Measuring results from open contracting in Ukraine

Curated on Posted on by Stefaan Verhulst

Kathrin Frauscher, Karolis Granickas and Leigh Manasco at the Open Contracting Partnership: “…Ukraine is one of our Showcase and Learning (S&L) projects, and we’ve already shared several stories about the success of Prozorro. Each S&L project tests specific theories of change and use cases. Through the Prozorro platform, Ukraine is revolutionizing procurement by digitizing the process and unlocking data to make it available to citizens, CSOs, government, and business. The theory of change for this S&L project hypothesizes that transparency and the implementation of the Open Contracting Data Standard (OCDS), combined with multi-stakeholder collaboration in the design, promotion and monitoring of the procurement system, is having an impact on value for money, fairness and integrity.

The reform introduced other innovations, including electronic reverse auctions and a centralized procurement database that integrates with private commercial platforms. We co-created a monitoring, evaluation, and learning (MEL) plan with our project partners to quantify and measure specific progress and impact indicators, while understanding that it is hard to attribute impacts to distinct aspects of the reform. The indicators featured in this blog are particularly related to our theory of change.

We are at a crucial moment in this S&L project as our first round of comprehensive MEL baseline and progress data are coming in. It’s a good time to reflect on key takeaways and challenges that arose when defining and analyzing these data, and how we are using them to inform the Prozorro reform.

Openness can result in more competition and competition saves money.

One of the benefits of open contracting appears to be improving market opportunity and efficiency. Market opportunity focuses on companies being able to compete for business on a level playing field.

From January 2015 to March 2017, the average number of bids per tender lot rose by 15%, demonstrating an increase in competition. Even more notable, the average number of unique suppliers during that same time grew by 45% for each procuring entity, meaning that agencies are now procuring from more and more diverse suppliers….

High levels of responsiveness can benefit procuring entities.

Those agencies that leverage their opportunities to interact with business and citizens throughout the contracting cycle, by actively responding to questions and complaints via the online platform, tend to conduct procurement more smoothly, without high levels of amendments or cancellations, than those who don’t. Tenders with a 100% response rate to feedback have a 66% success rate, while those with no response, show a 52% success rate. The portal provides procuring entities with the resources needed to address questions and problems, saving time, effort and money throughout the contracting process.

People are beginning to trust the public procurement process and data more.

According to a survey of 300 entrepreneurs conducted by USAID, most respondents believed that Prozorro significantly (27%) or partially (53%) reduces corruption. Additionally, fewer respondents who participated in procurement said they faced corruption when using the new platform (29%) compared to the old system (54%). These numbers only tell a part of the story, as we do not know what those outside of the procurement system think, but they are a necessary first step towards measuring increased levels of trust for the public procurement process. We will continue looking at trust as one of the proxies for health of an open procurement process.

Citizens are actively seeking out procurement information.

Google search hits grew from 680 in the month of January 2015 to more than 191,000 in the month of February 2017 (tracking 43 related keywords). This means the environment is shifting to one where people are recognizing that this data has value; that there is interest and demand for it. Implementing open contracting processes is just one part of what we want to see happen. We also strive to nurture an environment where open contracting data is seen as something that is worthwhile and necessary.

The newly established www.dozorro.org monitoring platform also shows promising results…..

The main one is feedback loops. We see that procuring entities’ responsiveness to general questions results in better quality procurement. We also see that only one out of three claims (request to a procuring entity to amend, cancel or modify a tender in question) is successfully resolved. In addition, there are some good individual examples, such as the ones in Dnypro and Kiev. While we do not know if these numbers and instances are sufficient for an effective institutional response mechanism, we do know that business and citizens have to trust redress mechanisms before using them. We will continue trying to identify the ideal level of institutional response to secure trust and develop better metrics to capture that….(More)”.

Will Computer Science become a Social Science?

Curated on Posted on by Stefaan Verhulst

Paper by Ingo Scholtes, Markus Strohmaier and Frank Schweitzer: “When Tay – a Twitter chatbot developed by Microsoft – was activated this March, the company was taken by surprise by what Tay had become. Within less than 24 hours of conversation with Twitter users Tay had learned to make racist, anti-semitic and misogynistic statements that have raised eyebrows in the Twitter community and beyond. What had happened? While Microsoft certainly tested the chat bot before release, planning for the reactions and the social environment in which it was deployed proved tremendously difficult. Yet, the Tay Twitter chatbot incident is just one example for the many challenges which arise when embedding algorithms and computing systems into an ever increasing spectrum of social systems. In this viewpoint we argue that, due to the resulting feedback loops by which computing technologies impact social behavior and social behavior feeds back on (learning) computing systems, we face the risk of losing control over the systems that we engineer. The result are unintended consequences that affect both the technical and social dimension of computing systems, and which computer science is currently not well-prepared to address. Highlighting exemplary challenges in core areas like (1) algorithm design, (2) cyber-physical systems, and (3) software engineering, we argue that social aspects must be turned into first-class citizens of our system models. We further highlight that the social sciences, in particular the interdisciplinary field of Computational Social Science [1], provide us with means to quantitatively analyze, model and predict human behavior. As such, a closer integration between computer science and social sciences not only provides social scientists with new ways to understand social phenomena. It also helps us to regain control over the systems that we engineer….(More)”

How Open Data Can Revolutionize a Society in Crisis

Curated on Posted on by Stefaan Verhulst

Beth Noveck at BrinkNews:”…These myriad open data success stories, however, depend on the political will to be transparent and collaborative. There is a looming risk that governments will only post what is expedient and noncontroversial while seeking recognition for their proactive disclosure—a practice increasingly referred to as “open-washing.” Governments of all political stripes refuse to disclose data when they should. The data to be found on government websites is not always the information most in demand by journalists, activists, and researchers.

Especially as political administrations turnover, there is a risk that change will result in a failure to collect and publish important data. These practices will be subject to the vagaries of politics.

The genie should not, however, be put back in the bottle.

Open data appeals to both right and left politically: the former sees open data as a pathway to smaller, more efficient government and the latter sees open data as a tool to pursue more effective social programs. The bipartisan interest in evidence-based approaches to governing should fuel greater demand for access to administrative information of all kinds—including the data that agencies collect about companies, workplaces, the environment, and the world beyond government.

Government data should be open in part because of the ill-effects of secrecy, but also because taxpayers have paid for the collection of this data by government in its role as regulator and researcher.

It is a pragmatic tool to make government and companies more accountable at solving social problems and to help communities make better informed buying decisions. It helps create jobs and generate entrepreneurship. Perhaps of paramount importance, open data can advance civil rights and help us to govern more legitimately and effectively….(More).

Behavioural Insights and Public Policy

Curated on Posted on by Stefaan Verhulst

OECD Report: ““Behavioural insights”, or insights derived from the behavioural and social sciences, including decision making, psychology, cognitive science, neuroscience, organisational and group behaviour, are being applied by governments with the aim of making public policies work better. As their use has become more widespread, however, questions are being raised about their effectiveness as well as their philosophical underpinnings. This report discusses the use and reach of behavioural insights, drawing on a comprehensive collection of over 100 applications across the world and policy sectors, including consumer protection, education, energy, environment, finance, health and safety, labour market policies, public service delivery, taxes and telecommunications. It suggests ways to ensure that this experimental approach can be successfully and sustainably used as a public policy tool…(More)”.

Towards an experimental culture in government: reflections on and from practice

Curated on Posted on by Stefaan Verhulst

 Jesper Christiansen et al at Nesta: “…we share some initial reflections from this work with the hope of prompting a useful discussion about how to articulate the value of experimentation as well as what to consider when strategically planning and doing experiments in government contexts.

Reflection 1: Experimentation as a way of accelerating learning and exploring “the room of the non-obvious”

Governments need to increase their pace and agility in learning about which ideas have the highest potential value-creation and make people’s lives the rationale of governing.

Experimental approaches accelerate learning by systematically testing assumptions and identifying knowledge gaps. What is there to be known about the problem and the function, fit and probability of a suggested solution? Experimentation helps fill these gaps without allocating too much time or resource, and helps governments accelerate the exploration of new potential solution spaces.

This approach is often a key contribution of government policy labs and public sector innovation teams. Units like Lab para la Ciudad in Mexico City, Alberta Co-Lab in Canada, Behavioural insights and Design Unit in Singapore, MindLab in Denmark and Policy Lab in the UK are specifically set up to promote, develop and/or embed experimental approaches and accelerate user-centred learning in different levels of government.

In addition, creating a culture of experimentation extends the policy options available by creating a political environment to test non-linear approaches to wicked problems. In our training, we often distinguish between “the room of the obvious” and the “room of the non-obvious”. By designing portfolios of experiments that include – by deliberate design – the testing of at least some non-linear, non-obvious solutions, government officials can move beyond the automatic mode of many policy interventions and explore the “room of the non-obvious” in a safe-to-fail context (think barbers to prevent suicides or dental insurance to prevent deforestation).

Reflection 2: Experimentation as a way of turning uncertainty into risk

In everyday language, uncertainty and risk are two notions that are often used interchangeably; yet they are very different concepts. Take, for example, the implementation of a solution. Risk is articulated in terms of the probability that the solution will generate a certain outcome. It is measurable (e.g. based on existing data there is X per cent chance of success, or X per cent chance of failure) and qualitative risk factors can be developed and described.

Uncertainty, on the other hand, is a situation where there is a lack of probabilities. There is no prior data on how the solution might perform; future outcomes are not known, and can therefore not be measured. The chance of success can be 0 per cent, 100 per cent, or anything in between (see table below).

There is often talk of the need for government to become more of a ‘risk taker’, or to become better at ‘managing risk’. But as Marco Steinberg, founder of strategic design practice Snowcone & Haystack, recently reminded us, risk-management – where probabilities are known – is actually something that governments do quite well. Issues arise when governments’ legacies can’t shape current solutions: when governments have to deal with the uncertainty of complex challenges by adapting or creating entirely new service systems to fit the needs of our time.

For example, when transforming a health system to fit the needs of our time, little can be known about the probabilities in terms of what might work when establishing a new practice. Or when transforming a social care system to accommodate the lives of vulnerable families, entirely new concepts for solutions need to be explored. “If you don’t have a map showing the way, you have to write one yourself,” as Sam Rye puts it in his inspirational example on the use of experimental cards at The Labs Wananga….

Reflection 3: Experimentation as a way to reframe failure and KPIs

Reflection 4: Experimentation on a continuum between exploration and validation

Reflection 5: Experimentation as cultural change…(More)”.

Technology Use, Exposure to Natural Hazards, and Being Digitally Invisible: Implications for Policy Analytics

Curated on Posted on by Stefaan Verhulst

Justin Longo, Evan Kuras, Holly Smith, David M. Hondula, and Erik Johnston in Special Issue of Policy & Internet on Data and Policy: “Policy analytics combines new data sources, such as from mobile smartphones, Internet of Everything devices, and electronic payment cards, with new data analytics techniques for informing and directing public policy. However, those who do not own these devices may be rendered digitally invisible if data from their daily actions are not captured. We explore the digitally invisible through an exploratory study of homeless individuals in Phoenix, Arizona, in the context of extreme heat exposure. Ten homeless research participants carried a temperature-sensing device during an extreme heat week, with their individually experienced temperatures (IETs) compared to outdoor ambient temperatures. A nonhomeless, digitally connected sample of 10 university students was also observed, with their IETs analyzed in the same way. Surveys of participants complement the temperature measures. We found that homeless individuals and university students interact differently with the physical environment, experiencing substantial differences in individual temperatures relative to outdoor conditions, potentially leading to differentiated health risks and outcomes. They also interact differently with technology, with the homeless having fewer opportunities to benefit from digital services and lower likelihood to generate digital data that might influence policy analytics. Failing to account for these differences may result in biased policy analytics and misdirected policy interventions….(More)”

Drones used in fight against plastic pollution on UK beaches

Curated on Posted on by Stefaan Verhulst

Tom Cheshire at SkyNews: “On a beach in Kent, Peter Koehler and Ellie Mackay are teaching a drone how to see.

Their project, Plastic Tide, aims to create software that will automatically pick out the pieces of plastic that wash up here on the shingle.

“One of the major challenges we face is that we can only account for 1% of those millions and millions of tonnes [of plastic] that are coming into our oceans every year,” Mr Koehler told Sky News.

“So the question is, where is that 99% going?”

He added: “We just don’t know. It could be in the water, it could be in wildlife, or it could be on beaches.

“And so what the Plastic Tide is doing, it’s using drone technology to image beaches in a way that’s never been done before, on a scientific scale. So that you can build up a picture of how much of that missing 99% is washing up on our beaches.”

Mr Koehler and Ms Mackay use an off-the-shelf drone. They select the area of beach they want to film and a free app comes up with a survey pattern flight path – the drone moves systematically up and down the beach as if it were ploughing it.

The images taken are then uploaded to a scientific crowd-sourcing platform called Zooniverse.

Anyone can log on, look at the images and tag bits of plastic in them.

That will build up a huge amount of data, which will be used to train a machine-learning algorithm to spot plastic by itself – no humans required.

The hope is that, eventually, anyone will be able to fly a drone, take images, then computers will automatically scan the images and determine the levels of plastic pollution on a beach.

This summer, Mr Koehler and Ms Mackay will travel all 3,200 miles of the UK coastline, surveying beaches….

There’s no new, groundbreaking piece of technology here.

Just off-the-shelf components, smart thinking and a desire to put a small dent in a huge problem….(More)”

From disaster planning to conservation: mobile phones as a new tracking tool

Curated on Posted on by Stefaan Verhulst

, , and  in The Conversation: “We can learn a lot about things by studying how they move through the world and interact with the environment.

In the past, for example, it was possible to study the mobility of people within the United States by monitoring things such as the movement of banknotes. Today we can use something that is much more global and widely available than US cash.

Mobile phones have almost totally infiltrated human society, with the number estimated at more than 7 billion in 2014. Ownership of mobile phones continues to grow, even in some of the poorest countries.

Many of those phones are geolocated, continuously providing the geographic location of the user, so effectively acting as tracking devices for human populations.

As biologists, our understanding of animals has been transformed over the past four decades by our ability to track their movements and behaviour.

We were interested to see what we can learn from the use of mobile phones tracking, as we show in a study published this month in Trends in Ecology and Evolution.

It’s now possible to use the mobile phone data to gain a better insight into human movement under certain conditions.

For example, mobile phone data was used to study the movement of people during the 2010 earthquake and subsequent cholera outbreak in Haiti, and Hurricane Sandy in the United States in 2012.

It was interesting to note that the human reaction to escape from certain events we found was close to that of some animal groups, such as birds and fish, when fleeing from attack.

Such studies can help predict how people will respond in the future to any emergencies, and help to improve the delivery of any aid or disaster relief.

Conservation with mobile phones

The detail, immediacy and sheer volume of data from mobile phones also offers innovative ways to monitor and possibly solve some of the most pressing conservation problems that animal populations now face.

For example, geolocated phones are changing the way we tackle the crisis of illegal wildlife trade.

Not only is it a major driver of species extinctions, but the human cost is high with more than 1,000 wildlife rangers killed in the line of duty over a ten-year period.

In India, rangers on the front line use a smartphone app to monitor movements and record sightings of targeted species, such as tigers, and to report suspicious activity.

In Africa, mobile phones help rangers collate social and environmental information about reserves and encounter rates with animals killed by poachers….(More)”

Analytics Tools Could Be the Key to Effective Message-Driven Nudging

Curated on Posted on by Stefaan Verhulst

 in Government Technology: “Appealing to the nuances of the human mind has been a feature of effective governance for as long as governance has existed, appearing prominently in the prescriptions of every great political theorist from Plato to Machiavelli. The most recent and informed iteration of this practice is nudging: leveraging insights about how humans think from behavioral science to create initiatives that encourage desirable behaviors.

Public officials nudge in many ways. Some seek to modify people’s behavior by changing the environments in which they make decisions, for instance moving vegetables to the front of a grocery store to promote healthy eating. Others try to make desirable behaviors easier, like streamlining a city website to make it simpler to sign up for a service. Still others use prompts like email reminders of a deadline to receive a free checkup to nudge people to act wisely by providing useful information.

Thus far, examples of the third type of nudging — direct messaging that prompts behavior — have been decidedly low tech. Typical initiatives have included sending behaviorally informed letters to residents who have not complied with a city code or mailing out postcard reminders to renew license plates. Governments have been attracted to these initiatives for their low cost and proven effectiveness.

While these low-tech nudges should certainly continue, cities’ recent adoption of tools that can mine and analyze data instantaneously has the potential to greatly increase the scope and effectiveness of message-driven nudging.

For one, using Internet of Things (IoT) ecosystems, cities can provide residents with real-time information so that they may make better-informed decisions. For example, cities could connect traffic sensors to messaging systems and send subscribers text messages at times of high congestion, encouraging them to take public transportation. This real-time information, paired with other nudges, could increase transit use, easing traffic and bettering the environment…
Instantaneous data-mining tools may also prove useful for nudging citizens in real time, at the moments they are most likely to partake in detrimental behavior. Tools like machine learning can analyze users’ behavior and determine if they are likely to make a suboptimal choice, like leaving the website for a city service without enrolling. Using clickstream data, the site could determine if a user is likely to leave and deliver a nudge, for example sending a message explaining that most residents enroll in the service. This strategy provides another layer of nudging, catching residents who may have been influenced by an initial nudge — like a reminder to sign up for a service or streamlined website — but may need an extra prod to follow through….(More)”

Closing the Loop

Curated on Posted on by Stefaan Verhulst

A Conversation With Chris Anderson: “If we could measure the world, how would we manage it differently? This is a question we’ve been asking ourselves in the digital realm since the birth of the Internet. Our digital lives—clicks, histories, and cookies—can now be measured beautifully. The feedback loop is complete; it’s called closing the loop. As you know, we can only manage what we can measure. We’re now measuring on-screen activity beautifully, but most of the world is not on screens.

As we get better and better at measuring the world—wearables, Internet of Things, cars, satellites, drones, sensors—we are going to be able to close the loop in industry, agriculture, and the environment. We’re going to start to find out what the consequences of our actions are and, presumably, we’ll take smarter actions as a result. This journey with the Internet that we started more than twenty years ago is now extending to the physical world. Every industry is going to have to ask the same questions: What do we want to measure? What do we do with that data? How can we manage things differently once we have that data? This notion of closing the loop everywhere is perhaps the biggest endeavor of our age.

Closing the loop is a phrase used in robotics. Open-loop systems are when you take an action and you can’t measure the results—there’s no feedback. Closed-loop systems are when you take an action, you measure the results, and you change your action accordingly. Systems with closed loops have feedback loops; they self-adjust and quickly stabilize in optimal conditions. Systems with open loops overshoot; they miss it entirely…(More)”