# HR Master Data: Data quality, data model, a leading system > The same person in five systems with five truths: How an HR data model is created, which system is leading, how clean-up and interfaces function, and how quality is maintained long-term. URL: https://techport.ai/en/hr-beratung/hr-daten-und-systeme/stammdaten --- 1. [HR Consulting](/en/hr-beratung)/ 2. [HR Data and Systems](/en/hr-beratung/hr-daten-und-systeme)/ 3. Master Data Quality and Single Source of Truth [HR Data and Systems](/en/hr-beratung/hr-daten-und-systeme) # Master Data Quality and Single Source of Truth By Redaktion techport.ai, HR-Beratung · Last updated on 21 August 2026 The HR department reports 412 employees, payroll 418, controlling 405, and Active Directory 460 active accounts. Everyone is right, according to their own definition. Nobody can say how many people work for the company today. Every report begins with a discussion about the numbers instead of their meaning. Master data forms the basis of every analysis, every interface, and every automation. If it is maintained independently in multiple systems, it drifts apart. The solution is not more diligence, but a leading system, a data model, and interfaces that supply the rest. ## How you will notice it * Organisational units are named differently in each system, and the assignment of individuals is never quite accurate anywhere. * Changes are recorded multiple times: in the HR system, in payroll, in IT. * Analyses begin with clean-up. The report takes days; the question should have taken minutes. * During the last system migration, data was transferred as it was, including 'dead wood'. ## Why this happens Systems were introduced at different times for different purposes. Each has its own fields, its own mandatory entries, its own understanding of organisation. Interfaces are missing or only transfer parts. And no one is responsible for the data as a whole, only for their own system. ## This is how we proceed 1. **Inventory.** We record which systems manage personal data, which fields, which source, which responsibility. This creates a map of data flows with all duplicate entries. 2. **Define Data Model and Leadership.** For each data field, it is determined which system is leading and who maintains it. The HR system leads on person and organisation, time management on timesheets, and payroll on remuneration. Everything else is copies, provided via interface. 3. **Clean-up.** Duplicates, 'dead wood', contradictory assignments, and empty mandatory fields are systematically processed, with rules and assigned responsibilities, not in a night shift. 4. **Set up Interfaces and Checks.** The leading system automatically supplies the others. Quality rules continuously check for discrepancies, and a brief monthly report shows where data diverges. ## What you gain from it * One figure for the workforce, and every report starts with the content. * Changes are recorded once and are correct everywhere. * System migrations, reporting, and automation become possible because the foundation is sound. ## From our projects When we inquire about employee numbers from all systems in projects, we regularly receive four or five different values. The clean-up itself is less work than expected; defining the leading system for each data field is more so, as it alters responsibilities. Quality rules, which run automatically monthly and report discrepancies to those responsible, keep the data consistently clean in our experience. One-off clean-ups without rules deteriorate within a year. ## Good to know Article 5 of the General Data Protection Regulation requires accurate and up-to-date data and its deletion as soon as the purpose ceases. Scattered copies in multiple systems complicate both of these requirements and turn requests for information into a search. A data model with clear governance is therefore also a data protection measure. For retention periods: payroll documents six to ten years according to commercial and tax law, personnel files generally three years after an employee leaves, applicant data six months after rejection. ## Frequently asked questions Do we need our own master data management system? Not for HR. The HR system is the master data system for individuals and organisations. What is usually missing are the rules and interfaces, not another system. How do we prevent data from deteriorating again? Through responsibility and use. Every field has an owner, quality rules run automatically, and the data is needed in processes where errors are immediately noticeable. Data on which payroll is based remains clean. ## Let's talk about Master Data Quality and Single Source of Truth In a thirty-minute first call we clarify where your biggest lever is and whether we are the right partner for it. [Book a first call](/en/kontakt)[Our software](/en/loesungen) ## Further reading [HR Data and SystemsSelecting and implementing HR softwareHow to successfully select an HR system: derive requirements from processes, make vendors comparable, involve the works council and data protection, plan migration, and secure usage.](/en/hr-beratung/hr-daten-und-systeme/hris-auswahl)[HR Data and SystemsImplementing People Analytics correctlyWhy dashboards remain unused and how People Analytics works: Management questions, methodology, data sources, evaluation, communication. With data protection and co-determination.](/en/hr-beratung/hr-daten-und-systeme/people-analytics)[Remuneration and RetentionError-free payrollErrors in payroll cost trust and money. How a payroll audit identifies causes, when a system change is due, what to consider with outsourcing, and how interfaces eliminate duplicate data entry.](/en/hr-beratung/verguetung-und-bindung/payroll)[KnowledgeHR MetricsDefinitions and formulas that read the same across the company.](/en/hr-beratung/kennzahlen)[KnowledgeHR GlossaryKey HR terms, briefly explained.](/en/hr-beratung/glossar) Back to the field [HR Data and Systems](/en/hr-beratung/hr-daten-und-systeme) ## Sources * [Regulation (EU) 2016/679 (GDPR), EUR-Lex](https://eur-lex.europa.eu/eli/reg/2016/679/oj) Rt Written by [Redaktion techport.ai](/ueber-uns), HR-Beratung Mehr als 15 Jahre Erfahrung in HR-Prozessen und HR-Systemen, Einführung von HR-Software in mittelständischen Unternehmen, Verhandlung von Betriebsvereinbarungen zu IT-Systemen. This page reflects the position as at the date shown and does not constitute legal advice. For specific questions we work together with your legal advisers. 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