Stakeholder Dialogues

Data and data-driven solutions are already shaping food systems and the ways we produce, consume and govern food.

What are the perceptions
and experiences of
food system participants
of the data economy


Stakeholders have diverse, but complementary views on and experiences in data economy. While they speak from their own experience, they also take broader than a single stakeholder perspective on data economy. They consider links, relations and mutual impacts between different food system stakeholders.  

Food value chain actors: input suppliers, farmers, processors, retailers, caterers, consumers, waste management companies
Food system support actors: equipment manufacturers, advisors, researchers, policy makers, food control agencies, funding bodies, media
Data actors: providers of data solutions in food systems (e.g., digital platforms, digital technology and service providers, data sharing platforms, cloud service providers, etc.)
Actors from adjacent sectors: health, environment, territorial development



Winners / Losers

Data economy should benefit the entire food system and its stakeholders / There are factors that influence the equal access to data and capability to use

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Technical / Social

Insufficient interoperability hampers effective use of data and innovations in the food system / Technical solutions need to be supported by social and legal ones

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Benefits / Costs

Data has potential to improve performance / Costs (technological, socio-economic and environmental) associated with every step of data management

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Data supported decisions / Data overload

Data help monitor, gain knowledge, inform decisions / Data abundance and poor-quality data undermine their effective and sound use in decision-making

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Comprehensive approach / Economic focus

Potential to improve environmental performance and management / Current dominant economic focus of data economy lowers the priority of environmental and social sustainability

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Sharing / Control

Data sharing can improve transparency, innovation and empower stakeholders / There are issues of control over data and risks around security, competitiveness

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Tailored novelties / Data (in)capability

Tailored data-based solutions incite sustainable decisions and practices / Data literacy, access to data and digital infrastructure are still problematic

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Promote / Protect

Coordination, rules and policy intervention for fair data economy / Overregulation that limits data economy for food systems

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Key stakeholder recommendations –
preconditions to arrive at fair data economy

Policy interventions to address the issues of power imbalances, data privacy and security, and interoperability

Collaboration and mutual agreements between food system stakeholders on data sharing and correct use of data

Improving data literacy and skills of food system stakeholders (to support data-driven decisions and practices for a sustainable food system)


While the term “data economy” is new for many food system stakeholders, they are aware of the role of data in their daily professional lives. Still, many stakeholders experience limited control and influence on data economy processes.

  • Food system stakeholders perceive they are mutually connected and interdependent in data economy. Hence, collaboration and joint solutions are needed, but they are also complex and challenging to achieve.
  • To achieve fair data economy for sustainable food systems that is beneficial for all the food system participants and the environment, food system stakeholders expect proportional regulations, legal guidance and participatory governance. 

Contributors: Sandra Šūmane, Maija Ušča, Tālis Tisenkopfs (BSC), Monika Gębska, Edward Majewski, Sławomir Jarka, Agnieszka Biernat-Jarka (SGGW), Pia Groenewolt, Maciej Otmianowski (VUB), Femke Meulman, Marc-Jeroen Bogaardt, Kelly Rijswijk (WR). Design: Foodscale Hub


Data economy should be beneficial for the entire food system and all the stakeholders within it. However, depending on their access to data and capability to make use of it, some stakeholders benefit more than others.   

Perceived winners – Perceived losers: 
Big – Small 
Rich – Poor 
Powerful – Vulnerable 
Retailers, processors – Farmers, consumers 
Data companies – Data owners, data end-users 
Private sector – Public sector 
Well educated, incl. researchers – Less educated 
Young people – Old people 
Men – Women 
High-income countries in the Global North – Low- and middle-income countries in the Global South 

“Farmers are the weakest chain in the food systems. All actors need data from farmers, and they are not getting enough benefit from it.” (Researcher)  

“Digital transformation and data economy are more accessible for bigger players in the food system. This is due to financial and other costs involved.” (Data actor) 

“There is a risk that data reproduce existing unequal social structures and leave marginalised groups out as there are no data about them. Also, data that are the prototype of white men are less meaningful for women.” (Health actor)

Technical solutions of interoperability are also closely linked to social and legal ones, such as development of common understanding, common public and private standards, enhancing willingness and trust to share data. 

“There is a big issue of interoperability. Suppose you have a tractor produced by one company gathering data. When you change this tractor for a tractor produced by another company, you will lose all data from the first tractor. This method keeps clients loyal, but as a consequence, data has only a limited use.” (Policy maker) 

“Interoperability means that there is good understanding and an agreement among the stakeholders what kind of data are existing and how this data is flowing. Interoperability requires that there are restrictions and norms which regulate who can access this data and how it can be used.” (Equipment manufacturer) 

As intermediaries, advisors work with many databases of different organisations, and those databases need to be compiled. Data interoperability can be very complicated.  .. It is very difficult to negotiate with other data holders about automated data.” (Advisor organisation) 

Data economy is associated with improved performance, such as optimized food production, research efficiency, policy implementation etc. In the meantime, adoption of data solutions is not always seen as beneficial and there are costs associated with every step of data management, starting from data collection, to storage, access and use. Data solutions can involve significant technological, socio-economic and environmental costs.  

“The economic benefit comes from the possible immediate reaction of a decision-maker. Companies can survive due to the innovative use of data concerning the market. Data are available more frequently, and shorter time window opportunities arise.” (Farmer organisation) 

IT consumes energy, there is a carbon footprint; rare minerals are in everything that demands computation. We need to keep an eye on it and balance. High tech demands a lot of environmental resources. That’ll be even more an issue in the future if data field is expanding in a rapid pace“. (Data actor) 

“Digital technologies (such as software based on algorithms, AI, IOT, Blockchain) are not tangible and farmers do not see that they bring in direct benefits. The prior motivation of farmers is to provide good products and take care of their animals. This is where they receive direct compensation from. It is difficult to bring data into this. This differs from the bigger data companies who see a business model in data, for farmers this is an additional task.” (Dutch discussion)

“Data flow ensures that very fast reactions are possible at every chain element, starting from procurement to the situation in shelves. Data flow is used to make all the orders, to forecast procurement, to get information about customers.” (Retailer organisation) 

“There is the problem of reliability and credibility of data. Different sources may provide different data on the same subject. Significant obstacle in proper use of data is that often data are not complete. The quality of dataset can be unknown – who and how verifies it?” (Polish discussion) 

Data economy has a good potential to improve environmental performance of food systems through more effective management of resources, supporting more sustainable and climate-friendly food-related behaviours and practices in the entire food-chain, including reduction of food waste.  However, current data economy has a strong economic focus: economic data, economic value of data, data application for economic purposes dominate. This eventually leads to lower prioritising of environmental and social sustainability dimensions in food systems. 

“Data economy is an essential for the realisation of the goals in agriculture that citizens expect and request – ensuring high food security, high-quality standards, welfare, sustainability and environmental protection.” (Farmer organisation) 

“The current data flows are skewed towards economic indicators and production side of a complex food system.  The consumer perspective on data should be put more in foci putting emphasis on nutritional, health, environmental and social functions of food. Such a reorientation of food system data ‘mentality’ could trigger changes in consumption models with positive impact on the environment, health and community wellbeing.” (Latvian discussion) 

“The topic of data economy for food systems is very current for three reasons. Firstly, sustainability: food has such a high impact on sustainability, biodiversity and climate change. Second, food safety and food security: the variety we have in food is phenomenal these days, but at the same time now we’ve seen through the Ukraine war and also through COVID that it’s a fragile system. Third, fairness: we see food prices increasing, and I am worried about people that cannot afford healthy nutrition. Also, for entrepreneurs, it is very difficult to get into the food space because it is highly regulated and there are big players there. All of this calls for data-based approaches, but for ones that are not worsening the situation or the biases, but the opposite.” (Consumer organisation)

Data sharing improves transparency across the entire food system, contribute to innovations, and empower stakeholders. On the other hand, data sharing entails loss of control over one’s data and is associated with risks such as data insecurity, reduced competitiveness and economic advantage, overcontrol and repressions in case of non-compliance with formal requirements. 

“Transparency and proper control are beneficial in food production. All food entities are exposed to multiple hazards (e.g., biological or chemical), resulting in a high likelihood of contamination.  That is why instantaneous information about operations at all food production stages reduces companies’ and consumers’ risks.” (Farmer organisation)     

We need transparency to move towards sustainability transitions. We need to be aware of requirements from suppliers or for products. But if you become very transparent, you lose of your competitive advantage. If everyone has access to it, then what happens to your market position?” (Retailer organisation) 

“Citizens often wonder if they can request data holders to delete their data. They feel that data is being collected about them, but they are unable to utilize the same data to empower themselves or support businesses and stakeholders aligned with their interests.” (Belgian discussion)

Data-based tailored, customized, personalized solutions incite food system stakeholders to adopt novel sustainable food-related decisions and practices. To become knowledgeable and responsible users of data and data solutions, stakeholders need access to data and appropriate digital infrastructure, equipment, tools, skills and data intelligence, which is not always the case.  

“Data can help to define more specific and better targeted aims to solve problems in food systems, e.g. data on waste structure can help to identify specific food waste groups and develop targeted solutions to reduce them.” (Latvian discussion) 

“Data availability is one side, and the other side is how you analyse data and what you get out of data. Some advisors have these skills, while other still need to acquire them. Until you do not know how to turn data into conclusions and decisions, data remain just data.” (Advisor organisation)

“In the agrifood sector, you see that farmers do not always have access to the data that they create. They could simply not have access, but they can also not know how to get that access. .. Farmers, as data owners, often lack the capacity to use [data]. Among others, this is a result of minimal access to digital infrastructures.” (Dutch discussion)    

Data economy needs coordination. Stakeholders expect proportional policy interventions that steer fair data economy and shared rules regarding data rights and responsibility. However, they do not wish to be overregulated and overcontrolled.  

“There should be regulations and public actors that balance the existing asymmetry, counteract power imbalances”. (Researcher)  

“Sometimes there is a huge bureaucratic burden. But maybe it must be well regulated and transparent for the sake of a safe future. [Data] regulations can become problematic if they have a negative impact on progress and development, if we exaggerate and wish to protect everything.” (Food control agency)

“The importance of data governance [increases] as trust emerges as a recurring challenge in the context of the data economy. Even with the implementation of blockchain technology, a stronger regulatory structure is necessary for effective governance. Drawing parallels to land regulation, the need for a robust framework to ensure responsible management and utilization of data becomes evident.” (Belgian discussion)

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