international development

Workplace innovation in the public sector

Curated on May 11, 2016August 15, 2018 by Stefaan Verhulst

Eurofound: “Innovative organisational practices in the workplace, which aim to make best use of human capital, are traditionally associated with the private sector. The nature of the public sector activities makes it more difficult to identify these types of internal innovation in publicly funded organisations.

It is widely thought that public sector organisations are neither dynamic nor creative and are typified by a high degree of inertia. Yet the necessity of innovation ought not to be dismissed. The public sector represents a quarter of total EU employment, and it is of critical importance as a provider and regulator of services. Improving how it performs has a knock-on effect not only for private sector growth but also for citizens’ satisfaction. Ultimately, this improves governance itself.

So how can innovative organisation practices help in dealing with the challenges faced by the public sector? Eurofound, as part of a project on workplace innovation in European companies, carried out case studies of both private and public sector organisations. The findings show a number of interesting practices and processes used.

Employee participation

The case studies from the public sector, some of which are described below, demonstrate the central role of employee participation in the implementation of workplace innovation and its impacts on organisation and employees. They indicate that innovative practices have resulted in enhanced organisational performance and quality of working life.

It is widely thought that changes in the public sector are initiated as a response to government policies. This is often true, but workplace innovation may also be introduced as a result of well-designed initiatives driven by external pressures (such as the need for a more competitive public service) or internal pressures (such as a need to update the skills map to better serve the public).

Case study findings

The state-owned Lithuanian energy company Lietuvos Energijos Gamyba (140 KB PDF) encourages employee participation by providing a structured framework for all employees to propose improvements. This has required a change in managerial approach and has spread a sense of ownership horizontally and vertically in the company. The Polish public transport company Jarosław City Transport (191 KB PDF), when faced with serious financial stability challenges, as well as implementing operational changes, set up ways for employees’ voices to be heard, which enabled a contributory dialogue and strengthened partnerships. Consultation, development of mutual trust, and common involvement ensured an effective combination of top-down and bottom-up initiatives.

The Lithuanian Post, AB Lietuvos Pastas (136 KB PDF) experienced a major organisation transformation in 2010 to improve efficiency and quality of service. Through a programme of ‘Loyalty day’ monthly visits, both top and middle management of the central administration visit any part of the company and work with colleagues in other units. Under budgetary pressure to ‘earn their money’, the Danish Vej and Park Bornholm (142 KB PDF) construction services in roads, parks and forests had to find innovative solutions to deal with a merger and privatisation. Their intervention had the characteristics of workplace partnership with a new set of organisational values set from the bottom up. Self-managing teams are essential for the operation of the company.

The world of education has provided new structures that provide better outcomes for students. The South West University of Bulgaria (214 KB PDF) also operates small self-managing teams responsible for employee scheduling. Weekly round-tables encourage participation in collectively finding solutions, creating a more effective environment in which to respond to the competitive demands of education provision.

In Poland, an initiative by the Pomeranian Library (185 KB PDF) improved employee–management dialogue and communication through increased participation. The initiative is a response to the new frameworks for open access to knowledge for users, with the library mirroring the user experience through its own work practices.

Through new dialogue, government advisory bodies have also developed employee-led improvement. Breaking away from a traditional hierarchy is considered important in achieving a more flexible work organisation. Under considerable pressure, the top-heavy management of the British Geological Survey (89 KB PDF) now operates a flexible matrix that promotes innovative and entrepreneurial ways of working. And in Germany, Niersverband (138 KB PDF), a publicly owned water-management company innovated through training, learning, reflection partnerships and workplace partnerships. New occupational profiles were developed to meet external demands. Based on dialogue concerning workplace experiences and competences, employees acquired new qualifications that allowed the company to be more competitive.

In the Funen Village Museum in Odense, Denmark, (143 KB PDF) innovation came about at the request of staff looking for more flexibility in how they work. Formerly most of their work was maintenance tasks, but now they can now engage more with visitors. Control of schedules has moved to the team rather than being the responsibility of a single manager. As a result, museum employees are now hosts as well as craftspeople. They no longer feel ‘forgotten’ and are happier in their work….(More)”

The report Workplace innovation in European companies provides a full analysis of the case studies.

The 51 case studies and the list of companies (PDF 119 KB) the case studies are based on are available for download.

Fifty Shades of Open

Curated on May 10, 2016August 3, 2018 by Stefaan Verhulst

Jeffrey Pomerantz and Robin Peek at First Monday: “Open source. Open access. Open society. Open knowledge. Open government. Even open food. Until quite recently, the word “open” had a fairly constant meaning. The over-use of the word “open” has led to its meaning becoming increasingly ambiguous. This presents a critical problem for this important word, as ambiguity leads to misinterpretation.

“Open” has been applied to a wide variety of words to create new terms, some of which make sense, and some not so much. When we started writing this essay, we thought our working title was simply amusing. But the working title became the actual title, as we found that there are at least 50 different terms in which the word “open” is used, encompassing nearly as many different criteria for openness. In this essay we will attempt to make sense of this open season on the word “open.”

Opening the door on open

The word “open” is, perhaps unsurprisingly, a very old one in the English language, harking back to Early Old English. Unlike some words in English, the definition of “open” has changed very little in the intervening thousand-plus years: the earliest recorded uses of the word are completely consistent with its modern usage as an adjective, indicating a passage through or an access into something (Oxford English Dictionary, 2016).

This meaning leads to the development in the fifteenth century of the phrases “open house,” meaning an establishment in which all are welcome, and “open air,” meaning unenclosed outdoor spaces. One such unenclosed outdoor space that figured large in the fifteenth century, and continues to do so today, is the Commons (Hardin, 1968): land or other resources that are not privately owned, but are available for use to all members of a community. The word “open” in these phrases indicates that all have access to a shared resource. All are welcome to visit an open house, but not to move in; all are welcome to walk in the open air or graze their sheep on the Commons, but not to fence the Commons as part of their backyard. (And the moment at which Commons land ceases to be open is precisely the moment it is fenced by an owner, which is in fact what happened in Great Britain during the Enclosure movement of the sixteenth through eighteenth centuries.)

Running against the grain of this cultural movement to enclosure, the nineteenth century saw the circulating library become the norm — rather than libraries in which massive tomes were literally chained to desks. The interpretation of the word “open” to mean a shared resource to which all had access, fit neatly into the philosophy of the modern library movement of the nineteenth century. The phrases “open shelves” and “open stacks” emerged at this time, referring to resources that were directly available to library users, without necessarily requiring intervention by a librarian. Naturally, however, not all library resources were made openly available, nor are they even today. Furthermore, resources are made openly available with the understanding that, like Commons land, they must be shared: library resources have a due date.

The twentieth century saw an increase in the use of the word “open,” as well as a hint of the confusion that was to come about the interpretation of the word. The term “open society” was coined prior to World War I, to indicate a society tolerant of religious diversity. The “open skies” policy enables a nation to allow other nations’ commercial aviation to fly through its airspace — though, importantly, without giving up control of its airspace. The Open University was founded in the United Kingdom in 1969, to provide a university education to all, with no formal entry requirements. The meaning of the word “open” is quite different across these three terms — or perhaps it would be more accurate to say that these terms use different shadings of the word.

But it has been the twenty-first century that has seen the most dramatic increase in the number of terms that use “open.” The story of this explosion in the use of the word “open” begins, however, with a different word entirely: the word “free.”….

Introduction
Opening the door on open
Speech, beer, and puppies
Open means rights
Open means access
Open means use
Open means transparent
Open means participatory
Open means enabling openness
Open means philosophically aligned with open principles
Openwashing and its discontents
Conclusion“

Yelp, Google Hold Pointers to Fix Governments

Curated on May 10, 2016August 3, 2018 by Stefaan Verhulst

Christopher Mims at the Wall Street Journal: “When Kaspar Korjus was born, he was given a number before he was given a name, as are all babies in Estonia. “My name is 38712012796, which I got before my name of Kaspar,”says Mr. Korjus.

In Estonia, much of life—voting, digital signatures, prescriptions, taxes, banktransactions—is conducted with this number. The resulting services aren’t just more convenient, they are demonstrably better. It takes an Estonian three minutes to file his or her taxes.

Americans are unlikely to accept a unified national ID system. But Estonia offers an example of the kind of innovation possible around government services, a competitive factor for modern nations.

The former Soviet republic—with a population of 1.3 million, roughly the size of SanDiego—is regularly cited as a world leader in e-governance. At base, e-governance is about making government function as well as private enterprise, mostly by adopting the same information-technology infrastructure and management techniques as the world’s most technologically savvy corporations.

It isn’t that Estonia devotes more people to the problem—it took only 60 to build the identity system. It is that the country’s leaders are willing to empower those engineers.“There is a need for politicians to not only show leadership but also there is a need to take risks,” says Estonia’s prime minister, Taavi Rõivas.

In the U.S., Matt Lira, senior adviser for House Majority Leader Kevin McCarthy, says the gap between the government’s information technology and the private sector’s has grown larger than ever. Americans want to access government services—paying property taxes or renewing a driver’s license—as easily as they look up a restaurant on Yelp or a business on Alphabet’s Google, says Neil Kleiman, a professor of policy at New York University who collaborates with cities in this subject area.

The government is unlikely to catch up soon. The Government Accountability Office last year estimated that about 25% of the federal government’s 738 major IT investments—projected to cost a total of $42 billion—were in danger of significant delays or cost overruns.

One reason for such overruns is the government’s reliance on big, monolithic projects based on proposal documents that can run to hundreds of pages. It is an approach to software development that is at least 20 years out of date. Modern development emphasizes small chunks of code accomplished in sprints and delivered to end users quickly so that problems can be identified and corrected.

Two years ago, the Obama administration devised a novel way to address these issues:assembling a crack team of coders and project managers from the likes of Google,Amazon.com and Microsoft and assigning them to big government boondoggles to help existing IT staff run more like the private sector. Known as 18F, this organization and its sister group, the U.S. Digital Service, are set to hit 500 staffers by the end of 2016….(More)”

‘Big data’ was supposed to fix education. It didn’t. It’s time for ‘small data’

Curated on May 10, 2016August 3, 2018 by Stefaan Verhulst

Pasi Sahlberg and Jonathan Hasak in the Washington Post: “One thing that distinguishes schools in the United States from schools around the world is how data walls, which typically reflect standardized test results, decorate hallways and teacher lounges. Green, yellow, and red colors indicate levels of performance of students and classrooms. For serious reformers, this is the type of transparency that reveals more data about schools and is seen as part of the solution to how to conduct effective school improvement. These data sets, however, often don’t spark insight about teaching and learning in classrooms; they are based on analytics and statistics, not on emotions and relationships that drive learning in schools. They also report outputs and outcomes, not the impacts of learning on the lives and minds of learners….

If you are a leader of any modern education system, you probably care a lot about collecting, analyzing, storing, and communicating massive amounts of information about your schools, teachers, and students based on these data sets. This information is “big data,” a term that first appeared around 2000, which refers to data sets that are so large and complex that processing them by conventional data processing applications isn’t possible. Two decades ago, the type of data education management systems processed were input factors of education system, such as student enrollments, teacher characteristics, or education expenditures handled by education department’s statistical officer. Today, however, big data covers a range of indicators about teaching and learning processes, and increasingly reports on student achievement trends over time.

With the outpouring of data, international organizations continue to build regional and global data banks. Whether it’s the United Nations, the World Bank, the European Commission, or the Organization for Economic Cooperation and Development, today’s international reformers are collecting and handling more data about human development than before. Beyond government agencies, there are global education and consulting enterprises like Pearson and McKinsey that see business opportunities in big data markets.

Among the best known today is the OECD’s Program for International Student Assessment (PISA), which measures reading, mathematical, and scientific literacy of 15-year-olds around the world. OECD now also administers an Education GPS, or a global positioning system, that aims to tell policymakers where their education systems place in a global grid and how to move to desired destinations. OECD has clearly become a world leader in the big data movement in education.

Despite all this new information and benefits that come with it, there are clear handicaps in how big data has been used in education reforms. In fact, pundits and policymakers often forget that Big data, at best, only reveals correlations between variables in education, not causality. As any introduction to statistics course will tell you, correlation does not imply causation….
We believe that it is becoming evident that big data alone won’t be able to fix education systems. Decision-makers need to gain a better understanding of what good teaching is and how it leads to better learning in schools. This is where information about details, relationships and narratives in schools become important. These are what Martin Lindstrom calls “small data”: small clues that uncover huge trends. In education, these small clues are often hidden in the invisible fabric of schools. Understanding this fabric must become a priority for improving education.

To be sure, there is not one right way to gather small data in education. Perhaps the most important next step is to realize the limitations of current big data-driven policies and practices. Too strong reliance on externally collected data may be misleading in policy-making. This is an example of what small data look like in practice:

It reduces census-based national student assessments to the necessary minimum and transfer saved resources to enhance the quality of formative assessments in schools and teacher education on other alternative assessment methods. Evidence shows that formative and other school-based assessments are much more likely to improve quality of education than conventional standardized tests.
It strengthens collective autonomy of schools by giving teachers more independence from bureaucracy and investing in teamwork in schools. This would enhance social capital that is proved to be critical aspects of building trust within education and enhancing student learning.
It empowers students by involving them in assessing and reflecting their own learning and then incorporating that information into collective human judgment about teaching and learning (supported by national big data). Because there are different ways students can be smart in schools, no one way of measuring student achievement will reveal success. Students’ voices about their own growth may be those tiny clues that can uncover important trends of improving learning.

Edwards Deming once said that “without data you are another person with an opinion.” But Deming couldn’t have imagined the size and speed of data systems we have today….(More)”

A Framework for Understanding Data Risk

Curated on May 5, 2016August 3, 2018 by Stefaan Verhulst

Sarah Telford and Stefaan G. Verhulst at Understanding Risk Forum: “….In creating the policy, OCHA partnered with the NYU Governance Lab (GovLab) and Leiden University to understand the policy and privacy landscape, best practices of partner organizations, and how to assess the data it manages in terms of potential harm to people.

We seek to share our findings with the UR community to get feedback and start a conversation around the risk to using certain types of data in humanitarian and development efforts and when understanding risk.

What is High-Risk Data?

High-risk data is generally understood as data that includes attributes about individuals. This is commonly referred to as PII or personally identifiable information. Data can also create risk when it identifies communities or demographics within a group and ties them to a place (i.e., women of a certain age group in a specific location). The risk comes when this type of data is collected and shared without proper authorization from the individual or the organization acting as the data steward; or when the data is being used for purposes other than what was initially stated during collection.

The potential harms of inappropriately collecting, storing or sharing personal data can affect individuals and communities that may feel exploited or vulnerable as the result of how data is used. This became apparent during the Ebola outbreak of 2014, when a number of data projects were implemented without appropriate risk management measures. One notable example was the collection and use of aggregated call data records (CDRs) to monitor the spread of Ebola, which not only had limited success in controlling the virus, but also compromised the personal information of those in Ebola-affected countries. (See Ebola: A Big Data Disaster).

A Data-Risk Framework

Regardless of an organization’s data requirements, it is useful to think through the potential risks and harms for its collection, storage and use. Together with the Harvard Humanitarian Initiative, we have set up a four-step data risk process that includes doing an assessment and inventory, understanding risks and harms, and taking measures to counter them.

Assessment – The first step is to understand the context within which the data is being generated and shared. The key questions to ask include: What is the anticipated benefit of using the data? Who has access to the data? What constitutes the actionable information for a potential perpetrator? What could set off the threat to the data being used inappropriately?

Data Inventory – The second step is to take inventory of the data and how it is being stored. Key questions include: Where is the data – is it stored locally or hosted by a third party? Where could the data be housed later? Who might gain access to the data in the future? How will we know – is data access being monitored?

Risks and Harms – The next step is to identify potential ways in which risk might materialize. Thinking through various risk-producing scenarios will help prepare staff for incidents. Examples of risks include: your organization’s data being correlated with other data sources to expose individuals; your organization’s raw data being publicly released; and/or your organization’s data system being maliciously breached.

Counter-Measures – The next step is to determine what measures would prevent risk from materializing. Methods and tools include developing data handling policies, implementing access controls to the data, and training staff on how to use data responsibly….(More)

Impact of open government: Mapping the research landscape

Curated on May 4, 2016July 19, 2019 by Stefaan Verhulst

Stephen Davenport at OGP Blog: “Government reformers and development practitioners in the open government space are experiencing the heady times associated with a newly-defined agenda. The opportunity for innovation and positive change can at times feel boundless. Yet, working in a nascent field also means a relative lack of “proven” tools and solutions (to such extent as they ever exist in development).

More research on the potential for open government initiatives to improve lives is well underway. However, keeping up with the rapidly evolving landscape of ongoing research, emerging hypotheses, and high-priority knowledge gaps has been a challenge, even as investment in open government activities has accelerated. This becomes increasing important as we gather to talk progress at the OGP Africa Regional Meeting 2016(link is external) and GIFT(link is external) consultations in Cape Town next week (May 4-6) .

Who’s doing what?
To advance the state of play, a new report commissioned by the World Bank, “Open Government Impact and Outcomes: Mapping the Landscape of Ongoing Research”(link is external), categorizes and takes stock of existing research. The report represents the first output of a newly-formed consortium (link is external) that aims to generate practical, evidence-based guidance for open government stakeholders, building on and complementing the work of organizations across the academic-practitioner spectrum.

The mapping exercise led to the creation of an interactive platform (link is external) with detailed information on how to find out more about each of the research projects covered, organized by a new typology for open government interventions. The inventory is limited in scope given practical and other considerations. It includes only projects that are currently underway. It is meant to be a forward-looking overview, rather than a literature review–and are relatively large and international in nature.

Charting a course: How can the World Bank add value?
The scope for increasing the open government knowledge base remains vast. The report suggests that, given its role as a lender, convener, and a policy advisor the World Bank is well positioned to complement and support existing research in a number of ways, such as:

Taking a demand-driven approach, focusing on specific areas where it can identify lessons for stakeholders seeking to turn open government enthusiasm into tangible results.
Linking researchers with governments and practitioners to study specific areas of interest (in particular, access to information and social accountability interventions).
Evaluating the impact of open government reforms against baseline data that may not be public yet, but that are accessible to the World Bank.
Contributing to a better understanding of the role and impact of ICTs through work like the recently-published study (link is external)that examines the relationship between digital citizen engagement and government responsiveness.
Ensuring that World Bank loans and projects are conceived as opportunities for knowledge generation, while incorporating the most relevant and up-to-date evidence on what works in different contexts.
Leveraging its involvement in the Open Government Partnership to help stakeholders make evidence-based reform commitments….(More)

Four Steps to Enhanced Crowdsourcing

Curated on May 3, 2016August 3, 2018 by Stefaan Verhulst

Kendra L. Smith and Lindsey Collins at Planetizen: “Over the past decade, crowdsourcing has grown to significance through crowdfunding, crowd collaboration, crowd voting, and crowd labor. The idea behind crowdsourcing is simple: decentralize decision-making by utilizing large groups of people to assist with solving problems, generating ideas, funding, generating data, and making decisions. We have seen crowdsourcing used in both the private and public sectors. In a previous article, “Empowered Design, By ‘the Crowd,'” we discuss the significant role crowdsourcing can play in urban planning through citizen engagement.

Crowdsourcing in the public sector represents a more inclusive form of governance that incorporates a multi-stakeholder approach; it goes beyond regular forms of community engagement and allows citizens to participate in decision-making. When citizens help inform decision-making, new opportunities are created for cities—opportunities that are beginning to unfold for planners. However, despite its obvious utility, planners underutilize crowdsourcing. A key reason for its underuse can be attributed to a lack of credibility and accountability in crowdsourcing endeavors.

Crowdsourcing credibility speaks to the capacity to trust a source and discern whether information is, indeed, true. While it can be difficult to know if any information is definitively true, indicators of fact or truth include where information was collected, how information was collected, and how rigorously it was fact-checking or peer reviewed. However, in the digital universe of today, individuals can make a habit of posting inaccurate, salacious, malicious, and flat-out false information. The realities of contemporary media make it more difficult to trust crowdsourced information for decision-making, especially for the public sector, where the use of inaccurate information can impact the lives of many and the trajectory of a city. As a result, there is a need to establish accountability measures to enhance crowdsourcing in urban planning.

Establishing Accountability Measures

For urban planners considering crowdsourcing, establishing a system of accountability measures might seem like more effort than it is worth. However, that is simply not true. Recent evidence has proven traditional community engagement (e.g., town halls, forums, city council meetings) is lower than ever. Current engagement also tends to focus on problems in the community rather than the development of the community. Crowdsourcing offers new opportunities for ongoing and sustainable engagement with the community. It can be simple as well.

The following four methods can be used separately or together (we hope they are used together) to help establish accountability and credibility in the crowdsourcing process:

Agenda setting
Growing a crowdsourcing community
Facilitators/subject matter experts (SME)
Microtasking

In addition to boosting credibility, building a framework of accountability measures can help planners and crowdsourcing communities clearly define their work, engage the community, sustain community engagement, acquire help with tasks, obtain diverse opinions, and become more inclusive….(More)”

Supply and demand of open data in Mexico: A diagnostic report on the government’s new open data portal

Curated on May 3, 2016August 3, 2018 by Stefaan Verhulst

Report by Juan Ortiz Freuler: “Following a promising and already well-established trend, in February 2014 the Oﬃce of the President of Mexico launched its open data portal (datos.gob.mx). This diagnostic –carried out between July and September of 2015- is designed to brief international donors and stakeholders such as members of the Open Government Partnership Steering Committee, provides the reader with contextual information to understand the state of supply and demand for open data from the portal, and the speciﬁc challenges the mexican government is facing in its quest to implement the policy. The insights oﬀered through data processing and interviews with key stakeholders indicate the need to promote: i) A sense of ownership of datos.gob.mx by the user community, but particularly by the oﬃcials in charge of implementing the policy within each government unit; ii) The development of tools and mechanisms to increase the quality of the data provided through the portal; and iii) Civic hacking of the portal to promote innovation, and a sense of appropriation that would increase the policy’s long-term resilience to partisan and leadership change….(More)”

See also Underlying data: http://bit.ly/dataMXEng1; Spanish here: http://bit.ly/DataMxCastell; Underlying data:http://bit.ly/dataMX2

A Political Economy Framework for the Urban Data Revolution

Curated on April 30, 2016August 3, 2018 by Stefaan Verhulst

Research Report by Ben Edwards, Solomon Greene and G. Thomas Kingsley: “With cities growing rapidly throughout much of the developing world, the global development community increasingly recognizes the need to build the capacities of local leaders to analyze and apply data to improve urban policymaking and service delivery. Civil society leaders, development advocates, and local governments are calling for an “urban data revolution” to accompany the new UN Sustainable Development Goals (SDGs), a revolution that would provide city leaders new tools and resources for data-driven governance. The need for improved data and analytic capacity in rapidly growing cities is clear, as is the exponential increase in the volume and types of data available for policymaking. However, the institutional arrangements that will allow city leaders to use data effectively remain incompletely theorized and poorly articulated.

This paper begins to fill that gap with a political economy framework that introduces three new concepts: permission, incentive, and institutionalization. We argue that without addressing the permission constraints and competing incentives that local government officials face in using data, investments in improved data collection at the local level will fail to achieve smarter urban policies. Granting permission and aligning incentives are also necessary to institutionalize data-driven governance at the local level and create a culture of evidence-based decisionmaking that outlives individual political administrations. Lastly, we suggest how the SDGs could support a truly transformative urban data revolution in which city leaders are empowered and incentivized to use data to drive decisionmaking for sustainable development…(More)”