Back to all blogs

Simulation and Scenario Modelling: The Future of Smarter Housing Data

Few sectors feel the weight of uncertainty quite like social housing, where every decision carries real-world consequences for people, properties, and communities. It’s no surprise then that the idea of planning ahead in a more dynamic, data-driven way has gathered momentum in recent years, especially as the sector faces increasing regulatory pressure, mounting operational costs, and changing tenant expectations. So it’s no surprise that the theme of “simulation” and “scenario modelling” is quickly moving from theoretical to essential.

Speaking at Mobysoft’s Moving from Data to Smarter Data panel at Housing 2025, Chris Fleck, Chief Product Officer at Mobysoft, put it succinctly: “Simulation is the key thing. Being able to model your business and do ‘what-if’ planning – that’s the future.”

What-If Planning in a Sector That Needs Certainty

Social housing is inherently complex. Tenant needs evolve. Property portfolios age. Funding models shift. In this climate, the traditional approach of reacting to change as it happens simply isn’t good enough. What providers increasingly need is the ability to test potential outcomes before they happen.

This is where simulation tools and scenario modelling come in. Much like stress testing in finance, these tools allow organisations to explore different futures: What happens if we shift resource from reactive repairs to planned maintenance? How might tenant arrears change if Universal Credit thresholds are adjusted? What staffing levels do we need to maintain repairs SLAs during peak winter months?

These are not abstract hypotheticals. They are critical questions tied to service delivery, workforce planning, asset management and financial resilience. And if housing providers can answer them before acting, they stand a much better chance of making effective decisions.

The wider economic environment makes this even more pressing. Inflation, interest rates, and policy shifts all add unpredictability. Scenario modelling in social housing helps cut through that uncertainty and enables boards and leadership teams to plan from a place of insight, not instinct.

From Reactive to Predictive

While many housing associations have become adept at descriptive data analysis (“What happened?”), the next step is prescriptive and predictive insight. That means forecasting likely events and recommending proactive actions to take.

As Fleck explained, “You’ve got a complex business. And a very complex and diverse customer base. Simulation helps you understand: if I change the mix of services, or the type of interventions, what would happen?”

This shift also responds to emerging expectations around transparency and performance from the Regulator of Social Housing. With new Tenant Satisfaction Measures (TSMs) in effect since April 2023, social landlords are under increasing pressure to demonstrate not only what they’re doing, but why they’re doing it. Simulation tools offer an audit trail of thinking that supports this.

The Tech Is Coming — But the Culture Has to Change Too

Mobysoft’s upcoming PropertySense® platform promises to bring together rent, repairs and third-party data to build what Fleck calls the “Mobysoft Property View”: a unified, AI-driven profile of each home and tenant, enriched with vulnerability markers and service histories.

But technology is only part of the equation. Jason Wickens, CEO of Incito Solutions, was candid in pointing out that most housing organisations simply aren’t structured to use data in a truly dynamic way.

“Social landlords aren’t set up to use data in real-time. The organisational structures just aren’t designed for it,” Wickens noted. It’s not a tech barrier, but a human one.

That’s why defining what key terms actually mean – like “repeat repair” or “vulnerability” – matters so much. Fleck put it bluntly: “You can have perfect data, beautifully organised. But if no one knows how to use it, or what decisions to make from it, it’s worthless.”

This alignment needs to happen across frontline, operational, and executive teams. It also needs governance support, so innovation is not paralysed by compliance concerns – a point Wickens elaborated on in the same session.

Four women and one man, all wearing safety vests, meet around a conference table with charts and papers; the man hands a hard hat to one woman, suggesting a discussion or briefing in an office with large windows. ©Mobysoft

Connected Housing Ecosystems

The longer-term ambition? A truly connected housing ecosystem. That means systems and services that are interoperable; where a repair request, income record and vulnerability flag all feed into a single decision-making view.

This is already starting to happen. At Golding Homes, Executive Director Rebecca Taylor spoke about using EDI and repairs data to identify women aged 30-39 as their most frequent repairs users and their most dissatisfied customer group. That insight triggered changes to communication and scheduling strategies – all without waiting for a disrepair claim or complaint.

Meanwhile, data-sharing partnerships with third-party support organisations enabled early interventions that prevented over 100 potential homelessness cases. This is predictive analytics for housing providers, already in motion.

But the next step is scaling it. Automating it. Making it accessible to decision-makers in real time, not months later via static reports.

Getting Ready for a Predictive Future

So what needs to happen next for what-if planning for social landlords to become standard practice?

  • Investment in simulation tools for asset management, workforce planning, and income forecasting.
  • Widespread agreement on data definitions to avoid confusion and duplication.
  • Designing reports for action, not just for board packs.
  • Embedding data specialists within service delivery teams, not siloed in IT or strategy.

The bottom line? Simulation is more than a buzzword. It’s a mindset shift that allows social landlords to be proactive rather than reactive. To use data not just to describe what’s happened, but to shape what happens next.

As Fleck summed up: “If you can simulate what’s coming, you can shape your services around it. That’s what will unlock the next five years.”

Want more insight?

Catch the full Moving from Data to Smarter Data panel discussion from Housing 2025 — now available on the Mobysoft YouTube channel.

Join Chair Engin Yilmaz (Mobysoft) and expert panellists Jason Wickens (Incito Solutions), Rebecca Taylor (Golding Homes), and Chris Fleck (Mobysoft) as they explore how social landlords can strike the right balance between data governance and innovation. Packed with real-world examples and practical takeaways, it’s a must-watch for anyone looking to unlock the power of housing data responsibly.

Mobysoft
Latest posts by Mobysoft (see all)
Tags: , , , , ,