Technology only works when processes and people can move with it
In many parts of the agrifood sector, sensors, data, software and automation are already close to daily practice. A grower sees measurement data on a screen, a livestock farmer follows signals from the barn and a developer works on an application that performs well in a pilot. Still, daily use often turns out to be more complex. Systems do not automatically connect, roles are not always clear and teams need to decide together which action should follow from which data. The Digital Maturity Assessment helps to make this situation concrete.
Broad knowledge question
Where does implementation get stuck when the technology is already there
The central question behind the DMA is how agrifood companies can systematically assess their digital maturity. This is important because smart agricultural technology only creates value when it fits the work process, the available knowledge and the way decisions are made. In practice, the data may already be available, while it is still unclear who owns it, who works with it and what next step is needed. By making this visible, it becomes clearer why an application works more quickly in one environment than in another.
Approach
One practical application shows what is already in place and what is still missing
The Digital Maturity Assessment was developed within NXTGEN Hightech as a sector-specific maturity test for agrifood. The method is applied to one specific practical application, such as a system for measuring, steering or automation. The assessment looks at technology, but also at the work process, division of roles, knowledge within the team, strategy and agreements about data. The method is based on an analysis of more than 35 international maturity models and uses six main themes, 18 criteria and five levels, ranging from ad hoc to innovative.
Goal
From separate signals to choices that support daily use
The goal of the DMA is to help companies or pilot locations gain a clearer picture of where they currently stand. A team may discover, for example, that the technology is sufficiently developed, but that data connections, responsibilities or training have not yet been properly arranged. In this way, digital development becomes less of a general discussion and more of a practical conversation about choices, priorities and next steps. This helps organisations use technology more successfully and apply it more widely.
Result and reflection
A maturity profile makes improvement easier to discuss
Applying the DMA results in a maturity profile of the practical application. The main organisational and technological bottlenecks are brought together in a short recommendation report with targeted next steps. This helps organisations decide what needs attention first and where collaboration with developers, researchers or other partners is needed.
Successful outcomes:
The test shows that daily use often gets stuck because of work processes, role division or agreements, not technology alone.
For each practical application, it becomes clear which step is needed first, such as better data connections, ownership or training.
The report supports conversations about priorities, collaboration and wider implementation in practice.
Lessons learned:
A pilot may work well, while management, ownership and training are still missing.
Improvement requires attention to technology and organisation at the same time.
By identifying bottlenecks early, the step towards daily use becomes less dependent on trial and error.