Privacy Engineering
The technical and architectural implementation of privacy: data minimisation, aggregation, anonymisation and its limits, consent architectures, suppression, access control and privacy-by-design as an engineering discipline rather than a policy statement.
Workplace evidence is people data, and the entire evidence enterprise stands on its legitimacy: one surveillance scandal poisons every stream for years. Privacy engineering is what makes the evidence architecture trustworthy by construction — cohort thresholds that hold, consent that is real and revocable, aggregation that resists re-identification. It is not the compliance layer on the platform; it is the condition of the platform's licence to exist.
- What is the minimum data this decision actually requires?
- Do the aggregation and suppression controls genuinely prevent identification — including by combination?
- What does meaningful consent require in an employment relationship, where power is asymmetric?
- Where are the re-identification and function-creep risks in this evidence architecture?
- Privacy engineering research and privacy-by-design frameworks
- Re-identification and anonymisation-limits literature (aggregation is harder than it looks)
- GDPR and employment-context data protection guidance
- The governance record: consent rates, suppression events, access logs
Data minimisation as the default posture — collect for decisions, not for optionality; cohort thresholds (minimum five) enforced technically, not procedurally; individual-level data only with explicit, revocable, consequence-free consent; purpose limitation engineered so function creep requires deliberate governance rather than quiet drift; the negative guarantees published and kept.
Workplace Passport
A consent-aware individual workplace profile — proprietary to the Workplaced platform — through which employees express the conditions under which they can work effectively.
Data Requests
Build a structured evidence inventory across business, workforce, portfolio, financial and technology data before fieldwork begins.
Occupancy Assessment
Occupancy validates, challenges and enriches workplace demand — measuring how space is actually used, not how its use is reported.
Booking Behaviour Analysis
The systematic analysis of reservation behaviour — what people book, hold, abandon and avoid — as a continuous demand signal and early-warning layer for friction.
Anonymisation optimism: 'the data is anonymised' claimed for datasets that re-identify trivially by combination (team, floor, day). The engineering literature is clear that aggregation and suppression require actual design; privacy claims that rest on intention rather than architecture fail exactly when tested.
Meaningful consent under employment power asymmetry remains genuinely unresolved — legally, ethically and practically. It is the workplace evidence field's hardest honest question.