Complexity, risk, uncertainty and change


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Business management, particularly for those intent upon ‘change’ or responsible for managing exposures, needs a rigorous, objective, measurement of the endogenous properties (complexity) that enables the functionality from which (through interactions with exogenous parties) the business generates the revenues that sustain it in changing and turbulent economic times.

“Complexity increases cost and decreases flexibility — often in unforeseen ways — and also tends to decrease stability,”….

Peter Leukert, CIO of Commerzbank

It is the number, nature and integrity of dynamic, multi-scalar, interactions that are the sources of strength (enabling performance greater than the sum of the parts). The ability to distinguish and respond to ‘signals’, that maintain the variety, effectiveness and agility of the complex system, from the ‘noise’ of flawed metrics, self-serving culture, hierarchical structure (silos), skewed incentives – of an unsustainable, failed or failing, model (reliant upon  assumption, reflexive, subjective, statistical analysis and prediction) that has its foundation in flawed (linear) economic thinking.

We won’t get different or better answers while we keep on asking the same questions.

For meaningful change to occur and to be sustained requires a rigorous justification, sufficient to counter financial projections that satisfy the goals of C-level short-termism that are detrimental to the stability and long term health of the business.

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Beyond Data Mining:: knowledge mining


We live in the digital age. The flow of data is truly impressive. Statistics inform us that each year we generate more data than the past generations did in decades. But the problem is that Information Technology (IT) has concentrated on simply automating old ways of thinking, creating bottlenecks and problems we didn’t even imagine, and not really inventing new processes or approaches. There is little innovation going on in the IT arena. But one thing is certain, we are drowning in data and we’re thirsty for knowledge…

Turn data into structure

Structure is the overture to knowledge. But what is knowledge? What is a “body of knowledge”? Setting aside ontological hair-splitting  we could say that a body of knowledge is equivalent to a structured and dynamic set of inter-related rules. The rules can be crisp or fuzzy or both. But the key here is structure. Structure is the skeleton upon which a certain body of knowledge can be further expanded, refined, modified (this is why we say “dynamic”). One could say that structure forms the basis of a model or of a theory. Today there exist many ways of extracting structure from data. Statistics is one way. Building models based on data is another. But because building models and mis-handling of statistics has contributed to the destruction of a big chunk of our economy, we have invented a new method of identifying structure in data – a model-free method, which if free of statistics and building models. A method which is “natural” and un-biased.

via Ontonix – Complex Systems Management, Business Risk Management.

Data Mining: Detecting patterns isn’t the same as looking for them


LOS ANGELES, CA - AUGUST 30:  Big Bird arrives...

Image by Getty Images via @daylife

In the fine tradition of Sesame Street this blog is brought to you by the word APOPHENIA and the number 2 [two being the number of members from the Linkedin “Risk, Regulation & Reporting” Forum (on Linkedin) – Vladimir Seroff and Joe Erl – to whom I owe a debt of thanks, for inspiring this blog].

This Ontonix presentation illustrates, the limitations of conventional statistical analysis, when data does not conform to a linear fit…how inconvenient, misleading and downright dangerous! Read more of this post