Modelling and simulation

Modelling and Simulation

Understanding complex systems, testing policy scenarios, and forecasting outcomes with confidence

Mortar's Modelling and Simulation practice helps organisations move from reactive decision-making to evidence-led foresight. We build bespoke analytical models and simulation environments that allow you to understand how complex systems behave, test the potential impact of policy and service changes before you implement them, and allocate resources where they will have the greatest effect.

Our tools are designed to be accessible and actionable — not just technically impressive. We translate complex analytical outputs into clear, interpretable insights that decision-makers can act on with confidence.

How it Works

We work with your analysts, policy leads, and operational teams to understand the decisions you need to make and the data you have available. We then design and build models that are calibrated to your context — whether that is a discrete event simulation of a housing service, an agent-based model of community behaviour, or a statistical forecast of demand.

Problem scoping: Define the decision you are trying to support, the variables that matter, and the data that is available — before writing a single line of code.
Model design and build: Develop a model that reflects the real-world system you are working with, validated against historical data and stress-tested for edge cases.
Scenario testing: Run structured simulations to explore how the system responds to different inputs, interventions, and external conditions.
Insight communication: Present outputs clearly — through interactive dashboards, scenario reports, and facilitated workshops — so that findings translate directly into decisions.

Key Features

Our Modelling and Simulation solution brings rigorous analytical methods to bear on the policy and operational challenges facing public sector organisations.

Demand Forecasting We build statistical and machine-learning models that forecast service demand over time. These models account for seasonality, demographic trends, and the effects of policy change — helping organisations plan capacity and allocate resources more effectively.
Discrete Event Simulation We model the flow of people, cases, or resources through a service system, identifying bottlenecks, wait times, and capacity constraints. These simulations are particularly valuable for redesigning pathways in health, housing, and social care.
Agent-Based Modelling We build agent-based models that simulate the behaviour of individuals within a system — capturing the complex, emergent dynamics that simpler models miss. These models are well-suited to exploring the effects of policy interventions on community behaviour and outcomes.
Scenario Planning and Sensitivity Analysis We run structured scenario analyses to test how robust your plans are under different assumptions. By systematically varying key parameters, we identify the conditions under which outcomes are most sensitive to change — and where your decisions are on solid ground.
Interactive Dashboards and Visualisation We present model outputs through intuitive, interactive dashboards that allow decision-makers to explore scenarios themselves. Our visualisations are designed for clarity — making complex analytical outputs accessible to non-technical audiences.
Model Validation and Peer Review We apply rigorous validation processes to all our models, testing outputs against historical data and subjecting our methods to internal and external review. We document assumptions, limitations, and uncertainty clearly, so that users can interpret results with appropriate confidence.

Case Study Highlight

Mortar developed a demand forecasting model for an integrated care partnership in the north of England, projecting service demand across housing, health, and social care over a five-year horizon. The model enabled commissioners to identify a significant funding gap eighteen months earlier than previous planning methods — allowing them to redesign service pathways before the shortfall became a crisis. Read more

Why It Matters

Public services operate in environments of genuine complexity. Demand is hard to predict, resources are constrained, and the consequences of poor decisions fall disproportionately on the most vulnerable. Modelling and Simulation gives organisations the tools to navigate this complexity — not by eliminating uncertainty, but by understanding it well enough to make better decisions.

The value of modelling is not in producing a single definitive forecast. It is in creating a shared, evidence-based frame for conversation — one that helps organisations align around what they know, acknowledge what they don't, and plan accordingly. Our models are designed to support that conversation, not replace it.

Get in Touch

If your organisation is facing decisions about capacity, investment, or service redesign that would benefit from better analytical foundations, we would be glad to discuss how our Modelling and Simulation practice can help. Get in touch to find out more.