The indivisibility principle of the 2030 Agenda is considered key for the implementation of policies in pursuit of the Sustainable Development Goals (SDGs). Therefore, science is not only asked to develop new methods for assessing SDG target interactions but also to translate findings of methodological insights into policy advice for easy take-up by policymakers. The present paper demonstrates how to adopt the multi-criteria analysis technique Analytic Network Process (ANP) for prioritizing SDG targets in considering all positive and possible indirect SDG target interactions at once. The application of the ANP is linked to a multi-method setting embracing positive scores derived from the analytical methods Nilsson-scale, a cross-impact matrix, and network analysis techniques. This supports the prioritization of SDG targets when considering n-order neighbours in a network with respect to their synergies. The ANP allows evaluating the synergistic potential and progress controllability of SDG target rankings calculated by CI-matrix metrics and thus provides conclusions on the importance of n-order interactions of SDG targets in a network for the final ranking. We showed that the application of a combination of different analytical methods improves the overall quality of the formulated policy advice regarding its scope and methodological profoundness. In this context, we compared the analytical methods involved with respect to their ability to formulate policy advice and finally presented a framing how to translate methodological results into concrete and applicable policy advice.

2030 年议程的不可分割性原则被认为是实施可持续发展目标 (SDG) 政策的关键。因此，科学不仅需要开发评估可持续发展目标目标相互作用的新方法，而且还需要将方法论见解的发现转化为政策建议，以便决策者采用。本文演示了如何采用多标准分析技术分析网络过程 (ANP) 来优先考虑所有积极的和可能的间接 SDG 目标相互作用。ANP 的应用与包含从尼尔森量表、交叉影响矩阵和网络分析技术的分析方法得出的正分数的多方法设置相关联。这支持在考虑可持续发展目标时优先考虑网络中的n阶邻居的协同作用。ANP 允许评估由 CI 矩阵指标计算的 SDG 目标排名的协同潜力和进度可控性，从而提供关于网络中 SDG 目标的n阶交互对最终排名的重要性的结论。我们表明，不同分析方法的组合应用提高了所制定政策建议的范围和方法学深度的整体质量。在此背景下，我们比较了所涉及的分析方法制定政策建议的能力，并最终提出了如何将方法论结果转化为具体和适用的政策建议的框架。