Hereon Transformation Cases

Strengthening transformative science.

The “Hereon Transformation Cases” project aims to strengthen transformative science. With our toolbox for transdisciplinary work, we support science, society, politics and business in jointly developing innovative solutions for the future.

From critical design and stakeholder workshops to small real-world laboratories, Delphi surveys and funding opportunities - the “Hereon Transformation Cases” test these tools in real transformation projects at the Helmholtz Center Hereon and offer practical support and implementation aids.

Funded by the Federal Ministry of Education and Research (BMBF), we focus on holistic approaches to promote cooperation and actively shape a sustainable future together.

The goal: holistic change beyond the boundaries of science.

One challenge in the current transfer process is that larger, ground-breaking ideas and long-term system solutions in particular have an implementation disadvantage compared to smaller and clearly market-oriented innovations. In most cases, these groundbreaking and disruptive ideas cannot be further developed, validated in a system context and then implemented, as the appropriate transfer instruments are not currently available.

Through the application of transformative science, non-university research institutions such as Hereon can play a much greater role in the much-needed transformation for a better future than traditional transfer can.

The “Hereon Transformation Cases” project of the Helmholtz Center Hereon has set itself this task.

What is transformative science?

Emergence of transformative science

Characteristics of transformative science

Advantages of transformative science

The transformation cycle

A central concept in transformative science is the equal involvement of academic and non-academic stakeholders as joint researchers (co-design, co-research, co-creation) and the transformation cycle, which organizes the joint research and transformation process into four different ideal-typical phases that are run through repeatedly (iterative approach). This model helps to systematically design and continuously optimize transformations.

1. analyze the problem

A specific problem or need for change is recognized by all stakeholders, described and defined on an ongoing basis (problem-building). The joint problem definition integrates the different perspectives and is part of the negotiation of what is relevant for the different stakeholders.
Knowledge of the socio-technical system plays an important role here (system knowledge).

2. develop a vision

The next step is to develop visions of desirable futures. Researching and describing the current situation defines the starting point; by developing futures, the different values and ideas of where we want to go become visible and can be discussed. Who wants to realize which goals (target knowledge)? Which ones can be realized together, which ones have to be negotiated?

3. experiment and adapt

Based on the results of the evaluation, strategies are adapted and, if necessary, the cycle is repeated in order to facilitate continuous improvement. in the best case, the vision development process gives rise to concrete questions and possible measures that can be implemented and tested quickly. This can be done through pilot projects or small-scale real-life experiments. The effectiveness of the measures is reviewed to determine whether the desired goals have been achieved, which surprising phenomena occur and which time dependencies and learning effects of the system are necessary (transformation knowledge).

4. distribute and learn

In this step, previous activities are reflected upon and important findings are distilled. By reflecting together on what learning effects are relevant for whom, the stakeholders can get to know each other better in terms of their rationale for action and work better together. The findings and action guidelines that can be derived are recorded in various formats and shared with interested communities as beta versions at an early stage in order to be able to continuously integrate external feedback and generalize findings from the project. In this way, transformation knowledge is documented and distributed.

Examples from practice