Masters thesis in Data & AI: Data-driven financial scenarios for food forests Veenendaal • Info Support

Food forests are gaining attention as a sustainable form of agriculture, but entrepreneurs lack reliable models to evaluate financial returns. This thesis challenges you to investigate whether data from related sectors, such as fruit and nut production, can be used to design transparent scenario models. By building and validating a prototype, you will apply your data and modeling skills to support real-world investment decisions in sustainable farming.

ð¡Areas of Interest: Agro-ecology or regenerative agriculture, Data analysis and model development, Sustainable entrepreneurship, Socio-economic impact evaluation

Food forests combine food production with ecological restoration and are seen as a promising answer to challenges in biodiversity and climate adaptation. Yet, entrepreneurs face a major obstacle: the lack of reliable insight into financial returns. Especially those with experience in fruit and nut production need transparent, data-driven models to realistically evaluate investment scenarios. Current models are too generic, lack transparency in their assumptions, and do not sufficiently use real-world data, making them of limited practical value.

Voedselboys, a Dutch initiative supporting agricultural entrepreneurs, faces this challenge when guiding farmers who want to start or scale up a food forest. In collaboration with them, this thesis explores how financial models can be improved to provide entrepreneurs with better insights for investment decisions. There is a clear need for a flexible and well-substantiated model that uses data from both food forests and related sectors to create realistic scenarios.

You will investigate to what extent available data from related sectors (fruit and nut production) can serve as a basis for financial scenario models for food forests. You will formulate and test the hypothesis that yield, labor, and price data from these sectors can be reliable references for modelling the financial performance of food forests.

The research consists of the following steps:

• Collect, analyze and compare datasets from food forests and related sectors to evaluate their reliability and applicability.
• Develop a technical prototype (for example a Python application, web dashboard or API) that validates the use of these sector figures as input for food forest scenario calculations.
• Validate your findings and the prototype with feedback from entrepreneurs and domain experts.
• Based on the results, provide concrete recommendations for further development and application of financial models for food forests.

About Info Support

Info Support specializes in custom software, data/AI solutions, management, and training and is active in the Finance, Industry, Agriculture, Food & Retail, Mobility & Public, and Healthcare sectors. We provide solid and innovative solutions for complex and critical software issues. Our headquarters are located in Veenendaal (NL) and Mechelen (BE). At present, approximately 500 employees are employed by Info Support.

Info Support's working method is characterized by a number of core values: solidity, integrity, craftsmanship, and passion. These core values are intertwined in our work and the way we interact with each other.

To ensure that all employees are always up to date with the latest developments, Info Support has an in-house knowledge center that eagerly satisfies the hunger for more or different knowledge and skills.

B2 language proficiency in Dutch is required.