Whenever I was working on a project, I was always puzzled by the look I got when I asked about communication policy.
In most cases, communication is considered “embedded” in the activities- hence, no need whatsoever to plan or set guidelines.
This is a short article (1000 words is the limit), summarizing some suggestions that I keep sharing since late 1980s, when I was working everyday in a different project/site.
If you read once in a while this chaotic website of mine, you know that I wrote here and there about change management.
I would like to share here some experience from my activities, and why I believe that adopting a common framework might be sub-optimal, but a smart allocation of resources.
To summarize:
The title sounds a mouthful?
Well, you can thank WordPress: the original title was “Non-regulatory approach toward systemic risk management and entropy reduction” 
Moving down to Earth- what is the purpose of this posting?
Sharing, as usual, experience. But this time, something more: a business model and plan.
The visible title of this section is “Genome and brain mapping”.
The link is named “cathedrals”.
It is not a criticism: it is a realistic assessment.
Beside the human genome and brain mapping, this section will discuss also how these and other mapping initiatives could affect not just science and medicine, but our everyday life.
This post is part of a series, first published in May 2009.
You want your model to work in reality, and therefore you have to assume that others have their own models.
It is a game. Like playing chess. Or the usual “prisoner’s dilemma”.
From models, we will move to the interaction between models- and between different decision paths within a model.
A down-to-earth introduction to the game theory.
This post is part of a series, first published in May 2009.
When you build a model of reality, you try to reduce complexity.
Reducing complexity means making choices- and reducing the risk of something unexpected affecting the results of your model.
Actually, it means also reducing the number of parameters- and, therefore, making any evolution in your world more predictable.
But reality is not necessarily limited by your definition: and managing the reality within a model requires more that planning beforehand for what you know, in terms of activities or risks.
You have also to identify what is the “normal” way in which your model will react to unexpected changes in the “reality” surrounding your model.
This post is part of a series, first published in May 2009.
If you identify the “risks”, what could affect the conditions that you assumed that could affect your execution of the plan, then you will end up monitoring that:
It is not just the journey that you have to keep in check; it is also the destination.
This post is part of a series, first published in May 2009.
You do not need to know just what you are supposed to do, but also where you are, and where you should be.
If you are a perfect project manager with all the certifications required: probably you should skip this section, as it could be depressingly simple.
But it is not just progress itself- is the measuring and definition of progress that matter.
This post is part of a series, first published in May 2009.
In my definition, a plan is neither cast in stone, nor just an intellectual exercise done because it is supposed to be done.
But what, after defining a model of your reality, and identifying the changes required and their impacts, should be part of your planning activity?
This post is part of a series, first published in May 2009.
Searching & Machine intelligence & Decisions
Tuesday, May 19th, 2009How the addition of WolframAlpha as a search engine could complement Google services to create a new market.
Services? Access and structure knowledge. And a new form of knowledge management.
Tags: alpha, analyst, artificial, brio, business, competitive, comshare, dimension, dss, eis, explain, fitness, game, google, intelligence, knowledge, magazine, management, model, online, project, prolog, theory, training, web, wolfram, yale
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