Week 1 (KM), knowledge management class discussion

Hi,

Starting from today I’ll be doing a series of blogs on knowledge management (KM), for five weeks on what I am supposed to learn from my class.  Knowledge is not for hoarding so I’ll try sharing as accurately as I can, my gained understanding and knowledge.

This week I will be looking at:

• Data, information, knowledge

• What is knowledge
• Tacit knowledge
• Explicit knowledge

 

• What is the relationship between data, information and knowledge.

Information system IT people will try saying there’s a clear relationship between these but in truth no such clear relationship exists. There is a relationship between data and information, not really between knowledge. I’ll get back to that later on.

Data – represent raw or organised pictures, words, many documents, numbers like a stack of pizza plates after shop closes. To count or get a picture to compare against previous stack of pictures over many weeks, will give information on what days of the week most number of customers eat pizza. Thereby the shop won’t waste making extra pizza dough every day.

This has still not turned into knowledge as this situation of customer numbers can still change over many months and events that change with seasons. For management running the shop, in order to gain knowledge on the changing of customer numbers, they will need experience over many years. Keeping a good eye on how many random and seasonal events affect customer moods will enable themselves to be knowledgeable for their efficiency.

“Information is not knowledge.” ― Albert Einstein

And as you can see this part is only people and only people oriented. Therefore, if you believe an IT company can give you knowledge with a KM system it is only wishful thinking, once again my opinion from my experience believe it or not is up to you.

1. What is knowledge

To say I know with firm genuine knowledge;

a good example is how many people (astronauts excluded) say they know that earth is round when they haven’t even seen it themselves. Astronauts have had first-hand experience can say they know with firm conviction. If you can say without a doubt and with conviction, I know then it’s false and is not knowledge.

2.               Tacit and Explicit knowledge

Tacit knowledge is the knowledge of past experiences and expertise of fields and explicit knowledge is the  knowledge captured into a form of information in order that other people or machines can learn from.

An example is the hospitality industry when new staff members are trained by an expert and thereby the knowledge that experts leave behind.

Experts that know the art of service and the art of anything like thinking on the spot is not a type of knowledge that can be encoded in KM systems

When trying to retrain staff after losing staff, according KM system that can only hold basic information. Such staff will fail the company and the company will fail as a result of lowered standards.

Cool that’s all for this week see you’ll next week when we talk about making dumb terminals out of humans and creating SAI (Super Artificial intelligence) as means of KM.