In this tutorial, we will discuss the DIKW Model of ITIL (Data, Information, Knowledge, and Wisdom Model). This model is also known as the DIKW Hierarchy or DIKW Pyramid. In this tutorial, you will learn what is a DIKW Model? How the data is transformed into wisdom? And what are the usage and limitations of DIKW Hierarchy?
What is the DIKW Model in ITIL?
DIKW Model is an essential part of ITIL Knowledge Management under the Service Transition Module. It is the graphical representation of how knowledge can be organized within the organization.
[See Also: ITIL Knowledge Management]
We know that, when we collect raw data, it comes in a jumbled form. DIKW Model describes how the data can be processed and transformed into information, knowledge, and wisdom.
The full form of DIKW Hierarchy is as below:
“D” = Data
“I” = Information
“K” = Knowledge
“W” = Wisdom
The DIKW model of transforming data into wisdom can be viewed from two different angles: contextual and understanding.
As per the contextual concept, one moves from a phase of gathering data parts (data), the connection of raw data parts (information), formation of whole meaningful contents (knowledge) and conceptualize and joining those whole meaningful contents (wisdom).
From the understanding perspective, the DIKW Pyramid can also be seen as a process starting with researching & absorbing, doing, interacting, and reflecting.
The DIKW hierarchy can also be represented in terms of time. For instance, the data, information, and knowledge levels can be seen as the past while the final step - wisdom - represents the future.
Refer to the following diagram to understand the representation:
The "Data" of DIKW Hierarchy:
The first step in this DIKW model is Data. Collection of raw Data is the primary requirement for reaching a meaningful result in the end. Any measurements, logging, tracking, records etc are all considered as data. Since the raw data is collected in bulk, it includes various things both useful and not so useful contents.
These are completely raw Data and do not provide any meaningful result that can be used by the IT Service provider. Therefore the data doesn't answer any questions nor draw any conclusion.
To understand how the Data is transformed into usable results using the DIKW Pyramid model, we will discuss each of the subsequent steps of the of DIKW hierarchy (i.e. - information, knowledge, and wisdom) using sample scenarios.
For Example, Let’s assume the scenario is - 500 Users visits CertGuidance.com daily to take online lessons. This is the raw data we have got from statistics.
The "Information" of DIKW Pyramid:
Information can be termed as the data that has been given a meaning by defining relational connections. Here, the word "meaning" represents processed and understandable data that may or may not be a useful piece of content from the organization perspective.
In information processing system, a relational database creates information from the data stored within it.
The information hierarchy stage of DIKW Pyramid reveals the relationships in the data, and then the analysis is carried out to find the answer to Who, What, When and Where questions.
Now let come to the above example, the data “500 users visit CertGuidance.com per day” is quite a generic number to get any insight. Now, to do the capacity planning and availability planning, we must process it through information stage of DIKW Hierarchy.
Now we can get answers like - 250 Users visit ITIL Training, 225 User visits WordPress Tutorial, 25 Users just visits the homepage. Out of them, 60% is in the age group of 20-35 years, 20% in age group of 35-45 Years. Also, we get 70% of our visitors between 9 AM to 11 PM.
See, the generic data now become an information answering the questions of Who, What, When, and Where. This is the output we can get from information stage.
The "Knowledge" of DIKW Model:
Knowledge is the third level of DIKW Model. Knowledge means the appropriate collection of information that can make it be useful.
Knowledge stage of DIKW hierarchy is a deterministic process. When someone "memorizes" information due to its usefulness, then it can be said that they have accumulated knowledge.
Every piece of knowledge itself has useful meanings, but it can't generate further knowledge on its own.
In information management system, most of the applications you use, such as modelling, simulation etc, exercise some sort of stored knowledge.
The knowledge step tries to find the answer to the "How" question. Specific measures are pointed out, and the information derived in the previous step is used to answer this question.
With respect to our scenario, we must find the answer that “How do professionals between the age group of 25-35 years use our tutorial?”
The “Wisdom” of DIKW Hierarchy:
The Wisdom is the fourth and the last step of the DIKW Hierarchy. It is a process to get the final result by calculating through extrapolation of knowledge. It considers the output from all the previous levels of DIKW Model and processes them through special types of human programming (such as the moral, ethical codes, etc.).
Therefore, Wisdom can be thought as the process by which you can take a decision between the right and wrong, good and bad, or any improvement decisions.
Alternatively, we can say that in wisdom stage, the knowledge found in the previous stage is applied and implemented in practical life.
Wisdom is the topmost level in the DIKW pyramid and answers the questions related to "Why".
In case of our example scenario, one example of wisdom gained might be that due to 70 % of the working professionals visit our tutorials to get help with their certifications and technology needs.
Analyzing Organizational Issues Using the DIKW Hierarchy:
Data: A way to identify the raw external inputs such as the facts and figures that are yet to be interpreted.
Information: Analyze the raw data to determine the organizational needs. An important aspect of information management is that apart from answering questions it can also help to find other solutions in organizational contexts.
Knowledge: Determines how something is remembered by an individual or how information is applied by them.
Wisdom: Uncover why the derived knowledge is applied by individuals in a specific way. i.e. - finding the reason behind any decision-making.
The Usage and Limitations of ITIL DIKW Model:
Same as all other models, DIKW Model also has its own limits. You may have noticed that the DIKW Hierarchy is quite linear and follows a logical sequence of steps to add more meaning to data in every step forward. But the reality is often quite different than that. The Knowledge stage, for example, is practically more than just a next stage of information.
One of the principal critiques of this DIKW Pyramid is that it’s a hierarchical process and misses several important aspects of knowledge. In today's world, where we use various ways to capture and process more and more unstructured data, sometimes forces us to bypasses few steps of DIKW.
Though the previous statement is quite true, however, the result still stays the same, such as what we do with the data warehouse and transforming data through big data analytics into decisions and actions (Wisdom).
We hope that you have enjoyed the above article describing the DIKW Model of ITIL Knowledge Management. Be with us to explore free training on Leading Technologies and Certifications.
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