A substantial quantity of berries is grown in Sweden, estimated at more than 550 000 tons every year. Intriguingly, only a fraction of this amount (some 2 5%) finds practical utilization. Historically, the low utilization rate can be attributed to a scarcity of harvesting personnel, challenges in accessing the harvesting sites, and logistical complexities. Even with the current berry picking value chain, which is mostly operated by seasonal Thai pickers, numerou s challenges persist. The workers’ work and life conditions are not satisfactory, and efficiency is low, making up a value chain that is far from sustainable. In an attempt for more efficient and sustainable chains, some innovative solutions are practiced in a European innovation project, FAIRCHAIN. These innovative solutions include (i) developing an app to track berries and spot more probable places to find berries in real time, and (ii) cleaning and processing the berries locally into products like jam o r use them as an ingredient in other products (e.g., dairy products) in different scales. We, however, regardless of the scale and prospectives of the innovations, put together a model to assess how sustainable these innovations are compared to the current value chains. Significance of such assessments in helping decision making and designing new value chains while considering different aspects of sustainability is clear. In pursuit of this objective, we have formulated a comprehensive framework tailored to evaluate the sustainability of the proposed innovations within the context of Multi Criteria Decision Analysis (MCDA). To establish the foundation of this framework, we selected 18 important sustainability indicators for potentially shaping the sustainability outcomes of various innovative solutions, covering the three foundational pillars of sustainability: environmental considerations, social responsibility, and economi c viability. These indicators are Capacity development , Fair contracts and fair pricing , Human safety and health , Collective bargaining , Food sovereignty , Labor rights and Equity , Quality of life , Food quality , Local procurement , Local employment , Stability of market , Product information , Profitability , Stability of production , Land use , Energy use , Biodiversity , and Atmospheric impacts . Leveraging the Analytical Hierarchy Process (AHP), we systematically assigned relative weights to these indicators, foste ring a nuanced evaluation process. The preliminary results indicate that social indicators (such as Quality of life and Capacity development ) and economic ones (such as Stability of production and Local employment ) gain the highest It is worth noting that the entirety of data to feed this model was gained after multiple rigorous sessions of discussion and weighting by the informed project partners to reach ultimate consensus. This is ongoing research and here we rely on showcasing the framework to highlight its capabilities and strengths and discuss its limitations. Insights found in such inclusive holistic assessment hold significant value for decision makers who need to see t he big picture before intervention decisions such as small and large scale innovations in short and long term.