First Annual Training Day on DMDU methods

by: Steven Popper

The Society for Decision Making under Deep Uncertainty held its first annual training day event on 15 November 2016 at World Bank Headquarters in Washington, DC. This was the day prior to the start of the DMDU Society’s annual two-day workshop. The Society’s leadership team has decided that a training day will precede future DMDU workshops under the direction of the chair for education and training in coordination with that year’s workshop organizing committee. This decision is a direct response to an interest expressed through the questionnaire on education and training distributed to the Society’s membership earlier in 2016. The survey disclosed not only an interest in such a session but a willingness to participate on the part of students, DMDU analysts and methodologists, and policy practitioners.

This year’s training day planning team was led by the current chair, Steven Popper (RAND) with considerable assistance from the chair for Communication and Outreach, Marjolijn Haasnoot (Deltares). The day was designed to serve several purposes: to provide first-time workshop attendees with sufficient background on key DMDU concepts to participate in the topical sessions planned for the annual workshop’s following two days; to create a common forum for discussions among students, scholars and practitioners; to create face-to-face engagement between methodologists and those interested in learning DMDU methods; and for the first time present a common vocabulary and framework for comprehending the quickly proliferating world of DMDU technique and application.

The main themes that wove the entire day together were DMDU concepts, DMDU methods and DMDU in application. Steven Popper introduced the day and then assisted Marjolijn Haasnoot in presenting an interactive exercise/game designed by her and her Deltares colleagues. The purpose was to engage all participants as a group in gaining a practical understanding of the principal tenets and themes of DMDU analysis. This was then followed by Steven Popper presenting a preliminary nine-step framework by which to characterize the purpose and outcomes of various methods that would later be presented.
These preliminaries before lunch set the stage for two hours of DMDU technique and applications demos afterward. Building upon the success of a similar event organized by the organizing committee of 2015’s DMDU Workshop at Deltares and TU Delft in the Netherlands, six teams presented a 30-minute session four times each across the two-hour demo time slot. This meant that attendees could select those of most interest to them and be assured of receiving a full presentation in a systematic manner. Doing so called for great effort on the part of the presenting teams: Decision Scaling – Casey Brown (U Massachusetts); Dynamic Adaptive Policy Pathways – Marjolijn Haasnoot; Many Objective Robust Decision Making Using OpenMORDM – David Hadka (Penn State); Strategic Infrastructure System Investment Analysis – Anthony Hurford and Dr Evgenii Matrosov (Manchester U); DMDU Tools for Delta Planning – David Groves (RAND); and Exploratory Modeling Analyst’s Workbench – Jan Kwakkel (TU Delft.)

The day concluded with two further presentations. The first, organized by Vincent Marchau (Radboud U) and Warren Walker (TU Delft), allowed those authors contributing to a new edited volume sponsored by the Society to give very brief presentations on the book’s chapters. The book under preparation, DECISIONMAKING UNDER DEEP UNCERTAINTY – FROM THEORY TO PRACTICE (Marchau, Walker, Bloemen, Popper (eds.); Springer Verlag, forthcoming) is designed to be a unified textbook on DMDU techniques and applications. This was then followed by a final panel discussion intended for interactive engagement with training day participants. James Hall (Oxford U), chair of the 2017 DMDU Workshop organizing committee, along with Robert Lempert (RAND) and Jan Kwakkel, the Society’s current president and vice president, led a discussion on “What is in the DMDU analyst’s tool kit?” This served also as the general Q&A session to wrap up the training day.

The response to this program was positive on the part of the participants as well as the presenters. Planning is currently underway by the Society’s leadership team to incorporate the lessons of this first effort and present a suitably modified and improved version in November 2017 at the 5th annual DMDU Workshop scheduled for Oxford University. As in Washington, the current intention is to open participation not only to those who will be attending the subsequent workshop but also on a limited basis to outsiders with an interest in learning more about DMDU analysis in both theory and practice.

Suggestions for further reading (to be elaborated):

Hadka, D., Herman, J., Reed, P.M., Keller, K. (2015) “An Open Source Framework for Many-Objective Robust Decision Making”, Environmental Modelling & Software, v74, 114-129, 2015.

Haasnoot, M., J.H. Kwakkel., W.E. Walker, J.M ter Maat (2013) Dynamic adaptive policy pathways: A method for crafting robust decisions for a deeply uncertain world. Global Environmental Change, http://dx.doi.org/10.1016/j.gloenvcha.2012.12.006

Kwakkel, J.H. Exploratory Modeling Analysis Workbench. http://simulation.tbm.tudelft.nl/ema-workbench/contents.html

Brown, C., Y. Ghile, M. Laverty, and K. Li (2012), Decision scaling: Linking bottom-up vulnerability analysis with climate
projections in the water sector, Water Resour. Res., 48, W09537, http://dx.doi.org/10.1029/2011WR011212 
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Bridging the False Divide: Are We Ignoring the Role of Adaptive Operations for Improving the Efficiency, Resilience and Robustness of Planned Infrastructure?

by: Patrick Reed

This blog reports on one of the session of the annual meeting of 2016. The sessoin was organized by Patrick Reed (Cornell University), Jan Kwakkel (TU Delft),  Andrea Castelletti (Politecnico di Milano), Laura Bonzanigo (World Bank). Invited speakers were Julie Quinn (Cornell University) and Marc Jaxa-Rozen (TU Delft).

Session Focus: This session explored the interplay between short-term adaptive operations and their influence on long-term planning is particularly relevant for irreversible decisions for long-lived infrastructures that present complex ecological impacts, and must reliably meet multi-sectoral demands (e.g., reservoirs, energy production/transmission, transportation networks, etc.). A core theme throughout this whole session is that current DMDU frameworks that truly seek robustness must better exploit information feedbacks, tailor adaptivity so that triggered actions are contextually appropriate, and minimize lock in.  The session was organized into three case study presentations, five posters, and an interactive serious table top game. This suite of multi-sector examples helped clarify emerging innovations and persistent challenges related to bridging the planning and management divide.

Case Study Example #1 (Speaker: Patrick Reed, Research Triangle Region, NC, USA): This case study highlighted emerging work bridging the Many-Objective Robust Decision Making (MORDM) and Dynamic Adaptive Policy Pathways (DAPP) DMDU frameworks.  The example showed how the region’s water utilities’ long term infrastructure pathways are strongly shaped by their short term conservation policies and their ability to consider regional water transfers. Cooperatively developed, shared investments across four municipalities expand the capacity to use short term transfers to better manage severe droughts with fewer irreversible infrastructure options. Cooperative pathways are also important for avoiding regional robustness conflicts, where one party benefits strongly at the expense of one or more the others. A significant innovation of this work are the mix of weekly and annual dynamic risk-of-failure action triggers that allow for new information feedbacks and provide high levels of adaptivity.

Suggested Further Reading:

Zeff, H., J. Herman, P. Reed and G. Characklis (2016). “Cooperative drought adaptation: Integrating infrastructure development, conservation, and water transfers into adaptive policy pathways.” Water Resources Research, http://dx.doi.org/10.1002/2016WR018771

Case Study Example #2 (Speaker: Julie Quinn, Red River Basin, Vietnam):  This case study highlighted that simple deterministic and static rule-based abstractions of reservoirs that are commonly employed in standard simulation frameworks  are unable to realistically consider the complex dynamics and key sources of information that shape river basin operations. Consequently, they also fail to explore the full set of tradeoffs across alternative operating policies seeking to balance evolving multi-sector basin demands under changing hydroclimatic forcings. This case study illustrated how to better sample and quantify the adaptive capacity of a complex multi-reservoir system in the Red River Basin to manage evolving pressures related to energy security, food security, and urban flood risks.

Suggested Further Reading:

Giuliani, M., D. Anghileri, A. Castelletti, P. Nam Vu and R. Soncini-Sessa (2016). “Large storage operations under climate change: expanding uncertainties and evolving tradeoffs.” Environmental Research Letters 11(3), http://dx.doi.org/10.1088/1748-9326/11/3/035009

Case Study Example #3: (Speaker: Marc Jaxa-Rozen, Dutch ATES Planning & Management): This case study highlighted how short term centralized and cooperative control mechanisms fundamentally shape the long term value and efficiency of Aquifer Thermal Energy Storage (ATES) systems. ATES systems can significantly reduce energy demand for building heating and cooling. However, these systems are affected by uncertainties ranging from daily energy demand to multi-year geohydrological processes, leading to suboptimal outcomes under the static planning approaches which are currently used to manage this technology in the Netherlands. Price-based coordination mechanisms may yield improved performance under these uncertainties, by providing greater operational flexibility for ATES operators and supporting the design of self-organized institutional arrangements as an alternative to static permits.

Suggested Further Reading:

Rostampour, V., M. Jaxa-Rozen, M. Bloemendal and T. Keviczky (2016). “Building Climate Energy Management in Smart Thermal Grids via Aquifer Thermal Energy Storage Systems1.” Energy Procedia 97, http://dx.doi.org/10.1016/j.egypro.2016.10.019

Posters

  1. Michael Green, Global Sustainability Institute, “Real options and robust adaptive management in irrigated agriculture and urban drainage: supporting the next generation of UK climate change projections”.
  2. Steven Popper, RAND Corporation, “Future Force Planning: The Present is Prologue”.
  3. Lauren Cook, Carnegie Mellon University, “Using precipitation data from climate change projections in engineering resiliency applications under deep uncertainty”.
  4. Kim Smet, Harvard University, “Flexibility in flood management design: proactive planning under uncertainty”.
  5. Vivek Srikrishnan, Pennsylvania State University, “Identification of signposts for adaptive flood risk management in the Netherlands”.

Serious Table Top Interactive Game (Lead Facilitator: Julie Quinn):  The session ended by engaging all of the participants to team up in a simulated river basin decision problem. The teams had to confront severe flood risks to a major city, water shortages for agriculture, and highly variable energy production. Each team had to divide its players to advocate for specific hydropower, agriculture, and urban flooding interests.  The game had three stages: (1) choose between two candidate formulations, (2) specify performance requirements for your sector, and (3) exploit interactive visual analytics to explore tradeoffs and negotiate a compromise.  A key take home point from the game is that “problem framing” itself is a critical deep uncertainty and false perceptions of system requirements and their tradeoffs can yield severe and unexpectedly negative unintended consequences.

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Deep Uncertainty and the Long-Term: Time, the policy challenge and enablers for policy persistence

by Judy Lawrence and Robert Lempert

At the conclusion of the DMDU workshop at Deltares, The Netherlands in 2015, we identified political scientists as an additional group that could inform the discussions at the next annual workshop. Accordingly, we designed a problem session at the annual workshop at the World Bank in 2016, entitled: Deep Uncertainty and the Long-Term: Time, the policy challenge and enablers for policy persistence. Whether or not decision makers consider the implications of their decisions for future generations under changing conditions depends on a range of institutional, political, behavioural and ethical factors. One of these is the extent to which policy decisions are influenced by short-termism or presentist bias. This in turn, depends on the political context within which decisions are made.

Tools developed for decision making under conditions of uncertainty and change, need to be ‘fit’ for the changing environment and for the political context, to enable policies to persist over time and adapt to changing conditions. Or the political context could be changed using commitment devices. Thus, for successful implementation of policies that can persist over the long term or be adjusted as the world changes, we need to understand the drivers that motivate the actors.

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What are the topics of this year’s annual meeting? A word cloud

by  Marjolijn Haasnoot, Laura Bonzanigo

Tomorrow we will start our 4th annual meeting of the Society for Decision Making under Deep Uncertainty. Like last year we made word cloud of the titles of the presentation, abstract and posters.  As expected ‘uncertainty’ is one of the most frequent words this year. However, this has not always been the case. If you look back at the word clouds from previous meetings (see picture below), you see this pops up in the second meeting, and in the third meeting this becomes DEEP uncertainty. Is uncertainty increasing?
Regarding the policy domains and topics that are addressed ‘infrastructure’ and ‘climate’ stand out in this year’s meeting. The topic of ‘water’ follows after that. In previous years water was more present, while in the first meeting that was less of a clear policy topic that stood out. ‘Climate’ as topic for deep uncertainty has always been there, although less apparent in the titles of last years meeting. You might also notice a change from ‘robust decision making/analysis’ in the first meeting towards ‘adaptation/adaptive decision making’. The most outstanding difference the infrastructure in this year’s meeting. We are very much looking forward to hear more …

wordle-all-years

Word clouds are made with: http://www.wordle.net/create

 

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Programme for the 2016 annual workshop is now available!

The World Bank will host the 2016 DMDU workshop in Washington DC, on November 16 and 17, 2016, with a training on DMDU methodologies scheduled for November 15th, 2016. There is still place for the training, but it is running out fast. Please confirm here by October 15 if you have not done that already, to make sure we save you a spot! The annual meeting is fully booked. Please let us know if you will not come so there will be place for others to attend. Download the programme. Continue reading

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Embracing Uncertainty for Better Decision-Making

by Laura Tuck and Julie Rozenberg, Sustainable Development Practice Group, World Bank Group

We all face uncertainties.

What if the train’s late? What if it rains? What if traffic is bad? What if there’s a shift in government before the project starts?

Every day we’re hit by all the “what ifs” especially in our line of work at the World Bank Group, whether in the field or within our organization. But how do we best cope with this? Embracing uncertainties may be the answer.

The World Bank Group has been at the forefront of mainstreaming new methods to deal with uncertainties. In fact, you may not know this, but the World Bank is one of the founding members of the Society for Decision Making Under Deep Uncertainty.

Today’s decision makers face conditions of fast-paced, transformative, and often surprising change. Traditional decision analysis relies on point and probabilistic predictions. But under conditions of deep uncertainty, predictions are often wrong, and relying on them can prove costly and dangerous. Fortunately, new methods and processes now exist to help decision makers identify and evaluate robust and adaptive strategies, thereby making sound decisions in the face of these challenges. Continue reading

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Report from Session B5 on “Managing Uncertainty” at the 8th International Congress on Environmental Modelling and Software

by Joseph Guillaume

At the iEMSs2016 conference in Toulouse, the session on Decision Making under Deep Uncertainty (see blog report) was accompanied by a more generic one on “Managing Uncertainty”, organised by Joseph Guillaume (Aalto University), Tony Jakeman (Australian National University), Holger Maier (The University of Adelaide), Jiri Nossent (Flanders Hydraulics Research and Vrije Universiteit Brussel) and Evelina Trutnevyte (ETH Zurich).

The session emphasised the diversity of approaches for managing uncertainty. Contributions notably covered sensitivity analysis, scenario analysis, parameter estimation and uncertainty quantification. While not directly tied to Decision Making under Deep Uncertainty, it is important to remember that these techniques form the foundations of our analyses – the means of addressing any uncertainty that is not treated as deep. As argued in a recent publication in Environmental Modelling and Software (Maier at al. 2016), multiple paradigms for modelling the future tend to co-exist, with different parts of an analysis focussed on capturing best available knowledge, quantifying uncertainty, and exploring multiple plausible futures. Continue reading

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Deep Uncertainty at the International Congress on Environmental Modeling and Software

by Rob Lempert and Jan Kwakkel,

The 8th International Congress on Environmental Modeling and Software in Toulouse, France, on July 10-14, 2016, featured a track titled Advancing in Environmental Decision Making Under Deep Uncertainty: Emerging Tools and Challenges. The track was co-organized by Jan Kwakkel (Delft University of Technology), Patrick Reed (Cornell), Robert Lempert (RAND Corporation), and Marjolijn Haasnoot (Deltares). The track consisted of four sessions with four papers in each session.

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Annual Workshop

Registration for our annual workshop in Washington DC (November 16-17) is now closed.

This year’s workshop is organized around two key elements. First, the workshop will include 6 “problem-solving” sessions during which we will have group discussions around practical problems our Society members face in their work, and possible solutions. These will not be typical panel sessions since the audience will be actively involved. Second, the workshop will use posters as the primary means for participants to present their current work.  The workshop will integrate posters in three ways: (1) pitches in the problem-solving sessions for posters that speak to the problems described; (2) pitches in poster sessions; (3) informal discussions around posters during all breaks and social times. You will find below a short description of the 6 sessions that were selected for group discussions. Continue reading

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Report from the Third workshop on Decision Making under Deep Uncertainty

by Marjolijn Haasnoot (Deltares, Delft University), Judy Lawrence (New Zealand Climate Change Research Institute), Robert Lempert (RAND), Nidhi Kalra (RAND), Jan Kwakkel (Delft University)

 

In early November 2015 about 100 scientists and practitioners from all over the world shared their experiences and methods at the third annual meeting of the Society for Decision Making Under Deep Uncertainty in Delft, Netherlands. The workshop was hosted by Deltares, Delft University of Technology, and UNESCO-IHE and co-organized with RAND, the World Bank, Victoria University of Wellington’s Climate Change Research Institute, and staff of the Dutch Delta Programme.

Groepsfoto DMUU workshop

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Uncertainty Assessement in Ecosystem Services: Seven Challenges and Practical Responses (2017)

Hamel, P. and BP Bryant (2017). Uncertainty assessment in ecosystem services analyses: Common challenges and practical responses. Ecosystem Services 24, 1-15. doi:10.1016/j.ecoser.2016.12.008

Abstract: Ecosystem services (ES) analyses are increasingly used to address societal challenges, but too often are not accompanied by uncertainty assessment. This omission limits the validity of their findings and may undermine the ‘science-based’ decisions they inform. We summarize and analyze seven commonly perceived challenges to conducting uncertainty assessment that help explain why it often receives superficial treatment in ES studies. We connect these challenges to solutions in relevant scientific literature and guidance documents. Since ES science is based on a multiplicity of disciplines (e.g. ecology, hydrology, economics, environmental modeling, policy sciences), substantial knowledge already exists to identify, quantify, and communicate uncertainties. The integration of these disciplines for solution-oriented modeling has been the focus of the integrated assessment community for many years, and we argue that many insights and best practices from this field can be directly used to improve ES assessments. We also recognize a number of issues that hinder the adoption of uncertainty assessment as part of standard practice. Our synthesis provides a starting point for ES analysts and other applied modelers looking for further guidance on uncertainty assessment and helps scientists and decision-makers to set reasonable expectations for characterizing the level of confidence associated with an ES assessment.

Readers interested in uncertainty and ES may also find a recent workshop report on “Motivating and Improving Uncertainty Assessment in ES” interesting as well:

Finally, those having or seeking to produce good examples of such assessment are encouraged to submit to a new special issue on the topic, with submissions due September 30, 2017.

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Environmental Realism: Challenging Solutions (2017)

Cockerill, K., M. Armstrong, J. Richter, J. Okie. 2017. Environmental Realism: Challenging Solutions. Palgrave MacMillan 145p. ISBN 978-3-319-52824-3.

http://www.springer.com/us/book/9783319528236

Abstract from Chapter 1: Why Challenge Solutions?

Labeling a problem ‘environmental’ creates a pervasive belief that science and technology can, should, and will generate solutions for issues ranging from pandemic disease to stream functions to nuclear contamination. These, however, are ‘wicked problems’ that defy simple or long-term solutions, but rather must be continually managed. Further, what are defined in the 21st century as ‘environmental problems’ are often the consequence of perceived ‘solutions’ implemented in a previous era.The perception of these issues as problems is derived, in part, from Enlightenment ideas segregating Homo sapiens from nature and a belief that humans can contain or control biophysical processes. Solutionist thinking and language perpetuates a self-referential problem-solution-problem cycle that begs the question of what constitutes a ‘solution’ and simultaneously elides the reality that human systems and biophysical systems are inseparable.

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Robust decision making in data scarce contexts: addressing data and model limitations for infrastructure planning under transient climate change (2017)

Shortridge, J., Guikema, S. & Zaitchik, B. (2017) Robust decision making in data scarce contexts: addressing data and model limitations for infrastructure planning under transient climate change. Climatic Change 140: 323. doi:10.1007/s10584-016-1845-4

https://link.springer.com/article/10.1007/s10584-016-1845-4

Abstract: In the face of deeply uncertain climate change projections, robust decision frameworks are becoming a popular tool for incorporating climate change uncertainty into water infrastructure planning. These methodologies have the potential to be particularly valuable in developing countries where extensive infrastructure development is still needed and uncertainties can be large. However, many applications of these methodologies have relied on a sophisticated process of climate model downscaling and impact modeling that may be unreliable in data-scarce contexts. In this study, we demonstrate a modified application of the robust decision making (RDM) methodology that is specifically tailored for application in data-scarce situations. This modification includes a novel method for generating transient climate change sequences that account for potential variable dependence but do not rely on detailed GCM projections, and an emphasis on identifying the relative importance of data limitations and uncertainty within an integrated modeling framework. We demonstrate this methodology in the Lake Tana basin in Ethiopia, showing how the approach can highlight the vulnerability of alternative plans across different time scales and identify priorities for research and model refinement. We find that infrastructure performance is particularly sensitive to uncertainty in streamflow model accuracy, irrigation efficiency, and evaporation rates, suggesting that additional research in these areas could provide valuable insights for long-term infrastructure planning. This work demonstrates how tailored application of robust decision frameworks using simple modeling approaches can provide decision support in data-scarce regions where more complex modeling and analysis may be impractical.

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Testing the Scenario Hypothesis (2017)

Gong, Min , Robert Lempert, Andrew M Parker, Lauren A. Mayer, Jordan Fischbach, Matthew Sisco, Zhamin Mao, David H. Krantz, and Howard Kunreuther. “Testing the Scenario Hypothesis: An Experimental Comparison of Scenarios and Forecasts for Decision Support in a Complex Decision Environment.” Environmental Modeling and Software 91 (2017): 135-55.

http://www.sciencedirect.com/science/article/pii/S1364815216305060

Decision support tools are known to influence and facilitate decisionmaking through the thoughtful construction of the decision environment. However, little research has empirically evaluated the effects of using scenarios and forecasts. In this research, we asked participants to recommend a fisheries management strategy that achieved multiple objectives in the face of significant uncertainty. A decision support tool with one of two conditions—Scenario or Forecast—encouraged participants to explore a large set of diversified decision options. We found that participants in the two conditions explored the options similarly, but chose differently. Participants in the Scenario Condition chose the strategies that performed well over the full range of uncertainties (robust strategies) significantly more frequently than did those in the Forecast Condition. This difference seems largely to be because participants in the Scenario Condition paid increased attention to worst-case futures. The results offer lessons for designing decision support tools.

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Why pay attention to paths in the practice of environmental modelling? (2017)

Lahtinen, T. J., J. H. A. Guillaume, and R. P. Hämäläinen (2017), Why pay attention to paths in the practice of environmental modelling?, Environmental Modelling and Software, 92, 74–81, http://dx.doi.org/10.1016/j.envsoft.2017.02.019

Taking the ‘path perspective’ helps to understand and improve the practice of environmental modelling and decision making. A path is the sequence of steps taken in a modelling project. The problem solving team faces several forks where alternative choices can be made. These choices determine the path, together with the impact of uncertainties and exogenous effects. This paper discusses phenomena that influence the problem solvers’ choices at the forks. Situations are described where it can be desirable to re-direct the path or backtrack on it. Phenomena are identified that can cause the modelling project to get stuck on a poor path. The concept of a path draws attention to the interplay of behavioral phenomena and the sequential nature of modelling processes. This helps understand the overall effect of the behavioral phenomena. A path checklist is developed to help practitioners detect forks and reflect on the path of the modelling project.

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Understanding the failure to understand New Product Development failures: Mitigating the uncertainty associated with innovating new products by combining scenario planning and forecasting (2017)

Derbyshire, J. and Giovannetti, E. (2017) Understanding the failure to understand New Product Development failures: Mitigating the uncertainty associated with innovating new products by combining scenario planning and forecasting, Technological Forecasting & Social Change: http://www.sciencedirect.com/science/article/pii/S0040162516302980

In this paper we show that New Product Development (NPD) is subject to fundamental uncertainty that is both epistemic and ontic in nature. We argue that this uncertainty cannot be mitigated using forecasting techniques exclusively, because these are most useful in circumstances characteristic of probabilistic risk, as distinct from non-probabilistic uncertainty. We show that the mitigation of uncertainty in relation to NPD requires techniques able to take account of the socio-economic factors that can combine to cause present assumptions about future demand conditions to be incorrect. This can be achieved through an Intuitive Logics (IL) scenario planning process designed specifically to mitigate uncertainty associated with NPD by incorporating insights from both quantitative modelling alongside consideration of political, social, technological and legal factors, as-well-as stakeholder motivations that are central to successful NPD. In this paper we therefore achieve three objectives: 1) identify the aspects of the current IL process salient to mitigating the uncertainty of NPD; 2) show how advances in diffusion modelling can be used to identify the social-network and contagion effects that lead to a product’s full diffusion; and 3) show how the IL process can be further enhanced to facilitate detailed consideration of the factors enabling and inhibiting initial market-acceptance, and then the forecasted full diffusion of a considered new product. We provide a step-by-step guide to the implementation of this adapted IL scenario planning process designed specifically to mitigate uncertainty in relation to NPD.

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Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change (2017)

Almeida, S., Holcombe, E. A., Pianosi, F. and Wagener, T. (2017). Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change, Nat. Hazards Earth Syst. Sci., 17, 225-241, doi:10.5194/nhess-17-225-2017.

http://www.nat-hazards-earth-syst-sci.net/17/225/2017/

Landslides have large negative economic and societal impacts, including loss of life and damage to infrastructure. Slope stability assessment is a vital tool for landslide risk management, but high levels of uncertainty often challenge its usefulness. Uncertainties are associated with the numerical model used to assess slope stability and its parameters, with the data characterizing the geometric, geotechnic and hydrologic properties of the slope, and with hazard triggers (e.g. rainfall). Uncertainties associated with many of these factors are also likely to be exacerbated further by future climatic and socio-economic changes, such as increased urbanization and resultant land use change. In this study, we illustrate how numerical models can be used to explore the uncertain factors that influence potential future landslide hazard using a bottom-up strategy. Specifically, we link the Combined Hydrology And Stability Model (CHASM) with sensitivity analysis and Classification And Regression Trees (CART) to identify critical thresholds in slope properties and climatic (rainfall) drivers that lead to slope failure. We apply our approach to a slope in the Caribbean, an area that is naturally susceptible to landslides due to a combination of high rainfall rates, steep slopes, and highly weathered residual soils. For this particular slope, we find that uncertainties regarding some slope properties (namely thickness and effective cohesion of topsoil) are as important as the uncertainties related to future rainfall conditions. Furthermore, we show that 89 % of the expected behaviour of the studied slope can be characterized based on only two variables – the ratio of topsoil thickness to cohesion and the ratio of rainfall intensity to duration.

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Development and appraisal of long-term adaptation pathways for managing heat-risk in London (2017)

Kingsborough, Jenkins & Hall, Development and appraisal of long-term adaptation pathways for managing heat-risk in London, Climate Risk Management, 2017, http://dx.doi.org/10.1016/j.crm.2017.01.001

The risk of residential overheating and mortality is increasing due to the effects of global warming and the urban heat island effect and needs to be addressed through climate change adaptation. ‘Adaptation pathways’ have become widely recognised as an adaptation planning approach, but they have not been utilised for long-term planning for city-scale urban heat risk management. This paper applies adaptation pathway methodology to urban heat risk management. We use spatially coherent downscaled probabilistic climate change projections that account for changes in urban-land cover and the urban heat island to appraise adaptation pathways and inform long-term adaptation planning. We demonstrate that adaptation strategies focusing solely on urban greening or building level adaptation based on current best practice are unlikely to cope with the increasing levels of risk. Air-conditioning may play a growing role in managing heat-risk; however, increasing air-conditioning will exacerbate the urban heat island and further increase the risks of overheating.

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Preparing for disruptions: A diagnostic strategic planning intervention for sustainable development (2017)

Malekpour, S., Brown, R. R., de Haan, F. J., & Wong, T. H. F. (2017). Preparing for disruptions: A diagnostic strategic planning intervention for sustainable development. Cities, 63, 58–69. http://doi.org/10.1016/j.cities.2016.12.016

http://www.sciencedirect.com/science/article/pii/S0264275116301299

Despite the emphasis on sustainable development in some of the contemporary planning and policy rhetoric, we face an implementation deficit in practice. The impediments to the widespread adoption and successful implementation of sustainable infrastructure in cities’ critical sectors—such as water, energy or transport—are varied and complex. Although the scholarship has made some attempts to understand and categorize those impediments, not much has been said about how to identify them in a specific practical context. This study proposes a model for a diagnostic intervention in the ongoing process of strategic infrastructure planning, as a way of revealing context-specific impediments. The diagnostic intervention incorporates an explicit and reflexive consideration of short-term barriers and long-term disruptors into the strategic planning process, and assists with drafting the required coping strategies. The intervention has been tested in water infrastructure planning for one of the world’s largest urban renewal areas in Melbourne, Australia. This trial application provided promising outcomes for addressing the implementation deficit of sustainable development: it created a platform for various stakeholder groups to engage in explicit discussions on their confronted problems, which often have trans-organizational causes and impacts; it enabled reflexivity within the ongoing planning process; and, it helped to consider a large portfolio of future uncertainties to provide an enabling condition for more robust decisions to be made. Moreover, the trialed intervention provided empirical evidence in support of the scholarly discourse which contends that sustainable infrastructure delivery is not only about the development of technical solutions, but is also about the development of processes and tools that support the widespread adoption and successful implementation of those solutions in the face of wide-ranging impediments.

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