DATA PRIVACY

Our approach to data privacy removes the most common procurement blocker

The way we handle data — metadata only, pseudonymised throughout, group-level outputs, no content access — is materially less intrusive than conventional alternatives. And what 'group-level' means depends on organizational size

OVERCOMING DPO CONCERNS

The five objections we address before every engagement

DPO concern How we address it
Individuals can be identified We hold no re-identification key — that stays with the client. All outputs use pseudonymous IDs only
Data used for performance assessment No individual is named, scored, or ranked. Outputs describe organisational topology, not individual behaviour
Purpose not proportionate to data collected Organisational design is a defined, bounded, time-limited purpose. We process only the metadata the question requires
Risk profile vs. conventional alternatives Interviews, surveys, and management assessments all involve named individuals being observed or evaluated. We use aggregated, pseudonymised metadata. Lower exposure by design
Employee rights not properly considered We assist DPOs in confirming that employee notifications and LIA and DPIA assessments are completed before any processing begins
ORGANIZATIONAL SIZE

Why size changes the privacy picture

In a larger organization — typically above 200 people — groups of ten or more are genuinely anonymous. Individual identification from a group metric is not structurally possible

In a smaller organization — under approximately 200 people — group-level outputs can still allow identification by elimination. This difference directly affects how engagements are scoped and what the DPO conversation looks like

Larger organizations — typically 200+ employees

We apply our full output model. Findings are delivered at group level with minimum group sizes of ten (k≥10) enforced across all outputs. Three output configurations are available:

  • Structure-derived groupings — algorithmically derived groups of approximately ten
  • Question-driven findings — targeted findings in bands of k≥10
  • Formal team aggregation — group-level statistics aggregated to existing team boundaries
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Smaller organizations — under approximately 200 employees

The output model is adjusted to reflect higher re-identification risk. We work with the client and their DPO to agree an approach that is analytically fit for purpose and consistent with their data protection obligations

We are direct with clients when a proposed scope would not meet our privacy standards. If the analysis cannot be conducted in a genuinely privacy-safe way, we say so

Questions about our DPO Reference Guide or a specific engagement?

We respond to all privacy enquiries within five working days

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