Data Literacy for Data-Informed Policy & Regulation Design Playbook
- Practitioner
- Advanced
- Template Included
A framework for building data literacy specifically for policy and regulation design professionals — evidence quality assessment for policy decisions, understanding unintended consequence modeling, and appropriately weighing correlational evidence against the causal claims policy justification often requires.
Policy design has traditionally relied heavily on expert judgment
and stakeholder input — where does data literacy specifically fit in? Expert judgment and stakeholder input remain essential, but increasingly, policy justification relies on data-driven evidence, and genuine literacy means knowing whether that evidence actually supports the causal claims being made to justify a specific policy choice, not just whether supportive-looking data exists.
What's the most common data literacy gap specifically in policy
and regulation design? Using correlational evidence to justify policy as if it demonstrated causation — a policy justified by data showing two things moving together, without genuine causal evidence that the policy intervention would actually produce the desired effect.
Subscriber access
Unlock this playbook
This playbook — including every framework, template, and step-by-step section — is available free to Think Insights subscribers. Enter your email to unlock it instantly and get our weekly insights newsletter. No account needed, and access is remembered on this device.
