Assignment Wk 5: Data Management and Ethics
In order to create metrics, you need to have a credible, relevant, and complete data set to work with because unreliable data can affect your results. Raw data that is incomplete, irrelevant, or duplicated can limit the insights that come with HR analysis. Company time and money can be wasted by looking at a good research area, having good formulas but using the wrong information. As an HR professional it is important to ensure your data is complete and accurate to ensure you are making sound strategic decisions.
In this Assignment, you will analyze a business case and employ best practices of data collection and data management to address a hospitals financial and HR concerns related to employee layoffs.
To complete this Assignment, review Exercise 25: Employee Layoffs at St. Marys Hospital on pages 8385 of Nkomo, Fottler & McAfee (2011), Exhibit 2.1 Excel document and Exhibit 2.2 Excel document. Then, using the Excel documents, the Learning Resources for this week and other resources you have found in the Walden Library or online, respond to the following bullets points in a 4- to 6-page paper:
Identify the major problem or problems at St. Marys Hospital and the causes.
What are some alternatives for dealing with these problems?
How many months would it take to realize the savings if St. Marys relied on attrition (turnover) only?
What other cost savings ideas might be implemented to realize the target savings?
Develop a downsizing plan for implementing that will generate $7 million in annual savings. Give specific details concerning departments affected, the number of employees affected in each department as well as the savings by department. Also, discuss the use of seniority versus merit, the amount of notice, and out-placement activities. Provide a rationale for each recommendation, together with reasons why other alternatives were not chosen
What might be the effects of a downsizing plan on survivors in terms of morale, job security, quality, turnover, and productivity? How could you avoid or minimize any potential problems in these areas? (For this question cite at least one resource found in the course readings or in the Walden Library.)
Identify two possible long-term solutions for St. Marys Hospital once it gets its cash flow problems under control and eliminates its deficit, consider trends in the medical field to support your recommended solutions.
What limitations exist in using performance data as a criterion for downsizing? How can such limitations be overcome? (For this question cite at least one resource found in th
Please save your Assignment using the naming convention WK5Assgn+last name+first initial. (extension) as the name.
Click the Week 5 Assignment Rubric to review the Grading Criteria for the Assignment.
Click the Week 5 Assignment link. You will also be able to View Rubric for grading criteria from this area.
Next, from the Attach File area, click on the Browse My Computer button. Find the document you saved as WK5Assgn+last name+first initial. (extension) and click Open.
Note: It is highly recommended that you review the resources in the following order.
Pease, G., Byerly, B. & Fitz-enz, J. (2012). Human capital analytics: How to handle the potential of your organizations greatest asset. Hoboken, NJ: John Wiley & Sons.
Chapter 4, Its All About the Data (pp. 7999)
Appendix B: Getting Your Feet Wet in Data: Preparing and Cleaning the Data Set (181192)
Nkomo, S. M., Fottler, M. D., & McAfee, R. B. (2011). Human resource management applications: Cases, exercises, incidents, and skill builders (7th ed.). Mason, OH: Cengage Learning.
Exercise 25: Employee Layoffs at St. Marys Hospital (pp. 8385)
Credit Line: Human Resource Management Applications: Cases, Exercises, Incidents, and Skillbuilders, 7th Edition by Nkomo, S.M., Fottler, M.D., & McAfee, R.B. Copyright 2011 by Cengage Learning. Reprinted by permission of Cengage Learning via the Copyright Clearance Center.
Bersin, J. (2017, April 17). Viewpoint: Data Friend or enemy? Retrieved from https://www.shrm.org/resourcesandtools/hr-topics/technology/pages/data-friend-or-enemy.aspx
HR Technologist. (2018). People analytics: Building a data-driven HR function. Retrieved from https://www.hrtechnologist.com/articles/hr-analytics/people-analytics-building-a-datadriven-hr-function/
Bassi, L. (2011). Raging debates in HR analytics. People & Strategy, 34(2), 1418.
Schmidt, L., & Green, D. (2019, May 31). This is why data is now more essential than ever in HR. Fast Company. Retrieved from https://www.fastcompany.com/90357244/this-is-why-data-is-now-more-essential-than-ever-in-hr
Leong, K. (2017). Is your company using employee data ethically?
Moore, S. (2019, August 6). Dos and donts of using employee data. Retrieved from https://www.gartner.com/smarterwithgartner/dos-and-donts-of-using-employee-data/
Feinzig, S., Green, D., & Guenole, N. (2018). The grey area: Ethical dilemmas in HR analytics perspectives from the global workforce. Retrieved from https://www.ibm.com/watson/talent/talent-management-institute/ethical-dilemmas-hr-analytics/hr-ethical-dilemmas.pdf