Good Judgment Inc

I just wrapped up the 2-day Good Judgment Inc. Workshop with Warren Hatch, PhD, Marc Koehler, and Eva Chen, and it was fantastic! The content was excellent and incredibly practical, diving deep into the art and science of forecasting. The unexpected highlight was the group itself. It was one of the most uniquely thoughtful, globally diverse rooms I’ve been part of in a long time. People from different countries, disciplines, and worldviews all working through the same forecasting problems, and arriving at completely different (and often brilliant) angles. A few ideas that really stuck with me: • Great forecasting is a team sport: teams tend to be 10% more accurate than individuals! • Calibration beats confidence: systematic thinking, the BIN (Bias–Information–Noise) framework, and continuous updating consistently outperform intuition. • Better judgment is trainable: the shift from an inside view to a strong outside view compounds quickly. • Hybrid forecasting matters: strategically blending different reasoning styles, AI, and perspectives often yields the most accurate predictions. Grateful for the experience and the brilliant people I met. Highly recommend it to anyone serious about sharpening their judgment or improving decision quality. Brian Murray Barclay Lincoln Burns Jared Peterson Daniel Wilde Bryce Trueman Christian Berger

Here are some predictions for the coming year, from the experts at Good Judgment

I just signed up for the Good Judgment Inc two-day forecasting workshop, and I’m super excited! For those who aren’t familiar, the Good Judgment Project (founded by Philip Tetlock and Barbara Mellers) is the research team behind the concept of Superforecasting, using structured reasoning, calibration, and probabilistic thinking to make better predictions about uncertain futures. This connects directly to the work I’ve been exploring in Forecasting for Founders: how founders can apply the same forecasting mindset to startups, to make better bets, avoid overconfidence, and stay aligned with reality as it changes. Over the next few weeks, I’ll share some takeaways from the workshop and how these forecasting techniques translate from global events to product roadmaps, hiring plans, and fundraising timelines. Warren Hatch, PhD Brian Murray Vicente Kripka Daniel Wilde Jared Peterson Domingo Valadez https://lnkd.in/gcXY75WK #forecasting #decisionmaking #startups #superforecasting #learninginpublic

Turning Broad Scenarios into Actionable Forecasts At Good Judgment Inc, we map futures, not just bet on them. We use three key processes inspired by the Hancock-Bezold framework to sort what’s probable from what’s possible, preferable, and plausible. It’s an à la carte model, where we can pick and choose or combine the processes as needed for the task at hand. Strategic Foresight asks about plausible future worlds, identifying the driving forces (such as technological, economic, social, political, environmental) that combine into different scenarios and storylines to show decision makers the implications, risks, and strategic options. Subject matter experts are often the key players in this process, which has much in common with scenario planning. Often, clients will already have developed their scenarios. In other cases, we can collaborate with our strategic partners at ForgeFront to advance the foresight process, as we recently did on a joint project for the UK government on global biorisks. Policy Guidance brings in the decision makers to narrow the focus to their preferable worlds so that we're not chasing rainbows and instead evaluating their short list. The preferable worlds could include possible futures that didn't make the plausibility cut in the foresight process. Forecasting narrows the focus to which worlds are more probable. In this process, it's good to strip away the storylines that were generated by the scenarios (strong narrative drives can lull people into thinking something is more likely than is warranted) and to conceal the goals and identities of the decision makers (which can likewise tilt the scales). Ideally, your forecast will come from a crowd since we know that will deliver more accurate forecasts than any single individual over time. And the best crowd is Good Judgment's panel of professional Superforecasters. We've used versions of this framework since the early days of Good Judgment Inc. One of our first projects was for a multinational food manufacturer on alternative protein trends. We've also provided due diligence support for consulting agencies, investment firms, and government agencies. Here's how we applied this process in our recent project for the UK government with our ForgeFront colleagues: 1. Define the possible scenarios of concern 2. Distill the scenarios to the major threat of concern, in this case biorisk hazards 3. Identify specific biorisk hazards, such as the use of autonomous drones to deliver biological agents 4. Set a decision threshold that would activate a decision process 5. Pose the questions to the Superforecasters to generate the probabilities 6. Deliver a report with the probabilities, the drivers, and risks to the outlook By  integrating structured scenarios with decision thresholds and Superforecaster probabilities, we help leaders act sooner, with more confidence, and measure what matters. If that’s the discipline you want around high-stakes decisions, let’s connect.