Assignment 1: Business Process Modeling
Business processes are fundamental building blocks of any business. It is important to understand how information systems are used to automate, streamline, and/or re-engineer these processes to improve how any given business runs. We’ll explore this idea by applying BPMN (the Business Process Modeling Notation) on a couple of different business processes.
Assignment Intro Video
if the video resolution is not good, then go to the bottom corner of your video screen, click Source Chooser () button, and select the largest kbps
Assignment Overview
Please review these documents before you begin. You do not need to make your model “complex.” But, you should use the notation properly.
Introduction_to_BPMN.pdf
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BPMN_Standard_Symbols(2.0).pdf
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Sample Process Using BPMN 2.0.pdf
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REQUIREMENT:
Create a process model using the BPMN technique for each of the business processes assigned. With each model you should provide a narrative explanation of any assumptions you made while constructing the model or anything else that needs explanation. Note that all processes rely on at least some assumptions. Be sure that your assumptions do not contradict any of the terms of the assignment. In particular, be careful to not “assume away” any of the process’s complexities.
You should use a CASE tool called LucidChart to prepare your model. It allows you to draw the business process model and to export or save your diagram to a pdf or other (png) file format that can be uploaded to Canvas and displayed (so I can grade them). Please see the Lucid Chart Resources
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file to see how to sign-up and use Lucid Chart.
Upload your diagrams (in a readable format, pdf is best) to Canvas. Please use this format to name the files: “A1-uniqueID-RMV” and “A1-uniqueID-DUA” where uniqueID is your MU uniqueID (mine is gabelj5). You can upload a separate file for your assumptions, and use the same naming convention.
Create models for these business processes.
A. Cumberland County Registry of Motor Vehicles
The Registry of Motor Vehicles (RMV) in Cumberland County, Kansas, has recently simplified its license renewal process by automating the test-taking and fee-collection steps in the process. RMV notifies drivers when their licenses are about to expire. Drivers who renew their licenses in person at the RMV work with a computer that looks and functions like an ATM machine. The process is described in the following paragraphs. After keying in his or her current driver’s license number, the applicant is presented with a touch-screen display that pulls up test questions stored within the computer. Short video clips of typical traffic situations are shown, and questions are asked about each clip. The applicant responds to the questions by selecting from options presented on the screen. The terminal scores the test, allows users to change address or other personal information appearing on the screen, and “collects” the renewal fee. The user “pays” the fee by inserting his or her VISA or MasterCard into a designated slot on the computer. The computer then prints a scored answer sheet, which the applicant takes to a registry clerk. The clerk completes the process by administering a vision test, taking a picture of the applicant, and issuing a license.
B. Down Under Airlines
Down Under Airlines (DUA) processes over 400 million tickets a year. The process of issuing the tickets is highly automated; a record of each ticket sold is stored in DUA’s database. But when passengers turn in tickets, gate agents stuff the flight coupons into envelopes and ship them to DUA’s Denver headquarters. Because of discrepancies between the original records housed in the ticket database and actual ticket use as reflected by the flight coupons, DUA, like other airlines, has to match every coupon against every ticket in the database in order to accurately account for passenger revenues. With the volume of tickets involved, manual matching is a daunting task. Image processing to the rescue!
DUA’s new processing system, designed by one of the Big Four professional service firms, is designed as follows: When a ticket is sold to a passenger by a travel agent, by one of DUA’s own 30,000 ticket agents, or online; the seller enters a record of the ticket into DUA’s database, just as in the past. However, when flight coupons are received in Denver, they are now read by an image scanner that captures the images and stores them in an optical storage and retrieval library called Big File. The ticket number appearing on the flight coupon is also scanned by an optical character recognition (OCR) system. The ticket numbers (an index to the ticket images themselves) are stored in a relational database, which is used to track the location of each ticket image in Big File. Operators use a network of workstations to access ticket images. Special audit software matches each ticket image in Big File with ticket records in the mainframe database. If the image and record do not match (for instance, a three-leg ticket sold but only two legs used), the ticket number is included in the audit data. If the image and record do match, the ticket record is written to the passenger revenue data.
