2025 SDP Conference

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Speaker: Lonnie Chrisman (Lumina)

Abstract:

AI language models show promise for reshaping how organizations build and refine decision models. In this presentation, I will examine how an AI assistant helps streamline model-driven decision making by guiding problem formulation, structuring influence diagrams, and reducing the modeling expertise required. Through an illustrative, pre-recorded demonstration, I will showcase the potential for AI-based guidance to accelerate model creation, enhance collaboration, and reveal new insights.

Tom Keelin | My AI Friend

3/25/2025 10:20 AM PT - 3/25/2025 10:40 AM PT

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Speaker: Lee Failing

Abstract:

Gaining clarity about values and objectives is widely recognized as a foundation of good decision making. However, in the messy, increasingly polarized multi-party decision making processes that are common in resource and environmental management, decision professionals face some unique challenges in getting this clarity. This talk aims to offer both high level insights and practical skills related to:- understanding value-based decision making, why it matters, and how to balance this need with the equally compelling imperative to make evidence-based decisions- developing a shared set of objectives with people who have fundamentally different values, and using this to guide a collaborative decision process- leveling the playing field by hearing all voices and including all relevant values – including intangible values that are typically overlooked- making a dedicated space in the decision process for deliberating about value trade-offs and why that’s so critically important- using decision analysis tools and practices to keep the essential complexity in the conversation - fostering the mindsets that help people work together across difference- the critical role of co-learning and shared understanding - about both facts and values.Our experience is that people with wildly different values can work together and agree on solutions. But only if all relevant values are recognized, respected and addressed in a rigorous way in the decision process. As decision analysts and facilitators, we can learn to apply the principles and tools of our craft to help groups have richer and more productive value-based conversations that support better decisions.

Pat Leach | Insights on Integrating People and Process Quality to Empower Great Decisions

3/25/2025 10:20 AM PT - 3/25/2025 10:40 AM PT

Speaker: Somik Raha

Abstract:

One of the six requirements for great decisions is clarity on values. In this fireside chat, we will explore why it is important to get clear on the values behind value metrics, how metrics and values are related, and how we can uncover values.

Michelle Florendo | Emotional Intelligence in Decision Making: Turning Perceived Foes into Strategic Allies

3/25/2025 1:10 PM PT - 3/25/2025 2:00 PM PT

Speaker: Thomas Kehler

Abstract:

This paper describes the result of a long-term effort to create an AI architecture that combines the science of collective intelligence and AI for multi-criteria decision models. Early work on the application of developing causal models of investment decisions was published in a paper accepted for publication in NIPS 2018.1 That work was extended to a general AI architecture for decision intelligence.The system iis based on a Partially Observable Markov Decision Process POMDP using variational Bayesian mechanics as the generalized learning mechanism. The basic structure is to infer a casual decision process model using an adaptive learning strategy. The learning data is obtained via a single-blind, online collaborative process. The model aligns with work done in Active Inference and the Free Energy Principle. The system is learning the collaborating groupʼs (human and AI Agents) Free Energy Minimum—the most likely path to a successful outcome—for any given decision context.The learning model offers a Bayesian approximation model to the law of comparative judgment, commonly known as the A/B test. The system learns and generates a probability distribution relevant to the outcome, specifically a Pareto distribution. This effectively narrows down the choice alternatives by learning the collective preferences. This solution addresses the priority learning problem outlined in Brookʼs law, where the number of communication channels increases with the group size (n*(n-1)/2).The preference learning algorithm builds a Markov model from a sequence of agent prioritization events - agents are presented with a sample and allowed to rank their preferences in response to answers to a question. The evolving Markov model is used to guide the sample selection process. The diagonalized Markov model matrix trace represents the group's ‘resonance modesʼ of choice.

Steve Stein | AI for Organizational Decision Quality 101

3/25/2025 12:50 PM PT - 3/25/2025 1:10 PM PT

Speaker: Peter Wood

Abstract:

Without an appropriate frame in place ‘any path will do’ and teams will find it harder to make choices between alternatives. With a clear Frame that communicates the purpose, perspective and scope it makes decision-making efforts quicker and easier.We must recognize and effectively implement the art of achieving alignment on a well-defined frame, one that is commonly understood by the business sponsors, stakeholders, and the team. Only then can we reliably evaluate the opportunity or problem.

Reidar Bratvold | Impacts of Uncertainty on Decision-Making

3/25/2025 12:50 PM PT - 3/25/2025 1:10 PM PT

Keynote Speaker: Shandin Pete (Assistant Professor, of Teaching in the Earth, Ocean and Atmospheric Sciences Department at the University of British Columbia)

Abstract:

In an era of increasing uncertainty, the decisions we make regarding our environments carry profound consequences. There is a call to challenge conventional approaches to strategy and decision-making by examining the perspectives of systems grounded in land-based knowledge. Specifically, an expanded examination of Indigenous understandings of relationality and reciprocity may offer valuable insights into navigating complexity, fostering resilience, and highlighting ethical and sustainable choices.

Through stories of land, people, and ecosystems, an exploration is engaged to offer a more complete look at Indigenous communities that have long engaged with uncertainty through adaptive practices and a deep understanding of interconnected systems. By recognizing the nuanced exchanges that shape ecological relationships, we can expand our frameworks for relating to environmental and strategic planning.

An invitation is offered to decision-makers to reflect on their own approaches, exploring how principles of reciprocity and relational science can inform corporate, governmental, and global strategies. An attempt is made to broadened perspective on collaborative decision-making while providing a consideration of Indigenous knowledge, not only as a source of insight but as a transformative guide for navigating today’s challenges.

TITLE: How Well Does Decision Analysis Support Decision-Making: A CEO’s Perspective

ABSTRACT: BC Hydro must navigate multiple, and often competing objectives when making long-term capital investments amid uncertain electricity demand, a shifting legal landscape, and evolving market forces. Chris O’Riley, CEO of BC Hydro, shares his reflections on how decision analysis presented to the executive team does - and sometimes doesn’t - help them tackle complex decisions and value trade-offs.

Speaker: Mark Roseland

Abstract:

Community capital frameworks have been used with resounding success in various community types around the world — large, small, rural, urban, developed, developing. These frameworks resonate with very different communities because they encourage people to think strategically and systemically about values, existing capacity, and potential long-term impacts of specific policies, programs, and projects – a critical advance in sustainability innovation.  Furthermore, they help communities with few financial resources to recognize their wealth in other forms and become inspired to organize for community change.  Roseland have introduced the Community Capital Compass as a guide to navigating community change. Focused on sustainable community development, our Community Capital Lab is operationalizing the Compass as a decision-support dashboard available for every US state and county.Recent innovations in digital twin technologies add exciting new possibilities for the Community Capital Compass.  However, there is a growing digital divide between a relatively few larger, well-resourced cities and the more numerous smaller cities, towns, villages and tribes that cannot afford to access these technologies.  How can we use these tools to promote sustainable community development for all?  We are incorporating pilot digital twin initiatives in AZ and in FL, with the aim of democratizing access to these digital technologies and thus greatly expanding access to civic tech solutions that help communities address pressing community sustainability challenges.  Our efforts are designed to result in outcomes that amplify digital proficiency and inventive solutions, heighten community involvement, and bring about enduring sustainability initiatives.

Lyle Walker | Using the RAPID� Framework to Enhance Collaborative Decision-Making for Shared Transportation Objectives

Speaker: Geoff Osler

Abstract:

Mountain Guiding is fraught with uncertainty and risk due to exposure to changes in weather, conditions, and human factors. Furthermore, the number of important decisions over a day of guiding can be overwhelming. A sound process that is underpinned by a clear frame is critical.Training mountain guides in Canada presents the same challenges, along with others. Ultimately, instructors teaching on the courses are responsible for the safety of all the participants in an exam group. Still, they are not in the lead and must give the student leader the space they need to demonstrate their abilities. In other words, the instructor is driving from the backseat and has to choose carefully when, how, and if to intervene. In addition, there is the need to provide good training and ensure that standards are being met. You can see how the decision-making process can be unique and challenging!Instructors must be adaptable, adjusting the frame course to course, day to day, and even decision by decision. This adaptability is crucial, but it must always align and be anchored with the overarching goals set by the Association’s leadership to ensure consistent risk management and curriculum delivery. This can be a tricky balance.We’ll illustrate the framing process that we’ve been using and discuss some of the challenges we’ve had implementing it.

Ellen Coopersmith & Sam Vardy | To Pilot or Not to Pilot - Making the Business Case for New Technology Pilot Plants in the Circular Economy

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Speaker: Amy Day & Michelle Florendo with Lee Failing, Brian Putt & Bruce Judd

Abstract:

This panel will explore the expansive and often unrecognized landscape of Decision Education, highlighting how many professionals are already contributing to this field without explicitly realizing it. The discussion will cover approaches ranging from K-12 touniversity settings, extending into personal, societal, and professional development, to illustrate how pervasive and integral decision-making skills and education are across various domains.Highlights:1. Recognition of Existing Contributions: Emphasizing how attendees might already be involved in decision education through their current roles and activities, potentially without their explicit awareness.2. Diverse Educational Settings: Insights into decision education initiatives in K-12, higher education, and professional development.3. Real-World Applications: Examples of successful decision education strategies that have led to measurable improvements in decision-making skills.4. Broadening Impact: Discussion on how decision education can be evangelized and expanded beyond traditional educational settings to reach a wider audience.Objective: To showcase the breadth of decision education and inspire attendees to recognize their own roles within this critical field, encouraging them to consider how they can intentionally incorporate these strategies into their own contexts to maximize impact.

Speaker: Amy Day & Michelle Florendo

Abstract:

This 40-minute interactive workshop, led by Amy Day and Michelle Florendo, will focus on improving how decision-making professionals communicate with diverse audiences to enhance understanding and engagement. The session is designed to help participants refine their approach by emphasizing empathy, understanding pain points, and adapting their language to resonate with their listeners effectively. It addresses a critical gap in decision-making: the need for meaningful conversations that highlight the necessity of tools for effective decision-making. Highlights: 1. Identifying the Communication Gap: Discussion on how the primary challenge isn’t the lack of decision-making tools, but rather the crucial conversations that make stakeholders realize they need these tools. 2. Interactive Format: The session will engage attendees in practical exercises to practice real-time adjustments in their communication strategies. 3. Audience Engagement: Techniques to identify and address specific audience needs, focusing on creating compelling narratives around decision-making processes. 4. Empathy and Connection: Strategies to foster empathy with stakeholders to ensure communication is not just heard but also appreciated and acted upon. Objective: To empower decision-making professionals to bridge the communication gap by conveying the value of decision tools effectively, leading to better understanding, cooperation, and implementation of decision-related initiatives. Participants will leave with their next step in bridging the communication gap.

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Speaker: Elayne Ko

Abstract:

The use of decision analysis is frequently accompanied by a quantitative cashflow-based evaluation to inform late-stage pharmaceutical drug development investment decision. Currently, cashflow-based decision analytic models rely on subject matter experts within cross-functional teams to provide and/or to approve the quantitative inputs such as revenue from commercial, development costs from finance, risks (probability of technical and regulatory success) from clinical, and timelines from project management.To strive towards decision quality, the decision analysts make a concerted effort to 1) ensure the quantitative inputs are consistent with the decision frame, such as, the target medicine profile, the clinical development plan and 2) collaborate with the cross-function team members to obtain the inputs. However, several factors may contribute to the challenges of obtaining much-needed inputs to complete the quantitative evaluation, which may be a required component of the business case to be reviewed with management at the investment decision-making meetings.The decision analysts can explore various approaches to resolve the input gaps, e.g., leverage previous projects as analogue in combination with sensitivity analyses, to make progress towards completing the cashflow-based decision analytic models to facilitate the decision to fund a late-stage project.

Speaker: Brian Putt

Abstract:

A Cost and Schedule Risk Analysis (CSRA) tells the PM  the range of uncertainty in the cost and schedule, but doesn’t necessarily assist in identifying what is important for management to focus on. Management needs the chance (probability) that a task is on the critical path and the sensitivity of that task. A tornado diagram can help management understand the sensitivity of the overall completion time using P10 and P90 of the uncertainty of each task. The Chance of being on the critical path and the sensitivity of each variable  are then plotted on an XY graph. Management can then focus on those tasks with the highest chance of being on the critical path with the highest sensitivity.

Juan Ribes | Stochastic Multicriteria Decision Making

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Speaker: Sri Vaidyanathan

Abstract:

 In today's world, resources are becoming scarcer, and the burden of using these limited resources needs to be reduced. To address this, a shift from linear to circular supply chains is essential. These systems are complex, involving many stakeholders, reverse logistics, and changes to product design and business models. Circular supply chains aim to eliminate waste, use resources efficiently, and create closed-loop systems where materials and products are reused, refurbished, or recycled. This requires a new way of thinking about value creation in businesses.A structured and practical decision-making approach is essential to manage these complexities. Decision Quality (DQ) principles provide a systematic method to accelerate the transition to circular supply chains. DQ encompasses several key elements: reframing problems to uncover innovative solutions, balancing competing objectives, and improving data quality for better decision-making.Reframing can reveal new opportunities in the circular economy. For example, instead of viewing end-of-life products as waste, they can be seen as valuable inputs for new production cycles. This shift encourages business models and design strategies that focus on resource recovery and reuse. Balancing competing goals in circular models is also crucial. Clarifying values related to environmental impact, economic viability, operational feasibility, and social responsibility supports better decisions.Critical data needs for circular supply chain decisions include information on material flows, lifecycle impacts, and stakeholder engagement. Improving data quality involves addressing data collection challenges in complex, multi-stakeholder environments and finding innovative solutions for supply chain transparency.Case studies from the EU-funded DiCiM project, such as pay-per-use washing machines and circular automotive parts (e.g., tires, steering wheels, headlights, and sprockets), illustrate how DQ principles can be applied in real-world scenarios. These examples demonstrate how a decision-led approach can drive the transition to circular supply chains, benefiting both businesses and the environment

Speaker: Michelle Wellsbury

Abstract:

The Challenge: Power-to-liquid (PtL) fuels and products (e.g. Sustainable Aviation Fuel, e-Methanol, Green Ammonia) are produced via combination of green hydrogen (created from electrolysis of water using renewable energy) with waste CO2. These projects are a key component of the energy transition but face significant commercial and technical hurdles which require innovative solutions and a robust decision-making process.Unlike traditional energy projects, PtL developers often start with a blank sheet of paper in terms of the facility design, product pathway, and even choice of the final product. This presents a significant challenge, in terms of decision quality, since the answer to these questions is not immediately apparent. The decisions involved are complex, inter-linked and affected by factors both within and outside the developer’s control, and even by the rapidly changing regulatory landscape.io consulting will present how they are solving the intricate dynamics of PtL projects, supported by innovative system modelling and Decision Quality.DQ Embedded in System Modelling:- io’s dynamic emerge software allows developers to analyse and screen the entire PtL value chain solution space, including energy source optimisation, hydrogen production sizing and design, hydrogen storage, energy storage, PtL pathway(s) and product storage and offtake.- Inherent in the design of emerge is collaboration in the technical, commercial and environmental aspects of a project. Technical modules simulate and optimise the flow of electrons and molecules. The commercial module uses a large database of facility and component costs. The environmental module simulates the emissions performance across the facility lifecycle ensuring RFNBO compliance. A system solver links the three modules, which optimises the design for the lowest levelised cost of production.By embedding fundamentals of Decision Quality within our tools and processes, we are helping to unlock more projects and accelerate the energy transition.

Mike Benefiel & Mauricio Davidovich | Minimum Functional Objectives for Value of Information

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Speaker: John Mark Agosta

Abstract:

Decision Analysis (DA) and Data Science  teams often operate at cross-purposes,  using distinct frameworks.  This work demonstrates how current machine learning methods can be applied in a principled way to Decision Analysis. For example, machine learning methods do not make the prior explicit, but directly estimate posterior predictive distributions. Estimating likelihoods instead avoids this confounding.  Extending well-known textbook examples, such as value of information analysis, with estimation of likelihoods illustrates how this is possible. The result is a novel analytical approach that combines software tools that solve influence diagrams with Bayesian statistical methods. This advances the computational aspects of  Decision Analysis, aligning it with contemporary evidence-based practices.

Speaker: Max Henrion

Abstract:

As data scientists and decision analysts our job is often to help our clients find more useful decisions. A truck manufacturer wanted an analytical tool to help fleet managers decide how to electrify their fleets. They shared large volumes of telematics data recording for each truck and wanted to know which trucks are best suited for replacement by electric vehicles. But, that turned out to be a useless question. Rather, they must decide which trips are best suited for electric vehicles.

Eva Roa | Make Better Decisions With Data: Using Decision Analysis to Grow Analytical Maturity

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TITLE: Biases: identification, mitigation and their value-destroying impacts

ABSTRACT: Uncertainty, novelty and complexity lie at the heart of many decisions, and DA offers a range of “tools” for dealing with them. But these “tools” are only as good as their inputs. Years of behavioural research show that our brains are just not wired for good reasoning in these situations. We are subject to a variety of hidden biases, rules-of-thumb and judgmental errors that lead to poor decisions and thus worse outcomes than might otherwise be achieved. In particular, uncertainty is not a major problem per se, rather, it is the range of biases and flawed judgements that it opens the door to. This talk will highlight some of the most common, value-destroying biases and show how a cognitive science perspective can offer practical suggestions for avoiding or mitigating them. It will be illustrated by the results of research on 250+ technical professionals, whose jobs have a large element of uncertainty/risk, novelty and complexity. Subject matter expertise does not offer any protection from bias, and in some cases can even amplify it.

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Speaker: Reidar Bratvold & Tom Keelin 

Abstract:

Probabilistic forecasts often suffer from biases, typically leading to optimism and overconfidence. This results in benefits being overestimated, schedules and costs underestimated, and an overly narrow range of forecasted outcomes. In decision analysis, unbiased probability assessments are essential, as biased forecasts result in biased decisions, ultimately reducing the value promised when the investment decisions are made.Reference Class Forecasting (RCF) has been proposed as a solution to these biases. RCF, by adopting an "outside view," is effectively de-biasing forecasts compared to traditional, model-based methods, thereby supporting high-quality decision-making. However, despite its proven effectiveness and simplicity, the adoption of RCF has been limited. Many experts prefer more complex model-based approaches such as Monte Carlo simulations, ensemble methods, and machine learning, which are perceived as more rigorous because they use well-established numerical approaches and account for project-specific details (the "inside view").To address this challenge, we introduce a Metalog-based Bayesian approach that integrates reference class information with model-based forecasts. In this approach, the Bayesian prior is informed by the reference class, while the project-specific forecasts serve as likelihood functions, reflecting detailed project data. The Metalog distribution offers virtually unlimited shape flexibility, allowing for close matching of empirical distributions and generating continuous forecast updates as new data becomes available. This methodology was tested on real-world oil mega-projects, demonstrating that it removed bias from the original forecasts.Our findings suggest that the Bayesian RCF approach performs as well as, if not better than, classical RCF. Moreover, it offers distinct advantages, including increased transparency, flexibility in balancing the reference class with project-specific information, and a consistent statistical framework. We believe this approach may bridge the gap between those who rely on more complex model-based approaches and the benefits of adopting RCF, encouraging broader adoption, unbiased forecasts, and reduced bias-driven value destruction.

Speaker: Marc Bond

Abstract:

The human brain is a wondrous but flawed instrument. The ability of one’s brain to problem solve is immense. However, research has shown that, it is an imperfect engine. This adaptation has led to instinctive, intuitive, and emotional based techniques for problem solving and decision-making.These heuristic methods speed up the process of finding a satisfactory solution with little effort. Many times, these methods serve us well and lead to a satisfactory outcome. However, they also can lead to irrational behaviours, misguided interpretations, and poor decisions, otherwise known as cognitive biases. These biases allow for simple conclusions but often introduce systematic and repeatable errors. Due to the complicated nature of many businesses, several situations require more thorough analysis and critical thinking rather than the simplest and fastest route to a decision.The oil and gas industry, for example, is full of highly creative and intelligent people, leading to some outstanding successes. As decisions are often made in highly complex and uncertain situations, cognitive biases have occasionally led to costly decisions. Although some of this can be credited to technical failings, motivational biases, or circumstances beyond our control, often they can be attributed to cognitive biases.There are several mitigation strategies. One of significance is adopting and adhering to an assurance process. Exploration assurance helps to ensure consistent, objective, and independent evaluation on exploration project characterization and decisions. Left to the individual assessor or team, the predicted outcomes are often inconsistent and inaccurate. While the assurers themselves certainly can fall prey to cognitive biases, their independence from the work and wider perspective can shield them from some of the biases associated with prospect ownership or local management influence. Validation of technical assessments by exploration assurance has been shown to contribute to consistent and predictive portfolio management, and thus improved business performance.

Michael Doane | NLP-based Optimization of Success Estimates for Neuroscience Programs

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Speaker: Carl Spetzler 

Abstract:

In our current highly fractured society, Civil Discourse on controversial topics is a rarity. Our field provides a paradigm that can be the heart of civil discourse: Clear separation of preferences from alternative points of view; dedication to unbiased information; prediction of consequences based on sound reasoning; and a systematic dialog process to reach clarity before making up our mind. The skills to facilitate Civil Discourse are the same as those needed to be an effective Decision Professional. The need and hunger for such discourse seems palpable all around us. This presents an opportunity for us to be of service beyond our traditional decision consulting activities.

Speaker: Nathan Block

Abstract:

Effectively addressing issues such as climate change and rapid deployment of AI requires not just better decisions, but wiser decisions – decisions that better account for the broad range of considerations inherent in world’s use of energy.  A scientific study of wisdom has emerged and is providing educational models and practical tools that can promote wiser decisions. Making higher quality, more ethical, and wiser decisions about global challenges is of such import that it is time to fulsomely integrate the insights of these sciences.  To this, we must add an orientation toward a common good and a long-term, future focused perspective — generativity.  With that structure, wisdom can become phronesis – practical wisdom - and translate to an ability to encounter new situations and make high quality, wise decisions. The base is formed from a cognitive-focused model grounded in an awareness of the multiperspectival nature of complex situations, the limitations of one’s own knowledge, and the unpredictability of the future.  From there, insights from decision sciences are blended with those from the academic study of wisdom to outline a model for making wiser, more ethical, high-quality decisions.   This talk is based on a paper entitled, “Willful Wisdom: Harnessing Insights from Decision Science Toward Wiser Decision-Making on Climate Change and Energy Transition”  54 St. B. Tex. Envtl. L. J. 1 (Spring 2024).   https://www.texenrls.org/wp-content/uploads/2024/09/telj_54n1_text_low.pdf

Jennifer Harrington & Jim Driscoll | Decision Leadership: Insights, Opportunities, and Implications

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Speaker: Eric Johnson

Abstract:

An analysis was performed for the senior management team of "Queens", which was facing issues concerning IP litigation in various venues, alliances, M&A, and business operations. 100 interviews were conducted with C-suite members which encoded their expertise in a belief net with dozens of variables.  Assessment of legal expertise was difficult because explicit specification of a numeric probability might lead to liability issues, the outcomes of some variables are "soft" and not well defined, and assessment of future enterprise value in a variety of possible situations was complex and information-intensive.Methodologically, we found that:Modeling the value implications of ultimate outcomes explicitly and then analyzing such valuations from the point of view of information known at a previous time point gives a helpful assessment of stock values along the way.Using verbal terms for probability and asking that they be situated along a line that we interpret probabilistically allows quantitative analysis without requiring explicit numeric assessment.Using constructed verbal scales with simple point-count scoring attached to the terms gives a useful way to characterize soft concepts like management distraction or distributor concerns.Using discretized conditioning scales allows two-dimensional assessments to be tractable and comprehensible.Substantively, we found that Queens' operational and balance-sheet strength gave substantial negotiation leverage, but that timely settlement was necessary.Informed by this analysis, Queens settled the litigation promptly and tripled the value of its stock.

Speaker: Ulf Andresen, Subhas Das & Oro Awaritefe

Abstract:

Whale is a multi-billion dollar deepwater mega project that entered its execution phase after the Final Investment Decision (FID) in 2021, aiming for startup late 2024. While the ideal scenario is to maintain a "no change mindset" post-FID, external dynamic factors can necessitate changes to manage risks and preserve project value.Traditionally, the Management of Change (MOC) process governs changes during execution, involving a small team that ensures safety, compliance, and operability through a formal review and approval process. Practiced for decades, this piecemeal approach is efficient in delivery but often leads to limited articulation and ownership of ideas potentially leaving value uncaptured.For the Whale project, the MOC process was enhanced by integrating the Decision Quality (DQ) framework, involving a broader participation across disciplines. This inclusive approach expands the range of alternatives and ensures comprehensive decision-making taking risks and inter-dependencies into consideration, whether changes are reactive or elective. Despite initial challenges originating from cultural resistance and unfamiliarity, the DQ process has proven effective in minimizing rework and fostering value-based decisions beyond mere cost and schedule considerations.As the project neared its final year, a significant risk emerged, prompting the team to adapt quickly to protect the startup date and resolve conflicts. The DQ mindset, practiced throughout the project, made critical decision-making elements—like framing, identification of alternatives and value trade-off analysis—second nature. This facilitated data-and logic-driven discussions for critical decisions.The presentation will highlight practical examples, such as prioritizing pipelay vessels across overlapping offshore construction activities under uncertain weather conditions, where nominal burn rates can reach up to $2 million per day for offshore vessels. This approach underscores the importance of robust decision-making in complex project environments.

Phil Bradshaw | But What Did We Learn? Mapping the Process and Products of Collective Learning from Collaborative Planning

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Speaker: Erik Schneider & Diana Del Bel Belluz

Abstract:

The post-COVID reset, culture wars and the advent of generative AI have all impacted how organizations make decisions. How have these changes impacted organizational decision-making? Our Decision Capabilities Benchmarking Model is a novel framework designed to evaluate just that. Successfully tested with clients pre-COVID, we’re updating it for use by decision-making professionals in the new era. Comparative Analysis and Model Differentiation Our model goes beyond traditional frameworks to examine decision factors such as decision dialog, quantification, external stakeholders and lookbacks. This multidimensional approach results in practical insights across diverse organizational settings, including: ● Risk Management vs. Bias Awareness (balancing analytical assessments against psychological decision factors) ● Framing vs. External Stakeholders (revealing gaps between internal focus and external engagement) ● Collaborating to Align vs. Decision Governance (assessing governance in regards to collaboration) ● Learning Organization vs. Lookbacks (highlighting unfit training and gaps in feedback mechanisms)● Decision Dialogue vs. Risk Quantification (showing relative emphasis between data and discussions around it)Collaboration and Benchmarking InitiativeCentral to our initiative is a collaborative benchmarking effort, and we seek the support of SDP in distributing the survey to its members to ensure the robustness and accuracy of its findings. A comprehensive analysis would benefit all facets of the decision-making community, ensuring the model's relevance and effectiveness. We further invite SDP attendees to engage with the model's conceptual framework and potential applications, encouraging contributions that will refine and enhance its utility.

Speaker: Wayne Borchardt 

Abstract:

Empirical evidence for the relationship between decision quality and company performance has been elusive. Our regression results now show a robust, statistically significant confirmation of what we all suspected: Decision quality is indeed positively related to company performance.PwC’s 28th annual Global CEO Survey was conducted in late 2024 and collected the responses of 4,701 CEOs across all major industry sectors and 109 countries. The survey findings yield a strong connection between the profitability of companies and their mindsets and practices for strategic decision making. Specifically, our regression analysis found that companies who score in the top quintile of a decision-quality index created from the survey data have almost 30 percent higher industry-adjusted profitability than the others.Although we cannot make a causal claim, these findings have implications for CEOs who are likely unaware of the extent to which decision quality mindsets and practices are associated with better performance. Their leadership in instilling decision quality in their organizations might have profound effects.

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Speaker: Jim Driscoll & Jordan Stephens

Abstract:

Acquiring the skills of a decision professional isn’t easy. Many of us “never went to school for this,” and instead have had the good fortune to learn our craft from gifted colleagues, via intense self-study, and/or through years of trial and error.After over a decade teaching DQ/DA skills via traditional classroom methods - only to see those programs disrupted by the pandemic - the team within Intel's Center for Decision Leadership asked a critical question "how can we develop true DQ/DA skills in as many others as possible, at scale, and with limited resources?" Their answer is an innovative skill-building program that: Leverages the research on what makes learning “sticky” and promotes the acquisition of new skillsUtilizes automation to reach as many Intel employees as possibleHelps many individuals who wouldn’t or couldn’t take advantage of more traditional teaching methods get started on their DQ/DA learning journey Keeps learners active, engaged, and feeling supported.

Speaker: Charles Persinger

Abstract:

The number of “Decision Professionals” is limited compared to the vast number of decisions that could benefit from achieving “Decision Quality.” At Eli Lilly and Company, a small group of trained Decision Professionals has successfully broadened their impact within the Research and Development organization by leveraging collaboration. This approach includes training, tool development, embedding best practices into business processes, and fostering a decision-making culture. As a result, the group has significantly extended their reach, enabling Decision Quality for a higher volume of decisions and achieving Organizational Decision Quality. This success was recognized with the Raiffa-Howard Award from the Society of Decision Professionals.

Tobias Muller | Optimizing Decisions in Equinor: an Approach to Collaborative Subsurface Decisions

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Speaker: Chris Spetzler

Abstract:

Ron challenged us to teach more than just "DQ light”, to help every individual understand powerful concepts like conditional probability. Common sense DQ is accessible, even inspirational, in a short session  of 60-120 minutes. Stretching for deeper lessons, such as probabilistic reasoning in the face of uncertainty, requires greater time and intention. Decision Professionals can rely on high quality media, materials and delivery models developed by DEF to meet the rewarding challenge of working with educators, parents and youth.

Speaker: Jeremy Alexis

Abstract:

Illinois Tech is pioneering a Decision Quality (DQ) capability to enhance institutional decision-making, integrate DQ principles into the curriculum, and extend expertise to external stakeholders. This initiative is structured around three key workstreams: Internal Capability Development, Curriculum Integration, and External Outreach and Services. Internally, we have started intensive training, with a two-day session for academic leadership and a 12-week course focused on analysis, with participants spanning faculty, administration, and industry partners. A major case study on the future of graduate housing is underway, engaging top university decision-makers to demonstrate the DQ process. Additionally, DQ principles are being embedded into committee facilitation, strategic planning, and faculty decision-making processes. Curriculum integration efforts include the development of three structured DQ modules—DQ Overview, DQ Analysis, and DQ Consulting—to support Illinois Tech’s core curriculum redesign. To further strengthen applied learning, DQ tools are being created for integration into project-based courses such as interdisciplinary workshops, capstones, and co-ops. Externally, Illinois Tech is expanding its impact through an esteemed Board of Advisors, a webinar series, and online DQ learning resources in collaboration with leading organizations. The Center aims to achieve key milestones, including embedding DQ into high-level university decisions, securing financial sustainability, integrating DQ modules into undergraduate programs, and establishing Illinois Tech as a national leader in decision-making excellence. By measuring our success against benchmarks such as webinar engagement, institutional partnerships, and strategic planning outcomes, we are positioning DQ as a transformative force in education, leadership, and decision science. Finally, we will measure our success against benchmarks of the Raiffa-Howard award, charting our progress over the next three years as the center becomes embedded in our culture and systems.

Ali Abbas & Carl Spetzler | Integrating Ethics into Decision Curriculum

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Each year, the society awards a select few individuals or teams Hero awards in acknowledgement of their achievements in transforming and growing our profession and society. We therefore ask that you please take a moment to nominate candidates for the following awards:

Pioneer Award
Inspirational Achievement Award
Early Career Excellence Award
Community Service Award
Distinguished Service Award

Ron Howard’s unparalleled contributions to the field of Decision Analysis and his profound impact on countless lives deserve a heartfelt tribute. This reflection honors his remarkable journey and celebrates the enduring legacy he leaves behind.