Food Decision Engineering Tools

IFoRAC develops practical tools that help governments, international organizations and food-system actors identify priorities, compare options, manage uncertainty and monitor results.

Our decision briefs, analytical models, dashboards, interactive applications and AI-assisted workflows make Food Decision Engineering operational.

Built around a decision. Designed for repeated use.

Food systems generate growing volumes of information: laboratory results, surveillance data, inspections, outbreak reports, consumption surveys, scientific publications, trade information, climate indicators and supply-chain signals.

However, information may remain distributed across different systems, organizations and technical disciplines. Decision-makers can struggle to determine what matters, what requires action and which option offers the greatest expected benefit.

Food Decision Engineering tools organize evidence around the questions decision-makers need to answer:

1. What matters most?
2. What requires action now?
3. Which options are available?
4. What impact could each option produce?
5. What uncertainty could change the decision?
6. How will we know whether the action worked?

The purpose of a tool is not to display more data. It is to make an important decision clearer, more transparent and more repeatable.

A Food Decision Engineering tool begins with a clearly defined decision—not with a preferred model, dashboard or technology.

It connects:

• The decision and its accountable owner
• Scientific evidence and risk assessment
• Operational and surveillance data
• Expert knowledge and institutional experience
• Feasible risk-management options
• Uncertainty, constraints and trade-offs
• Implementation responsibilities
• Indicators for monitoring results
• A learning process for improving future decisions

FDE tools can support one immediate decision or become part of a recurring institutional decision system.

Short, structured products that translate evidence, uncertainty, options, trade-offs and recommended next steps into a format usable by risk managers and institutional leaders.

A decision brief can accompany a technical risk-assessment report or serve as a rapid decision-support product when time and data are limited.

Structured tools that identify available evidence, data quality, scientific disagreements, important gaps and uncertainties that could influence a decision.

They help organizations distinguish between evidence that is missing and evidence that would materially change the choice.

Quantitative or semi-quantitative models for comparing hazards, foods, populations, sectors, supply chains or interventions using transparent criteria.

They can support surveillance planning, inspection priorities, import controls and resource allocation.

Tools that estimate how alternative risk-management actions could affect exposure, illness, public-health burden or other relevant outcomes.

They can compare expected impact, feasibility, cost, residual risk, uncertainty and possible unintended consequences.

Interactive displays for exploring risk patterns, trends, geographic variation, alerts, scenarios and performance indicators.

FDE dashboards are organized around decisions and action triggers—not simply around the data available.

Applications and reproducible analytical workflows that allow users to update data, modify assumptions, compare options and communicate results without rebuilding the analysis.

These may include web applications, Shiny tools and documented R or Python workflows.

Governed use of artificial intelligence to support literature screening, evidence mapping, data extraction, model preparation and technical drafting.

AI supports efficiency, but scientific experts remain responsible for validation, interpretation and judgement.

Indicators and evaluation frameworks that assess whether an intervention produced the expected health, economic, operational or equity outcomes.

They create a feedback loop through which every decision can improve future decisions.

For complex or recurring decisions, IFoRAC can develop a Food Decision Twin: a living representation of the system through which a food-related decision is made.

A Food Decision Twin connects:

• Evidence and data inputs
• Risk-assessment models
• Assumptions and uncertainty
• Decision owners and responsibilities
• Risk-management options
• Decision rules and action thresholds
• Implementation indicators
• Results from previous decisions

It enables an organization to update evidence, test alternative scenarios, compare interventions and improve the decision process over time.

• Prioritizing foodborne disease interventions
• Adapting import inspections and sampling
• Monitoring climate-sensitive hazards
• Evaluating evidence for novel foods
• Comparing safety and sustainability options
• Managing recalls and supply-chain risks

A dashboard shows what is happening. A Food Decision Twin helps determine what should happen next.

The Food Decision Twin should be presented as a customizable IFoRAC service—not as an off-the-shelf software platform.

Clarify what must be decided, who owns the decision, when it occurs and what the tool must enable.

Output: Decision statement and user requirements

Identify evidence inputs, analytical methods, responsibilities, workflows and points where information and decisions are disconnected.

Output: Decision and evidence architecture

Develop the simplest useful version of the tool using available evidence and realistic user requirements.

Output: Working prototype

Test the assumptions, methods, outputs and user experience with scientific experts, decision-makers and intended users.

Output: Validated decision tool

Document the tool, establish governance, train users and define responsibilities for maintenance and updates.

Output: Operational tool and user guidance

Evaluate how the tool is used, whether it improves decisions and how it should adapt as evidence and institutional needs change.

Output: Maintenance and learning plan

Food Decision Engineering does not require every organization to begin with an advanced digital platform. Tools can be designed at different levels of capability.

Decision briefs, evidence maps, risk profiles, uncertainty registers and data-light prioritization models.

Connected datasets, exposure models, risk-ranking applications, dashboards and scenario-comparison tools.

Probabilistic models, predictive analysis, AI-assisted workflows, traceability-linked systems and adaptive monitoring.

The best tool is not the most technically advanced. It is the simplest tool that reliably improves the decision.an

FDE tools can be developed independently or as part of a Food Decision Mission.

Food Decision MissionExamples of supporting tools

Burden-to-ActionHazard-food priority map, intervention simulator and impact dashboard

Climate-Ready Food SafetyRisk-scenario explorer, early-warning indicators and action-trigger dashboard

Safe Innovation Fast-TrackEvidence-requirement matrix, uncertainty register and evaluation tracker

Balanced Food-System DecisionsMulti-criteria comparison model and interactive trade-off explorer

Every IFoRAC tool is designed to be:

• Decision-first: built around a defined decision and user.
• Fit for purpose: matched to the available evidence, stakes and capability.
• Transparent: assumptions, methods and limitations are visible.
• Explicit about uncertainty: users can see what could change the result.
• Reproducible: analyses can be reviewed, repeated and updated.
• Reusable: workflows reduce duplicated effort.
• Interoperable: data and outputs can connect with existing systems.
• Human-governed: accountable experts and decision-makers retain control.
• Secure: access, confidentiality and permissions are defined.
• Maintainable: ownership, versioning and updates are planned.
• Impact-oriented: use, decisions and results can be monitored.

Demonstrate how one priority decision could be supported using available data and evidence.

Design, validate and deploy a tool for a defined organizational decision or workflow.

Adapt an existing model or workflow to another country, institution, hazard or decision context.

Connect multiple tools, datasets, responsibilities and governance processes into a reusable organizational decision system.

Tell IFoRAC about the decision, its users, the available evidence and the current obstacles.

We will help determine whether the appropriate solution is a decision brief, prioritization model, dashboard, interactive application, Food Decision Twin or wider decision system.

Begin with the decision—not with the technology.

1. What decision should the tool support?
2. Who will use it?
3. How frequently is the decision made?
4. Which data and models are currently available?
5. What does the current workflow look like?
6. What should the tool produce?
7. Who will maintain it after deployment?