Service Learning: A Strategic Collaboration for Engineering Quality Concepts in Service Management Author: Richard Greenwood Department of Technology Management,

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Service Learning: A Strategic Collaboration for Engineering Quality Concepts in Service Management Author: Richard Greenwood Department of Technology Management, School of Engineering, University of Bridgeport, CT General Acknowledgement Sincere appreciation to my advisor, Dr. Elif Kongar and the managing members of Helthkare Products, LLC. Abstract This study focuses on the application of some of the basic tools of quality in the realm of a service business. A quality problem for small service businesses is debt collection from delinquent customer accounts. Quality control methods can be applied to analyzing the occurrence of customer payment trends and establish measures to control the frequency of this issue. Small businesses like Helthkare Products, LLC are particularly vulnerable to the risk of lower finances because of a limited source of revenue. With smaller customer bases they cannot afford to have excess outstanding debt from its customers because it puts them in a position of having a reduced working capital and cash flow. The use of quality control can help small businesses understand their customers as well as their own internal business processes so as to increase efficiency and improve customer relationship management. Results and Conclusions Use of the chosen quality models was helpful in identifying reasonable measures to address the issue of collecting bad debts. Data collection and quality analysis supported by engineering disciplines helped a service business to identify controllable periods in terms of months in the year and specific customers that could be targeted immediately to begin implementing tailored procedures to efficiently and effectively monitor and control customers purchasing and payment behavior. Managing the service will in essence create an environment to collect payments within an agreed time. This service business was able to validate a direct relationship between delinquent customers and months within the year where supply had improved to meet an increase in customer demand. These customers had the longest days before payment was received and also followed a monthly trend in their purchases. A customer analysis and a monthly analysis was done using the 3 quality control methods which are fixed graphical techniques seen above; a run chart, a Pareto chart, and a X-bar control chart. From the analysis we are able to see that some customer averages were as much as 28% higher than that of the customer with the lowest average. September experienced significantly higher delinquencies in payments and was 30.5% higher than June which had the lowest. Payment Penalty Training Unable to Collect Payment from Customers PoliciesProcedures PeopleTechnology Net 30 Payment terms to short Driver forget to pick up check payment Incorrect order processed Staff Accounting System Payment Processor Collection calls are made after payment due date No penalties for late payment Customer received wrong or defective order COD not received Payment Terms Collections Collections Department Customers not made aware of past due balance No or insufficent staff dedicated to Collections Role Inadequate training on collecting payments System does not send payment reminders Payment terminal does not accept all types of payment A process analysis engineering methodology known as service blueprinting was constructed in order to provide a qualitative description of the key elements related to the service. From this an Ishikawa diagram was developed to gain further analysis into the cause and effect relationship of variable factors causing the overall effect.