Strategic context
The company enables organisations to compare, analyse or activate data across controlled environments without routinely exposing complete underlying datasets to each participant. Its technology may use permissioning, matching, transformation, secure computation and governed outputs. The commercial promise is privacy-enhancing collaboration; the governance risk is that sophisticated architecture is treated as a substitute for lawful purpose, accurate claims or accountable use.
The Board seeks an advisor who can help define product trust, market boundaries, partner governance and responsible scale. The advisor will not certify compliance, act as data protection officer or make Board decisions.
Four governance systems to design
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Purpose and participation architecture. Define permitted collaboration purposes, participant roles, data authority, contribution rights, prohibited uses, onward action, withdrawal and termination. A technically possible query must not become a contractually or ethically permissible query by default.
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Privacy and output-control architecture. Advise on identity and access, query approval, minimum cohorts, suppression, differential or statistical protections where relevant, repeated-query risk, export, logging, retention and deletion. Outputs should be tested for re-identification and combination risk, not only direct identifiers.
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Evidence and claims architecture. Require explicit statements about what data is encrypted, transformed, retained or visible; which party holds keys; what administrators can access; what happens during support; and which guarantees depend on customer configuration. Marketing must distinguish design objective from independently demonstrated outcome.
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Commercial and ecosystem architecture. Govern cloud, data, identity, model, analytics and channel partners; participant concentration; pricing incentives; liability; audit rights; incident response; portability and exit. Revenue models should not encourage broader queries, longer retention or hidden reuse.
Board questions and deliverables
The advisor will help the Board decide which use cases the platform should refuse, which require enhanced review and which can scale through standard controls. Deliverables will include a use-case taxonomy, participant trust framework, output-risk model, claims register, partner standard, incident decision tree and Board dashboard.
Board reporting should address approved and rejected use cases; sensitive data categories; high-risk queries; output suppressions; administrator access; customer configuration exceptions; privacy testing; incidents; partner dependencies; non-standard contracts; retention exceptions; renewal; customer concentration; support burden and unit economics.
Candidate profile
Candidates should bring at least 20 years of experience across data platforms, privacy engineering, information governance, cybersecurity, enterprise software, digital advertising or regulated data use. Former data or technology executives, privacy leaders, CISOs, platform strategists and experienced technology advisors may be suitable.
IICA registration is not required. The candidate must disclose relationships with data providers, cloud vendors, analytics firms, customers, investors or competing platforms. The advisor may not present recommendations as legal certification or use the role to sell security, cloud, data, audit or consulting services.
Expected impact
Within six months, the Board should have a clear boundary between possible and permissible collaboration, truthful product claims and an escalation model for high-risk use. Within one year, the company should be able to scale standard use cases while refusing unsafe ones, demonstrate how privacy is preserved and explain who remains accountable at every stage.