PARTICIPATION

 

 

            Participation is extremely important for this online course.  Participation is not the same as attendance; active participation involves substantive, meaningful messages that add to the content of previous discussions, raise additional questions and issues, expand the thoughts of your classmates’ ideas, and in general, serve to perpetuate and enhance the discussion.

 

As part of the weekly assignments, I will post Discussion Questions as a thread.  Please use the threads to post your responses rather than starting new threads of your own.  Your active participation involves posting response messages 5 different days out of 7 days each week in order to earn the maximum participation points (see Grade Determination). Keep in mind, that your total activity in this online course should be equivalent to a traditional face-to-face classroom experience. For example, if the course is taught in an 6-7-week format (mini-term courses), the equivalent online activity should be approximately 6-7 hours each week. Online activity includes accessing Moodle to review course materials, posting comments to discussion threads etc.).

 

The following is an example of a “substantive, dynamic response:

 

Discussion Question

 

Drawing upon your personal (or professional) experience, provide an example(s) of your use of data in the context of making a decision.  Describe the data.  Was data collected from a census or just a sample? If only a sample was taken, why and what method was used? How was the data used to support the decision?  Were the methods used as descriptive or inferential?

 

Student A

 

During my days when I was managing a call center, I used data to make decisions on a daily basis.  One way was to track productivity levels of the associates.  This call center performed surveys for various industries.  The associates conducting the surveys were paid based on their completion of surveys per hour.

 

By looking at individual completion rates and the overall completion rates, you can determine who is doing well, who is not, and how much product is getting to the customer.  Breaking it down further, you could use the data to see times of best productivity (day, afternoon, night, weekends).  B to C calling always was better during weeknights, except on Friday’s because that night had the worst contact rate of all shifts.

 

The entire population was used as there were only about 110 on the payroll.  This was only one set of data that was used to manage the call center.  I used additional data to monitor customer account percentages, assign prosecution priority, and flags for excessive non-contact outcomes.

 

Student B

 

You are absolutely right!  There are other controls, especially  on the validity of the data.  As part of the quality control effort, a sample of completed surveys was graded for each associate.  This grading had a direct impact on pay.  If a customer hangs up in the middle of a survey, the associate was to comment on which question was the last one answered. 

 

Student A  

 

I forgot to mention, anyone caught forging surveys was considered cause for immediate termination.  I even fired one person for going through names in accounts and tagging them as no answer just to force the system to not have names to work.  There were many collection data points in the system with complete accountability so I could go back to see who worked what and when.

 

Student B

 

After reading these messages, I would agree that the additional controls would be exactly what are needed to avoid any abnormal occurrences of fraud.  I think the most important thing is that the consequences have to be so extreme that someone would not feel it is worth taking the risk of being terminated. 

 

Instructor

 

An interesting example.  Do you know how the names to be called were selected?  What kind of data was collected during the survey?

 

Student A

 

We had several business units.  The names were sent to us by our customers.  We performed customer satisfaction/retention and customer prospecting type survey mostly.  Our goal was to identify any problems or unhappiness that enabled us to fix the problem before the factory surveyed the customers.  Answers were also tracked over time; pie charts, bar charts, and tabular sheets were part of the overall finished product to the customer.  Monthly summaries were prepared, with year-to-date comparisons.