Using data and design to support people to stay in work

Curated on Posted on by Stefaan Verhulst

 at Civil Service Quarterly: “…Data and digital are fairly understandable concepts in policy-making. But design? Why is it one of the three Ds?

Policy Lab believes that design approaches are particularly suited to complex issues that have multiple causes and for which there is no one, simple answer. Design encourages people to think about the user’s needs (not just the organisation’s needs), brings in different perspectives to innovate new ideas, and then prototypes (mocks them up and tries them out) to iteratively improve ideas until they find one that can be scaled up.

Composite graph and segmentation analysis collection
Segmentation analysis of those who reported being on health-related benefits in the Understanding Society survey

Policy Lab also recognises that data alone cannot solve policy problems, and has been experimenting with how to combine numerical and more human practices. Data can explain what is happening, while design research methods – such as ethnography, observing people’s behaviours – can explain why things are happening. Data can be used to automate and tailor public services; while design means frontline delivery staff and citizens will actually know about and use them. Data-rich evidence is highly valued by policy-makers; and design can make it understandable and accessible to a wider group of people, opening up policy-making in the process.

The Lab is also experimenting with new data methods.

Data science can be used to look at complex, unstructured data (social media data, for example), in real time. Digital data, such as social media data or internet searches, can reveal how people behave (rather than how they say they behave). It can also look at huge amounts of data far quicker than humans, and find unexpected patterns hidden in the data. Powerful computers can identify trends from historical data and use these to predict what might happen in the future.

Supporting people in work project

The project took a DDD approach to generating insight and then creating ideas. The team (including the data science organisation Mastodon C and design agency Uscreates) used data science techniques together with ethnography to create a rich picture about what was happening. Then it used design methods to create ideas for digital services with the user in mind, and these were prototyped and tested with users.

The data science confirmed many of the known risk factors, but also revealed some new insights. It told us what was happening at scale, and the ethnography explained why.

  • The data science showed that people were more likely to go onto sickness benefits if they had been in the job a shorter time. The ethnography explained that the relationship with the line manager and a sense of loyalty were key factors in whether someone stayed in work or went onto benefits.
  • The data science showed that women with clinical depression were less likely to go onto sickness benefits than men with the same condition. The ethnography revealed how this played out in real life:
    • For example, Ella [not her real name], a teacher from London who had been battling with depression at work for a long time but felt unable to go to her boss about it. She said she was “relieved” when she got cancer, because she could talk to her boss about a physical condition and got time off to deal with both illnesses.
  • The data science also allowed the segmentation of groups of people who said they were on health-related benefits. Firstly, the clustering revealed that two groups had average health ratings, indicating that other non-health-related issues might be driving this. Secondly, it showed that these two groups were very different (one older group of men with previously high pay and working hours; the other of much younger men with previously low pay and working hours). The conclusion was that their motivations and needs to stay in work – and policy interventions – would be different.
  • The ethnography highlighted other issues that were not captured in the data but would be important in designing solutions, such as: a lack of shared information across the system; the need of the general practitioner (GP) to refer patients to other non-health services as well as providing a fit note; and the importance of coaching, confidence-building and planning….(More)”

Quantifying scenic areas using crowdsourced data

Curated on Posted on by Stefaan Verhulst

Chanuki Illushka Seresinhe, Helen Susannah Moat and Tobias Preis in Environment and Planning B: Urban Analytics and City Science: “For centuries, philosophers, policy-makers and urban planners have debated whether aesthetically pleasing surroundings can improve our wellbeing. To date, quantifying how scenic an area is has proved challenging, due to the difficulty of gathering large-scale measurements of scenicness. In this study we ask whether images uploaded to the website Flickr, combined with crowdsourced geographic data from OpenStreetMap, can help us estimate how scenic people consider an area to be. We validate our findings using crowdsourced data from Scenic-Or-Not, a website where users rate the scenicness of photos from all around Great Britain. We find that models including crowdsourced data from Flickr and OpenStreetMap can generate more accurate estimates of scenicness than models that consider only basic census measurements such as population density or whether an area is urban or rural. Our results provide evidence that by exploiting the vast quantity of data generated on the Internet, scientists and policy-makers may be able to develop a better understanding of people’s subjective experience of the environment in which they live….(More)”

Policy Diffusion at the Local Level: Participatory Budgeting in Estonia

Curated on Posted on by Stefaan Verhulst

Jelizaveta Krenjova and Ringa Raudla in Urban Affairs Review: “The existing studies on participatory budgeting (PB) have paid very limited attention to how this participatory tool has spread across local governments (LGs), what kind of diffusion mechanisms have played a predominant role, and which actors and factors have influenced its adoption. Our article seeks to address this gap in the scholarly discussion by exploring the diffusion of PB across LGs in Estonia, where it is a rather new phenomenon. Our qualitative study demonstrates that the diffusion of PB in Estonia has so far been driven by the interaction of two mechanisms: learning and imitation. We also find that an epistemic go-between, information-technological solutions, and the characteristics of the initial adopter played a significant role in shaping the diffusion process….(More)”

Forged Through Fire

Curated on Posted on by Stefaan Verhulst

Book by John Ferejohn and Frances McCall Rosenbluth: “Peace, many would agree, is a goal that democratic nations should strive to achieve. But is democracy, in fact, dependent on war to survive?

Having spent their celebrated careers exploring this provocative question, John Ferejohn and Frances McCall Rosenbluth trace the surprising ways in which governments have mobilized armies since antiquity, discovering that our modern form of democracy not only evolved in a brutally competitive environment but also quickly disintegrated when the powerful elite no longer needed their citizenry to defend against existential threats.?

Bringing to vivid life the major battles that shaped our current political landscape, the authors begin with the fierce warrior states of Athens and the Roman Republic. While these experiments in “mixed government” would serve as a basis for the bargain between politics and protection at the heart of modern democracy, Ferejohn and Rosenbluth brilliantly chronicle the generations of bloodshed that it would take for the world’s dominant states to hand over power to the people. In fact, for over a thousand years, even as medieval empires gave way to feudal Europe, the king still ruled. Not even the advancements of gunpowder—which decisively tipped the balance away from the cavalry-dominated militaries and in favor of mass armies—could threaten the reign of monarchs and “landed elites” of yore.?

The incredibly wealthy, however, were not well equipped to handle the massive labor classes produced by industrialization. As we learn, the Napoleonic Wars stoked genuine, bottom-up nationalism and pulled splintered societies back together as “commoners” stepped up to fight for their freedom. Soon after, Hitler and Stalin perfectly illustrated the military limitations of dictatorships, a style of governance that might be effective for mobilizing an army but not for winning a world war. This was a lesson quickly heeded by the American military, who would begin to reinforce their ranks with minorities in exchange for greater civil liberties at home.?

Like Francis Fukuyama and Jared Diamond’s most acclaimed works, Forged Through Fire concludes in the modern world, where the “tug of war” between the powerful and the powerless continues to play out in profound ways. Indeed, in the covert battlefields of today, drones have begun to erode the need for manpower, giving politicians even less incentive than before to listen to the demands of their constituency. With American democracy’s flanks now exposed, this urgent examination explores the conditions under which war has promoted one of the most cherished human inventions: a government of the people, by the people, for the people. The result promises to become one of the most important history books to emerge in our time….(More)”

Democracy Index 2016

Curated on Posted on by Stefaan Verhulst

The annual review by the Economist Intelligence Unit: “According to the 2016 Democracy Index almost one-half of the world’s countries can be considered to be democracies of some sort, but the number of “full democracies” has declined from 20 in 2015 to 19 in 2016. The US has been downgraded from a “full democracy” to a “flawed democracy” because of a further erosion of trust in government and elected officials there.

The “democratic recession” worsened in 2016, when no region experienced an improvement in its average score and almost twice as many countries (72) recorded a decline in their total score as recorded an improvement (38). Eastern Europe experienced the most severe regression. The 2016 Democracy Index report, Revenge of the “deplorables”, examines the deep roots of today’s crisis of democracy in the developed world, and looks at how democracy fared in every region….(More)“

Billboard coughs when it detects cigarette smoke

Curated on Posted on by Stefaan Verhulst

Springwise: “The World Health Organization reports that tobacco use kills approximately six million people each year. And despite having one of the lowest smoking rates in Europe, Sweden’s Apotek Hjartat pharmacy is running a quit smoking campaign to help smokers make good on New Year resolutions. Located in Stockholm’s busy Odenplan square, the campaign billboard features a black and white image of a man.

When the integrated smoke detector identifies smoke, the man in the billboard image comes to life, emitting a sharp, hacking cough. So far, reactions from smokers have been mixed, with non-smokers and smokers alike appreciating the novelty and surprise of the billboard.

Apotek Hjartat is not new to Springwise, having been featured last year with its virtual reality pain relief app. Pharmacies appear to be taking their role of providing a positive public service seriously, with one in New York charging a man tax to highlight the persistent gender wage gap….(More)”

The science of society: From credible social science to better social policies

Curated on Posted on by Stefaan Verhulst

Nancy Cartwright and Julian Reiss at LSE Blog: “Society invests a great deal of money in social science research. Surely the expectation is that some of it will be useful not only for understanding ourselves and the societies we live in but also for changing them? This is certainly the hope of the very active evidence-based policy and practice movement, which is heavily endorsed in the UK both by the last Labour Government and by the current Coalition Government. But we still do not know how to use the results of social science in order to improve society. This has to change, and soon.

Last year the UK launched an extensive – and expensive – new What Works Network that, as the Government press release describes, consists of “two existing centres of excellence – the National Institute for Health and Clinical Excellence (NICE) and the Educational Endowment Foundation – plus four new independent institutions responsible for gathering, assessing and sharing the most robust evidence to inform policy and service delivery in tackling crime, promoting active and independent ageing, effective early intervention, and fostering local economic growth”.

This is an exciting and promising initiative. But it faces a series challenge: we remain unable to build real social policies based on the results of social science or to predict reliably what the outcomes of these policies will actually be. This contrasts with our understanding of how to establish the results in the first place.There we have a handle on the problem. We have a reasonable understanding of what kinds of methods are good for establishing what kinds of results and with what (at least rough) degrees of certainty.

There are methods – well thought through – that social scientists learn in the course of their training for constructing a questionnaire, running a randomised controlled trial, conducting an ethnographic study, looking for patterns in large data sets. There is nothing comparably explicit and well thought through about how to use social science knowledge to help predict what will happen when we implement a proposed policy in real, complex situations. Nor is there anything to help us estimate and balance the effectiveness, the evidence, the chances of success, the costs, the benefits, the winners and losers, and the social, moral, political and cultural acceptability of the policy.

To see why this is so difficult think of an analogy: not building social policies but building material technologies. We do not just read off instructions for building a laser – which may ultimately be used to operate on your eyes – from knowledge of basic science. Rather, we piece together a detailed model using heterogeneous knowledge from a mix of physics theories, from various branches of engineering, from experience of how specific materials behave, from the results of trial-and-error, etc. By analogy, building a successful social policy equally requires a mix of heterogeneous kinds of knowledge from radically different sources. Sometimes we are successful at doing this and some experts are very good at it in their own specific areas of expertise. But in both cases – both for material technology and for social technology – there is no well thought through, defensible guidance on how to do it: what are better and worse ways to proceed, what tools and information might be needed, and how to go about getting these. This is true whether we look for general advice that might be helpful across subject areas or advice geared to specific areas or specific kinds of problems. Though we indulge in social technology – indeed we can hardly avoid it – and are convinced that better social science will make for better policies, we do not know how to turn that conviction into a reality.

This presents a real challenge to the hopes for evidence-based policy….(More)”

Be the Change: Saving the World with Citizen Science

Curated on Posted on by Stefaan Verhulst

Book by Chandra Clarke: “It’s so easy to be overwhelmed by everything that is wrong in the world. In 2010, there were 660,000 deaths from malaria. Dire predictions about climate change suggest that sea levels could rise enough to submerge both Los Angeles and London by 2100. Bees are dying, not by the thousands but by the millions.

But what can you do? You’re just one person, right? The good news is that you *can* do something.

It’s called citizen science, and it’s a way for ordinary people like you and me to do real, honest-to-goodness, help-answer-the-big-questions science.

This book introduces you to a world in which it is possible to go on a wildlife survey in a national park, install software on your computer to search for a cure for cancer, have your smartphone log the sound pollution in your city, transcribe ancient Greek scrolls, or sift through the dirt from a site where a mastodon died 11,000 years ago—even if you never finished high school….(More)”

Public services and the new age of data

Curated on Posted on by Stefaan Verhulst

 at Civil Service Quaterly: “Government holds massive amounts of data. The potential in that data for transforming the way government makes policy and delivers public services is equally huge. So, getting data right is the next phase of public service reform. And the UK Government has a strong foundation on which to build this future.

Public services have a long and proud relationship with data. In 1858, more than 50 years before the creation of the Cabinet Office, Florence Nightingale produced her famous ‘Diagram of the causes of mortality in the army in the east’ during the Crimean War. The modern era of statistics in government was born at the height of the Second World War with the creation of the Central Statistical Office in 1941.

How data can help

However, the huge advances we’ve seen in technology mean there are significant new opportunities to use data to improve public services. It can help us:

  • understand what works and what doesn’t, through data science techniques, so we can make better decisions: improving the way government works and saving money
  • change the way that citizens interact with government through new better digital services built on reliable data;.
  • boost the UK economy by opening and sharing better quality data, in a secure and sensitive way, to stimulate new data-based businesses
  • demonstrate a trustworthy approach to data, so citizens know more about the information held about them and how and why it’s being used

In 2011 the Government embarked upon a radical improvement in its digital capability with the creation of the Government Digital Service, and over the last few years we have seen a similar revolution begin on data. Although there is much more to do, in areas like open data, the UK is already seen as world-leading.

…But if government is going to seize this opportunity, it needs to make some changes in:

  • infrastructure – data is too often hard to find, hard to access, and hard to work with; so government is introducing developer-friendly open registers of trusted core data, such as countries and local authorities, and better tools to find and access personal data where appropriate through APIs for transformative digital services;
  • approach – we need the right policies in place to enable us to get the most out of data for citizens and ensure we’re acting appropriately; and the introduction of new legislation on data access will ensure government is doing the right thing – for example, through the data science code of ethics;
  • data science skills – those working in government need the skills to be confident with data; that means recruiting more data scientists, developing data science skills across government, and using those skills on transformative projects….(More)”.

How statistics lost their power – and why we should fear what comes next

Curated on Posted on by Stefaan Verhulst

 in The Guardian: “In theory, statistics should help settle arguments. They ought to provide stable reference points that everyone – no matter what their politics – can agree on. Yet in recent years, divergent levels of trust in statistics has become one of the key schisms that have opened up in western liberal democracies. Shortly before the November presidential election, a study in the US discovered that 68% of Trump supporters distrusted the economic data published by the federal government. In the UK, a research project by Cambridge University and YouGov looking at conspiracy theories discovered that 55% of the population believes that the government “is hiding the truth about the number of immigrants living here”.

Rather than diffusing controversy and polarisation, it seems as if statistics are actually stoking them. Antipathy to statistics has become one of the hallmarks of the populist right, with statisticians and economists chief among the various “experts” that were ostensibly rejected by voters in 2016. Not only are statistics viewed by many as untrustworthy, there appears to be something almost insulting or arrogant about them. Reducing social and economic issues to numerical aggregates and averages seems to violate some people’s sense of political decency.

Nowhere is this more vividly manifest than with immigration. The thinktank British Future has studied how best to win arguments in favour ofimmigration and multiculturalism. One of its main findings is that people often respond warmly to qualitative evidence, such as the stories of individual migrants and photographs of diverse communities. But statistics – especially regarding alleged benefits of migration to Britain’s economy – elicit quite the opposite reaction. People assume that the numbers are manipulated and dislike the elitism of resorting to quantitative evidence. Presented with official estimates of how many immigrants are in the country illegally, a common response is to scoff. Far from increasing support for immigration, British Future found, pointing to its positive effect on GDP can actually make people more hostile to it. GDP itself has come to seem like a Trojan horse for an elitist liberal agenda. Sensing this, politicians have now largely abandoned discussing immigration in economic terms.

All of this presents a serious challenge for liberal democracy. Put bluntly, the British government – its officials, experts, advisers and many of its politicians – does believe that immigration is on balance good for the economy. The British government did believe that Brexit was the wrong choice. The problem is that the government is now engaged in self-censorship, for fear of provoking people further.

This is an unwelcome dilemma. Either the state continues to make claims that it believes to be valid and is accused by sceptics of propaganda, or else, politicians and officials are confined to saying what feels plausible and intuitively true, but may ultimately be inaccurate. Either way, politics becomes mired in accusations of lies and cover-ups.

The declining authority of statistics – and the experts who analyse them – is at the heart of the crisis that has become known as “post-truth” politics. And in this uncertain new world, attitudes towards quantitative expertise have become increasingly divided. From one perspective, grounding politics in statistics is elitist, undemocratic and oblivious to people’s emotional investments in their community and nation. It is just one more way that privileged people in London, Washington DC or Brussels seek to impose their worldview on everybody else. From the opposite perspective, statistics are quite the opposite of elitist. They enable journalists, citizens and politicians to discuss society as a whole, not on the basis of anecdote, sentiment or prejudice, but in ways that can be validated. The alternative to quantitative expertise is less likely to be democracy than an unleashing of tabloid editors and demagogues to provide their own “truth” of what is going on across society.

Is there a way out of this polarisation? Must we simply choose between a politics of facts and one of emotions, or is there another way of looking at this situation?One way is to view statistics through the lens of their history. We need to try and see them for what they are: neither unquestionable truths nor elite conspiracies, but rather as tools designed to simplify the job of government, for better or worse. Viewed historically, we can see what a crucial role statistics have played in our understanding of nation states and their progress. This raises the alarming question of how – if at all – we will continue to have common ideas of society and collective progress, should statistics fall by the wayside….(More).”