Lab 2 Assignment

© 2009 by Rong Yang and Bruce Neubauer

Explanation

Knowledge management is not the same as information management, although the two are related. Whereas information management usually involves the storage and retrieval of data from databases knowledge management usually regards the sharing of knowledge among employees through formal or informal networks of personal associations. In other words, by analogy, information management is about, "the organization remembering," and knowledge management is about, "the organization thinking." If knowledge cannot flow easily through an organization and find its way into the minds of the "right" decision makers, important decisions will be made by individuals who do not have the knowledge they need, even though that knowledge exists elsewhere in the organization. Knowledge management is especially important in teams of first responders to emergency situations. This lab assignment involves the computer simulation of knowledge flowing through a very small network of first responders, including a "boss" who must make quick decisions with only the knowledge he/she has received from team members on the scene of the emergency.

Assignment and Deliverables

Using the SquareModel.doe file (opened in the Arena software application) you are to anticipate (hypothesize) what will be the consequences of variations in initial settings on the outcome of the simulation. You may use the output data made available on the screen as a means of testing your hypotheses. You can also open the detailed data file that SquareModel.doe produces to better understand what is happening and why.

The "deliverable" of this assignment is hard copy of the Microsoft Word file provided with the blanks filled in and the short essay written.

Overview of the SquareModel Model

SquareModel.doe is a Rockwell Arena simulation designed to allow the simulation of a simple communication network such as might be found among upper echelon individuals overseeing first responders in an emergency situation.

The particular network simulated here has just four active nodes and a half dozen communication connections:

Actors (nodes) 1, 2, and 3 all generate observations. They can either pass an observation on to one of the actors they are connected to or choose not to pass the observation on at all. This decision-making process is controlled by probabilities attached to each of the communication channels. Actor 4 is the “boss” – the decision maker.

When the simulation is over, a report is generated which gives information on the movement of observations, the number which reach the boss, and the number of times the various actors received more information than they could handle. Note that you must fully stop the simulation (the stop button in the VCR control) before the output file is completely written to disk.

Operation

The program is loaded into Arena by simply double-clicking on the .doe file or choosing File/Open from the Arena menu. Be sure to use the Save As menu option to save the model to a location on your computer you have access to. The Desktop or other location is fine, so long as you remember the location. The program is then executed by choosing Run/Go from the menu system, pressing the F5 key, or clicking on the run button on the VCR-style control at the top of the Arena display. The first thing you will see is an input form:

Under “Number of Observations”, the user can select how many observations environments 1, 2, and 3 (our actors 1, 2, and 3 above) will produce during the simulation. The box labeled “Transition Probabilities” allow the user to assign probabilities to the communication links – the numbers in each row must add up to 1 or less. Under “Cognitive Overload Cutoffs” the user can set the maximum of observations which each actor can handle – more than that and something will be lost. The Randomize check box allows the user a degree of control over how random the simulations are. Normally it should remain checked, which means everything in the simulation happens randomly. When it is unchecked, each time Arena is restarted, the same sequence of simulations begins again. Note that if you run the simulation several times with Randomize unchecked, the same simulation will not be repeated over and over – it is the repetition of a series that repeats. A name for the output file can also be chosen.

Once the simulation is underway, it looks something like this:

Observations are created by the members 1, 2, and 3. As they move through the simulation, they have different colors reflecting their origin. When an observation reaches one of the members, it is placed in a queue waiting to be dealt with. It is the size of these queues that determine whether an actor is suffering from cognitive overload. Suppose, for example, an actor has his cognitive overload cutoff set to three and his queue has three observations in it. If a fourth observation comes his way, the oldest observation in his queue will be deleted (it disappears from the simulation) before the new observation is added to the queue.

The Variables that You Can Initially Set

Many things in the real world can effect the flow of knowledge through a social network (organization or team). The three variables that you can set using SquareModel.doe are

· The number of events happening in the environment at the scene of the emergency.

· The limit of the ability of emergency responders on the scene to see and "process" what is happening.

· The propensity of the emergency responders to share what they are observing with others, including the "boss" who is working in some safe office and making all the decisions.

Directions to complete this Lab Assignment:

In order to complete this lab you must run multiple simulations of the Arena model and record both the inputs and the outcomes of each simulation on the pages provided as the "deliverable." One you have the SquareModel.doe file open in Arena, there is a SEQUENCE OF STEPS to run each iteration.

1) If you have not already done so, create a directory on C: drive named ArenaFiles. "Save As" the file as "run1A" (or whatever) and save it in the ArenaFiles directory.

2) If you have not already done so, set the "VCR" in Arena to slow down the simulation.

3) Press the "Play" (Go) button on the VCR.

4) You will see the input form where you can change settings. Set all the values in the form as indicated in the instructions on the "deliverable" pages provided. You can rename your Output File Name to run1Aoutput.txt. Leave the Randomize box checked. Click OK.

5) Run the simulation, observe what is happening. When the simulation runs to completion, click "No" to seeing Arena's results.

Click No when asked about viewing the results generated by Arena. Click "End" on the "VCR" to get out of run mode.

Use Windows Explorer to find the file that Arena created (and you named run1Aoutput.txt) and study it to better understand what happened in the simulation. Look for it in your AArenaFiles directory.

Study and interpret the resulting run1Aoutput.txt file. You can open and view it in NotePad. When you see something like

A total of 39 observations were intended for Observer 1.

22 (56.41%) of these originated with him.

this means that 22 of the 39 observations intended for Observer 1 were produced by Environment 1. Similarly for Observers 2 and 3.

When you see something like 1 → 0 it means that the team member did not communicate the message to anyone.

6) Fill out the information indicated on the "deliverable" pages and then continue to the next iteration by clicking the "play" button again, as indicated in "3" above.

7) When you have completed all the required iterations reflect on the results of the simulations. You can run additional simulations if you want to. Then answer the short essay question and hand in your deliverable to your instructor.