In the last article, the case study explained how easily even good intentions can lead to unintended and adverse consequences. The Indian government wanted to solve the problem but instead generated another, more serious problem that contributed to the death of thousands of farmers.
The failure of the Indian Government and the aid agencies can be explained by the inability of decision-makers to grasp the idea of interconnections and link a holistic perspective to proposed actions.
Before going further, I want to shift your attention to one of the metaphors frequently used to explain system thinking, called ‘iceberg’. The iceberg metaphor helps to analyse the underlying causes of events and patterns and from which the transition from thinking to action is suggested.
In the iceberg model (below), the part appearing above the surface represents an event or symptom. In this case, starvation. Below the surface reveals patterns of events. The question, ‘how often this event happen?’ is very important for a system thinker to design interventions in which events occuring with high frequency will obviously require more significant consideration. Likewise, if the food shortages happen at a certain time of the year, we might ask, in this instance or any similar situation, whether a pattern of behavior is beginning to emerge. If it is, we need to dig into a deeper level of the iceberg model to find out the root cause of the event.
Submerged below the pattern is the ‘structure’ which gives context and meaning of the behaviours higher up in the model. In the case study, all information, especially factors causing the starvation, need to be exploited at the macro and micro levels, because the government lacks a favorable financal policy to support the poor? Or does it happen because the government has failed to regulate the market so poor farmers can’t get access to high yield seedlings and other public services? Does it happen because the decision-makers directly involved lack knowledge of the natural market law of supply and demand. Or because they failed to recognise that giving sole authority to one company will lead to market manipulation? What about farmers who were the direct beneficiaries of this program? Were they involved in the decision-making process to design the intervention?
So what could the government and aid agencies have done differently to prevent unintended consequences, and therefore save the lives of thousand farmers? How could planners have used the iceberg model in the planning process?
First and foremost, the government and aid agencies could have prevented Monsanto gaining a monopoly by making others’ access to the market easier. More suppliers would have brought the cost of inputs down. However, this solution is only workable in countries with a market policy strong enough to control the monopoly. In India, where big suppliers have a tendency to collude with each other to manipulate the market, a stronger solution at macro level must be considered.
Second, the government should understand that the lack of capital becomes a phenomenon among the poor, especially poor farmers. Therefore, when introducing GM to farmers, the government should have additional programs to support farmers. Negotiating with government banks, private banks or even micro finance institutions to allow farmers to get loans with low interest rates and favorable payment conditions should be an option. This would ease the financial pressure for the farmers. More than that, India is well known among Global Microfinance for its high interest loans for the poor. So, what is the role of government to help the poor in India to get access to cheaper loans to reduce expenses and get more profit? This scenario, I think, is just one of many reflecting the weak governance in India in supporting the poor.
Third, the government should have tools to regulate the market to make sure supply will not be flood the market and destablise the rice price. For example, the Government could procure rice from farmers and put the excess into a stockpile to resell when demand outstrips supply.