Understanding Data Sharing— Data Triage: move fast and tidy up

(Open Google slide version http://bit.ly/data-triage)

Our data-enabled world will be continuously monitoring and learning. We must step up to the challenge of managing our individual agency as innovation outpaces regulation

I’ve been receiving a lot of calls this year from people asking how they can use data to ‘help’ in various situations (from climate to COVID).

even without an ‘emergency’, there is often a rush to technology-led solutions without considering the overall decision-making environment that will impact users.

The image above is a provocation: a potential process to ask how we can try and focus on what matters; that can unlock rapid-response from a frontline delivery team who can focus on solutions; that can pick up the pieces to address risks and harms.

Questions to consider

  • What problems are we really trying to solve — based on actual user needs?
  • How will data help these problems?
    (what data? when? what frequency is timely? what analysis? for whom?)
  • Who should act to convene and lead: a sector, public body, both?
  • When are solutions needed and what might be our MVP (minimum viable proposition) intervention? (nb: this may not need any data at the outset)
  • What single issue could act as an exemplar to focus everyone’s mind?
  • What institutional memory, standards, principles and practices can be created as a legacy output and how will we make it discoverable?

Roles & responsibilities

Steering = combined expertise to ensure decisions are timely, effective, comprehensive and address risk

A process outline (illustrative):

  1. A ‘Triage team’, comprising practitioners from the various domains, can act as the first point of call and consider the different user needs in the assessment and development of programmes.
  2. A ‘Governance/ Steering Group’ is assigned to approve recommendations and prioritises responses put forward by the Triage team.
  3. The Governance group can initiate rapid-response from a Delivery team who focus on solutions in the knowledge that there is a process overseeing and following them to ‘tidy up’ (rapid development is messy and leaves a data footprint).
  4. The Risk analysis team ‘follow’ the Delivery team, both documenting lessons learned, making sure that the output work is compliant with standards, regulation, principles and practices and highlighting areas for review and clean up. The Delivery team relies on this independent team managing risks arising or issues that materialise, enabling them to focus on delivery.
  5. The Clean up team follows the outputs of the Risk team to ensure data, code, and related digital assets are secure, deleted or otherwise made compliant.
  6. The Governance team have responsibility for both oversight and capturing outputs in an incremental manner to both (a) build usable institutional memory and (b) develop and input into living standards.

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