Data Integrity Challenges (and how to overcome them)
Download as PPTX, PDF1 like2,904 views
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.
Data Integrity Challenges (and how to overcome them)
- 1. Data Integrity Challenges (and how to overcome them)December 16, 2009
- 2. AgendaData Integrity DefinedCritical HR Data ElementsBusiness ImpactsGetting it RightWhatchaLookin’ For?Overcoming Data Integrity IssuesQ&A
- 3. Data Integrity DefinedSystem/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 ElementsReporting Relationships/HierarchyName and SSNDate Fields: Hire/Rehire/Acquisition/TOAD/ServiceSalary, Shift Differential, Comp Plan, PTO PlanWork Location/EEO LocationCompensation StructureContact InformationJob Codes/Families/TitlesCompanyBusiness UnitManagerDivisionEmployee NameSSNCC/DepartmentEEO LocationEEIDWork Location
- 5. ImpactsHR ReportingRecruiting, Hiring, and OnboardingBudgeting & 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 qualityInitiate discussions related to implementing a data quality strategy and business rulesConduct 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:AnalysisCleansing and StandardizationGrouping 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 AddressesRehires w/o old Employee Number (IF-THEN statements for validation)Location AuditListen to your employees – they know things!Remember: Not all processes will fit your situation
- 8. Overcoming Integrity IssuesEstablish 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 reversalsBuild data quality scorecardsAUTOMATE: Visualization tools.
- 10. Thank You!Aquire5215 N. O’Connor Suite 300Irving, Texas USA 75039Damon LovettDirector, Professional Servicesdamonlovett@aquire.com+ 1 214.278.5135http://twitter.com/damonlovettAquire.blog.comHelping over 2,700 companies manage 10,000,000+ employees across the globe.