Big Data still in naivety proves Elusive to Big Picture and Randomness

Big Data as it exists today is not necessarily a tool that creates the Big Picture. Most systems that exists today are designed based on predicated methods. These rely on known variables, the only constraint unknown are the values of the variables. Predicated system are constrained to create newer insight as they are bounded by system boundaries defined by known variables. The new emergent variables can be considered as the non-causal agents until the newer order of the complex system begins to emerge; in which the newer variables manifests.

To develop wider and deeper insight about the behavior of the complex system as the system driven by entropy moves from one order to next; it does require to bring into its realm the possible newer variables. Lack of adequate techniques (Bayesian network included) in discerning all the variables that affect the system behavior creates uncertainty. Predicated system as such are blind sighted to such uncertainties. This creates inadequacies in methods when dealing with the randomness in the system. Emergence of newer variables that begin to affect the system behavior become the newer causes. Predicated system cannot hone on the variables that  lie dormant as the non-causal agents.

The hidden non-causal agents can be discovered by creating 2nd order generative semantic models. Predicative systems as such are not designed to dramatically alter its behavior; but only reflect the behavior constrained by those variables considered in its initial design


Multi Lateral Cognition – Key Learning and Discerning Capability to Study Complex System

Simple View

Multi-Lateral View

Music by Bach, Chopin, Beethoven, Mozart – they helped to reach our experience beyond known boundary conditions.

Beethoven was deaf, he could not hear his own compositions. But then how did he create “ode to joy”… he believed god whispered to him…else how could he write the program for the composition that lifts one to heavenly levels….I chanced upon the idea of generative techniques that he employed in the way music progresses and creates emergent musical patterns…this is true stretch in experience of the boundary conditions…where the human mind listening to music is taken to unexplored areas….and joy that awaits is exhilarating and ecstatic.

A metaphor for generative transformation creating emergence from incorporation of Beethoven’s composition “emperor” integrated with a visualization of a dynamic state of complex system; in which there operates multiple influences on context. The influences are themseles in dynamic change, like a cube or tetrahedron or such having multilateral influences, all in dance, in motion and intersecting with one another. Each lattice, each bounce, each intersection producing a perception. Continous are such perceptions in creation, and each one is unique and every one perception produced is emergent, nothing from past produced…how to view such a dynamic system depicted above as A Metaphor for Generative emerging from the multi-lateral cognition.

Invention (Innovation) Not Strategy Creates Renaissance – Moving from Darwinian Adaptive to Generative Transformation

Invention (Innovation), Not Strategy Creates Renaissance. Most Darwinian concepts does not engender to developing creativity, and so to innovation. Instead it is about strategy for developing dominant position, this is not a sustainable model as history has shown. Instead, Enterprise Architects should begin reinforcing energy into lost opportunities in innovation and explore to create newer territories.

In the recent times, we saw the fall of Michael Porter’s ideas around corporate Darwinism. His company during the past two decades influenced the CEO’s with trickle down ideas and C level were enamoured by it, as it helped them device system giving them enormous clout. Suddenly the landscape has changed, the market response has been very different, from what the CEO’s sought. This is because Darwinian theory does not sustain. Inorganic decisions are not working. From recent HP’s fiasco (Autonomy acquisition), it is much evident how corporates are massively faltering. Decade back, Carly Fiorina then HP’s CEO sought EA framework based on Darwinian adaptive principles as a way to achieve business enablement. It has not worked. It is now exactly a decade since she introduced. Theories developed on Darwinian dominance has been flawed and it is now much evident. Porter’s company recently declared bankruptcy. Those ideas are history.

What killed Michael Porter’s Monitor Group

Check out interview with Carly’s Darwin EA framework to create adaptive capabilities.

Based on flawed ideas, corporates employed resources targeting to achieve market dominating capabilities. Against this landscape, IT unfortunately has been delivering diminishing return. To overcome the value struggle that IT could offer, various schemes in the industry has been probed. Especially, TOGAF itself has been maturing to develop dialogue for IT from being across LOB service provider, cost to profit center, to more ambitious as business enabler. The argument of Nicholas Carr’s IT Does Not Matter when seemed almost true, ideas around creating EA driven strategic operating model emerged. Jeanne Ross book on EA as Strategy – Achieve Competitive Advantage

These ideas are getting outmoded. The essence of creating sustainable business model is to keep throttle on innovation. Challenges still remain to solve or probably discover newer opportunities by innovation that creates generative system, which intrinsically allows for emergence.

Check out Jeanne Ross discussion on EA – IT in context of business transformation

MIT’s Ross on How Enterprise Architecture and IT More Than Ever Lead to Business Transformation

In my mind, even Jeanne dwells on conventional wisdom. She is not discovering newer landscape. She discuses to improve the leverage to achieve strategy for transformation. The question is why/ which / what / where/ when strategy and how transformation and finally what outcome??

Dealing with thoughts like these, EA is not a domain of IT alone. EA is an integrative subject that brings together several disciplines to solve both macro systemic and micro functional concerns. EA can be used to reimagine and repurpose architectures including those realized by IT.

Another concern that EA must tackle in its value proposition is the value it can help achieve at system level. The GDP related to digitization has been in the increase. However, what is not evident is the “productive” impact of the digitized portion of the GDP. Meaning what activities in the digitized world are essential to mankind’s survival, are productive GDP. Innovations are required in increasing the potential of the productive GDP driven by IT. This argument is crucial.

In my view, EA can offer a great leverage to reimagine future, besides achieving leverage in the existing operating model. In pursuit of such mission, EA does not belong to “IT” alone. What we need is generative and not mere adaptive transformation efforts. It is in generative system, where integrative disciplines will work to allow for tacit knowledge creation. It is this tacit knowledge that will trigger emergence of newer opportunities, creating emergent architecture.