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1 June 00
Springville Herald Case Study (Phase I)
.1 Data Table attached
. a.) Pareto Diagram attached
b.) We chose the Pareto diagram for this table, because it gives the most insight to the problem with the information provided. In this case, Copy error and Typesetting are the two mistakes that have the highest frequency.
c) The following is a report sent to management by the Technology Group
To Springfield Herald Management
Re "Customer Complaints" Meeting
We concluded this morning's meeting to address the complaints of the Springfield Herald's advertising, and with the help of the data you provided us we found that the advertising department had a total of 1 errors reported for the June 10th 00 issue. With the help of a diagram, we did find that the highest frequency of errors occurred in Copy Error and Typesetting (see attached Excel document Summary of Errors.doc). There were also high frequency of errors in the wrong position, wrong ad, velox and ones that were run in error. We request more information concerning these errors, specifically what the costs of these errors are.
. At this stage of the analysis, as stated in the report to management, the frequency of errors is not the only issue, but also what it is costing the paper in advertising. Information about the cost to the paper for the errors would be useful
Springville Herald Case Study (Phase )
.4 Data Table attached
.5 a) Graph attached
b) and c) We chose a side-by-side graph because we felt that the correlation between cost and occurrences were summarized best. It is most evident in this graph that even though the copy error occurred the most, it was not the most expensive. The error that cost the Springville Herald the most was ran in error.
.6 The following is a report sent to management by the Technology Group
To Management
Date June 10, 00
Re Advertising Errors
After our last meeting regarding reducing cost and focusing on errors we found that even though a particular error may occur most often, it is not necessarily the most costly. Attached is a chart showing the percent of occurrences and the percentage of associated cost. The four most expensive errors are 1) ran in error, ) typesetting, ) copy error and 4) wrong ad.
We would suggest focusing in on correcting and eliminating these four errors as they account for 71.% of the total cost of errors. Systems need to be set and followed to assure these errors are reduced if not eliminated.
The Springfield Herald Case Study (Phase )
.7 Data Table attached
.8 a) Side-by-Side Bar Chart Attached
b) Using the side-by-side bar chart clearly depicts interrelationships among dollar amounts for each of the different types of ran-in-error problems. Pie charts, although possible to develop individual side-by-side for each category, the perception of interrelationships would not be as noticeable as with the side-by-side bar chart.
c) We did not select a Pareto chart for this exercise because although Pareto charts are good for analyzing single category distributions, they are not so good for depicting relationships among multiple category distributions.
d) The following is a report sent to management by the Technology Group
To Springfield Herald Management
Re Cost of Ran-in-Error Problems
After careful analysis of the cost of advertising errors for the past calendar year, it is obvious from the attached data that the area that needs the most attention is in the policy area. Of the three different types of ran-in-error problems, sales and the composing room together accounted for only 10% of the problems, while policy accounted for the remaining 0%. Therefore, our recommendation is to focus on the policy area for corrective action.
e) Our recommended course of action would be to look for conflicting policies and/or vague policies that are open to a wide range of interpretation by individual users. Perhaps a survey could be conducted among the users, which could then be analyzed statistically.
Springville Herald Case Study (Phase 4)
. a) Stem & Leaf Plot attached
b) This phase of the exercise asked us to review the amount of different data cartridges used on a daily basis within the company. After reviewing the raw data, we produced a Stem & Leaf Plot to determine where the distribution of the data fell. From this plot, we concluded that most of the time the production area used between 1 and 0 different data cartridges daily. This represented 6 of the 111 different data points collected. Roughly 6% of the time, the area can expect to have between 1 and 0 different cartridge changes daily. This case also follows the widely held theorem concerning the 80-0 rule. In this case, 80% of the data cartridge changes occur between 1 and 60 times daily. For staffing purposes, the area should staff for this rate of occurrence. We reviewed other types of charts with this data but find that they did not provide the information necessary to make educated conclusions about the operation.
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