Building appetite for empirical guidance in developing countries

Building appetite for empirical guidance in developing countries

Besides health-related statistics like COVID19 cases, number of those recovering and number of the deceased, most countries lack data and statistics related to how the pandemic has impacted the economy. Without significant appetite for empirical evidence and guidance, it is difficult for policy makers to take appropriate precautions towards reviving the economy.  Data and evidence has never been so important in directing decisions on recovery and restoration of agro-based economies. The graphic below show the impact of COVID19 on potato supplies and price trends in Mbare market of Harare.

Lack of data and information along the supply chain leads to ad hoc decisions.  More importantly, without data and statistics, policy makers will not know what will be the price of staples like maize meal in the next six months or by the beginning of the next planting. COVID19 has revealed the importance of collecting data towards informing pricing models. When quantities of commodities in farming areas and volumes destined for the market are not known, price setting is an artificial exercise.  Mass markets are different to formal markets in that they tend to predict and prices when the commodities reach the market.

Who should have appetite for data?

In addition to policy makers, formal organizations like seed companies and processing companies should be interested in market data. For instance, volumes of commodities flowing into agriculture markets reflect inputs that have been provided or sold to farmers just as such volumes will guide processing companies in procurement decisions. More importantly, formal companies should be interested in data on what is happening in informal markets because the more informal the economy becomes, the more formal companies fail to understand the competitive landscape and eventually collapse.

Research institutions, government department and farmer unions should also have a strong appetite for data because they work with many people whose millions of insights should be collated to give a complete national picture. Individual farmers may not be able to demand data which they have no idea how to use or interpret it. In the same many consumers would rather eat a meal than be given different ingredients to make their own meals, farmers may just be interested in solutions not ingredients.  Otherwise restaurants and fast food chains would have gone out of business as consumers resort to preparing their own meals at home.

In most cases, individual farmers may not have uses for all the data comprising more than 80 commodities when they are only dealing with two or five. If you are selling a few buckets, information about all commodities may mean nothing.  Even if farmers are informed about prices of commodities, they may not have the power to influence price changes except may be to make decisions about selling to the local market. Big companies and research institutions who are more interested in understanding the entire value chain or ecosystem definitely need data. Wholesalers and processors need the data for projecting their trends and plans. On the other hand, since they are not technocrats, ministers should not be bombarded with complex data.

 Achieving collective impact through data

Development organizations like NGOs that have become used to pursuing isolated impact in rural Africa are being challenged by COVID19 to consider embracing collective impact through collective utilization of data. In big districts like Chimanimani or Lupane in Zimbabwe, it is not possible for a single NGO or a consortia of NGOs under one program to achieve real impact without bringing on board other actors in the same communities towards collective use of data. How can an NGO working with 10 000 beneficiaries hope to impact the entire community of more than 400 000 people?  Likewise, it is far-fetched for a program working only in 18 districts to dream of impacting a country with 60 districts without paying attention to the power of data.

Given the number of years they have been operating in African countries, some UN agencies would by now have built a huge knowledge base comprising fluid statistics.  Unfortunately that is not the case because such organizations work through consultants who just present reports after every assignment and walk away with much of the knowledge gathered from the field. When there is an outbreak of Fall Armyworm, Anthrax or locusts, African scientists are not able to generate home-grown solutions but have to tell farmers to spray chemicals imported from the West. Experiences of dealing with previous shocks have not been consolidated into a solid knowledge base. Every interventions starts from scratch.

The imported formal education system is partly to blame for this predicament. African experts cannot move beyond numbers that are just thrown around with no interpretation. For instance, a country can say its population consumes 1.8 million metric tons of maize annually but there are no attempts to break down the figures into what goes to processing companies, what goes for the Maputi industry and how much is taken by the green mealies consumption. Irrespective of pandemics like COVID19, agricultural commodities are always in transit and if the government does not know where commodities are coming from and going as well as in what quantities/volumes, policy making is like chasing greased pigs.  / /

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