Open innovation in the public sector


Sabrina Diaz Rato in OpenDemocracy: “For some years now, we have been witnessing the emergence of relational, cross-over, participative power. This is the territory that gives technopolitics its meaning and prominence, the basis on which a new vision of democracy – more open, more direct, more interactive – is being developed and embraced. It is a framework that overcomes the closed architecture on which the praxis of governance (closed, hierarchical, one-way) have been cemented in almost all areas. The series The ecosystem of open democracy explores the different aspects of this ongoing transformation….

How can innovation contribute to building an open democracy? The answer is summed up in these ten connectors of innovation.

  1. placing innovation and collective intelligence at the center of public management strategies,
  2. aligning all government areas with clearly-defined goals on associative platforms,
  3. shifting the frontiers of knowledge and action from the institutions to public deliberation on local challenges,
  4. establishing leadership roles, in a language that everyone can easily understand, to organize and plan the wealth of information coming out of citizens’ ideas and to engage those involved in the sustainability of the projects,
  5. mapping the ecosystem and establishing dynamic relations with internal and, particularly, external agents: the citizens,
  6. systematizing the accumulation of information and the creative processes, while communicating progress and giving feedback to the whole community,
  7. preparing society as a whole to experience a new form of governance of the common good,
  8. cooperating with universities, research centers and entrepreneurs in establishing reward mechanisms,
  9. aligning people, technologies, institutions and the narrative with the new urban habits, especially those related to environmental sustainability and public services,
  10. creating education and training programs in tune with the new skills of the 21st century,
  11. building incubation spaces for startups responding to local challenges,
  12. inviting venture capital to generate a satisfactory mix of open innovation, inclusive development policies and local productivity.

Two items in this list are probably the determining factors of any effective innovation process. The first has to do with the correct decision on the mechanisms through which we have pushed the boundaries outwards, so as to bring citizen ideas into the design and co-creation of solutions. This is not an easy task, because it requires a shared organizational mentality on previously non-existent patterns of cooperation, which must now be sustained through dialog and operational dynamics aimed at solving problems defined by external actors – not just any problem.

Another key aspect of the process, related to the breaking down of the institutional barriers that surround and condition action frameworks, is the revaluation of a central figure that we have not yet mentioned here: the policy makers. They are not exactly political leaders or public officials. They are not innovators either. They are the ones within Public Administration who possess highly valuable management skills and knowledge, but who are constantly colliding against the glittering institutional constellations that no longer work….(More)”

From big data to smart data: FDA’s INFORMED initiative


Sean KhozinGeoffrey Kim & Richard Pazdur in Nature: “….Recent advances in our understanding of disease mechanisms have led to the development of new drugs that are enabling precision medicine. For example, the co-development of kinase inhibitors that target ‘driver mutations’ in metastatic non-small-cell lung cancer (NSCLC) with companion diagnostics has led to substantial improvements in the treatment of some patients. However, growing evidence suggests that most patients with metastatic NSCLC and other advanced cancers may not have tumours with single driver mutations. Furthermore, the generation of clinical evidence in genomically diverse and geographically dispersed groups of patients using traditional trial designs and multiple competing therapies is becoming more costly and challenging.

Strategies aimed at creating new efficiencies in clinical evidence generation and extending the benefits of precision medicine to larger groups of patients are driving a transformation from a reductionist approach to drug development (for example, a single drug targeting a driver mutation and traditional clinical trials) to a holistic approach (for example, combination therapies targeting complex multiomic signatures and real-world evidence). This transition is largely fuelled by the rapid expansion in the four dimensions of biomedical big data, which has created a need for greater organizational and technical capabilities (Fig. 1). Appropriate management and analysis of such data requires specialized tools and expertise in health information technology, data science and high-performance computing. For example, efforts to generate clinical evidence using real-world data are being limited by challenges such as capturing clinically relevant variables from vast volumes of unstructured content (such as physician notes) in electronic health records and organizing various structured data elements that are primarily designed to support billing rather than clinical research. So, new standards and quality-control mechanisms are needed to ensure the validity of the design and analysis of studies based on electronic health records.

Figure 1: Conceptual map of technical and organizational capacity for biomedical big data.
Conceptual map of technical and organizational capacity for biomedical big data.

Big data can be defined as having four dimensions: volume (data size), variety (data type), veracity (data noise and uncertainty) and velocity (data flow and processing). Currently, FDA approval decisions are generally based on data of limited variety, mainly from clinical trials and preclinical studies (1) that are mostly structured (2), in data sets usually no more than a few gigabytes in size (3), that are processed intermittently as part of regulatory submissions (4). The expansion of big data in the four dimensions (grey lines) calls for increasing organizational and technical capacity. This could transform big data into smart data by enabling a holistic approach to personalization of therapies that takes patient, disease and environmental characteristics into account. (Full size image (309 KB);Download PowerPoint slide (492 KB)More)”

From Nairobi to Manila, mobile phones are changing the lives of bus riders


Shomik Mehnidrata at Transport for Development Blog: “Every day around the world, millions of people rely on buses to get around. In many cities, these services carry the bulk of urban trips, especially in Africa and Latin America. They are known by many different names—matatus, dalalas, minibus taxis, colectivos, diablos rojos, micros, etc.—but all have one thing in common: they are either hardly regulated… or not regulated at all. Although buses play a critical role in the daily life of many urban dwellers, there are a variety of complaints that have spurred calls for improvement and reform.

However, we are now witnessing a different, more organic kind of change that is disrupting the world of informal buses using ubiquitous cheap sensors and mobile technology. One hotbed of innovation is Nairobi, Kenya’s bustling capital. Two years ago, Nairobi made a splash in the world of urban transport by mapping all the routes of informal matatus. Other countries have sought to replicate this model, with open source tools and crowdsourcing supporting similar efforts in Mexico, Manila, and beyond. Back in Nairobi, the Magic Bus app helps commuters use sms services to reserve and pay for seats in matatus; in September 2016, MagicBus’ potential for easing commuter pain in the Kenyan capital was rewarded with a $1 million prize. Other programs implemented in collaboration with insurers and operators are experimenting with on-board sensors to identify and correct dangerous driver behavior such as sudden braking and acceleration. Ma3Route, also in Nairobi (there is a pattern here!) used crowdsourcing to identify dangerous drivers as well as congestion. At the same time, operators are upping their game: using technology to improve system management, control and routing in La Paz, and working with universities to improve their financial planning and capabilities in Cape Town.

Against this backdrop, the question is then: can these ongoing experimental initiatives offer a coherent alternative to formal reform? …(More)”.

Data in public health


Jeremy Berg in Science: “In 1854, physician John Snow helped curtail a cholera outbreak in a London neighborhood by mapping cases and identifying a central public water pump as the potential source. This event is considered by many to represent the founding of modern epidemiology. Data and analysis play an increasingly important role in public health today. This can be illustrated by examining the rise in the prevalence of autism spectrum disorders (ASDs), where data from varied sources highlight potential factors while ruling out others, such as childhood vaccines, facilitating wise policy choices…. A collaboration between the research community, a patient advocacy group, and a technology company (www.mss.ng) seeks to sequence the genomes of 10,000 well-phenotyped individuals from families affected by ASD, making the data freely available to researchers. Studies to date have confirmed that the genetics of autism are extremely complicated—a small number of genomic variations are closely associated with ASD, but many other variations have much lower predictive power. More than half of siblings, each of whom has ASD, have different ASD-associated variations. Future studies, facilitated by an open data approach, will no doubt help advance our understanding of this complex disorder….

A new data collection strategy was reported in 2013 to examine contagious diseases across the United States, including the impact of vaccines. Researchers digitized all available city and state notifiable disease data from 1888 to 2011, mostly from hard-copy sources. Information corresponding to nearly 88 million cases has been stored in a database that is open to interested parties without restriction (www.tycho.pitt.edu). Analyses of these data revealed that vaccine development and systematic vaccination programs have led to dramatic reductions in the number of cases. Overall, it is estimated that ∼100 million cases of serious childhood diseases have been prevented through these vaccination programs.

These examples illustrate how data collection and sharing through publication and other innovative means can drive research progress on major public health challenges. Such evidence, particularly on large populations, can help researchers and policy-makers move beyond anecdotes—which can be personally compelling, but often misleading—for the good of individuals and society….(More)”

Why Big Data Is a Big Deal for Cities


John M. Kamensky in Governing: “We hear a lot about “big data” and its potential value to government. But is it really fulfilling the high expectations that advocates have assigned to it? Is it really producing better public-sector decisions? It may be years before we have definitive answers to those questions, but new research suggests that it’s worth paying a lot of attention to.

University of Kansas Prof. Alfred Ho recently surveyed 65 mid-size and large cities to learn what is going on, on the front line, with the use of big data in making decisions. He found that big data has made it possible to “change the time span of a decision-making cycle by allowing real-time analysis of data to instantly inform decision-making.” This decision-making occurs in areas as diverse as program management, strategic planning, budgeting, performance reporting and citizen engagement.

Cities are natural repositories of big data that can be integrated and analyzed for policy- and program-management purposes. These repositories include data from public safety, education, health and social services, environment and energy, culture and recreation, and community and business development. They include both structured data, such as financial and tax transactions, and unstructured data, such as recorded sounds from gunshots and videos of pedestrian movement patterns. And they include data supplied by the public, such as the Boston residents who use a phone app to measure road quality and report problems.

These data repositories, Ho writes, are “fundamental building blocks,” but the challenge is to shift the ownership of data from separate departments to an integrated platform where the data can be shared.

There’s plenty of evidence that cities are moving in that direction and that they already are systematically using big data to make operational decisions. Among the 65 cities that Ho examined, he found that 49 have “some form of data analytics initiatives or projects” and that 30 have established “a multi-departmental team structure to do strategic planning for these data initiatives.”….The effective use of big data can lead to dialogs that cut across school-district, city, county, business and nonprofit-sector boundaries. But more importantly, it provides city leaders with the capacity to respond to citizens’ concerns more quickly and effectively….(More)”

Organizational crowdsourcing


Jeremy Morgan at Lippincott: “One of the most consequential insights from the study of organizational culture happens to have an almost irresistible grounding in basic common sense. When attempting to solve the challenges of today’s businesses, inviting a broad slice of an employee population yields more creative, actionable solutions than restricting the conversation to a small strategy or leadership team.

This recognition, that in order to uncover new business ideas and innovations, organizations must foster listening cultures and a meritocracy of best thinking, is fueling interest in organizational crowdsourcing — a discipline focused on employee connection, collaboration and ideation. Leaders at companies such as Roche, Bank of the West, Merck, Facebook and IBM, along with countless Silicon Valley companies for whom the “hackathon” is a major cultural event, have embraced employee crowdsourcing as a way to unlock organizational knowledge and promote empathy through technology.

The benefits of internal crowdsourcing are clear. First, it ensures that a company’s understanding of key change drivers and potential strategic priorities is grounded in the organization’s everyday reality and not abstract hypotheses developed by a team of strategists. Second, employees inherently believe in and want to own the implementation of ideas that they generate through crowdsourcing. These are ideas borne of the culture for the culture, and are less likely to run aground on the rocks of employee indifference….

How can this be achieved through organizational crowdsourcing?

There is no out-of-the-box solution. Each campaign has to organically surface areas of focus for further inquiries, develop a framework and set of questions to guide participation and ignite conversations, and then analyze and communicate results in a way that helps bring solutions to life. But there are some key principles that will maximize the success of any crowdsourcing effort.

Obtaining insightful and actionable answers boils down to asking the questions at just the right altitude. If they’re too high up, too broad and open-ended, the usefulness of the feedback will suffer. If the questions are too broad — “How can we make our workplace better?” — you will likely hear responses like “juice bars” and “massage therapists.” If the questions are too narrow — “What kind of lighting do we need in our conference rooms?” — you limit the opportunity of people to use their creativity. However, the answers are likely to spark a conversation if people are asked, “How can we create spaces that allow us to generate ideas more effectively?” Conversation will flow to discussion of breaking down physical barriers in office design, building social “hubs” and investing in live events that allow employees from disparate geographies to meet in person and solve problems together.

On the technology side, crowdsourcing platforms such as Jive Software and UserVoice, among others, make it easy to bring large numbers of employees together to gather, build upon and prioritize new ideas and innovation efforts, from process simplification and product development to the transformation of customer experiences. Respondents can vote on other people’s suggestions and add comments.

By facilitating targeted conversations across times zones, geographies and corporate functions, crowdsourcing makes possible a new way of listening: of harnessing an organization’s collective wisdom to achieve action by a united and inspired employee population. It’s amazing to see the thoughtfulness, precision and energy unleashed by crowdsourcing efforts. People genuinely want to contribute to their company’s success if you open the doors and let them.

Taking a page from the Silicon Valley hackathon, organizational crowdsourcing campaigns are structured as events of limited duration focused on a specific challenge or business problem….(More)”

Corporate Social Responsibility for a Data Age


Stefaan G. Verhulst in the Stanford Social Innovation Review: “Proprietary data can help improve and save lives, but fully harnessing its potential will require a cultural transformation in the way companies, governments, and other organizations treat and act on data….

We live, as it is now common to point out, in an era of big data. The proliferation of apps, social media, and e-commerce platforms, as well as sensor-rich consumer devices like mobile phones, wearable devices, commercial cameras, and even cars generate zettabytes of data about the environment and about us.

Yet much of the most valuable data resides with the private sector—for example, in the form of click histories, online purchases, sensor data, and call data records. This limits its potential to benefit the public and to turn data into a social asset. Consider how data held by business could help improve policy interventions (such as better urban planning) or resiliency at a time of climate change, or help design better public services to increase food security.

Data responsibility suggests steps that organizations can take to break down these private barriers and foster so-called data collaboratives, or ways to share their proprietary data for the public good. For the private sector, data responsibility represents a new type of corporate social responsibility for the 21st century.

While Nepal’s Ncell belongs to a relatively small group of corporations that have shared their data, there are a few encouraging signs that the practice is gaining momentum. In Jakarta, for example, Twitter exchanged some of its data with researchers who used it to gather and display real-time information about massive floods. The resulting website, PetaJakarta.org, enabled better flood assessment and management processes. And in Senegal, the Data for Development project has brought together leading cellular operators to share anonymous data to identify patterns that could help improve health, agriculture, urban planning, energy, and national statistics.

Examples like this suggest that proprietary data can help improve and save lives. But to fully harness the potential of data, data holders need to fulfill at least three conditions. I call these the “the three pillars of data responsibility.”…

The difficulty of translating insights into results points to some of the larger social, political, and institutional shifts required to achieve the vision of data responsibility in the 21st century. The move from data shielding to data sharing will require that we make a cultural transformation in the way companies, governments, and other organizations treat and act on data. We must incorporate new levels of pro-activeness, and make often-unfamiliar commitments to transparency and accountability.

By way of conclusion, here are four immediate steps—essential but not exhaustive—we can take to move forward:

  1. Data holders should issue a public commitment to data responsibility so that it becomes the default—an expected, standard behavior within organizations.
  2. Organizations should hire data stewards to determine what and when to share, and how to protect and act on data.
  3. We must develop a data responsibility decision tree to assess the value and risk of corporate data along the data lifecycle.
  4. Above all, we need a data responsibility movement; it is time to demand data responsibility to ensure data improves and safeguards people’s lives…(More)”

Understanding Actionable Intelligence for Social Policy


Video on “The Actionable Intelligence (AI) model is a new approach to policy development. The AI approach is supported by Integrated Data Systems (IDS) which link administrative records from multiple agencies to give a broader view of social problems and policy solutions. The use of linked administrative data allows policy analysts, program evaluators and social innovators to test new social program ideas at a much lower cost and higher speed. AI uses these IDS to create a newly informed dialogue among executive leaders, stakeholders and researchers regarding what works best, for whom and in the most cost effective way….(More videos from AISP-UPENN)

Understanding Actionable Intelligence for Social Policy from AISP_UPENN on Vimeo.

RideComfort: A Development of Crowdsourcing Smartphones in Measuring Train Ride Quality


Adam Azzoug and Sakdirat Kaewunruen in Frontiers in Built Environment: “Among the many million train journeys taking place every day, not all of them are being measured or monitored for ride comfort. Improving ride comfort is important for railway companies to attract more passengers to their train services. Giving passengers the ability to measure ride comfort themselves using their smartphones allows railway companies to receive instant feedback from passengers regarding the ride quality on their trains. The purpose of this development is to investigate the feasibility of using smartphones to measure vibration-based ride comfort on trains. This can be accomplished by developing a smartphone application, analyzing the data recorded by the application, and verifying the data by comparing it to data from a track inspection vehicle or an accelerometer. A literature review was undertaken to examine the commonly used standards to evaluate ride comfort, such as the BS ISO 2631-1:1997 standard and Sperling’s ride index as proposed by Sperling and Betzhold (1956). The literature review has also revealed some physical causes of ride discomfort such as vibrations induced by roughness and irregularities present at the wheel/rail interface. We are the first to use artificial neural networks to map data derived from smartphones in order to evaluate ride quality. Our work demonstrates the merits of using smartphones to measure ride comfort aboard trains and suggests recommendations for future technological improvement. Our data argue that the accelerometers found in modern smartphones are of sufficient quality to be used in evaluating ride comfort. The ride comfort levels predicted both by BS ISO 2631-1 and Sperling’s index exhibit excellent agreement…(More)”

The Innovation-Friendly Organization


Book by Anna Simpson: “This book explores five cultural traits – Diversity, Integrity, Curiosity, Reflection, and Connection – that encourage the birth and successful development of new ideas, and shows how organizations that are serious about innovation can embrace them.

Innovation – the driver of change and resilience – It is totally dependent on culture, the social environment which shapes how ideas emerge and evolve. Ideas need to breathe, and culture determines the quality of the air. If it’s stuffy and lacks flow, then no idea, however brilliant, will live long enough to fulfil its potential.

Creating these innovation-friendly conditions is one of the key challenges facing organizations today, and one that is especially difficult for them – focused as they are on efficiency and control. Innovation, Anna Simpson argues, begins with diversity of thought and attitude: the opposite of conformity and standardisation.

Likewise, with ongoing pressures to deliver results before yesterday, how can organizations allow sufficient space for the seemingly aimless process of following interesting possibilities and pondering on the impact of various options?Anna Simpson shows how large organizations can adapt their culture to enable the exchange of different perspectives; to support each person to bring their whole self to their work; to embrace the aimlessness that fosters creative experimentation; to take the time to approach change with the care it deserves, and – lastly – to develop the collective strength needed to face the ultimate ‘sledgehammer test’….(More)”.