My paper co-authored with Yuan Lin, Towards Evidence-Driven Policy Design: Complex Adaptive Systems and Computational Modeling, will appear in The Innovation Journal: The Public Sector Innovation Journal.
I hope to use this post to begin a discussion on this question. Specifically, how do we define network resiliency when examining large-scale public sector networks. These networks span multiple-levels from individuals to organizations and may even involve consortiums. Consider the case of the US intelligence community (USIC). The USIC involves both public sector organizations (e.g. CIA, NSA, FBI, etc) but also collaborates with intelligence agencies in other countries (e.g. MI6, BND) and even private organizations (Xe Services LLC). The USIC must ensure that its network is resilient. Its resiliency is dependent not only how well it plans for, and executes, responses to changes in its internal and external, but also how well its network (which consists of many organizations it does not have formal control, or even influence, over) fairs in times of crises.
Today, I was examining the literature in telecommunication networks for concepts that we could draw on. The engineering literature has a myriad of concepts that we could draw on to build a framework for organizational network resiliency. For example, consider the concept of load-balancing. Load balancing is essential to the design of robust electronic networks. While its primary purpose is to allow us to plan for efficient usage of resources, load balancing also helps with managing against overload on devices. To describe the concept without getting too technical, one might conceptualize load balancing as follows: incoming information requests to a network are distributed to the appropriate device within the network by a load-balancer. The load-balancer is responsible for routing the request to the best available device (different algorithms might be used for this, and we can have different criteria for determining the best device to route a request to). Load balancing can help us design failsafe mechanisms (for e.g., if one node is down then traffic is routed to a backup node).
Should we have load-balancing mechanisms for organizational networks? Absolutely! I actually think that organizational networks do have implicit load-balancers. Some view these as gatekeepers? Gatekeepers play a vital role in determining how information moves within networks. Do you know of any organizations that manage their gatekeepers mindfully? If so, how do they do it? Also, are there other organizational concepts that are similar to load-balancing?
During my visit to the CIS @ LSE, I conducted an inquiry into how ecological models might help us understand robustness of networks, especially terrorist networks. One idea that I worked hard on is how do agents within a network adapt under conditions of duress. For example, assuming you took away a food source from an ecosystem, how might the various entities (species) adapt and create work-a-rounds? Would the nature of competition among the species change? Would the patterns that drive the reorganization of the ecosystem be predictable?
Along with my doctoral student, Yuan Lin, I have co-authored an article that describes how we might move towards evidence-driven policy design. This article draws from the keynote that I have at the 2010 Computational Social Science Society Conference.
Efforts to design public policies for social systems tend to confront highly complex conditions which have a large number of potentially relevant factors to be considered and rapidly changing conditions where continuous adaptation delays or obscures the effect of policies. Given unresolvable uncertainty in policy outcomes, the optimal solution is difficult, if ever possible, to nail down. It is more reasonable to choose a solution that is robust to as many future scenarios that might ensue from the decision. Arriving at such a solution requires policy makers to actively explore and exploit rich information to support their decision making in a cost-efficient, yet rigorous manner. We name this new working style as evidence-driven policy design and outline the characteristics of favorable evidence. We then argue that computational modeling is a potential tool for implementing evidence-driven policy design. It helps the study and design of solutions by simulating various environments, interventions, and the processes in which certain outcomes emerge from the decisions of policy makers. It allows policy makers to observe both the intended and, equally important, unintended consequences of policy alternatives. It also facilitates communication and consensus-building among policy makers and diverse stakeholders.
The Internal Revenue Service Business Modernization Project undertaken by the Tax Agency of the US Government has been singled out as an example of a massive failure. As envisioned, the project was intended as an Enterprise-wide intervention that would provide modern services and effective data access to citizenry and several government agencies. After more than a decade and 3 billion dollars later, the results appear to be less than exemplary. Sandeep Purao and I have a paper accepted for presentation at the Enterprise Architecture Research (TEAR2010) Workshop that identifies different stakeholders who participated in the project, and analyzes the sentiments and confidence each expressed regarding the fate of the project. We conclude with lessons learned from our investigation including recognizing the importance of multiple stakeholders for Enterprise-wide initiatives.
Purao, S., and Desouza, K.C. “An Enterprise-wide Intervention at IRS: A Longitudinal Analysis of Stakeholder Sentiments,” In Proceedings of the 5th Trends in Enterprise Architecture Research (TEAR2010) Workshop, Delft, Netherlands (November 12, 2010).
Sandeep Purao and I have a paper accepted at the 44th Hawaii International Conference on System Sciences in the Electronic Government Track (Development Methods for Electronic Government, Minitrack). The paper analyzes the IRS’s Business Systems Modernization Project using sentiment analysis.
We describe results from historical analysis of a large-scale, public sector effort: the IRS Modernization Project that has already spanned a decade and consumed more than 3 billion dollars. The results focus on analysis of Sentiments and Confidence expressed by different stakeholders, as found in various documents. We explore how such analyses may provide a window on project progress and potential early clues that may contribute to preventing undesirable outcomes in the future.
Reference: Purao, S., and Desouza, K.C. “Looking for Clues to Failures in Large-Scale Public Sector Projects: A Case Study,” In Proceedings of the Forty-Forth Hawaii International Conference on System Sciences (HICSS-44), Los Alamos, CA: IEEE Press, Kauai, HI, (January 4-7, 2011).
Sandeep Purao (IST, Penn State University) and I have a paper accepted for presentation at the International ACM Conference on Management of Emergent Digital EcoSystems (MEDES’10) (Bangkok, Thailand).
Abstract: Large IT projects, such as the US Government’s Internal Revenue Service Business Modernization Effort, can take a decade or more and consume billions of dollars. Traditional approaches to the study of such projects emphasize concerns such as requirements monitoring, progress tracking and risk mitigation. We propose an alternative approach guided by a digital ecosystems view instead of a hierarchical, decision-oriented view. We argue that this perspective is more suited to understand how such projects evolve and cause changes in the underlying digital ecosystem characterized by not only the IT infrastructure but also the transactional relationships among stakeholders. We illustrate our arguments by drawing on an archaeological case study of the IRS effort, and discuss implications of the digital ecosystem perspective for the study of large IT projects.
Reference: Purao, S., and Desouza, K.C. “Large IT Projects as Interventions in Digital Ecosystems,” In Proceedings of the International ACM Conference on Management of Emergent Digital EcoSystems (MEDES'10), Bangkok, Thailand (October 26-29. 2010).
I will be giving a keynote address at the 2010 Computational Social Science Society Conference (CSSS). CSSS 2010 is hosted by the Center for Social Dynamics and Complexity and the Consortium for Biosocial Complex Systems at. For more information on the conference, please click here [LINK].
From Hunches to Evidence Driven Policy Design: Leveraging Information through Simulation
Constructing public policy, whether at the national or local level, is a complex undertaking. Complexity arises from the number of stakeholders involved, varying agendas and incentives, resource constraints, a multitude of interacting variables, multiple time horizons, and even political climates. Due to these complexities, we too often categorize political and social problems as ‘wicked’ and unanalyzable. The default option is to take a haphazard approach to policy design, most often the outcome of the ego-based debates and negotiations of the decision-makers. In this keynote address, I will argue for a move from hunches (or intuition) to evidence driven policy construction. Today, due to the advancement of computational power and modeling techniques, we can simulate complex scenarios. Simulation gives us an ability to move policy construction from an activity primarily driven by historic case analysis and intuitions, to more of an applied science, where we can actually predict and control phenomenon. Through simulation we can, with reasonable certainty, ascertain the cost, benefit, risk, impact, and value proposition of a given policy. Using examples from simulation projects, such as a project that examined strategic options for dismantling terrorist networks, I will demonstrate how we can move policy design from being an ‘art’ to more of a ‘science.’
Volodymyr V. Lysenko and I have authored paper that explores the possibilities of the Internet as a tool for supplying information necessary for the organization and mobilization of successful opposition movements, especially under non-democratic regimes. Examples of the roles the Internet plays in the political processes in Russia are discussed in detail. In particular, the recent cyberprotest cases of the Ingushetiya.ru website and the movement to release political prisoner Svetlana Bakhmina are investigated. Besides showing the Internet’s significant role in organizing modern protests, these cases also demonstrate that in environments where practically all traditional mass-media are under the authorities’ control, the Internet becomes the major source of alternative information. Our paper offers a look at how deploying technologies can bring about social change, even in some of the most difficult political environments.
The paper will appear in Technology Forecasting and Social Change. Volodymyr and I will present the paper at the Harriman Institute for the Etiology and Ecology of Post-Soviet Media Conference at Columbia University on May 7-9, 2010.
Jared Keller, Yuan Lin, and I authored a paper that describes how agent-based modeling can be used to consider policy options for dismantling terrorist networks. The paper will appear in Technology Forecasting and Social Change.
Dismantling Terrorist Networks: Evaluating Strategic Options Using Agent-Based Modeling
Dismantling dark networks remains a critical goal for the peace and security of our society. Terrorist networks are the most prominent instantiation of dark networks, and they are alive and well. Attempts to preemptively disrupt these networks and their activities have met with both success and failure. In this paper, we examine the impacts of four common strategies for dismantling terrorist networks. The four strategies are: leader-focused, grassroots, geographic, and random. Each of these strategies has associated pros and cons, and each has different impacts on the structure and capabilities of a terrorist network. Employing a computational experimentation methodology, we simulate a terrorist network and test the effects of each strategy on the resiliency of that network. In addition, we test scenarios in which the terrorist network has (or does not have) information about an impending attack. Our work takes a structural perspective to the challenge of addressing terrorist networks. Specifically, we show how various strategies impact the structure of the network in terms of its resiliency and capacity to carry out future attacks. This paper also provides a valuable overview of how to use agent-based modeling for the study of complex problems in the terrorism, conflict studies, and security studies domains.
I have a new paper accepted for publication. The paper, “Information and Knowledge Management in Public Sector Networks: The Case of the US Intelligence Community” will appear in the International Journal of Public Administration.
This paper contributes to the public management literature by exploring the critical challenges that underpin the construction of robust information and knowledge management strategies in networked settings. The ability of the network to sustain itself, thrive, and achieve its objectives depends on the success that the network has in organizing and coordinating its constituent organizations. The network’s collaborative information and knowledge management strategy is critical to the functioning of the network and the achievement of objectives. A robust information and knowledge management strategy will bring organizations in the network together, help them share resources, collaborate on efforts, and further their objectives in a holistic manner. An inadequate information and knowledge management strategy might lead to disconnects in organizations due to lack of information sharing, poor collaborative knowledge generation, lack of coordination, leading to a fragmented network. Drawing on a multi-year, multi-method, and multi-organization study of the United States Intelligence Community (USIC), the paper puts forth a comprehensive framework to examine information and knowledge management challenges within the USIC, as well as other organizations.