Business Question

This is an individual assignment that needs 3 replies to other similar discussion on your opinion.

As you are aware by now that Decision Analysis and Modeling DAaM) is a very important part of Decision Support Systems. It makes the main component of Model Base Component of DSS. DAaM is also known by other names, (such as Decision Science, Management Science, Operations Research, etc.). Moreover, you must be familiar with the seven steps of DAaM application in problem solving. I did discuss and will again discuss DAaM in the class. Clearly DAaM covers a very vast body of modeling techniques applicable to many business situations. One interesting and complicated aspect of DAaM is how to formulate decision problems. Indeed, problem definition and formulation are the first critical steps of problem solving. It is often known as the first steps of modeling. Typically, DAaM is covered in MGMT 630 (or EM 602 – a pre-required course in our MBA program).

Clearly, problem formulation is a major aspect of knowledge acquisition in the Knowledge Management (KM) construct. By the way, KM is one important course in the MBA program. There is a course MGMT 650, which you may want to take as part of your MBA.

I am inviting you to read the article entitled “Just Modeling Through: A Rough Guide to Modeling,” and participate in a forum discussion to analyze and discuss the parallels between modeling and knowledge management. A PDF copy of this paper is seen attached at the bottom of this description of this assignment, as well as at the bottom of Module 8 (which covers KM). Please also do some research to find out as much as you can about the Four Quadrants of Knowledge Management. There are many articles you can easily and quickly find on this subject matter on the Internet. I am inviting you to conduct some research to enrich your knowledge about both modeling and KM.

As I inferred above, there are many parallels between Modeling and KM process. As you navigate to find your way through both, the following four (4) issues will quickly come to mind and challenge your curiosity. In Modeling as in KM, you must deal with

What you know you know(a double positive),

What you don’t know you know(negative + positive),

What you know you don’t know(a positive + negative), and

What you don’t know you don’t know(a double negative).

Below are the forum questions that you must first answer before you can answer the opinion expressed by others. Failing to answer these questions will significantly reduce your score on this assignment.

Questions:

Do you agree about the parallel between Modeling (i.e., particularly the problem formulation phase) and Knowledge acquisition phase of the problem? Please state and explain why or why not.

Now assume that there is a parallel. Please write a brief essay to draw a contrast between the difficulties you meet during Modeling (as part of the knowledge acquisition as you try to solve a decision analysis problem. You are specifically asked to draw a parallel on the four quadrants of KM (with the elements seen listed above)

Finally, consider the possibilities and prospects of extending modeling and KM with Artificial Intelligence (AI). Clearly, AI can greatly expand the possibilities of DMaM (as well as DSS) well beyond any limits we can imagine today. As I stated several times during our class discussions, AI has the potential for great creativities and goods, and also the great disasters and evils (thus, AI can be great disruptor to do both good and bad things to humans and the environment.). Please discuss how in your views, AI can shape up our future (for both good and bad)? Give detailed examples based on your opinions supported by research findings.

Just Modeling Through: A Rough Guide to
Modeling
MICHAEL PIDD
Department of Management Seienee
The Management School
Lancaster University
Lancaster LAI 4YX
United Kingdom
Skill in modeling is one of the keys to success in OR/MS practice. This has been recognized for many years, but we often
give it only lip service. Models are used in many ways in
OR/MS practice. A few simple principles of modeling may be
useful. The six principles discussed here cover simplicity versus complexity; model development as a gradual, almost
piecemeal process; dividing larger models into smaller components; using analogies; proper uses of data; and finally the way
in v^hich the modeling process can seem chaotic. Others may
wish to comment on these principles and add their own.
W
hen I am fortunate enough to visit
rized in the one word, modeling. In this pa-
a new country, I usually try to
buy one of the Rough Guides, since the
prejudices of the writers seem fairly close
to my own. The guides point out the good
(and bad) in the place to be visited, and
they attempt the impossible by trying to
give a flavor of the country in a few pages,
I have been active in OR/MS both as an
academic and as a practitioner since the
early 1970s. In my experience, the real
technical heart of OR/MS can be summa-
per, I will attempt to provide a rough
guide to modeling, with principles that I
and others have found useful and that
seem to resonate with students and
practitioners.
Others have written at length on the
useful principles of modeling. Morris
[1967] outlined some hypotheses about
modeling that he had found useful and
that illustrate the difference between modeling as an intuitive process and the for-
Copyright © 1999, Institute for OperaKons Research
and the Management Sciences
0092-2102/99/2902/0118/$5.00
This paper was refereed.
PROFESSIONAL—OR/MS EDUCATION
PHILOSOPHY OF MODELING
INTERFACES 29: 2 March-April 1999 (pp. 118-132)
A ROUGH GUIDE
mal study of existing models. Little [1970]
discussed how the then emerging technology of interactive computing could be employed to develop models that managers
would be likely to use. Hugh Miser and
Ed Quade had much to say on the subject
in their magnum opus on craft issues in
systems analysis [Miser and Quade 1988].
Hodges [1991] argued that even bad models may be used in satisfactory ways, even
if those models fall short of their creator’s
original intentions. Pat Rivett has written
much on the subject of modeling, and
Rivett [1994] provided a number of examples to illustrate a general approach to
model building. Powell [1995] discussed
how modeling skills may be taught to
MBA students and suggested six ]