For the CFO on workforce cost
Workforce cost is the largest line you cannot forecast well. This is the material on labour cost modelling, demand and supply forecasting, the ROI cases that hold, and where the assumptions usually break.
What is the workforce going to cost, and what is the return? Contractors, overtime and late reskilling are usually a bigger number than the hiring plan itself.
For the role
The same library, sorted by what you're actually responsible for.
Roles
Agree the baseline
Total labour cost, contractor share, overtime and vacancy cost, from one source both finance and HR accept.
One scenario, quantified
Model one plausible demand shift and price it. Assumptions written down and reviewable.
Planning in the same rhythm as finance
The people plan and the financial plan reviewed together, on the same numbers, every quarter.
26 poster
How far ahead can we realistically forecast headcount?
A direct answer on realistic headcount forecasting horizons, and why accuracy drops fast beyond a few quarters.
ComparisonWorkforce planning6 minStrategic versus operational workforce planning
A comparison of strategic and operational workforce planning, and why organisations need both running at once.
GuideWorkforce planning6 minScenario planning for workforce cost
How to build two or three workforce cost scenarios that give leadership a real choice, not a single forecast.
GuideWorkforce planning8 minWorkforce demand and supply forecasting, explained plainly
A plain-language guide to forecasting how much workforce you need and how much you will actually have.
Why the pilot looked good and the rollout did not
Pilots often succeed because a small, motivated team gets close support and a manager who champions the change. Rollout removes both at the same time the audience grows, so the same tool meets less attention and more resistance. The fix is to remove support gradually across the rollout, not all at once after the pilot ends.
The task model: breaking roles into plannable units
How to break a role into tasks small enough to plan capacity, automation and hiring against.
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.
RegulationPeople analytics and metrics5 minDefining attrition so two teams agree
A concrete rule set for calculating attrition so HR and finance never present conflicting numbers again.
GuidePeople analytics and metrics6 minThe metric layer the people function runs on
How a shared metric layer turns scattered HR reporting into one language everyone can trust.
Readiness checklist before your first HR model
Before building an HR model, confirm the underlying data has stable worker identities, agreed field definitions, a known refresh cadence and documented gaps. Skipping this checklist does not remove the risk; it just moves the discovery of bad data from before the project to after it ships. Ten minutes of checking saves months of rework.
Manager 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.
GuideAdoption and change6 minAdoption 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.
GlossaryGovernance and the EU AI Act4 minHuman oversight, defined
A plain-language definition of human oversight as used in AI governance and the EU AI Act.
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.
Logging and human oversight, built into HR agents from day one
Logging and human oversight are easier to design in from the start than to retrofit after an HR agent is live. Every consequential action an agent takes should be recorded with enough context to review, and a named person should be able to pause, question or reverse it. Treat both as product requirements, not compliance add-ons.
Why 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.
AnalysisSkills and workforce models6 minSkills data decays faster than most teams plan for
Why skills records go stale within months and how to set a realistic refresh cycle.
GuideSkills and workforce models7 minA skills inventory you can finish this quarter
A scoped approach to building a usable skills inventory in weeks, not years.
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.
What should never be automated in HR
Some HR decisions should stay with a human regardless of agent capability: termination, disciplinary outcomes, final pay decisions, and anything requiring judgement about a person's character or intent. Automating the analysis behind these is fine. Automating the outcome removes accountability from a decision that needs someone to own it.
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.
CaseAgents in HR6 minInside an HR service desk agent, three months in
A synthetic case walking through an HR service desk agent in production, with the numbers behind its performance.
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.
AnalysisPeople analytics and metrics5 minDashboards versus decisions
Why more dashboards rarely produce more decisions, and what actually closes that gap.
Worker identity across systems, not just one
Worker identity breaks when a person moves between contract types, legal entities or systems and picks up a new ID each time. This fragments their history and makes tenure, mobility and attrition analysis unreliable. A durable identifier that follows the person, not the record, is what keeps their history intact across every transition.
What an HR data foundation actually is
The structural layer that must be true before any HR model or agent can be trusted.
Want to see how this looks in your setup? The intro call takes 30 minutes, and we start with the CFO view.
You get a straight answer, even when it is no.
From a first agent in production to the full people-function stack.
The full library, searchable and filterable.