Availability Engineering

It's not only associated with IT assets but with other departments also. Availability is primarily used by the IT staffs to relate with the availability of the IT services in the organization. However other departments can also take a cue from the same and a process can be implemented to ensure that productivity and efficiency are not lost because of non availability of the resources. By intertwining Human asset engineering and Workability quotient Matrix an organization can achieve avalability index for each and every department. So apart from network gears, applications, databases and equipments other forces that actually runs the organization can also be made available despite of forced closures (bandhs), floods, earthquakes etc etc.

The premise to this remains very very simple:

For example I am hit by a flood.  I am small business. All I have is 50 staffs and all my staffs are located in one geography and every one is stranded. The flood has taken my data center down. I visualized this and have created a stand by center (hot, warm, cold) 100 miles away from my geography, so now I can switch open all my work by activating this mirror, but wait, who is going to perform the duties as all are stranded?

This basic never get answered by any one. The reason remains that one can replenish the hardwares and softwares but not human capital or rightly said human asset. 

At our company, which is a small consulting outfit and does niche work in the area of feasibility, assessment, value engineering and strategic management we have devised a simple solution. Despite what may happen even if one human resource is standing the work will go on. And how we have achieved that:

By re-engineering our work process. We have distributed the work space in various parts of the city with every batch of work (each activity is defined as a batch of work) that is happening gets updated instantaneously on web, on email, on phone, on paper and on files located at every ones house. So we afford to the have the luxury of loosing instant data at the time of happening.  And technology plays very small part in it. We never enter office together, we ensure that one person knows exactly what the other is doing and vice versa, we ensure that every one works on a collaborative framework, where each piece of knowledge gets shared among each other except the financial data. 

This definitely throws some challenges essentially in terms of data sharing that may happen with the outsiders, but why is law there for? We ensure that the contracts are stringent and we spell out the penalties so well that rarely one may think of sharing an important piece outside. Is this is dictatorship? No this is human asset engineering blended with workability matrix. Interesting isn't? More on this later....

The curious case of performance

The stream collaboration effect has thrown some questions. What is with performance? How we can systematically imbibe the effect of it in the model? I am planning to encompass the set of roles, skills, activities, practices, tools, and deliverables as key denominators for each and every block. 

What is interesting to note that the forces that act upon the model are predefined! History glass tells me that each of these sequels and prequels are almost look alike! A food for thought.

The model looks good. Still not sure it is making any sense to do such deep study, which may not yield any result at all. However I am enjoying this phase of development and it certainly is helping me individually to learn hitherto unknown stuffs. 

The Stream collaboration Effect

This remains one of the close subjects. I have been researching for a while now, to draw similarities between ecosystem of survival through adding different study streams as fundamental economy blocks. It's about building the blocks one by one, which are interdependent on each other. Drawing parallels from the various streams of study I am building a framework that can be a model of showing interdependencies that exist in the global economy. For example I have drawn similarities between Geography, History, Science and Arts. I have denoted a specific legend for each of these streams.

Legends:

1) Geography: Boundry of restriction for travel. 

2) History: The rise and demise of empires for reasons that are apt

3) Science: A collaboration between rational thinking, execution and brilliance

4) Art: Timing

The real interesting part of collaborating all these in a graph shows that one is interdependent on each other and they behave exactly the way the other behaves. If one is good the other shows positive coordinates and vice versa.

Now the challenge is to incorporate a dateline and then simulate the collaboration effect. All precisely done can we see a definite model that can classify the way economy will behave? The main ingridient that remained to be simulated is the breach conditions (violations). 

I am hopeful that model will see the day light by next spring. 

Quick Facts about Mamata

Born in Kolkata, Mamata Banerjee completed degrees in work education from Basanti Devi College and an LLB from Jogesh Chandra Chaudhuri Law College under Calcutta University. She started her political career with Congress (I). In 1984, she became one of India's youngest parliamentarians ever, beating veteran Communist politician Somnath Chatterjee, from the Jadavpur parliamentary Constituency in West Bengal. Losing her seat in 1989 in an anti-Congress wave, she was back in 1991, having settled into the Calcutta South Lok Sabha constituency. She retained the Kolkata South seat in the 1996, 1998, 1999, 2004 and 2009 elections.

What is with dreams?

What is it with dreams? Why we dream? Why we try to achieve something, which is vague at times? And when these dreams gets shattered, when we fail why we get mocked? Wasn't it was told to us that dreams are important? 

Then why mock when ones dream gets shattered. Since last two weeks I have seen things happening to some one else which happened to me some years back. There are similarities and I saw the desperation on that man's face. He reminded me of days when I faced uncertainty, gloom and was almost perished. Don't want this guy to meet his nemesis so soon. Don't want him to loose out because he dreamt.

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