On 16th May 2024 I led a 90 minute session as part of the Digital Academy Masterclass, hosted by the Government of Azerbaijan’s Innovation and Digital Development Agency, and delivered by Digital Nation.
I’ve broken the presentation into 4 parts. After an introduction, this is Part 1 considering the potential of data to deliver public value; Part 2 asked how do we go about building a data-driven public sector; and Part 3 explored how to unlock the value of data without losing public trust.
Unless otherwise indicated or an obvious screenshot, the images were generated by ChatGPT.
So let’s start with understanding the transformative potential of data in delivering public value.
The volume of data we generate and the importance we place on it is growing exponentially, but the critical question is: how effectively are we harnessing this data?
In 2010 the world as a whole generated 2 zettabytes of data. Last year that figure was put at a staggering 120 zettabytes of data. To put that in some perspective, one zettabyte equals a trillion gigabytes.
And to put that into some personal perspective, the first computer I had in my family had a hard disk of just over 1 gigabyte. Last year the world generated enough data for 120 trillion of those machines.
The numbers are staggering.
But it’s not just growth in numbers, there’s a profound shift in how we collect, store, and use information.
In 2006, Clive Humby coined the phrase ‘data is the new oil’ in his work to help a supermarket unlock the habits of their customers.
By 2017, The Economist declared data as the world’s most valuable resource, surpassing oil.
In fact, this analogy may understate the potential value of data to generate more than oil. For example, in Norway the oil industry accounts for 20% of gross domestic product. Research has suggested that the data economy will surpass the value created by Norwegian petroleum by 2030.
Data is much cheaper to source, store, exchange, share and transport. More than one person can derive value from data at the same time, and it can be used more than once to do new things. Indeed, ultimately the more we put data to use the more valuable it becomes
But the analogy may also minimise the potential harms of data, which could potentially outstrip those of oil.
Data needs careful management.
Data can have negative and unintended consequences if misused and abused
Data centres are essential for processing and storing data but they consume significant resources.
And just like an oil spill, a data breach can have long-lasting and damaging repercussions.
Let’s start by looking at the different ways data can generate value. The OECD suggests that it can help to think of data’s role in answering three stages of the different ‘tenses’ of government:
- Anticipating and planning
- Delivery
- Evaluation and monitoring
The first place to start is with asking that question – what might happen? How can data help government anticipate and plan for the future?
Let’s start by thinking about how you design policy. This is the tried and tested model for the use of data – academic and research data that makes better decisions. Specifically thinking about “Evidence-based policy making”.
Data is powerful for helping design the best policy.
A powerful and helpful example is that of efforts to answer this question: how do you improve attendance and test scores in Kenyan schools?
The team were using Randomised Controlled Trials. They’re a very familiar device in the world of medicines when trying to understand the efficacy (or dangers) of new drugs.
Would free school uniforms help? New textbooks? More teachers?
Then someone had a bright idea from left field: what about deworming the children?
They added that into the trial. And they discovered that it reduced absenteeism by 25%.
The eventual conclusion was that $0.05 could keep a child in class for an extra day in their schooling. The Deworm The World programme has gone on to claim $23bn of benefits not just around education but about the wider economy and health too.
Having solid data foundations also allows for anticipating change and forecasting needs across different areas of demand: housing, health, education, etc.
Carrying out regular census collection helps societies plan for what might be coming and thinking through the implications of a falling birth rate on adult social care, or in the case of an increase, on the need for more teachers for example.
Data platforms for statistics are very well established, with examples on the slide from Slovenia, Azerbaijan and Denmark reflecting just three from around the world.
This administrative aspect of understanding society has been the bread and butter of government for much longer than the Internet has been around.
But what extra value can it unlock?
Data-enabled prediction and modelling techniques make it possible to work with all of this data to anticipate societal, economic or natural developments.
The last of this first area is that of foresight.
Traditional planning tools and methods rely on the past and current factors, whereas futures and foresight methods embrace uncertainty and encourage the analysis and consideration for a range of future possibilities to inform decision-making and public policy.
The future is not a fully formed, knowable entity which exists objectively somewhere else.
It is an emergent, socially constructed entity which always and only partially exists subjectively in the here-and-now.
As my former colleagues in the OECD Observatory of Public Sector Innovation say – there is no absolute future, but there are many relative futures.
Those futures can take many different forms: predicted, projected, preferred, path–dependent, probable, plausible, and possible.
In Canada, Policy Horizons operates at the federal level to help the Government of Canada develop future-oriented policy and programs that are robust and resilient in the face of disruptive change.
So that’s the value of data for anticipating and planning, for pondering the question ‘what could happen’?
But what about how data can help understand what’s happening right now?
The second area is about the use of data for delivering government – the day to day ins and outs of the public services and policy implications that people experience.
Let’s start by thinking about a practical example of how a government uses data to better implement policy
The Portuguese government created a Social Energy Tariff to assist with energy costs in 2010.
The service required eligible users to sign up and register to receive it, but the initial data showed that those who should have benefited from the tariff were not registering to receive it.
User research identified that these people were unaware that they needed to apply for it.
This prompted a decision to automate the process and make it proactive. Using Portugal’s Interoperability Platform for the Public Administration (iAP), data could be shared between the Directorate General for Energy and Geology, energy companies, the tax system, and the social security system.
Portugal was able to benefit from its interoperability platform and that sort of technical infrastructure is so crucial to delivering services, which brings me to an example that might be familiar to everyone in this room.
And that is the interoperability of data and unlocking of service value offered by the X-Road.
After its creation in Estonia in 2001 it’s now operational in more than 10 countries around the world including Azerbaijan.
The claimed impact is incredible – within the X-tee ecosystem, 3m working hours are saved every year, 3 000 different services are saved and 2.5billion transactions are supported.
Huge numbers, massive impact – all from unlocking the value of data for delivering policy and services.
That’s thinking about data as a tool for putting good things in motion but what about real-time data to allow for responsive government?
Public transport is often a good source of innovation on this. For example, in Singapore the Land Transport Authority gathers a huge amount of data in real-time about buses, bus stops and individual travellers (which is anonymised).
This data provides detailed models of how users move around the city, which helps with understanding traffic patterns, how the transportation network is used, and what problems need to be addressed with the network.
When congestion is detected, additional buses are deployed.
The SLTA claims a 92% reduction in crowded bus services, despite increase in daily bus ridership and a 3- to 7-minute reduction in the average waiting time on popular bus services
They’re now working on a system that would use comprehensive, real-time, aggregated traffic data to intervene more effectively by adjusting traffic light timings and providing priority for buses.
So that’s the value of data for delivery, for asking how can data contribute towards the question of ‘what is happening’?
Finally, we think about what has actually happened. Data can add value in evaluating and monitoring what’s been going on.
The first area to think about is how we measure the impact of interventions we carry out.
And to do that we’ll go back to Portugal.
The initial prompt for creating the Social Energy Tariff was a knowledge about a section of society that needed help.
Then they paired the policy implementation with monitoring of numbers: those numbers showed there was a problem.
We spoke about how interoperability provided the means for automating the process but the role of data doesn’t end there.
Because now it was possible to monitor the impact. That showed an almost fivefold increase in the number of households benefitting in just three months. Ultimately, this intervention provided financial support to 7% of the Portuguese population without requiring them to validate their eligibility.
Data can also help as the record of decision making. This can be internal, or it can help with fighting corruption.
For example, in Chile the procurement authority publishes detailed buying and selling activity for public sector organisations. It’s possible to follow the thread through from the spend of public buyers, to their tenders, and then on to the contracts and associated paperwork.
Finally, data is used for monitoring performance.
We all got familiar with open data dashboards for COVID-19. I confess it’s a long time since I looked at Johns Hopkins but here it is having stopped the clock on 676 million cases.
It can also be used for individual services, showing what’s going on in real-time. Take this example of the register to vote service that periodically draws interest when the numbers signing up spike. Here a couple of tweets from 2016 when there were huge numbers signing up ahead of the Brexit referendum.
Here again the data from the last 6 weeks showing that spike just before the deadline for being registered in the UK’s recent local elections.
Or data can be used for grander monitoring of the whole system of government as per this ambitious effort from the USA. On performance.gov you can drill down into different objectives.
For example, you can find out how well the Department of Housing and Urban Development is doing against its brief to “make homelessness rare, brief, and non recurring by reducing the number of people experiencing unsheltered homelessness by 7% from 2023 levels.”
Or a more technical gaol at the General Services Administration to increase adoption of login.gov
They’re very different high level targets, reported on in detail and in the open.
And so that’s how data can help with evaluation and monitoring of what’s actually happened.
Taken in isolation there’s a lot of value to be derived but it’s also important to recognise the phases as a continuum:
- The application of data in the “anticipation and planning” phase to design an intervention will lead to a policy or a service.
- During “delivery” of that policy or service new data will be generated and insights applied
- That activity will subsequently provide data for the “evaluation and monitoring” of performance and impact.
Those insights are then both feeding back into delivery, and forward into future thinking.
Another important aspect of public value is that of open government data.
It’s great to see that Azerbaijan has its open data website and that efforts are ongoing to do more and more to innovate with it.
There are three primary areas where Open Government Data offers value.
It offers economic value: the private sector can benefit from easier access to information, content and knowledge, which contributes to the development of innovative services and the creation of new business models.
For example, the company Doctrine, uses case law published by the French government on Légifrance to power its search engine, which provides lawyers with relevant information to help them prepare their cases.
Open data can help increase government accountability by shedding light on their activities, decisions and spending, allowing citizens and government to better monitor the flow and use of public money within and beyond borders.
We had a look at Chile and how data allows for auditing procurement decisions and tackling corruption and fraud but accountability may also concern simple errors.
For example, a New York citizen was looking at parking ticket data. He discovered thousands of tickets issued for vehicles that were legally parked. He got in touch with the New York Police Department to report his findings. A few weeks later, he received a thoughtful and polite note from the NYPD acknowledging the error and listing steps taken to correct it.
The data highlighted that parking officers had misunderstood a change in the rules.
And there’s a general social value to government operating in an open and transparent fashion. But there are also specific opportunities associated with opening up data and seeing what can emerge from a participatory and collaborative point of view.
Countries across the globe are hosting hackathons that encourage teams to come together and work with open data in response to particular challenges.
So, in this first part we’ve looked at data’s role in answering four questions about how data can generate public value:
- What might happen?
- What’s happening?
- What actually happened?
- How can Open Government Data contribute?
Now it’s over to you to reflect on your experiences and think about the use of data within your organisations.
Go back to the introductory slides, read Part 2 on how to go about building a data-driven public sector; or Part 3 on how to unlock the value of data without losing public trust.