Insights
What we know, written down.
The knowledge base behind Empley. Guides, analyses, comparisons, checklists and definitions for leading AI transformation from people, HR and finance. Every entry starts with the answer and shows where the evidence comes from.
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What we write about
The pillars are written as questions a buyer actually asks, not as our product catalogue.
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Everything here should be usable right away: a checklist to run through, a calculation to fill in, a comparison that makes the choice easier. We do not write anything we would not use ourselves in an engagement.
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28 entries, filterable
Filter by type, topic, decision stage, role and maturity. Everything is searchable without a reload.
28 poster
What an HR data foundation actually is
The structural layer that must be true before any HR model or agent can be trusted.
GuideHR data quality5 minData contracts between HRIS and analytics
A practical way to stop HRIS changes from silently breaking analytics and models downstream.
AnalysisHR data quality5 minWorker identity across systems, not just one
Why a stable worker identifier matters more than any single system's own employee ID.
ChecklistHR data quality5 minReadiness checklist before your first HR model
Nine checks to run before commissioning any predictive or generative HR model.
The metric layer the people function runs on
A metric layer is the shared set of calculations, sitting between raw HR data and every dashboard or report, that defines exactly how each number is produced. It stops finance, HR and managers from each computing attrition or headcount a different way. Every people analytics capability, from dashboards to predictive models, depends on this layer being correct and stable.
Defining attrition so two teams agree
A concrete rule set for calculating attrition so HR and finance never present conflicting numbers again.
AnalysisPeople analytics and metrics5 minDashboards versus decisions
Why more dashboards rarely produce more decisions, and what actually closes that gap.
QuestionPeople analytics and metrics5 minWhich HR metrics should reach the board?
A short list of workforce metrics that belong in board packs, and why most dashboards do not qualify.
GuideAgents in HR6 minWhat is an HR agent, and where should it stop?
A plain definition of an HR agent, where it earns trust first, and the line it must not cross.
Inside an HR service desk agent, three months in
In this assessment scenario, an HR service desk agent handled 61 percent of tier-one queries without escalation after three months, cutting median response time from six hours to four minutes. Escalation to a human rose only for pay and leave disputes. The pattern illustrates where agents earn trust fastest: high-volume, low-ambiguity requests.
Human-in-the-loop levels for HR agents
A four-level scale for how much human review an HR agent needs, from full sign-off to full autonomy.
ManifestoAgents in HR5 minWhat should never be automated in HR
A short list of HR decisions that should stay with a human, regardless of how capable agents become.
ComparisonSkills and workforce models5 minSkills taxonomy versus job architecture
How a skills taxonomy and a job architecture differ, and why most organisations need both, in order.
GuideSkills and workforce models6 minThe task model: breaking roles into plannable units
How to break a role into tasks small enough to plan capacity, automation and hiring against.
A skills inventory you can finish this quarter
Most skills inventories fail because they try to map every skill for every role at once. A narrower approach works better: pick one business question, map only the roles and skills that answer it, then expand. This delivers a usable inventory in weeks and creates momentum for the next round.
Skills data decays faster than most teams plan for
Why skills records go stale within months and how to set a realistic refresh cycle.
RegulationGovernance and the EU AI Act8 minWhy employment counts as high-risk under the EU AI Act
What the high-risk classification for employment and worker management means in practice for HR teams.
GuideGovernance and the EU AI Act7 minLogging and human oversight, built into HR agents from day one
A practical approach to designing logging and human oversight into HR agents rather than adding them later.
ChecklistGovernance and the EU AI Act6 minA DPIA checklist for people analytics projects
A working checklist for scoping a data protection impact assessment before a people analytics project goes live.
Human oversight, defined
Human oversight means a person can understand, question and, where necessary, override or stop an AI system's output before it takes effect or causes harm. For HR, this means a named individual with the authority, time and information to intervene in decisions that affect employment, not a passive approval step.
Adoption rate is a model, not a feeling
How to define and track adoption rate as a measurable model instead of relying on impressions from a few power users.
GuideAdoption and change6 minManager enablement: the step most AI-in-HR rollouts skip
Most AI-in-HR programmes train end users but leave line managers without a script for the new workflow.
AnalysisAdoption and change7 minWhy the pilot looked good and the rollout did not
Pilots succeed on hand-picked teams and close attention; rollouts fail when both disappear at once.
GuideAdoption and change5 minA four-week pilot plan for an AI-in-HR tool
A week-by-week checklist for running an AI-in-HR pilot with a clear deliverable at each stage.
Workforce demand and supply forecasting, explained plainly
Demand and supply forecasting means estimating, separately, how much work needs doing and how many people will be available to do it, then comparing the two over time. Demand comes from business plans and workload drivers; supply comes from current headcount adjusted for attrition, internal moves, and hiring pipeline. The gap between the two is the actual planning problem, not either number alone.
Scenario planning for workforce cost
How to build two or three workforce cost scenarios that give leadership a real choice, not a single forecast.
ComparisonWorkforce planning6 minStrategic versus operational workforce planning
A comparison of strategic and operational workforce planning, and why organisations need both running at once.
QuestionWorkforce planning5 minHow far ahead can we realistically forecast headcount?
A direct answer on realistic headcount forecasting horizons, and why accuracy drops fast beyond a few quarters.
Recently reviewed
The AI Act and HR practice both move fast. Every entry has a review date, and numbers without a current source are rewritten as qualitative statements.
Three surfaces that keep us honest
We do not just publish conclusions. The sources, the measurement and the comparisons are all open.
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