Agricultural modelling & prediction
- Predictive modelling of yields and production
- Forecasting agricultural performance and analysing yield factors
- Support for planning cropping seasons
All practice areas
Practice area
Predictive Modelling, Data & Decision Support
Using data and modelling to plan, anticipate risks and decide with confidence.
- Farms
- Businesses
- Investors
- Institutions
- Agricultural projects
Purpose of this practice
CEADSA uses data, modelling tools and foresight analysis to improve agricultural planning, anticipate risks and strengthen the quality of technical, economic and financial decisions.
What we actually do
Decision support
- Comparative analysis of systems and crop management practices
- Crop choice and optimised resource allocation
- Investment scenario analysis
Risk analysis
- Identifying and analysing agricultural and climate risks
- Scenario and sensitivity analysis
- Resilience strategies
What the project can provide
These are possible deliverables to be agreed according to your project’s scope and objectives.
Data inventory and quality review
Identify sources, coverage, limitations and processing needs before analysis.
Model or scenario analysis
Build analysis around the question, with explicit assumptions and limitations.
Decision-support indicators
Present results in a form that helps compare options and track changes.
Documentation and handover
Explain methods and conditions of use to support understanding of results.
From the first conversation to project scoping
Collaboration starts with shared needs and an explicit scope.
Understand the request
Identify objectives, context, stakeholders and open questions.
Define the scope
Clarify activities, deliverables, working arrangements and resources.
Build a proposal
Agree on an approach, timeline and validation criteria before starting.
Scoping this expertise
What if our data is incomplete?
An inventory identifies feasible analysis, limitations to document and useful additions. Methods should match data quality and coverage.
Can a prediction be treated as certain?
Modelling relies on data and assumptions. Results need to be interpreted with their uncertainties, limitations and scope of validity.
Let’s discuss your needs
Share your context with us: we will propose a tailored approach, from study to implementation.
Other practice areas
Institutions & Development Actors
Informing public decision-making, strengthening the effectiveness of interventions and accelerating the transformation of agri-food systems.
Businesses & Agribusiness
Reconciling economic performance, climate resilience, environmental responsibility and social inclusion.
Training, Capacity Building & Learning
Developing the skills and learning systems that accelerate the adoption of agroecological practices.
Certification, Quality & Compliance
Preparing, structuring and improving your management systems all the way to the certification audit.