Decision-Centred Modelling (DCM)

Foundations, Architecture, and Application to Industrial Process Heat Decarbonisation

Seyed Ahmad Mahmoudi Lahijani

2026

A Framework for Complex Decisions Under Deep Uncertainty

Decision-Centred Modelling (DCM)

Foundations, Architecture, and Application to Industrial Process Heat Decarbonisation

"The decision makes the boundary; the artefact makes the connection."

Read the Framework → GitHub Discuss

The Central Problem

Most planning problems look tractable until you realise that the consequences which will determine whether your decision was right lie outside the model you used to make it. Outside the physical boundary. Outside the time horizon. Outside the organisational perimeter. Outside the domain any single expert was trained to see.

This framework is a response to that structural problem. It applies to infrastructure planning, corporate strategy, policy design, financial decisions, and anywhere that long-horizon commitments interact with genuine uncertainty and multiple stakeholders who see the same situation differently.

Three Questions This Framework Addresses

When should the boundary of your analysis be different from the boundary of the system you are studying? Conventional modelling draws boundaries around what is physically tractable. Decision-centred modelling draws them around what must remain visible for the comparison to be valid — which is often much larger, and almost always different.

How do you compare alternatives honestly when no one can agree on the probability of the futures that determine which is better? Not by assigning probabilities anyway and computing expected values. By evaluating how each alternative behaves across the full range of plausible futures — measuring regret, robustness, and satisficing rather than a single weighted average outcome.

How do you build an environment that can grow toward what matters without destroying what it has already established? Through governed artefacts, stable interfaces, and progressive refinement guided by what the diagnostics reveal as most consequential next. The architecture is self-directing: at each step, it reveals where the analytical torch should turn next.

This Framework Is For

Researchers

Working on DMDU, integrated assessment, and complex systems. The architecture provides a modular, governed basis for multi-scale exploration.

Practitioners

Infrastructure planners, energy analysts, and strategists navigating long-horizon commitments under genuine uncertainty.

Policymakers

Seeking analyses that reveal system-level incentive misalignments invisible to single-perspective assessments.

Anyone

Facing decisions where the most consequential outcomes lie outside the frame you started with. The thinking applies far beyond engineering.

Four Principles

Decision First

Boundaries are drawn by the decision context, not by physical system extent. The model develops toward what influences the decision, not toward completeness of the system description.

Governed Artefacts

Every output that enters the comparison chain is schema-conforming, provenance-carrying, and validation-gated. Without governance, results cannot be trusted across versions or questioned after the fact.

Deep Uncertainty

When probabilities over futures are contested, the right standard is robustness: how does this choice perform across the range of conditions that cannot be agreed upon?

Progressive Refinement

A bounded, honest starting point that reveals its own next steps is more valuable than a comprehensive but opaque system. The architecture is designed to grow toward what matters.

Modules from orientation to synthesis

Sub-modules with technical specifications

Propositions constituting the intellectual claim

∞

Domains this architecture can be applied to

The Framework at a Glance

Diagram 1: Seven analytical layers — from facility demand construction through the governed backbone to the decision layer.

Diagram 2: Module dependency map — prerequisite reading paths across Modules 0 through 7.

Navigate by Purpose

If you are...	Start here
New to this framework — start here	Module 0: Orientation (15 min)
A researcher in DMDU, integrated assessment, or systems modelling	Part I: The Decision Problem
An energy system modeller or tool developer	Part II: The Framework Design
A practitioner or corporate strategist	Module 4: Domain Translation
Working in NZ energy policy or infrastructure	Module 5: NZ Context
Interested in the full proof of concept and results	Part IV: The Proof of Concept
Evaluating the intellectual contribution	Module 7 §7.6: Eleven Propositions
Thinking about applying this outside energy systems	Module 7 §7.9: Beyond Infrastructure
Wanting to contribute a domain extension	GitHub Discussions

How to cite this work

Mahmoudi Lahijani, S.A. (2026). Decision-Centred Modelling (DCM): Foundations, Architecture, and Application to Industrial Process Heat Decarbonisation. Open framework platform. Auckland University of Technology. https://ahmad-mahmoudi-coder.github.io/DCM/

Related publications
Lahijani, A.M., Protheroe, M.D. & Gschwendtner, M. (2025). A modelling tool selection for decarbonising industrial process heat systems. Renewable & Sustainable Energy Reviews, 210, 115149. doi:10.1016/j.rser.2024.115149
PhD thesis and preprint: available after examination and submission (2026).

Seyed Ahmad Mahmoudi Lahijani — 2026 · Auckland University of Technology · Repository · Glossary · Contribute

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