Internal Medicine Faculty Affairs Staffing Analysis Program & Operations Analysis University of Michigan Health System

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1 Internal Medicine Faculty Affairs Staffing Analysis Program & Operations Analysis University of Michigan Health System Final Report Delivered to: Cheryl Sweetland Manager, Faculty Affairs Internal Medicine University of Michigan Health System Tammy Ellies Project Manager Internal Medicine University of Michigan Health System Submitted by: Yinghao Ni, Senior, IOE, University of Michigan Jung Gyun Yoo, Senior, IOE, University of Michigan Muxun Zhang, Senior, IOE, University of Michigan Group 14 Date Submitted: December 10, 2007

2 Table of Contents Executive Summary... 3 Background... 3 Methodology... 3 Findings & Conclusions... 4 Recommendation... 4 Introduction...5 Background...5 Goals and Objectives... 6 Methodology... 6 Perform Literature Search... 6 Review existing data and flowchart... 7 Build a computer model... 7 Validate exiting data and collect needed data... 7 Analyze model... 7 Formulate recommendation... 7 Findings... 8 Staffing model... 8 Time estimates... 9 Work volume... 9 Workload condition... 9 Conclusion Recommendations Appendices Appendix A Portion of Existing Data of Work Volume by Activity & Month Appendix B Existing Data of Work Time Appendix C Activities in FA Appendix D Current procedure for Advertising Appendix E Activity Description for VA Credentialing Appendix F Work load condition of staff in FA area Appendix G Work load condition of HR Generalists (recommended) Appendix H Recommended Staffing Plan for HR Generalists

3 Executive Summary This report is a detailed account of our analysis of the current workload distribution used in the University of Michigan Health System, Internal Medicine Department, Faculty Affairs Area. Staff members in the Internal Medicine, four HR Generalists, one HR Associate, and one FA Administrator, handle numerous tasks from 12 divisions of the University Health System and some outside clients. And staff members experienced highly unbalanced work distribution over the years; for example, staff members are heavily overloaded in July and have idle time in September. The Manager and Project Manager of the Faculty Affairs Area, asked us to evaluate the current workload distribution process and improve the process by building a computer based model to eliminate unnecessary overtime and idle time for the staff members in the Area. After examining the current situation, our team developed a model for balancing workload distribution for staff members and, in turn, reducing the incidental overtime and idle time. Background Approximately 500 faculty members are in 12 divisions in the University Health System that work in the Department of Internal Medicine. The Faculty Affairs Area coordinates all the faculty human resources activities including four main aspects: recruitment, employment, maintenance and termination. Four HR Generalists, one HR Associate, one FA Administrative Assistant and one FA manager are responsible for the human resources activities for 12 divisions in University Health System with different process time for each task and varying volume of work month to month every year. Due to fluctuating volume over time, staff members are vulnerable to overwhelming workload during certain period of the year and significant idle time for the rest of the year. Methodology Our team conducted the following methodology in chronological order to engage into the addressed workload distribution problem. Perform Literature Search Our team performed literature searches of existing staffing models. The literature research included: Human Resource Staffing Model Report for the Massachusetts Court System Staffing Models & Staffing Plans approach for Orient Point Consulting LLC Review existing data and flowchart The team reviewed existing data and flowcharts of the current job process. This information gave the team a full understanding of the current staffing model. 3

4 Build a computer model Our team developed a model to estimate staffing requirements by month, division, activity, and staff member. The model has been developed in Excel and is flexible for the manager to update and change data as needed. Validate existing data and collect needed data The time data, time to complete each task, and the volume data, monthly quantity of tasks given to the department, were provided to the team from the beginning. Thus the team validated the existing data first, and then collected new data that were not given. Both data validation and collection procedures were performed through interviewing all the staff members in Faculty Affair Area. Our team obtained expert estimates for the existing and missing data to further improve the model. Analyze Model Our team met weekly with the Clients to analyze and gain feedback on the model. The model was adjusted accordingly. The main focus of the analysis was flexibility of data inputs and reliability of model outputs. Formulate Recommendation Our team used the most updated data to develop a recommended staffing plan for year Findings & Conclusions Based on the estimates of task duration and work volume, our team used the staffing model to estimate the workload condition of the staff in FA area. The staffing model showed the expected workload for four FA Generalists, one FA Associate and one FA Administrator for each month by using the data from year The results showed that almost every HR generalists are overloaded in May, July and October while they have more idle time in the rest of the year. Recommendation The team recommends that the current staffing plan for HR generalists should be slightly changed for year Since General Medicine division requires the most time to complete all the tasks, one HR generalist should be designated only for the General Medicine division. The team also encourages the staff to share the work load during the peak period. It is also important to improve the work condition by training program or hiring part-time students. 4

5 Introduction The Faculty Affairs (FA) area within the Department of Internal Medicine of the University of Michigan Health System (UMHS) coordinates faculty human resource activities for its 12 divisions. For the staff of the FA area, it is unclear if the current work distribution is appropriate. They potentially have an overwhelming workload during certain periods of time and have some idle time for the rest of the year. FA would like to improve the current staffing plan in order to get evenly distributed workload while still providing a high level of service. In response, the team collected and validated the working volume and time estimates (Appendix A & B) for respective activities. Based on the validated data, the team also developed a dynamic staffing model to reflect the current workload conditions for the personnel in FA and to improve the staffing plan of the department. The main objective of the report is to develop a model to eliminate unnecessary work overload and idle time and to recommend a methodology to achieve balanced staffing levels for the future. Background Approximately 500 faculty in 12 divisions, including Division of Allergy, Division of Infectious Disease and etc., work in the Department of Internal Medicine. The Faculty Affairs area coordinates all faculty human resources activities including four main aspects: recruitment, employment, maintenance and termination. Four HR Generalists, one HR Associate, one FA Administrative Assistant, and one FA manager are responsible for the human resources activities such as posting or advertising in recruiting aspect and re-credentialing or license renewals in maintaining and etc. Each activity requires different working time for the staff and the volume of a certain activity varies from month to month every year. Since FA could not hire and dismiss staff frequently according to the work load, this causes the issue that the staff might have overwhelming workload during certain period of time and has some idle time for the rest of the year. For example, because most of the faculty will start working in the hospital after summer, an HR generalist would be extremely busy in June and July due to the high volumes of work. To evenly distribute workload while still providing a high level of service, appropriate volume & time data of peak & non-peak periods should be obtained and a flexible model that can predict the future staffing plan was needed. 5

6 To fulfill the project, the following key issues were driving the need for this project: A staffing analysis was needed to know the best way to allocate the central staff to the divisions to evenly distribute the work load while providing a high level of service. Because of fluctuation of data year to year and division by division, the department needed a dynamic staffing model that can predict staffing needs prospectively based on expected volumes for the current year. Goals and Objectives The main objectives of the project for the team were the following: Develop a computer based dynamic Model in Microsoft Excel Validate existing Tim/Volume data and Collect additional data if needed Recommend a staffing plan for Fiscal Year 2008 The team developed a staffing model to be used by the Manager of the FA area on an ongoing basis. We also collected and validated data including volumes in different periods and time for all FA activities through interviewing the staff members. One of the primary goals of the project was to recommend a staffing plan for Fiscal Year However, due to insufficient amount of data and time to validate the existing data, the team was only able to recommend a staffing plan for four HR Generalists. Methodology Our team followed the methodology below to approach this project. Our team first performed a literature search to achieve understanding of Staffing Model. Then we reviewed existing Time and Volume data of Faculty Affairs provided by Project Manager. After the review, the team developed fully functioned computer-based model and delivered it to the Project Manager. Then the team interviewed the staff members to validate the existing data and collect missing data through interview process. Finally, the team analyzed the model with the project manager and formulated a recommended staffing plan for HR Generalists for Fiscal Year 08. Perform Literature Search Our team performed a literature search of past developed staffing model. Human Resource Staffing Model Report for the Massachusetts Court System and Staffing Models & Staffing Plans approach for Orient Point Consulting LLC were studied. 6

7 Review existing data and flowchart The team reviewed existing data and flowchart of current job process. It allowed our team to have a full understanding of current process and build on to the current process to improve it. Build a computer model Our team developed a model to estimate staffing requirements by month, division, activity, and staff member. The model is developed in Excel and is flexible for the manager to update and change data as needed. The model also allows Volume and Time estimates to be updated with new forecasts to see the impact to staffing needs. It also allows new activities to be added for future improvement. Validate existing data and collect needed data The time data, time to complete each task, and the volume data, monthly quantity of tasks given to the department, were provided to the team from the beginning of the project. Thus, we validated the existing data first, and then collected new data that were not given. Data validation and collection were performed through interviewing all the staff members in Faculty Affair Area; each team members met with staff members individually, and asked the duration and monthly quantity of the task. Since the primary objective of the project was developing a model, our team had limited time available for data validation and collection process. Analyze Model The team met weekly with the Clients to analyze and gain feedback of the model. The model was adjusted accordingly. The main focus of the analysis was flexibility of data inputs and reliability of model outputs. At this phase, we determined whether further data collection and analysis were necessary. If needed, our team moved back to data validation and collection phase and repeated the validation and collection procedure to improve the model. Formulate Recommendation Our team formulated a recommendation to improve Faculty Affairs workload distribution. Our team used the most current data to develop a recommended staffing plan for year However, due to insufficient amount of data and time to validate the existing data, the team was only able to recommend a staffing plan for four HR Generalists. The recommendation includes new division assignment, workload share plan among the staff members, and staff training program to improve the work procedure. 7

8 Findings Because the staffing model requested by the client had the first priority, the team developed the staffing model based on the initial non-validated data provided by project coordinator immediately after literature search. Then, the team interviewed with the FA staff, and obtained estimates of task duration and work volume for most of the FA activities. Finally, the staff model provided conclusions of the current workload situation based on the existing data and data estimates. However, because the data included only the majority of the activities taking place in the FA instead of all of them, the workload generated by the staffing model based on the data would be underestimated compared to the actual workload. Staffing Model After working with the project s client and the coordinator, the team developed the fully functioned model. The inputs of the model are the work volume by department by month, and the task duration to perform each HR activity collected or verified by the team. The output of the model is the workload condition of the staff in FA area; the model outputs staff members with work overload and ones with idle time by month. It allows volume and duration estimates to be updated with new forecasts to see the impact to staffing needs. It also allows new activities to be added or removed for future improvement. By inputting the estimates of work volumes and task durations to the model, it displays the expected workload for the three types of staff, including HR Generalists, FA Associate, and HR Administrator. For example, based on the existing data, as shown in Appendix F, some HR generalists are overloaded from May to September according to the result computed by the model. As shown in Table 1, (152) under the month of July means HR generalist 1 is expected to work 152 hours more than the monthly available work time in July. On the other hand, HR Generalist 2 is expected to work 22 hours less than expected in July. Table 1: Workload Condition from Appendix G Position May Jun Jul Aug Sep HR Generalist 1 (139) (161) (152) HR Generalist (40) HR Generalist 3 (12) (88) (90) (49) (55) HR Generalist 4 46 (38) (50) (40) (38) 8

9 Time estimates By asking the staff about the procedure and estimated duration for each activity during interview, the team collected the first-hand data for the activity duration estimates. Then, the team verified the estimates by discussing them with the client and coordinator. The verified work duration estimates are shown in Appendix B. The data are arranged by different activity for various staff position. The cells left blank represents the tasks that are not responsible for the corresponding staff position. Work volume The team also collected and verified the existing data for the work volume of each activity by department by month. Part of the work volume data for Allergy and Cardiovascular (Card) department are shown in Appendix A. The blank cells indicate that the team was not able to verify the work volume for those activities. Workload Condition After inputting the validated task duration and work volume data, the staffing model generated the workload condition of FA from January 2006 to December Table 2 below shows the number of staff needed in each month and the average value in 2006 for four HR Generalists, one HR Associate and one HR Administrator. The results show that FA needed more than 4 HR Generalists from May to Sep, especially in Jun and July. Because not all the activities that happened in FA were included in the model, the team couldn t conclude the workload for HR Associate and FA Administrator. Table 2 Workload Condition in FA based on existing data HR Generalists HR Associate FA Administrator Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Average

10 Conclusion According to the activity data input into the staffing model, the team concluded that the current workload distribution caused overtime work in some months but more idle time in the rest of the year. The uneven work load distribution along the year is especially obvious for HR generalists. Currently, certain numbers of tasks of divisions are assigned to each HR generalist. However, the time required to complete each tasks differs significantly and the volume of tasks for each month fluctuates unpredictably, which causes the non-uniform workload distribution among the staff members. The current situation of the staff workload is shown in the model. As shown in Appendix F, for the current situation, HR generalist 1, 3 and 4 are overloaded in April, May, June, July and September. Meanwhile, the work time of HR generalist 2 is not utilized ideally, since he/she still has extra work time during the busy months. In July, if HR generalist 2 does not share the work load, HR generalist 1, 3 and 4 would have to work 160, 90 and 50 hours more respectively. This is certainly an unbalanced condition. Using the Staffing model, it is possible to achieve better staffing plan to avoid unnecessary overtime and idle time. The Manager will be able to have a good overview of assigning tasks to the most suitable staff member to not result in any unnecessary time conflict. The model will provide flexibility of assigning tasks to the staff members and will result in fair distribution of tasks among the staffs. Also Manager will be able to keep the constant number of staff members, thus reducing management cost. Recommendations The team developed recommendations for the current problems presented in the conclusion. The objective is to assign right amount of work to the staff to achieve a better workload distribution. Since the workload of HR generalists is not balanced over the year, the team recommends the following improvements, including part of the staffing plan for HR generalists. The team used the work volume and time estimate data from 2006 as a reference in recommending the staff plan for New division assignment Currently, certain tasks of division are assigned to certain staff member. Instead of using the current task assignment, the team recommends implementing new task assignment. General Medicine division requires the most amount of time to complete all tasks; thus, the staff who is assigned to General Medicine division experience work overload. The team recommends dedicating General Medicine division tasks to one HR Generalist. The new assignment of the divisions to the HR generalists is shown in Appendix G. As shown in Appendix G, the work load condition is better than the current situation for HR generalists in Appendix F. 10

11 Sharing workload among the staff Even using the new staff plan for HR Generalists cannot eliminate all the uneven distribution of the workload. The team recommends that during the peak period, certain HR generalists share the work load for anyone who is extremely overloaded. According to Appendix G, in April, HR generalist 2, 3 and 4 could share the workload of HR generalist. In August and September, HR generalist 1 could help the rest of the staff. It is also reasonable to hire some part-time during peak period if necessary. Training and improvement As interviewing the staff, the team found out there could be much improvement in the current procedure of the activities. The FA area can launch training program to help share the experience of the staff and improve the current procedure by decrease the total time needed for the activities. 11

12 Appendix A: Portion of Existing Data of Work Volume by Activity & Month 12

13 Appendix B: Existing Data of Work Time 13

14 Appendix C: Activities in FA 14

15 Appendix D: Current procedure for Advertising 15

16 Appendix E: Activity Description for VA Credentialing 16

17 Appendix F: Work load condition of staff in FA area Workload Condition (Available working time per month - Personnel working time per month) (Value in "()" shows overloading) Hour per Month Position Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec HR Generalist (111) (145) (161) (160) 39 (15) HR Generalist HR Generalist (12) (88) (90) (49) (55) HR Generalist (38) (50) (40) (38) HR Associate (44) FA Admin

18 Appendix G: Work load condition of HR Generalists (recommended) Workload Condition (Available working time per month - Personnel working time per month) (Value in "()" shows overloading) Hour per Month Position Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec HR Generalist (111) (139) (161) (152) HR Generalist (2) 7 (11) (8) (57) HR Generalist (64) (58) (31) (39) HR Generalist (38) (50) (40) (38)

19 Appendix H: Recommended Staffing Plan for HR Generalists Task Assigned to HR Generalist Department Allergy 0 yes 0 0 Card yes Gen Med yes Geriatrics/IOG 0 yes 0 0 GI 0 yes 0 0 Hem/Onc 0 0 yes 0 ID yes IntMedDept 0 yes 0 0 MEND 0 0 yes 0 MMG yes Neph 0 yes 0 0 Pulm 0 yes 0 0 Rheum yes 19

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