Digital innovation in Agri & Food
Agriculture and food production is increasingly being digitalised by using all kind of smart devices and intelligent software systems. It may seem like only technical specialists and engineers can help digitalisation, but we think digital innovation is much more a social experiment requiring socio-economic insight.
What do you need? We can help you with:
Data Science and Artificial Intelligence for Agriculture
Machine learning and data science can be applied to many different challenges in agricultural organizations. For instance, farmers can use large amounts of data that they produce to optimize their risk-return ratio while respecting the boundaries set by nature (e.g. healthy cattle) and law (e.g. nitrogen limits). However, these tools create high expectations that are not always realistic. When digitizing an organization, it is important to work with these tools effectively to turn data into added value for your business.
Data-driven business modelling
The Internet of Things holds a big promise to boost digital innovation in the agriculture and food sector. For example, it allows for precision farming and for improving quality monitoring throughout the value chain.
Optimizing information systems in agri-food
Growing amounts of data require organizations in the agriculture and food sector to be flexible and to pro-actively integrate their data. But before you start storing, analysing, and presenting data, it is crucial to set your objectives, uncover bottlenecks in organizational processes and involve stakeholders.
Creating dynamic innovation ecosystems
Digital technologies such as the Internet of Things or Blockchain are often introduced with high expectations. Unfortunately, in practice it is often difficult to apply them, leading to disappointing adoption rates and less impact than expected.
Responsible data governance
Data sharing is an important condition for digital innovation in the agri-food domain. However, in practice it is challenging to realise trusted data sharing.
Our multidisciplinary, collaborative & agile approach
Initially, it is usually unclear what you can do with your data. How do you use your data in the most effective way? How do you combine your data with those of external sources and partners to create added value?
To help you get the most out of your data, we developed a multidisciplinary and collaborative approach.
We bring the right partners together who step-by-step develop digital solutions step-by-step. In this development process, we are not only supported by state-of-the-art knowledge on data science, information modelling, and management, but also by business modelling, governance, and ethics.
In our projects we combine use cases from various sectors. In this way, we can learn from each other: We create synergies by building a vibrant innovation ecosystem and collaboration space. We do this in small projects as well as in large-scale pilots such as IoF2020.
About digital technologies
As mentioned before, applying digital technologies should be embedded in an integrated innovation process. This process should be optimally supported by socio-economic knowledge.
Besides applying our socio-economic approach, in some of our projects we explore specific digital technologies, such as:
- Blockchain Technology
- Artificial Intelligence
- Big Data Analytics
- Machine Learning
- Linked Data
- Internet of Things
- Smart Networks and Services (5G)
If you are interested in one of these specific technologies, please contact us and we can help you to address your questions.
About Wageningen Economic Research
Why choose us:
- Refreshing insights
- Domain & sector knowledge
- Interactive & integrated approach
- Operating on every continent
- Internationally leading
- One stop shop