. Originally, things evolved in a single stack. Then more vertical stacks developed more or less in parallel, with little integration. And ultimately, the various concepts play into each other, in reciprocal and recursive fashion, causing the effect of emergence (complex behavior arising from comparatively simple parts).

The network effect and emergence are not to be underestimated in the evolution of what is known as "Business Intelligence" today. Ultimately they will contribute to various different technologies, methods, and cultural paradigms to converge into the next level of intelligence, business being just a part of it, but with much dependent on and impacted by.