Integrating Soft Systems Methodology and Value-Focused Thinking for multi-agent decision problems: The SSM–VFT Integrated Structuring Framework (SSM-VFT/ISF)

In the complex world of business and supply chains, decisions are rarely made by a single person sitting alone in a room. Instead, they emerge from a web of interactions between many different people—farmers, factory owners, logistics managers, and buyers—who all bring their own unique views, values, and priorities to the table. When these groups try to solve a problem together, such as how to distribute milk or allocate orders, they often run into a hidden obstacle: they do not just disagree on how important a factor is, they often do not even agree on what the factors are. One person might see "quality" as a matter of trust and long relationships, while another sees it as a specific laboratory measurement. If a decision model is built on a single, pre-agreed list of criteria, it risks ignoring these deep differences, leading to solutions that look mathematically perfect but fail in the real world because they do not reflect the true nature of the situation. To navigate this, researchers have developed methods to help groups first understand their own messy reality before trying to solve it. Two of the most powerful tools for this are Soft Systems Methodology, which helps people map out their different perspectives and relationships, and Value-Focused Thinking, which helps them turn their core values into clear, measurable goals.

A team of researchers from universities in Brazil set out to combine these two tools into a single, unified process designed specifically for groups where everyone belongs to the same side of a network, such as a group of dairy farmers trying to improve their collective performance. They called this new framework the SSM–VFT Integrated Structuring Framework. Their goal was to create a procedure that could first preserve the unique, individual perspective of every single person involved, and then carefully weave those separate views into a common set of measurements that the whole group could agree upon. Rather than forcing everyone to adopt a standard list of criteria from the start, their method allows each person to build their own map of the problem, identify what they truly value, and define what success looks like for them. Only after these individual maps are drawn does the group come together to find the common ground, ensuring that the final list of criteria is not a compromise that erases important differences, but a negotiated structure that respects the origin of every idea.

To test this approach, the researchers applied it to a Local Productive Arrangement in Venturosa, a region in the Agreste area of Pernambuco, Brazil, where small dairy producers supply milk for cheese making. They focused on three specific farmers who represented three very different ways of doing business. The first farmer was a traditional operator with thirteen years of experience, producing about 3,500 liters a week, whose world was defined by long-standing, trust-based relationships with buyers. The second was an adaptive producer with only three years of experience, making 2,000 liters a week, who was focused on collaborating with others to buy supplies and stay competitive in a changing market. The third was a technological professional with eight years of experience and a weekly output of 7,000 liters, who relied on mechanized milking, computerized management, and strict quality certifications to differentiate their product. These three men operated in the same network, yet they saw the decision problem through completely different lenses.

The researchers began by working with each farmer individually. They asked them to draw a "Rich Picture," a free-form sketch that captured their personal view of the situation, including the people involved, the tensions they felt, and the flow of information. For the traditional farmer, this picture centered on the stability of his relationships and the fairness of the price he received. For the adaptive farmer, the drawing highlighted the need for collaboration and the unpredictability of the market. For the technological farmer, the sketch focused on laboratory data, technical standards, and the return on investment for his expensive equipment. From these pictures, the researchers helped each farmer extract their core values and turn them into strategic goals. They then used a series of questions to dig deeper, asking "Why is this important?" to distinguish between the ultimate ends the farmers wanted to achieve and the means they used to get there. This process revealed that while all three wanted to sell milk, the traditional farmer saw "fair pricing" as an end in itself, while the technological farmer saw "pricing linked to quality indicators" as a way to prove the value of his technology.

Once the individual goals were clear, the researchers helped each farmer build a "Conceptual Model." This was a description of how their ideal system would work if everything went perfectly, free from the constraints of the current reality. By comparing what the farmers actually experienced in their daily work with what they imagined was possible, the team identified gaps and opportunities. For the traditional farmer, the gap was between his desire for stable partnerships and the informal nature of his current contracts. For the technological farmer, the gap was between his high standards and the lack of formal channels to share his data with buyers. This step ensured that the goals were not just wishful thinking but were grounded in a clear understanding of what needed to change. The researchers then checked which of these ideal actions were actually feasible, considering the farmers' resources, costs, and local culture. This filtered out ideas that were too expensive or culturally difficult to implement, leaving a list of practical, achievable steps for each person.

The final and most critical stage was bringing the three farmers together to build a shared language. The researchers laid out the specific measurements each farmer had developed for their own success. The traditional farmer measured success by the length of his partnerships and the frequency of his conversations with buyers. The adaptive farmer looked at how often he delivered on time and how much he saved through group buying. The technological farmer focused on his internal rate of return and the number of premium buyers he could attract. In a collaborative workshop, the group did not simply vote on a list; they negotiated a common set of attributes that could represent all three perspectives. They realized that "partnership stability" could be measured by the duration of contracts for the first farmer, the reliability of the second, and the number of premium buyers for the third. "Milk quality" could be measured by the use of cooling tanks for the first, bacterial counts for the second, and compliance with technical standards for the third. Through this process, they created a single, unified list of six criteria: partnership stability, communication frequency, technical quality of milk, price differential, degree of formalization, and planning capacity.

The result was a common measurement basis that allowed the group to evaluate future decisions without losing the specific concerns of any individual member. The study showed that it is possible to structure a complex, multi-person problem without forcing everyone to agree on the same definition of success from the start. By first honoring the unique worldview of each participant and then carefully translating those views into a shared structure, the framework produced a set of criteria that was both representative of the group and traceable back to its individual origins. The researchers found that this approach prevented the premature homogenization of ideas, where the unique strengths of different profiles are lost, and instead created a robust foundation for future decision-making. The study suggests that in any network where diverse actors must work together, the path to a good decision begins not with a shared list of rules, but with a deep understanding of the different maps each person is holding.