Data Integrity Challenges (and how to overcome them)
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This document discusses data integrity challenges in human resources (HR) data and how to overcome them. It defines data integrity as rules that govern database referential integrity, security, and data input/output processes. Critical HR data elements are identified such as employee name, salary, and job information. Impacts of poor data integrity discussed are issues with HR reporting, compliance auditing, and financial reporting. The document provides recommendations for getting data integrity right such as establishing business rules, regular training, and making audits a monthly process. It emphasizes automating data quality checks and scorecards to continuously monitor integrity.
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Riordan Manufacturing HRIS framework was secured in 1992. Their HR framework was intended to track workers' data. For example, their individual data, pay rate, individual absolution for tax purposes, contract date and vacation hours and so forth. While then again Riordan lawful framework and activities are taken care of by Litteral & Finkel. Litteral & Finkel gives lawful administrations like tax law, land transactions, employee law, migration matters, and work law and custom regulations. In this paper we will examine the HR framework reconciliation with tools to make a single coordinated application. The organization ought to have more particular data systems technology (Thite.et.al, 2008). This paper will recognize and portray existing and required business frameworks and subsystems. Comment by Owner: Great! Comment by Owner: It is unclear what “to have more particular data systems technology” means.
Riordan Manufacturing is a worldwide plastic producer utilizing 550 individuals with the yearly profit of $46 million. The organization is completely claimed by Riordan Industries, a Fortune 500 organizations. The major stakeholders in the company include; the company president and its CEO the chief operating officer, the vice president of research and development, the sales and marketing vice president, the human resources director, the chief financial officer, the company employees, customers and managers will enable provide information for the HR information systems. Comment by Owner: Good on the stakeholders.
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Data Integrity Challenges (and how to overcome them)
- 1. Data Integrity Challenges (and how to overcome them) December 16, 2009
- 2. Agenda Data Integrity Defined Critical HR Data Elements Business Impacts Getting it Right WhatchaLookin’ For? Overcoming Data Integrity Issues Q&A
- 3. Data Integrity Defined System/Database: Rules that govern the referential integrity of the database application as well as the infrastructure on which it resides. Security: information can only be accessed or modified by those authorized to do so. Process: The creation and adherence of rules that govern the inputs/outputs of HR data to ensure minimal error. Field: Measure of quality, accuracy, reliability and completeness of HR data based on error detection.
- 4. Critical HR Data Elements Reporting Relationships/Hierarchy Name and SSN Date Fields: Hire/Rehire/Acquisition/TOAD/Service Salary, Shift Differential, Comp Plan, PTO Plan Work Location/EEO Location Compensation Structure Contact Information Job Codes/Families/Titles Company Business Unit Manager Division Employee Name SSN CC/Department EEO Location EEID Work Location
- 5. Impacts HR Reporting Recruiting, Hiring, and Onboarding Budgeting & Financial Reporting (SEC reporting, etc.) Compliance Auditing (SOX, RHESPA, Safe Harbor) The Bottom Line (i.e., higher costs paid for incorrect salary) “Many HR departments haven’t realized that they have the same responsibility for maintaining the safekeeping of their digital information as they have for their paper records,” - Arlie C. Skory, SPHR, Principal at Skory & Associates
- 6. Getting it Right! Networking: Increase your knowledge of data quality Initiate discussions related to implementing a data quality strategy and business rules Conduct environmental scanswww.ihrim.orgwww.shrm.orghttp://network.hrmtoday.com/http://blog.aquire.com/ Begin the process of applying data quality business rules, progressing through the following areas: Analysis Cleansing and Standardization Grouping and Matching
- 7. So…WhatchaLookin For? Develop a baseline Start with the basics: Orphans (orgs/EE's with broken report-to) Blanks (job title, code, cost center, job grade) Recycled/Duplicate Email Addresses Rehires w/o old Employee Number (IF-THEN statements for validation) Location Audit Listen to your employees – they know things! Remember: Not all processes will fit your situation
- 8. Overcoming Integrity Issues Establish and enforce business validation rules and processing standards. Regular system and process training. Always inquire about the source of your data. Make it Collaborative (multiple admins/analysts viewing and updating in real-time). Make your updates in mass and enable workflows. Keep it clean - Make audits a monthly process.
- 9. Overcoming Integrity Issues (cont.) Reduce the number of off-cycle payments and reversals Build data quality scorecards AUTOMATE: Visualization tools.
- 10. Thank You! Aquire5215 N. O’Connor Suite 300Irving, Texas USA 75039 Damon LovettDirector, Professional Servicesdamonlovett@aquire.com+ 1 214.278.5135 http://twitter.com/damonlovett Aquire.blog.com Helping over 2,700 companies manage 10,000,000+ employees across the globe.