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TL;DR

In February the Service Innovation Lab completed a three week discovery sprint on how policy, legislation and the business rules of government can be human and machine consumable.

‘Machine consumable’ means having rules so software can understand and interact with them such as with a calculation or eligibility criteria for a benefit.

This post looks at the outcomes of that discovery sprint from a policy perspective and what lessons can apply to designing a new way to draft legislation and deliver more effective government services.

Policy intent - avoiding ‘lost in translation’?

As a policy adviser, I need to juggle:

  • How do I create ‘future proof’ policies? For example, what will artificial intelligence (A.I.) mean for transport safety or how will someone seek and receive financial ‘robo-advice’?
  • How do I remove barriers preventing better policy design and delivery, such as why do people need to get things confirmed ‘in writing’ for different departments so they can access services?
  • How do I know if the policy is delivering the results we intended?

The Better Rules Discovery tests what “fit for purpose” could look like, using two real bits of legislation (the Rates Rebates Act (1973) and the Holidays Act (2003)).

This small project forces me to think about some big things. It’s not just about linking artificial intelligence and other technologies into government decision-making and service delivery models (though that is pretty amazing). The insights I take away are a bit broader, and are reflected in the discovery sprint report:

  • Service design fundamentals can improve policy advice - Policy advisers offer solutions to gnarly amorphous questions such as how do we increase business innovation, solve child poverty and lower greenhouse gas emissions? Techniques such as co-design, agreed common definitions of the problem and ‘end to end’ thinking through to implementation can help uncover information a traditional, linear policy approach may not. These approaches may benefit all policy advisers, not just those focussed on delivering a government service, or drafting legislation.
  • It’s not about us, it’s about them – As public servants we help the public and access services. Techniques used in the Better Rules project such as concept, decision, flow models and mapping customer journeys offer ways to unpack the steps people take to access a service. And they debunk some assumptions we may have.
  • Take the imperfect first step – We should use some approaches explored in the Better Rules project such as spending more time to agree on the problem definition, before leaping to solutions or having multi-disciplinary teams.
  • Focus on the ideal future end state – It’s more invigorating to focus on what could be than on thrashing the same old problem. Integrating digital thinking in developing policy (including concepts like pseudocode and software code) can flush out new possibilities and embed digital options into our solutions. It would also encourage more end-to-end thinking, rather than throwing my policy solution over your operational fence.

The fundamentals proposed in the Better Rules project opens up bigger questions, such as how we pivot like this within a legislative and Ministerial system that is not particularly agile?

I like the further possibilities this project presents. To me this could lead to a more efficient, happier public service. It’s exciting to be a policy adviser in an environment where we can make incremental, constant change to improve the lives of New Zealanders and improve the chance of a policy being successfully implemented. Who doesn’t want to do their job better?

Now, where can I find a software developer to teach me to code…

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