Thanks, David. I had a quick look, and I can see why you connected it to the Explainer. The idea of binding access decisions directly to explicit conditions is very much part of the gap I was pointing to.
What remains especially interesting to me is what happens when a relevant condition changes outside the immediate access decision itself. That is usually where the governance problem starts to get harder.
The customer service example shows the gap clearly: the approval was valid when it was given, but the workflow changed afterwards and nobody was positioned to notice that its basis no longer held. Your line "Defining a rule is one thing. Being able to act on it is another." captures why a policy document alone does not create the capability to govern use. What practical trigger would you recommend for deciding that an already approved use case needs a new assessment?
I would tie the trigger to the conditions on which the original approval depended. If one of those conditions changes materially, the approval should no longer be treated as automatically valid.
In the example, the shift from non-confidential to confidential customer data would be such a trigger. The harder governance question is how the organization becomes aware that a relevant condition has changed in the first place.
That is a clear way to frame it: the approval carries its own conditions, so a material change to any of them reopens the assessment. On the awareness question, I would place the obligation with whoever changes the workflow. If each approval records the conditions it relied on, such as the data class, the user group and the decision being supported, then any change request that touches one of those fields can be routed back for review before it goes live, rather than discovered afterwards. We see the same pattern in engineering design review: the error is rarely in the original approval, it is in the change that nobody sent back for checking.
Yes, that is exactly the useful operational move: make the conditions behind the approval explicit enough that a change can be checked against them before it goes live.
The remaining difficulty is that not every relevant change originates in a formal workflow change request. Provider updates, model changes or changes in connected data sources can also alter the conditions without the workflow owner actively changing anything. That is where the detectability problem becomes harder.
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Thanks, David. I had a quick look, and I can see why you connected it to the Explainer. The idea of binding access decisions directly to explicit conditions is very much part of the gap I was pointing to.
What remains especially interesting to me is what happens when a relevant condition changes outside the immediate access decision itself. That is usually where the governance problem starts to get harder.
The customer service example shows the gap clearly: the approval was valid when it was given, but the workflow changed afterwards and nobody was positioned to notice that its basis no longer held. Your line "Defining a rule is one thing. Being able to act on it is another." captures why a policy document alone does not create the capability to govern use. What practical trigger would you recommend for deciding that an already approved use case needs a new assessment?
I would tie the trigger to the conditions on which the original approval depended. If one of those conditions changes materially, the approval should no longer be treated as automatically valid.
In the example, the shift from non-confidential to confidential customer data would be such a trigger. The harder governance question is how the organization becomes aware that a relevant condition has changed in the first place.
That is a clear way to frame it: the approval carries its own conditions, so a material change to any of them reopens the assessment. On the awareness question, I would place the obligation with whoever changes the workflow. If each approval records the conditions it relied on, such as the data class, the user group and the decision being supported, then any change request that touches one of those fields can be routed back for review before it goes live, rather than discovered afterwards. We see the same pattern in engineering design review: the error is rarely in the original approval, it is in the change that nobody sent back for checking.
Yes, that is exactly the useful operational move: make the conditions behind the approval explicit enough that a change can be checked against them before it goes live.
The remaining difficulty is that not every relevant change originates in a formal workflow change request. Provider updates, model changes or changes in connected data sources can also alter the conditions without the workflow owner actively changing anything. That is where the detectability problem becomes harder.