Inventory algorithmic management systems currently used for scheduling, scoring or monitoring staff.
Digital Transformation & Artificial Intelligence
Governing Algorithmic Management and AI-Driven Employee Monitoring
Learn to govern algorithmic scheduling, performance scoring and monitoring systems, from legal classification and worker consultation to fairness audits and appeal routes.
🗓️Duration5 training days
📚Content4 modules · 8 sessions
🎓On completionAccredited attendance certificate
About the programme
Course Overview
Algorithms now schedule shifts, score productivity, flag disengagement and recommend disciplinary action in many workplaces, often introduced by a single department without the legal, HR and works council review that such systems require. This course equips managers, HR leaders and compliance specialists to bring these systems under proper governance without assuming every algorithmic tool must be abandoned. Participants learn to inventory where algorithmic management already operates, classify each system's legal risk under employment and AI-specific rules, and assess whether workers were consulted before deployment as many jurisdictions require. The course covers designing meaningful transparency, meaning explanations that workers can actually act on rather than generic notices, building an appeal route for automated scheduling or scoring decisions, and running fairness audits that check for disparate impact across protected groups. It closes with the governance structure needed to keep pace with new systems as they are introduced, including a sign-off gate before any new monitoring or scoring tool goes live. Participants leave with a system inventory, a risk classification for at least one live tool and a draft appeal and audit process.
Expected Learning Outcomes
Classify each system's legal risk against employment law and AI-specific regulatory requirements.
Assess whether worker consultation obligations were met before a system was deployed.
Design transparency notices that explain automated decisions in terms workers can act upon.
Build an appeal process that lets a worker challenge an automated scheduling or scoring decision.
Run a fairness audit checking algorithmic outputs for disparate impact across protected groups.
Establish a sign-off gate that requires legal and HR review before any new monitoring tool goes live.
Who Should Attend
HR directors overseeing workforce scheduling and performance systems
Compliance and legal teams reviewing employment technology
Works council and employee representative liaisons
Operations managers using algorithmic scheduling or scoring tools
Data protection officers assessing employee monitoring systems
Technology leaders procuring workforce management software
Course Modules
Select any module to see its sessions and points.
01Mapping Algorithmic Management in the Organisation
2 sessions · 8 points
Session 1Inventorying Scheduling, Scoring and Monitoring Tools
- Survey departments to identify every tool that schedules shifts, scores output or monitors activity.
- Record who introduced each system, when, and whether HR or legal was involved in the decision.
- Classify each tool by the type of decision it makes: scheduling, scoring, flagging or recommending action.
- Identify systems that combine data sources, such as location tracking with productivity scoring, as higher risk.
Session 2Legal Classification of Employment AI Systems
- Assess whether a system meets the criteria for high-risk AI in employment contexts under applicable AI regulation.
- Check obligations for automated decision-making under data protection law, including rights to human review.
- Review sector or jurisdiction-specific rules on algorithmic scheduling and predictive shift allocation.
- Document the classification decision and its reasoning so it can withstand later regulatory scrutiny.
02Consultation and Transparency
2 sessions · 8 points
Session 1Worker Consultation Before and After Deployment
- Determine whether works councils or employee representatives had a legal right to be consulted on the system.
- Design a retrospective consultation process for systems already deployed without proper worker input.
- Document worker feedback and concerns raised during consultation, and how each was addressed or declined.
- Set a consultation trigger so future systems are reviewed with representatives before go-live, not after.
Session 2Meaningful Transparency and Explanation
- Draft explanations of automated decisions in terms of the specific factors that drove the outcome.
- Avoid generic transparency notices that name the system but give workers nothing to act upon.
- Provide workers a channel to ask how a specific score or schedule was generated in their own case.
- Test explanations with a sample of workers to confirm they are understood, not just legally sufficient.
03Fairness and Impact Auditing
2 sessions · 8 points
Session 1Auditing for Disparate Impact
- Analyse scheduling, scoring or flagging outcomes for statistically significant differences across protected groups.
- Investigate whether input data, such as availability patterns, embeds indirect discrimination into outputs.
- Compare algorithmic outcomes against outcomes from the prior manual process to isolate the tool's effect.
- Document audit findings and remediation actions in a form that satisfies both HR and legal review.
Session 2Building an Appeal and Human Review Route
- Design an appeal process that lets a worker request human review of an automated scheduling or scoring decision.
- Set service standards for how quickly an appeal must be reviewed and a response given to the worker.
- Train the reviewers who handle appeals so they understand how the underlying algorithm generates its output.
- Track appeal volumes and outcomes as an early warning indicator of systemic problems with the tool.
04Governance Structure and Ongoing Oversight
2 sessions · 8 points
Session 1A Sign-Off Gate for New Systems
- Require legal, HR and data protection sign-off before any new monitoring or scoring tool is deployed.
- Build a standard risk assessment template so new systems are evaluated consistently against past ones.
- Set a threshold for which system changes require re-review rather than being treated as routine updates.
- Assign clear ownership for the sign-off process so it is not bypassed under delivery pressure.
Session 2Ongoing Monitoring and Escalation
- Schedule periodic re-audits of live systems rather than treating the initial fairness audit as final.
- Set escalation routes for when frontline managers report the algorithm producing implausible outputs.
- Report governance activity and audit outcomes to senior leadership on a regular cycle.
- Retire or retrain systems that repeated audits show are producing unfair or unreliable outcomes.
What the participant receives
4 course modules
A structured syllabus
8 training sessions
across 5 days
32 detailed points
Applied, detailed content
Accredited attendance certificate
On completing the programme
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