EDUCATIONAL IMPLICATIONS

   
   It appears that one of the issues in defining the terms data, information, knowledge, and wisdom is the role of understanding and meaning making. One can memorize data, and parrot it back. One processes data (organizes it into meaningful chunks?) to produce information. Parroting such chunks sounds more like being educated--but this can be done with little understanding or ability to make use of the information. Knowledge is a step further on the scale. It involves understanding and ability to make use of the data and information to answer questions, solve problems, make decisions, and so on. Wisdom has to do with using one's knowledge in a responsible (wise) manner.

Difference Between Data , Information , Knowledge and Wisdom

      
     To begin with, organizational data, information, knowledge, and wisdom, all that emerge from the social process of an organization, and are not private. In defining them,we are not trying to formulate definitions that will elucidate the nature of personal data, information, knowledge, or wisdom. Instead, to use a word that used to be more popular in discourse than it is at present, we are trying to specify inter subjective constructs and to provide metrics for them. 

A datum is the value of an observable, measurable or calculable attribute. 

      Data is more than one such attribute value. Is a datum (or is data) information? Yes, information is provided by a datum, or by data, but only because data is always specified in some conceptual context. At a minimum, the context must include the class to which the attribute belongs, the object which is a member of that class, some ideas about object operations or behavior, and relationships to other objects and classes. 

      Rather, information, in general terms, is data plus conceptual commitments and interpretations. Information is data extracted, filtered or formatted in some way (but keep in mind that data is always extracted filtered, or formatted in some way). 

      Knowledge is a subset of information. But it is a subset that has been extracted, filtered, or formatted in a very special way. More specifically, the information we call knowledge is information that has been subjected to, and passed tests of validation. Common sense knowledge is information that has been validated by common sense experience. Scientific knowledge is information (hypotheses and theories) validated by the rules and tests applied to it by some scientific community. Organizational knowledge in terms of this framework is information validated by the rules and tests of the organization seeking knowledge. The quality of its knowledge then, will be largely dependent on the tendency of its validation rules and tests to produce knowledge that improves organizational performance (the organization’s version of objective knowledge). 

      Wisdom, lastly, has a more active component than data, information, or knowledge. It is the application of knowledge expressed in principles to arrive at prudent, sagacious decisions about conflicting situations. From the viewpoint of the definition given of organizational knowledge, we now ask what an organization is doing when it validates information to produce knowledge, it seems reasonable to propose that the validation process is an essential aspect of the broader organizational learning process, and that validation is a form of learning. 

      So, though knowledge is a product and not a process derived from learning, knowledge validation (validation of information to admit it into the knowledge base) is certainly closely tied to learning, and depending on the definition of organizational learning, may be viewed as derived from it.

        There has been much discussion on the web recently about the Data-Information-Knowledge-Wisdom or DIKW hierarchy and it is described by Patrick Lambe as "that most hallowed of mental models and glib explanations".

       Here is a little bit of reading for you. I have started with Patrick as I think he provides a very balanced view of the concept. Like most diagrams of this kind so much depends on how you interpret its meaning.

       Personally, I have never thought of it as a model and have never tried to use it to describe any form of process of moving from one to the other. I have simply seen it as a pretty diagram and have used it when explaining the differences between, data, information and knowledge and in recent years dropped it from my slide-set.

Data + Knowledge = Information

Bottom Step on the Wisdom Ladder:  Data

       Data  means raw counts of things.  Data can be useful or not useful.  In and of itself, data has no meaning.  If we count the number of cars  that stop at the stop sign on our block per hour for a week, that’s data.  It may be useful or not, depending on the context.  It has no meaning until it is placed in a  context.  Data can be accurate or inaccurate.  It can also be reliable or unreliable, valid or invalid.  What’s the difference? Imagine a target at which we shoot arrows using some machine.  If we shoot ten  arrows and they all cluster around one spot in the lower left corner of the target, we have a reliable machine, but not a very accurate valid one.  If we shoot ten arrows that scatter all over the target, but whose hit points all average out to the  middle, we have a pretty accurate (“valid”) machine, but it’s not very reliable.  When we collect data, we want  to use instruments that are both reliable (they get consistent results within a reasonable spread of error) and valid (they really measure what we intend them to measure).  The differences are subtle, but important for anyone who collects - and seeks to interpret - data.  Data is only as good as the measurement device we use to collect it: and if we fall asleep watching our street corner, we are not a very good data collector!

Second Step on the Wisdom Ladder:  Information
 

      When we put a whole lot of data together that is related toone subject, it can be collected to yield information.  In other words, (sets of data) + (collection of related data sets) = information.  Let’s say we want to buy a car.  we can collect a lot of data about makes of cars, performance ratings, prices and so on.  Once we do that, we have a lot of information about cars and the auto market.  Until we think about this collection of  data - this information - and put it in context, it is “dumb.”  By that it mean it has no meaning.  This is what we are flooded with every day.  On the Internet, we can find lots and lots of information - dumb collections of data.  Some of that information may be useful, and some of it may be accurate.  But  living in an “information age” means we are flooded all the time with access  to more information than we can possibly have time to put in context. We don’t have time to decide what it means, and it comes at us so fast!  The amount of information available to anyone in the world today is absolutely staggering, given  historical standards.  It is truly, lierally mind-boggling.

  

Third Step on the Wisdom Ladder: Knowledge

        Once we spend some time interpreting and understanding a  body of information, then we have knowledge.  This takes time.  While technology has greatly reduced the cost involved in assembling and storing data, and in transferring and storing information, technology has not done anything to make the process of creating knowledge any quicker or cheaper.  Creating knowledge still takes brains, thought and time - especially today when there is so much more information available to wade through.  People can become knowledge experts for a  given subject, which, in an “information age,”means they really are just advanced, perpetual students for that  given subject. We rely on these people to help us bypass the costly process of wading through large bodies of information ourselves. As a result, the credibility of knowledge experts is that much more important (and often hard to assess).  On the one hand, we have to be able to trust them to give us honest, valid and reliable knowledge, and on the other, we lack the subject specific knowledge to know whether or not they are really as reliable and credible as we need them to be.  It’s a  catch-22:  if we had the knowledge with which to judge them, we would not need them in the first place!  So what’s the solution?

Top Step on the Wisdom Ladder: Wisdom

       Wisdom is precious - and worth paying for.  It comes from the ability to synthesize various streams of knowledge - even seemingly unrelated bodies of knowledge - enough to be able to make  informed judgments about various ideas and propositions that may lie outside  of our own direct areas of expertise.  Certain patterns in nature repeat themselves, no matter where they may be found.  Wisdom entails having  enough experience and perspective to spot such patterns and trends so that various bodies of knowledge can be put in context, combined and applied appropriately. Inevitably, wisdom requires a deep,  perhaps intuitive understanding of human nature - of ambition, styles of  intelligence, human motivations, etc. - enough to allow the possessor of wisdom to make judgments about representations of knowledge that lie outside of his or her own expertise.  This is  how we can escape from the dilemma of the need to make judgments about experts who posses bodies of knowledge that we lack.  Wisdom amounts to something more than “street smarts,” but the sharpness of judgment implied by the phrase “street smarts” is encompassed by wisdom.

For example your grandparents may perhaps have been short on book smarts (“knowledge”) but long on wisdom.  In an “information age,” technology cannot confer wisdom:  wisdom takes more time to  develop and cultivate than even knowledge does (how many people do you know  with advanced degrees who lack wisdom or wise judgment?).  For this reason, wisdom is at an even higher premium, perhaps, than it has ever been, and when you find a good, credible source of wisdom (a person) who can help you make good judgments and grow your own store of wisdom, that’s a relationship to build and hold  firm.  This is why really good  mentoring is so valuable, and why the most effective executives and leaders  are extremely adept at understanding other people. Wisdom combines the seasoned experience of connecting and reviewing bodies of  knowledge, together with a genuine grasp of human nature and the ways of the  world, to allow for the proper use of data, information and knowledge.  Wise people, therefore, cultivate connections with other wise people or reliable knowledge experts, because this is the most effective way to leverage and benefit from vast stores of knowledge in this “information age.”

Data is not information, information is not knowledge, knowledge is not intelligence, intelligence is not wisdom.

FROM A BUSINESS POINT OF VIEW

The following three definitions are quoted from Godbout (January 1999).

       Data constitutes one of the primary forms of information. It essentially consists of recordings of transactions or events which will be used for exchange between humans or even with machines. As such, data does not carry meaning unless one understands the context in which the data was gathered. A word, a number or a symbol can be used do describe a business result, inserted in a marriage contract or a graffiti on the wall. It is the context which gives it meaning, and this meaning makes it informative. 

       Information extends the concept of data in a broader context. As such it includes data but it also includes all the information a person comes in contact with as a member of a social organization in a given physical environment. Information like data, is carried through symbols. These symbols have complex structures and rules. Information therefore comes in a variety of forms such as writings, statements, statistics, diagrams or charts. Some information theorists insist on the concept of form as the differentiating factor and the essence of information.

        Where does knowledge fit in this scenario? Information becomes individual knowledge when it is accepted and retained by an individual as being a proper understanding of what is true (Lehrer, 1990) and a valid interpretation of the reality. Conversely, organizational or social knowledge exists when it is accepted by a consensus of a group of people. Common knowledge does not require necessarily to be shared by all members to exist, the fact that it is accepted amongst a group of informed persons can be considered a sufficient condition. This is also true of «public domain» knowledge. The fact that it is readily available in writing or published material does not entail that everybody should be knowledgeable about it to meet the condition of being "common knowledge".

      Godbout presents these definitions in an article discussing roles of computers in the field called "knowledge management." Knowledge management is of steadily growing importance in running a business or similar types of organizations.

   ARRANGING THE TERMS ALONG A SCALE

   

    
      The terms Data, Information, Knowledge, and Wisdom are sometimes presented in a form that suggests a scale.

       However, in no sense do these four terms define some sort of linear equal-interval scale. They do, however, help us to discuss the design of an educational system as well as current and potential uses of computers. For example, we all accept that computers can be used for the input, storage, processing, and output of data. But, there is considerable disagreement about whether a computer can have knowledge or be knowledgeable--or have wisdom and be wise.

     In the good old days, in the early history of using computers to do business data processing, computers were data processing machines. There were lots of workshops and courses on data processing. "Raw data" was processed to produce reports that were then analyzed by management to make management decisions. Hourly time sheets of workers were processed to produce payroll checks and summary reports on employee costs.

     Later came the idea of computers processing data to produce information. Payroll data can be put together with other cost data, sales data, and so on to produce information about which products are most profitable. The huge collection of raw data can be processed into reports that facilitate high level management decisions.

   

     Computer Science Departments became Computer and Information Science Departments. Terms such as Information Technology (IT) and Information and Communication Technology (ICT) arose because they better described the computer field.

     In more recent years, businesses and others have worked to use computers to process information so that it becomes or is closely similar to knowledge. Knowledge in a person's head is used for posing and solving problems, posing and answering questions, defining decision making situations and making decisions, posing tasks to be accomplished and accomplishing the tasks, and so on. Nowadays, computers make lots of decisions without human intervention. That is, they receive data as input and they process it in a manner that produces decisions and actions as output. When a human does this, we talk about the level of knowledge, skill , and intelligence that the person has.

The graph below reflects the learning journey whereby we progressively transform the raw, unfiltered facts and symbols into information, knowledge, and eventually into intelligence and wisdom.

The discussion in this section leads to questions such as:

1. Can a computer system have knowledge and be knowledgeable?
2. Can a computer system have wisdom and be wise?
3. How should these ideas and answers affect business and education?

DATA

- Information, often in the form of facts or figures obtained from experiments or surveys, used as a basis for making calculations or drawing conclusions.

- Information, for example, numbers, text, images, and sounds, in a form that is suitable for storage in or processing by a computer

INFORMATION

- Definite knowledge acquired or supplied about something or somebody.

- The collected facts and data about a particular subject.

 - A telephone service that supplies telephone numbers to the public on request. 

- The communication of facts and knowledge.

- Computer data that has been organized and presented in a systematic fashion to clarify the underlying meaning 

a formal accusation of a crime brought by a prosecutor, as opposed to an indictment brought by a grand jury.

KNOWLEDGE 

- General awareness or possession of information, facts, ideas, truths, or principles.

- Clear awareness or explicit information, for example, of a situation or fact .

- All the information, facts, truths, and principles learned throughout time.

- Familiarity or understanding gained through experience or study.

WISDOM 

- The knowledge and experience needed to make sensible decisions and judgments, or the good sense shown by the decisions and judgments made.

- Acculated knowledge of life or in a particular sphere of activity that has been gained through experience.

- An opinion that almost everyone seems to share or express 

ancient teachings or sayings .

  - Information consists of data, but data is not necessarily information. Also, wisdom is knowledge, which in turn is information, which in turn is data, but, for example, knowledge is not necessarily wisdom. So wisdom is a subset of knowledge, which is a subset of information, which is a subset of data.

DEFINITION 

  
     Management Information Systems (MIS) is the term given to the discipline focused on the integration of computer systems with the aims and objectives on an organisation.

   The development and management of information technology tools assists executives and the general workforce in performing any tasks related to the processing of information. MIS and business systems are especially useful in the collation of business data and the production of reports to be used as tools for decision making. 

APPLICATIONS OF MIS

  With computers being as ubiquitous as they are today, there's hardly any large business that does not rely extensively on their IT systems.

However, there are several specific fields in which MIS has become invaluable.

* Strategy Support

   While computers cannot create business strategies by themselves they can assist management in understanding the effects of their strategies, and help enable effective decision-making.

   MIS systems can be used to transform data into information useful for decision making. Computers can provide financial statements and performance reports to assist in the planning, monitoring and implementation of strategy.

   MIS systems provide a valuable function in that they can collate into coherent reports unmanageable volumes of data that would otherwise be broadly useless to decision makers. By studying these reports decision-makers can identify patterns and trends that would have remained unseen if the raw data were consulted manually.

   MIS systems can also use these raw data to run simulations – hypothetical scenarios that answer a range of ‘what if’ questions regarding alterations in strategy. For instance, MIS systems can provide predictions about the effect on sales that an alteration in price would have on a product. These Decision Support Systems (DSS) enable more informed decision making within an enterprise than would be possible without MIS systems.

* Data Processing

   Not only do MIS systems allow for the collation of vast amounts of business data, but they also provide a valuable time saving benefit to the workforce. Where in the past business information had to be manually processed for filing and analysis it can now be entered quickly and easily onto a computer by a data processor, allowing for faster decision making and quicker reflexes for the enterprise as a whole.

MANAGEMENT BY OBJECTIVES

 
   While MIS systems are extremely useful in generating statistical reports and data analysis they can also be of use as a Management by Objectives (MBO) tool.

   MBO is a management process by which managers and subordinates agree upon a series of objectives for the subordinate to attempt to achieve within a set time frame. Objectives are set using the SMART ratio: that is, objectives should be Specific, Measurable, Agreed, Realistic and Time-Specific.

   The aim of these objectives is to provide a set of key performance indicators by which an enterprise can judge the performance of an employee or project. The success of any MBO objective depends upon the continuous tracking of progress.

   In tracking this performance it can be extremely useful to make use of an MIS system. Since all SMART objectives are by definition measurable they can be tracked through the generation of management reports to be analysed by decision-makers.

BENEFITS OF MIS 

  The field of MIS can deliver a great many benefits to enterprises in every industry. Expert organisations such as the Institute of MIS along with peer reviewed journals such as MIS Quarterly continue to find and report new ways to use MIS to achieve business objectives.

CORE COMPETENCIES

   Every market leading enterprise will have at least one core competency – that is, a function they perform better than their competition. By building an exceptional management information system into the enterprise it is possible to push out ahead of the competition. MIS systems provide the tools necessary to gain a better understanding of the market as well as a better understanding of the enterprise itself.

ENHANCE SUPPLY CHAIN MANAGEMENT

   Improved reporting of business processes leads inevitably to a more streamlined production process. With better information on the production process comes the ability to improve the management of the supply chain, including everything from the sourcing of materials to the manufacturing and distribution of the finished product.