Mb0047 Management Information System Solved Assignment

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1 What are the differences between data and information? Briefly explain the different types of information systems.

Differences between data and information

Explain the types of information systems

Answer: Data is a raw collection of facts. The word raw indicates that the facts have not been processed in any way. When processed, data is called information. For example, consider the act of booking a ticket on the Indian Railways (IR) website. Let us assume that you have already picked your source station, the place where you will start your journey,



2 How to use information system to support competitive strategy? Explain with an example for each strategy

5 strategies and its use of information system

Examples for each of the strategies



Competitive StrategyUse of Information SystemsExample
Create barriers to entry for competitionTo create barriers to entry of new competition, firms may lock-in existing customers with loyalty programmes and free access accounts created with information systems. Data from such loyalty programmes can also be used to identify customer tastes and patterns of buying to further provide them with goods and services.Yatra.com is an online travel portal that enables customers to buy airline and railway tickets from its site. It maintains a loyalty programme by providing discount coupons to customers who purchase frequently.

3 a. Explain First-order and second-order effects

  1. Distinguish between hierarchy and matrix organisational structures
  2. Explain First-order and second-order effects
  3. Distinguish between hierarchy and matrix organisational structures

Answer: a) The outcome of the implementation of a new IS could be positive or not, and this will depend on the situation at the organisation. The outcomes that arise as a direct consequence of the introduction of an IS are known as first-order effects. They are usually visible in organisations in the form of increased speed of processing of data or increased volume of processing and these are what any organisation would have intended to



4 Briefly explain the Customer Relationship Management (CRM) system. What are the various facilities created by CRM?

Explain the CRM System

Examples of various facilities created by CRM

Answer: The idea of CRM systems is to integrate all functions related to sales and marketing on a common platform. These functions include those that require support to sales and marketing staff and also those that


5 Briefly explain the different aspects of the need for database systems.

Explain any eight aspects of the need for database systems

Answer: Different aspects of the need for database systems

Data independence: Databases allow data pertaining to an activity or a domain to be maintained independently. This independence means that the data is stored in separate files in a structured manner, and the creation and updating of the data is done independent of its uses. For instance, in a college, a database of students is updated when a student joins or leaves the college, changes address, changes phone number,



6 Why privacy is important for individuals in the organisations? Briefly explain. How workplace electronic monitoring is done in the organizations?

Explain the reasons why privacy is important in the organisations

Explain the ways in which electronic monitoring is done in the organisations


Answer: Information systems are used widely across organisations, and they enable data and information to be widely distributed for use. When the data pertains to individuals (relating to their work, personal habits, or


SMU MBA SPRING 2016-2017

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SMU MBA SPRING 2016 Assignments are available. For Booking ,Kindly mail us on kvsude@gmail.com OR call us to +91 9995105420  or S M S your “ Email ID ” us in the following Format  “  On +91 9995105420 we will reach back you with in 24H ”

MB0047 : Explain with an example of your own the difference between data, information, knowledge and wisdom.

There is probably no segment of activity in the world attracting as much attention at present as that of knowledge management. This arena of activity  quickly found there didn’t seem to be a wealth of sources that seemed to make sense in terms of defining what knowledge actually was, and how was it differentiated from data, information, and wisdom. What follows is the current level of understanding piece together regarding data, information, knowledge, and wisdom.

According to Russell Ackoff, a systems theorist and professor of organizational change, the content of the human mind can be classified into five categories:

  • Data: symbols
  • Information: data that are processed to be useful; provides answers to “who”, “what”, “where”, and “when” questions
  • Knowledge: application of data and information; answers “how” questions
  • Understanding: appreciation of “why”
  • Wisdom: evaluated understanding.

Ackoff indicates that the first four categories relate to the past; they deal with what has been or what is known. Only the fifth category, wisdom, deals with the future because it incorporates vision and design. With wisdom, people can create the future rather than just grasp the present and past. But achieving wisdom isn’t easy; people must move successively through the other categories.

A further elaboration of Ackoff’s definitions follows:

Data… data is raw. It simply exists and has no significance beyond its existence (in and of itself). It can exist in any form, usable or not. It does not have meaning of itself. In computer parlance, a spreadsheet generally starts out by holding data.

Information… information is data that has been given meaning by way of relational connection. This “meaning” can be useful, but does not have to be. In computer parlance, a relational database makes information from the data stored within it.

Knowledge… knowledge is the appropriate collection of information, such that it’s intent is to be useful. Knowledge is a deterministic process. When someone “memorizes” information (as less-aspiring test-bound students often do), then they have amassed knowledge. This knowledge has useful meaning to them, but it does not provide for, in and of itself, an integration such as would infer further knowledge. For example, elementary school children memorize, or amass knowledge of, the “times table”. They can tell you that “2 x 2 = 4” because they have amassed that knowledge (it being included in the times table). But when asked what is “1267 x 300”, they can not respond correctly because that entry is not in their times table. To correctly answer such a question requires a true cognitive and analytical ability that is only encompassed in the next level… understanding. In computer parlance, most of the applications we use (modeling, simulation, etc.) exercise some type of stored knowledge.

Understanding… understanding is an interpolative and probabilistic process. It is cognitive and analytical. It is the process by which I can take knowledge and synthesize new knowledge from the previously held knowledge. The difference between understanding and knowledge is the difference between “learning” and “memorizing”. People who have understanding can undertake useful actions because they can synthesize new knowledge, or in some cases, at least new information, from what is previously known (and understood). That is, understanding can build upon currently held information, knowledge and understanding itself. In computer parlance, AI systems possess understanding in the sense that they are able to synthesize new knowledge from previously stored information and knowledge.

Wisdom… wisdom is an extrapolative and non-deterministic, non-probabilistic process. It calls upon all the previous levels of consciousness, and specifically upon special types of human programming (moral, ethical codes, etc.). It beckons to give us understanding about which there has previously been no understanding, and in doing so, goes far beyond understanding itself. It is the essence of philosophical probing. Unlike the previous four levels, it asks questions to which there is no (easily-achievable) answer, and in some cases, to which there can be no humanly-known answer period. Wisdom is therefore, the process by which we also discern, or judge, between right and wrong, good and bad. I personally believe that computers do not have, and will never have the ability to posses wisdom. Wisdom is a uniquely human state, or as I see it, wisdom requires one to have a soul, for it resides as much in the heart as in the mind. And a soul is something machines will never possess (or perhaps I should reword that to say, a soul is something that, in general, will never possess a machine).

The following diagram represents the transitions from data, to information, to knowledge, and finally to wisdom, and it is understanding that support the transition from each stage to the next. Understanding is not a separate level of its own.

  • Data represents a fact or statement of event without relation to other things. Ex: It is raining.
  • Information embodies the understanding of a relationship of some sort, possibly cause and effect. Ex: The temperature dropped 15 degrees and then it started raining.
  • Knowledge represents a pattern that connects and generally provides a high level of predictability as to what is described or what will happen next. Ex: If the humidity is very high and the temperature drops substantially the atmospheres is often unlikely to be able to hold the moisture so it rains.
  • Wisdom embodies more of an understanding of fundamental principles embodied within the knowledge that are essentially the basis for the knowledge being what it is. Wisdom is essentially systemic. Ex: It rains because it rains. And this encompasses an understanding of all the interactions that happen between raining, evaporation, air currents, temperature gradients, changes, and raining.

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Tags: Ackoff, Data, Information, Knowledge, Knowledge management, Russell Ackoff, Russell L. Ackoff, Wisdom


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