HR Technology, Systems & Digital Transformation

HR Technology, Systems & Digital Transformation

HR Technology, Systems & Digital Transformation is a structured track of 14 lessons that build a complete, interview-ready understanding of the topic. Work through them in order, then use the quiz and flashcards in each lesson to revise.

What this course covers

  • The HR Technology Stack and How the Pieces Connect - Core systems, talent modules, payroll and engagement tools, and the integrations.
  • Core HR Systems versus Talent Suites versus Best-of-Breed - The architecture choice, and the maintenance cost each option creates.
  • Applicant Tracking Systems and Recruitment Technology - What a tracking system should do, and how recruiters end up working around it.
  • Payroll & Time Systems and Their Integration Points - Where payroll connects to attendance, leave and finance, and where it breaks.
  • Learning Platforms & Learning Experience Systems - Management versus experience platforms, and what each is genuinely for.
  • Employee Service Platforms & HR Case Management - Service desks, knowledge bases and measuring HR service delivery.
  • Selecting an HR System: Requirements & Vendor Evaluation - Writing requirements, scoring vendors and avoiding a demo-driven decision.
  • Implementation: Data Migration, Testing & Go-Live - The sequence that works, and the data problems that surface during migration.
  • Driving Adoption After Go-Live - Why implementations technically succeed and practically fail, and how to prevent it.
  • HR Data Architecture, Definitions & Access Governance - Systems of record, agreed definitions and who may see which people data.
  • Process Automation in HR Operations - Which HR processes are worth automating, and which become fragile when automated.
  • AI Features in HR Systems: Evaluating Vendor Claims - Cutting through vendor AI claims to what the product actually does and evidences.
  • AI Assistants in HR Service Delivery - Automating employee queries, and deciding what must always reach a person.
  • Case Study: Reading Whether an Implementation Actually Worked - Adoption, data quality and cycle-time measures used to judge a real rollout.