Strategic Urban Foresight
Interview with Ben Dru + Julia Barashkov of Urban Futures Lab
As cities face growing uncertainty driven by shifting work patterns, climate stress, and cultural transformation, traditional urban planning methods may fall behind the speed of changes.
At CDFAM Amsterdam, Ben Dru and Julia Barashkov of Urban Futures Lab will present their framework for integrating computational analysis with cultural insight and stakeholder engagement into urban planning.
Their methodology seeks to move beyond static forecasts, using social data and local knowledge to explore multiple future scenarios.
In this interview, they discuss the limits of conventional planning, how trend data can be made meaningful, and what urban designers and computational modelers can learn from more adaptive approaches to future-making.
Can you start by introducing yourselves and the mission of Urban Futures Lab, and give us an overview of what you’ll be presenting at CDFAM Amsterdam?
We mitigate uncertainty through urban trend forecasting that challenges conventional planning approaches.
Traditional urban plans aim to reach arbitrary KPIs without questioning their relevance to how people actually want to live, work, shop and rest in the future, when these plans are implemented.
At CDFAM Amsterdam, we’ll demonstrate how our socially and culturally driven methodology creates more adaptive and resilient urban visions.
Your methodology blends computational analysis with cultural insight and stakeholder engagement. What motivated you to move beyond conventional trend forecasting models in the urban context?
Traditional trend forecasting relies on past patterns to predict the future. It focuses primarily on economic real estate trends or ecological climate factors. These methods fundamentally assume society and culture will remain static, which misses the crucial reality that human needs and behaviors constantly evolve.
Plans designed without accounting for social and cultural transformation become obsolete before they’re even completed.
How do you balance the quantitative data with qualitative cultural factors when building these urban scenarios?
Quantitative data reveals what’s happening, while qualitative cultural factors help us understand why these patterns matter and how they might evolve.
We gauge sentiments and preferences exhibited through various data sources. We then cross-reference them against drivers we identify through horizon scanning.
This helps us create urban scenarios that account for both measurable trends and the unmeasurable human experiences that shape cities.
Rather than predicting a single outcome, you focus on expanding the range of possible futures. How has this approach changed the way cities and organizations respond to uncertainty?
People have a tendency to plan for a desirable outcome. Expanding the range of possibilities prepares cities to address challenges before they become crises.
Considering a range of possibilities helps organizations develop strategic agility. By identifying critical uncertainties they can rehearse diverse response scenarios. This helps us go from forecasting into active future-making.
Can you share an example of a project where your strategic foresight framework helped shape meaningful decisions or interventions in a real urban environment?
We’re working with The Hague municipality on their policy to relocate office spaces from suburban areas into the city center while converting those outer zones to residential housing. They were unsure how to design these mixed-use developments for the future.
Using our strategic foresight framework, we analyzed emerging work patterns and identified key trends like hybrid work models, the need for flexible spaces, and changing commuting behaviors. Our analysis showed that traditional office designs were becoming obsolete.
Based on our insights, The Hague shifted their approach and are now experimenting, with our guidance, with several housing and planning models.
As you join CDFAM Amsterdam this year, what are you hoping to contribute to the conversation around computational design, and what kinds of insights or collaborations are you looking forward to?
We’re integrating socio-cultural metrics into computational analysis to expand the dialogue beyond technical optimization.
Computational models often miss the human dimension of cities’ cultural, emotional, and social contexts that determine whether designs succeed or fail.
We’re looking for collaborations that can help translate complex urban systems into accessible frameworks for democratic decision-making about our shared futures.
To connect with Ben, Julia, and other designers working across architecture, infrastructure, culture, and computation, join us at CDFAM Amsterdam 2025. Whether you’re building systems at the scale of a city or a component, CDFAM brings together people exploring how design can adapt to uncertainty and shape better outcomes. Register to attend now, space is limited.
