By Richard Berry. What are the differing characteristics of data? Why are they important for systems to function effectively? What is requisite variety of data? There are nine characteristics of data variety which agitate systems. These are volume, velocity, variety, veracity, validity, vulnerability, viscosity, vectors and virtualisation. Together, the ‘9Vs’ constitute a data requisite variety ... Read more| Integration and Implementation Insights
I borrow the term ‘dogma’ from W. V. Quine’s classic essay Two Dogmas of Empiricism, where he showed that unquestioned assumptions can quietly shape an entire field. Complexity science, too, rests on its own dogmas that deserve examination. In today’s post, I want to explore what I see as two fundamental dogmas with how we […]| Harish's Notebook – My notes… Lean, Cybernetics, Quality & Data Science.
In today’s post, I am exploring Ashby’s Law of Requisite Variety and why it might be both more necessary and more slippery than most presentations suggest. Ashby’s Law might not be just another management principle. It could be a window into how we navigate complexity when the world refuses to be pinned down by our […]| Harish's Notebook – My notes… Lean, Cybernetics, Quality & Data Science.
In today’s post, I am further exploring the notion of models and mental models. We often speak of mental models as though they are neat packages of knowledge stored somewhere in the mind. These models are typically treated as internal blueprints and as simplified representations of the world that help us navigate and make decisions. […]| Harish's Notebook – My notes… Lean, Cybernetics, Quality & Data Science.
In today’s post, I want to explore what I have been thinking of as the Cybernetics of Kindness. In my recent reflections, I have been drawn to the quiet power of compassion and kindness, part…| Harish's Notebook - My notes... Lean, Cybernetics, Quality & Data Science.