A systems thinking approach to address the complexity of agribusiness for sustainable development in Africa: a case study in Ghana

African countries have comparative advantages in the production and export of primary commodities; however, they face many sustainability challenges in the agricultural sector. Since the democratisation of many African countries—notably Ghana—a number of interventions, costing billions of dollars, have been implemented to overcome the challenges facing the agricultural industry, but with little success. The agricultural industry is characterised by complex challenges such as famine, food insecurity, poor soil and quality standards, political instability, inappropriate agricultural practices, and the depletion of natural resources. These challenges have worsened the plight of African farmers. The increasingly complex nature of the agricultural industry in Africa has led to an urgent need for the use of a systemic rather than traditional approach to solve agricultural problems. Capacity building using a systems thinking approach and the concept of an Evolutionary Learning Laboratory during a series of stakeholder workshops in Ghana, has had a remarkable effect on the ability of the agricultural industry to evolve, improve and increase its efficacy. Causal Loop and Bayesian Belief Network (BBN) modelling were used to develop systems models to determine the components and interactions between the policy and the social, environmental and economic dimensions of the industry. Insights were made into potential system behaviours and leverage points for the systemic interventions required for sustainable agricultural development. The results reveal that the behaviour over time of agricultural productivity is declining, although new agricultural lands are being exploited, leading to environmental degradation. System archetypes as diagnostic tools have contributed to understanding the cause of a fix ‘now’, which gives rise to a much bigger problem to fix ‘later’. The results illustrate how the structure, conduct and performance elements of the agricultural industry interact together to influence the survival and growth of the sector. The study identifies that stakeholders adopt several strategies to survive and compete, leading to overexploitation of the ecosystem. Results from the BBN models indicate that the implementation of systemically determined interventions, policies and strategies could result in the chance of raising ‘agricultural productivity’ as high as 92.2% from 57.5%, and it might be plausible to reduce poverty levels from 44.9% to 10.0%. This would also lead to a significant increase in farmers’ yields and profits. These BBNs are used for scenario testing to determine the potential outcomes of different systemic interventions by observing what happens to the system as a whole when a particular intervention/strategy or combination of interventions/strategies is implemented—that is, before any time or money is invested in implementation. This approach provides clarity on dealing with complex sustainability challenges and should gradually replace the reductionist approach (e.g., short-term quick fixes and treating the symptoms) in dealing with challenges and developing policies. The systems models will help governments to anticipate the long-term consequences of their decisions and actions, as well as help to avoid significant unintended consequences of policies and strategies such as ‘silo mentality’ and ‘organisational myopia’.Thesis (Ph.D.) (Research by Publication) -- University of Adelaide, Business School, 2016

“THE GREATER PUSH” FOR GROWTH AND SUSTAINABILITY IN AFRICA - EVIDENCE FROM GHANA

Over six decades, agricultural policies attempting to increase the competitiveness of project performance had limited success. This is due to the use of traditional project management methods that do not address the complex challenges encountered in a systemic way. This paper provides an example of how a systemic approach is applied to agricultural development. The findings are based on a series of workshops conducted in Ghana in 2013 and 2014. Findings include an established community development model, the “Greater Push” and a new way of measuring, monitoring and evaluating sustainable development with Bayesian Belief Network modelling that satisfies the ‘Bellagio Principles’ for measuring sustainable development indicators. This research contributes to systemic application in project management and can help policy-makers across the world to identify threats to sustainable economic growth and help them to anticipate unintended consequences of their decisions and actions before it is too late to reverse the trend

SYSTEMIC APPROACH TO EXAMINE THE STRUCTURE, CONDUCT AND PERFORMANCE MODEL OF AGRICULTURE IN AFRICA, EVIDENCE FROM GHANA

The continuous growth in population and consumption, the intensity of competition for land, water, and energy, and the overexploitation of the ecosystem, have affected Ghana’s ability to sustain food security and it natural resources. Over the years, many promising agricultural development initiatives could not provide sustainable solutions to agricultural challenges in most parts of Africa, including Ghana, leading to food system failures. The agricultural industry is a complex system and requires a holistic approach to dealing with root causes of challenges. This research therefore uses systems thinking tools including Casual Loop Diagrams (CLDs) and Bayesian Belief Network (BBN) modelling to develop new structural systems models where stakeholders determined the components and interactions between the Structure, Conduct and Performance (SCP) of the agricultural industry in Ghana using the Evolutionary Learning Laboratory (ELLab). The results illustrates how the SCP elements interact together to influence the survival and growth of the agricultural industry among driving forces. The study identifies that stakeholders adopt several strategies to survive and compete, which lead to the overexploitations of the ecosystem. The results from BBN models indicate that the implementation of systemically determined interventions, policies and strategies could significant improve the rate of business survival and growth from 58.8% to 73%, while the chances of improving the SCP could be increase from 39%, 28.3% and 36.4% to 80.1%, 55.9% and 62.4% respectively. This paper contributes to the systemic approach to SCP in that, the improvement of production and allocative efficiency may usher a greater potential for improving food security and the natural resources and further strengthen agricultural sustainability

A SYSTEMS THINKING APPROACH TO ADDRESS THE COMPLEXITY OF AGRIBUSINESS FOR SUSTAINABLE DEVELOPMENT IN AFRICA

African countries have comparative advantages in terms of land and relatively cheap labour cost compared to western countries in the production and export of primary commodities. However, there are many challenges such as sustainability issues, and the danger of “silo mentality” (in which fixing one problem “here” simply shifts the problem “there”) and “organizational myopia” (in which a short term fix “now” gives rise to a much bigger problem to fix “later”) facing the agriculture sector. Since the democratic progresses of many African countries, there have been a number of interventions to overcome the challenges facing the agriculture industry but with little success. The problem still persists and many budgeted billions of dollars for the agriculture sector have already been spent. The agriculture industry is a complex system economically, socially, and environmentally thus dealing with problems in isolation fails to produce lasting results. A survey and literature reviews was conducted to gather the mental models of all stakeholders involved in addition to the challenges of the agricultural sectors within Africa. Their opinion concerning how the system works, barriers to success and the system drivers, and possible strategies (solutions) to overcome these problems was analysed. These results developed four system models for agribusiness sustainability using a “systems thinking” or integrated approach and tools such as casual loop diagrams and Bayesian Belief Network models. Casual loop modeling were used to determine the components and interactions between the policy, social, environmental and economic dimensions to provide insights into potential systems behavior and to facilitate leverage points and systemic intervention strategies that are required for sustainable development of the agriculture industry. The Bayesian Belief Network models reveal that farmer education, access to both seasonal production, access to information, quality seeds and cold storage facilities will help drive overall export performance by 8.2%, increasing market share by 11.7%, raising export volume by 22% and enhance farmer’s profit by 13.1%. This approach will enable and assist farmers, policymakers, researchers and donors to successfully manage the agriculture and food systems so as to strengthen food security, enhance rural livelihoods, and improve environmental sustainability in the context of the challenges arising from agriculture production in Africa. These will also help stakeholders and governments to anticipate the long-term consequences of their decisions and actions, as well as the unintended consequences of policies and strategies and avoid “silo mentality” and “organizational myopia”. This will further induce innovative agribusiness with an entrepreneurial approach and empower the youth to be successful agribusiness entrepreneurs through an innovative and systemic approach