Well before COVID19 showed up, many African governments and development organizations had begun investing in digital dashboards as tools for consolidating and presenting information on their activities. In a digital sense, dashboards try to present comprehensive information in real time as opposed to basing decisions on historical data scattered in different government departments and projects. Formal institutions have awakened to the fact that relying on historical data is like driving while looking in the rear view mirror.
Enriching forecasting processes and models
Following COVID19, entire economic sectors like agriculture as well as government departments and development agencies no longer have a reliable baseline for building their forecasting models. This development is forcing institutions to create real-time dashboards based on new drivers of change and multiple scenarios as opposed to forecasting models built upon macroeconomic indicators. Consequently, the pandemic as accelerated the evolution of several dashboards such as this one https://foodsystemsdashboard.org/ designed to make sense of food systems.
Where governments, development organizations and communities used to rely on historical data and intuitions to plan, recovering from COVID19 will most likely depend on how data is collected, analyzed and made sense in real-time of through dashboards. The pandemic has strong interdependence between African countries and food systems through cross-border trade that has continued to feed populations. Unfortunately, the movement of food largely uncaptured and unnoticed yet such details should be reflected on national dashboards.
If properly set up, dashboards can capture data with higher levels of precision and better inform socio-economic forecasting models. Due to the paucity of data in most African countries, macroeconomic indicators are not able to accurately reflect how different micro markets, production zones and consumers at different income levels are behaving to cope with shocks.
Using dashboards to guide agricultural transformation
Given their strong inclination on fresh and fluid data, dashboards can guide the formulation of transformative agricultural marketing policies by ensuring such processes are informed by:
- Comprehensive analysis of the entire national food basket.
- Thorough assessment of supply corridors for all commodities. This will reveal barriers to market participation for various commodities and actors.
- Updated market data (supply volumes, prices and actors for different markets) and interpretations.
- Local consumption patterns and taste preferences. Policy makers should understand changes happening in the local consumption landscape before focusing on exports.
In the absence of a robust dashboard, most agricultural policies are based on literature review and lack current market trends as well as information that should be flowing in real-time from the grassroots. Where data is lacking, policy makers should at least be informed by audiences who are the ultimate implementers of the policy especially supply chain actors like farmers and processors as well as exporters most of whom can be classified as small to medium scale.
Developing an accurate forecast requires building a new baseline based on the external data that affects all actors in ecosystems or value chains. This will enable governments, development agencies and the private sector to build resilient models by combining historical data with real-time data, showing volumes of commodities from hundreds of external data points and contributing to stronger forecasts.
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