managing innovation


This post is part of innov-hate, a brief series of thoughts and reflections on innovation in Government.

credit: Clark Tibbs


In how to do innovation I spoke about the thinking, talking and action needed to undertake the speculative activity of innovation to prove concepts in context. This requires patience and escaping the inertia of business norms. This brings a different set of expectations and managing these needs the right foundations. That’s what this post is about.

The right aspiration

The Government Digital Service (GDS) hopes for 2030 speak of a more flexible, cheaper and efficient overall government system — better for policy, better for delivery, better for users. Future public services built on

Assembly of interconnected components

Platform thinking and appropriate open standards. Things built to work with each other so if something should be shared or used again it can be.


Joint, cross-government efforts and perspectives on everything we do. Support and guidance from GDS who exist to help tie it all together.


Data as the foundational component of everything. Made easier to find, access and use — securely and appropriately — so we can offer tailored services.

For those involved in speculative activity across the public sector these give something to aim for from within your own organisational context and plans.

The right team

These aspirations point to a team ethos of developing healthy ecosystems of peers, partners, suppliers and users, developing scalable processes, practices and infrastructural foundations and of making data more widely accessible.


Instilling ambition and vision within your organisational context is crucial. Empowering, supporting and motivating people to try new ideas or take risks. Developing entrepreneurialism, a growth and challenge mindset and delivery focused problem solvers by role-modelling with integrity and empathy.


Putting supportive structures in place for people to learn about new disciplines and working practices. Setting aside “20%” time to learn emerging technologies through practical application.


Bringing different perspectives together to generate a wealth of ideas for speculative initiatives. Multi-disciplinary, multi-vendor and partnership approaches and teams that better reflect society.

These all equip teams with resilience and confidence to rebalance the information asymmetry that comes with innovation hype. Finding the right people is always a topic of central concern – again patience is important.

The right use cases

Innovation is built on interdependencies. Managers must embrace this interconnectedness to bring value through innovation. It facilitates the link between tactical/short term and strategic/long term planning (medium term stuff tends to sort itself out). You have to find the sweet spot between

User need

Solving people’s problems rather than showing off solutions won’t always be seen as innovation. Users don’t really care about what is behind the curtain. They just want a problem solved or an outcome improved.

Data and technology

Cloud/serverless computing, deep/machine learning, encryption, artificial intelligence, automation offer powerful outcomes. But they come with terms and conditions such as the right infrastructure, standards, ethics, skills and culture. You have to choose wisely when picking potential solutions.

Speculative enough

Hypotheses that might be better, quicker or more practical to solve the problem or improve the outcome. Use cases that are realistic and testable in context. Assessing achievability vs speculation is the biggest challenge.

Identify, connect and accelerate the most promising ideas. Pause or stop those which don’t represent the most value right now. Reignite these later in a different context or format. Start small, scale quickly. Balance all this whilst supporting senior leaders. This is the crux of innovation. The right business sponsor at the right stage is important.

The right processes

Speculation in government can be complex. Applying traditional processes of governance, progress and metrics too early is risky and public sector context doesn’t often align with private sector models. Politics and bureaucracy are often seen as stifling innovative approaches. This area needs most consideration


Speculation comes before discovery. It requires more pragmatic approaches outside the GDS digital lifecycle to enable and encourage flexibility and speed. Frequent, light touch, appropriate decision points (funding, stop-go etc) are more suitable for responsiveness. See also agile procurement.


Most government innovation isn’t done with big budgets, however specific budgets to invest in speculation (technology, people, infrastructure or time) are needed. Investment in basic infrastructure that could facilitate innovation is also required — this is beginning to change in many parts of government.

Measuring success

You can only measure success if you have a goal. Not innovation for its own sake or getting hung up on financial or specific metric details too early – that will inevitably mean initiatives never get off the ground. Whether hype busting or mind opening, helping people see to believe is a positive goal.

Speculation should be at the core of exploring future public services. The next post — putting data to good use — gives examples of work in my own context. Bringing data and service design together to make data more accessible for users to make decisions.



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Ryan Dunn

Data Science Hub Lead @DWPDigital. These are my personal thoughts.