Trade Union Data Collection and Management Training Course

Trade Union Data Collection and Management Training Course

Introduction

In an era defined by the algorithmic management of labor and the rapid rise of Artificial Intelligence (AI), trade unions must pivot toward a data-centric advocacy model to remain relevant. Traditional shop-floor organizing is now intrinsically linked to digital sovereignty, where the ability to audit employer data and manage internal membership databases determines a union's bargaining power. Trade Union Data Collection and Management Training Course addresses the critical information asymmetry between employers and workers by equipping labor representatives with the technical skills to collect, protect, and leverage data for collective bargaining and occupational safety.

Modern labor movements face systematic assaults under the guise of globalization and digital transformation, necessitating a shift from reactive strategies to proactive data-driven mobilization. By mastering privacy-compliant data architectures and predictive analytics, union leaders can better anticipate workforce shifts, identify safety and health risks in automated systems, and provide personalized services to a diversifying membership base. This training bridges, the "digital skills mismatch," ensuring that union representatives are not just passive observers of technological change but active architects of a fair digital future.

Course Duration

5 days

Course Objectives

1. Enable representatives to identify and challenge biased algorithmic management systems
2. Establish frameworks for worker-owned data and digital rights in the workplace.
3. Utilize data analytics to forecast membership trends and optimize recruitment
4. Ensure full compliance with privacy regulations and the EU AI Act
5. Leverage wage data to close the gender pay gap and address income inequality.
6. Monitor occupational safety and health (OSH) through real-time digital reporting tools
7. Protect sensitive union databases from state-sponsored or corporate cyber-attacks.
8. Develop the skills to negotiate AI-related job reallocation and retraining clauses
9. Build data architectures that allow seamless communication across regional union branches.
10. Formulate labor policies grounded in robust statistical analysis of labor market outcomes
11. Adapt data collection for the gig economy and remote workforce
12. Use CRM tools to enhance solidarity through targeted digital communication.
13. Conduct technical audits of black-box systems used for worker disciplinary actions

Target Audience

1. Union Data Officers.
2. Collective Bargaining Negotiators
3. Occupational Safety & Health (OSH) Reps
4. Union Learning Representatives
5. Shop Stewards.
6. Labour Policy Researchers
7. Digital Transformation Committees
8. Platform & Gig Worker Organizers

Course Modules

Module 1: The Digital Labour Landscape

• History of labor technology-From industrialism to algorithmic management.
• The impact of AI and Automation on job security
• Understanding information asymmetry between employers and unions.
• The role of the EU AI Act and Platform Work Directive in labor law
• Case Study: Challenging "Black-Box" disciplinary systems in a logistics firm.

Module 2: Membership Data Architecture

• Building secure, scalable Cloud-based CRM systems for unions.
• Data entry protocols and maintaining database integrity.
• Strategies for digital recruitment and automated onboarding.
• Mapping membership density across sectors
• Case Study: Scaling a national union database from 10k to 100k members.

Module 3: Advanced Data Collection Techniques

• Designing mobile-first worker surveys for real-time feedback.
• Utilizing Open Source Intelligence (OSINT) for corporate research.
• Digital grievance tracking and workplace incident reporting.
• Integrating qualitative stories with quantitative data for advocacy.
• Case Study: Using real-time survey data to win a 24-hour strike.

Module 4: Data Privacy & Legal Compliance

• Implementing Privacy by Design in union operations.
• Rights of access: Forcing employers to disclose data collection methods
• Managing sensitive biometric and health data under GDPR.
• Legal frameworks for cross-border data transfers.
• Case Study: Navigating a data breach while protecting member identities.

Module 5: Analytics for Collective Bargaining

• Tools for wage gap analysis and benefit cost-projection.
• Visualizing labor trends using Tableau or Power BI.
• Benchmarking internal data against national labor statistics
• Economic modeling for cost-of-living adjustments.
• Case Study: Leveraging employer payroll data to expose gender pay disparities.

Module 6: Monitoring Algorithmic Management

• Auditing automated scheduling and performance tracking tools.
• Negotiating "Right to Explanation" clauses for AI decisions.
• Counter-surveillance: Protecting worker privacy from invasive monitoring.
• The intersection of AI and OSH
• Case Study: Deconstructing a warehouse algorithm that increased worker injuries.

Module 7: Cybersecurity for Labour Movements

• Threat modeling for union organizations.
• End-to-end encryption for internal union communications.
• Protecting against phishing and social engineering attacks.
• Developing a disaster recovery plan for union data.
• Case Study: Defending a union server during a high-stakes national election.

Module 8: Strategic Digital Mobilization

• Using data to segment audiences for targeted digital campaigns.
• A/B testing for union communication strategies.
• Measuring the impact of social media activism on strike participation.
• Building "Digital Solidarity" networks across global supply chains
• Case Study: A global "Day of Action" coordinated via encrypted data sharing.

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.