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Sugar from cane remains an important economic contributor in many countries. A lack of collaboration has been identified as a key problem in many of these regions. To date, few sugar researchers have exploited the valuable supply chain collaboration knowledge available in the literature, such as the Supply Chain Collaboration Index (SCCI). This paper seeks to address these issues.

Qualitative and quantitative data were collected from three sugarcane milling areas. The SCCI was contextualised from a psychological perspective and used in the quantitative data analyses. A special objective was to raise a number of pertinent questions, which would fast track stakeholders to a new level of collaboration.

Many relationships in the supply chain remain relatively positive. The main attributes of concern are stability, reliability, trust, personal relationships and communication. A lack of these attributes causes fragmentation, opportunism and a desire to over‐control. Mutuality and communication are key leverages in the system.

There is a need to understand how collaboration could be enhanced when stakeholders hold different balances of power. This study is still limited to sugarcane milling in South Africa.

This paper demonstrates a partially quantitative research methodology to understand collaboration in a food supply chain. The authors also propose a tool to help industry stakeholders to resolve current problems.

The psychological profiling of SCCI attributes and subsequent correspondence analyses is original. A framework of collaboration questions combined with Kepner‐Tregoe Problem Analyses is unique. These tools are generic to any agricultural supply chain.

The purpose of this paper is to develop and demonstrate a driving factors-based approach for identifying and ranking performance indicators in integrated sugarcane supply and processing systems (ISSPSs) on an on-going basis.

The research included a literature review, development of an approach, testing of the approach in four ISSPSs and checking the tests’ results for consistency with Southern Africa sugar industry benchmarks and external knowledge of the four ISSPSs.

The research offers a systematic approach for identifying and ranking performance indicators based on existing driving factors in ISSPSs. Results obtained from the application of the approach in four ISSPSs are consistent with industry benchmarks and external knowledge of the ISSPSs.

The approach was tested in only four ISSPSs. It is recommended that the approach should be tested in other complex systems to further validate its effectiveness. It is further recommended that the approach should be systematically compared with existing approaches that are used for identifying and ranking performance indicators.

This research is of academic value and of practical value to practitioners in ISSPSs. The research blends knowledge from network theory and cause-and-effect analysis to come up with a systematic approach for identifying and ranking performance indicators in ISSPSs on an on-going basis. Further, the approach identifies and ranks performance indicators as part of one data set. This approach has never, to the authors’ knowledge, been used in agro-industry before.