I”ve just had a day of intense modeling conversation followed up the next day a lunch meeting with an old friend who just left Microsoft. We worked together at Apple, and ran into other during years at Microsoft. Coincidentally, we saw each other a week after he left while he was on a charity holiday run. He left Microsoft after 14 years and I did too.
Given his recent departure and process of decompressing from 14 years at Microsoft I asked if he had reached an epiphany. He hadn’t yet, but I did.
There are many reasons why you want to create abstract models of complex systems.
Scientific modelling
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Example of scientific modelling. A schematic of chemical and transport processes related to atmospheric composition
Scientific modelling is the process of generating abstract, conceptual, graphical and or mathematical models. Science offers a growing collection of methods, techniques and theory about all kinds of specialized scientific modelling.
Modeling is an essential and inseparable part of all scientific activity, and many scientific disciplines have their own ideas about specific types of modeling. There is little general theory about scientific modeling, offered by the philosophy of science, systems theory, and new fields like knowledge visualization.
And, I have had fun discussing models with executives like Thetus’s Danielle Forsyth and Skanska’s Jakob Carnemark. We all see the benefit, but how do you get others to understand why modeling.
Modeling enables Trust of a technical solution.
For a trustful and friendly use of technology, the user must be able to have a clear mental model of its use and functioning (way of working), being it partial, superficial and even wrong, but at the same time sufficient for having precise expectations and for knowing how and what to do, i.e. sufficient for reducing uncertainty and perceiving safety and reliability.
So, why model the data center? It increases trust in the data center system including its users. Higher trusts promotes knowledge sharing.
It is clear how trust is a precondition for knowledge sharing and a result of it or, more precisely, that trust is a mediator, a catalyst of the process: it is a mental and interpersonal (cognitive, dispositional, and relational) precise condition for the two crucial steps in the organisational flow of knowledge.
The relationship between trust and knowledge sharing is circular: in order to trust Y, X must either have information about Y, helping him to evaluate Y's trustworthiness, or having knowledge in common with him that encourages the establishment of a trust relationship so as values sharing; on the other hand, in order to share knowledge, it is necessary to have a trust relation or atmosphere.
While caring of making knowledge capital explicit and circulating, an organisation should care of what are the beliefs of the actors about the knowledge itself, about the organisation values, authority, infrastructure, and about each-others, and what they expect and feel on the basis of such beliefs. In knowledge management organisations should monitor and build the right expectations in their members. Knowledge management entails a cognitive, affective, and structural "trust management" in organisations.
I’ve always done business assuming trust of the other party to create partnerships. I hadn’t thought about it as a separate property that indicates the health of the a system. Modeling if used right can increase trust of the modeling systems.
