Research approach

ReSolVe develops tools to help organisations choose viable supply-chain strategies as regulation, climate and markets change. The research connects disruption analysis with decisions about sourcing, inventory and network design, and tests these methods in Heineken’s packaging and brewing supply chains.

Research gap

From seeing disruption
to deciding what comes next.

Supply chains have greater visibility than ever. Yet regulatory requirements, cascading risks and changing conditions are often assessed separately.

ReSolVe connects them in one planning framework, so organisations can compare responses across continuity, cost and compliance.

Explore the concept model
A lime route connects two supply networks across a divide, illustrating the link between visibility and resilient planning.

See the disruption

Understand exposure across the network.

Compare responses

Connect risk, regulation and trade-offs.

Plan for resilience

Inform sourcing, inventory and network design.

Concept model

Changing conditions inform the resilience engine. It compares possible responses to support sourcing, inventory and network decisions. Select a condition to explore an example.

External conditions

Resilience engine

ReSolVe
01

Optimisation

Continuity · cost · compliance

02

Adaptation

Scenarios that evolve over time

03

Benchmarking

Strategies on shared measures

Planning strategies

Strategy options

  • Sourcing
  • Inventory & buffers
  • Network design
Resilience + regulatory readiness

Regulatory integration

A new carbon-border requirement changes the exposure of materials and suppliers. The engine brings that constraint into the comparison of sourcing and network options.

Illustrative planning pathways. This explains the research model; it is not a live simulation.

Objectives

Assess resilience

Develop a modular resilience assessment framework with regulatory requirements expressed through operational, financial and compliance indicators.

Compare responses

Develop and validate a resilience engine integrating cascading risk propagation, dynamic scenarios and multi-objective optimisation.

Test in industry

Validate the framework in two Heineken pilots, using procurement and operations data from packaging and brewing supply chains.

Support adoption

Define adoption pathways and scalable reuse models, supported by open-access tools, regulatory templates and stakeholder engagement.

Research questions

RQ1

Can resilience be formalised as a computable design variable by integrating regulatory constraints and multidimensional KPIs into supply-chain planning models?

RQ2

To what extent can adaptive planning engines simulate cascading and evolving disruptions across policy, climate and trade, and how do these simulations affect sourcing-strategy robustness?

RQ3

Which institutional and operational factors affect the adoption and usability of resilience planning tools, and how can toolkits support scalable, policy-aligned deployment across sectors?

From research to practice

Develop the methods, test them in industry,
and make them usable across supply chains.

Modelling

Connect regulatory requirements and disruption risks with the decisions organisations need to make.

Validation

Test the methods in Heineken’s packaging and brewing supply chains, using real procurement and operational data.

Adoption

Translate the research into accessible tools, guidance and training for businesses of different sizes.

Research activities

WP1: Resilience assessment framework

A modular methodology to quantify resilience trade-offs across operational, financial and regulatory dimensions. TU Delft and KPMG co-develop the framework; KPMG leads the work package.

1.1 Assessment framework and KPIs

Combine multi-criteria decision analysis and risk-propagation modelling. Define indicators and validate the methodology through practitioner consultation.

1.2 Regulatory integration

Classify CBAM, CRMA and CSDDD requirements by financial, operational and risk relevance. Integrate compliance pathways into resilience assessment.