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Defining Policy Informatics

I have been busy working on a statement that captures the essence of policy informatics. Here is my first-cut at the definition. I thank all those who have already provided comments on this version, especially Dr. Erik Johnston (Co-Director of the Center for Public Informatics at Arizona State University). Please do send me your comments, both positive and negative, and suggestions for improvement. Thanks.

Policy Informatics

Solving complex public policy problems, dilemmas, and challenges requires deliberate, and sophisticated, information analysis.

Policymakers often are faced with conflicting solutions to complex problems, thus making it necessary for them to test out their assumptions, interventions, and resolutions. Towards this end, it becomes critical for a policymaker to have an information-rich, interactive environment in which complex problems can be modeled, simulated, visualized, and studied.

Relevant information can range from being too abundant to hardly existent. In the former case, we face the challenge of leveraging large quantities of information under severe time and resource constraints. In the latter case, limited or incomplete information has to be used to make decisions on ambiguous solution spaces.

In deliberating, designing, and implementing policies, the policy makers and the public face a number of transactional and collaborative inefficiencies. Some of these inefficiencies arise from the simple reality that information held by both parties is difficult to articulate and even transfer, i.e. information is sticky. This makes it difficult for either party to collaborate as they do not fully empathize with the problems of the other.

In addition, advances in communication and computational technologies enable new pathways to solutions. Rather than trying to solve public problems, governments are able to empower its public to solve their own problems. Crowdsourcing and bottom-up, emergent, problem-solving are desirable as the public have a greater chance of taking charge of their own local problems, voicing their concerns, and arriving at locally relevant solutions. Designing and mobilizing platforms where citizen input is used effectively to solve local problems and collaborative forums improves the results, and therefore the relationships, for both the policy makers and the public.

Policy informatics is the study of how information is leveraged and efforts are coordinated towards solving complex public policy problems. Driven by the need to exploit information to tackle complex policy problems and to ensure efficient and efficient policy setting and implementation platforms, policy informatics seeks to

  • enhance policy analysis and design through visualizing, modeling, and simulating complex policy scenarios,
  • study the role of information systems and information-based governance platforms in policy planning, deliberation, and implementation,
  • advance the management of information systems projects in the public sector,
  • study how information analysis and management influences the design of participatory platforms, and
  • arrive at theoretical and practical frameworks to advance our knowledge of the roles of information analysis in policy setting, the use of computational techniques in policy contexts, and how information-driven policy setting influences the nature of governance and governance platforms.

Policy informatics helps us advance evidence-driven policy design, wherein scientific models and analyses drive decision-making for resolution of complex policy challenges, dilemmas, and problems. Policy informatics is an emerging field of both research and a community of practice focusing on 1) advancing decision-making in the public sector through information-centric analysis of evidence that leverages computational and technological advances, and 2) designing, managing, and evaluating of information systems and infrastructures for policy construction, analysis, and implementation. Policy informatics expands to the multi-disciplinary nature of the public administration discipline by infusing it with the advances of information technology, management of information systems, and computational and informational science perspectives.

 

How Not to Silence the Resistance – Strategic Direction

My article with Nicholas D. Sweers II, Shh! It’s vive la re´sistance..., which was originally published in the Journal of Business Strategy, is featured in the current issue of Strategic Direction.

8 Ways to Democratize Experimentation: HBR Blog

My third post on the Harvard Business Review site went live today. The post was written in collaboration with H. James Wilson and is titled, 8 Ways to Democratize Experimentation. Building on our previous post on experimentation, in this post, we offer 8 tips for organizations to consider as they try to infuse experimentation as part of every employee's work.

  1. Increase managerial attention.
  2. Train employees on the basics of conducting experiments.
  3. Accept that experimentation is a messy and untidy process.
  4. Deploy organizational resources and assets to give employees the time and space to experiment with their ideas.
  5. Build a process whereby experiments can be conducted in a systematic manner.
  6. Create a platform or bulletin board.
  7. Give intrinsically motivated experimenters the same care provided to "sanctioned," large-scale experiments.
  8. Start a working papers and presentation series for both researchers and practitioners.

 

We would love to hear your comments on the ideas presented.

Knowledge Transfer Behaviors and Social Networks: A Co-evolution Framework

Yuan Lin, my doctoral student, and I have a paper accepted for presentation at the Annual Meeting of the Academy of Management in San Antonio, Texas (August 12-16, 2011).

Individuals’ Knowledge Transfer Behaviors and Social Networks: A Co-evolution Framework

The boom of the network concept in organizational research has resulted in a growing interest in the interplay between organizational members’ knowledge transfer and their social network structure. This paper treats such interplay as a co-evolution process and lay out a theoretical framework, CO-evolution of Individuals and Networks (COIN), to facilitate its modeling. Using a simplified example, we identify the components of a co-evolution model that should be constructed based on substantive theories: cross-level causal mechanisms, network structural factors, individual heterogeneity and autonomy, the relationships among model assumption, inputs and outputs. COIN synthesizes theoretical or empirical evidence that can help construct these components from multiple disciplines (e.g., organizational research, statistics, physics, economics, and sociology). It decomposes the co-evolution process into key constructs and mechanisms and organizes existing theories around them. It also exposes gaps in related work which once filled can facilitate studies on network-behavior co-evolutio

Lin, Y.A., and Desouza, K.C. “Individuals’ Knowledge Transfer Behaviors and Social Networks: A Co-evolution Framework,” In Proceedings of the Annual Meeting of the Academy of Management, San Antonio, TX (August 12-16, 2011).

Innovation Audit and Visit @ Delta Faucet Company

Next week, I will visit with executives, project managers, platform leaders, and employees at the Delta Faucet Company (Indianapolis, Indiana). I will be conducting an innovation audit, learning about innovation strategies employed by Delta Faucet, and making strategic recommendations on how to bolster the innovation quotient of the organization. Having just completed a book titled Intrapreneurship: Leveraging Ideas within the Organization, I am looking forward to using the models described in the book to study how ideas are generated, mobilized, advocated and screened for, experimented with, commercialized, diffused and implemented by the Delta Faucet Company.

Securing Intellectual Assets: Integrating the Knowledge and Innovation Dimensions

At long last, I have received information that my paper on Securing Intellectual Assets: Integrating the Knowledge and Innovation Dimensions will appear in International Journal of Technology Management (Vol. 54, No. 2/3, 2011).

Abstract: The concept of intellectual asset security has received widespread attention in recent times. Much of this attention can be attributed to the fact that knowledge assets can be used to secure competitive advantages for organisations. Moreover, one might assert that in today’s knowledge-based economies and markets, it is these assets that truly differentiate organisations and are the only true source of sustainable competitive advantages. In order to have a robust program for managing intellectual assets, an organisation must account for its knowledge management and innovation processes. In this paper, drawing on 1) a semiotic-based model for knowledge management (Desouza, 2006), and 2) an organisational process of innovation (Desouza et al., 2006), the author describes an integrated process framework for the management of intellectual assets. The framework is then used to describe salient security management challenges faced when managing intellectual assets. Executives involved in security management programs in 23 organisations were interviewed to elicit key security management challenges faced by organisations when addressing intellectual assets. The concept of intellectual asset security has received widespread attention in recent times. Much of this attention can be attributed to the fact that knowledge assets can be used to secure competitive advantages for organisations. Moreover, one might assert that in today’s knowledge-based economies and markets, it is these assets that truly differentiate organisations and are the only true source of sustainable competitive advantages. In order to have a robust program for managing intellectual assets, an organisation mustaccount for its knowledge management and innovation processes. In this paper,drawing on1 a semiotic-based model for knowledge management (Desouza, 2006)2 an organisational process of innovation (Desouza et al., 2006), the author describes an integrated process framework for the management ofintellectual assets. The framework is then used to describe salient security management challenges faced when managing intellectual assets. Executivesinvolved in security management programs in 23 organisations were interviewed to elicit key security management challenges faced byorganisations when addressing intellectual assets.

Deploying IT for Organizational Innovation: Lessons from Case Studies

Along with several colleagues, Jaka Lindic (University of Ljubljana), Peter Baloh (BISOL, d.o.o), and Vincent Ribière (The Institute for Knowledge and Innovation (IKI-SEA), Bangkok University), I co-authored a paper for the International Journal of Information Management.

Organizations must innovate if they are to survive in today’s fiercely competitive marketplace. In this paper, we explore how leading organizations are using emerging technologies to enable novel forms of ideation that can radically increase the sheer volume of ideas they explore. In addition, we outline how organizations use technologies to cost effectively manage this increased volume of ideas by optimizing generation, mobilization, advocacy and screening, experimentation, commercialization, and even the diffusion and implementation of ideas. Critical to this is the management of knowledge during the innovation process.

Lindic, J., Baloh, P., Ribière, V.M., and Desouza, K.C. “Deploying Information Technologies for Organizational Innovation: Lessons from Case Studies,” International Journal of Information Management, Forthcoming.