The Global Hunger Index (GHI) 2022 ranked India 107 out of 121 countries. The index is calculated by normalizing and aggregating multi-dimensional data that includes mortality rates of children under-five, undernutrition among children, and food supply shortages.
India has a very robust food security program through its Public Distribution System (PDS) and a history of providing mid-day meals in its schools. Several regional governments and NGOs distribute free and subsidized meals to vulnerable populations using community kitchens. Have all these efforts not had much impact towards reducing hunger? Or, is the low score a result of regional imbalances? Can we use the underlying data to guide us in formulating policies that help direct investments that can lead to zero hunger?
While the index ranks countries, it is not actionable. A low or high ranking does not guide policymakers in taking corrective actions that can improve the outcome. Further, the degree of correlation of the three selected dimensions to the desired outcome is unknown and providing equal weight to all the dimensions only increases the opacity of the model. In addition, most of the data that goes toward the index are lagging indicators. Even if the goal were to be met today, the index may reflect only years later.
Some of the data collected is based on household surveys, which are expensive undertakings. To control costs, sample sizes are kept small, which can amplify errors when aggregated. Small sample sizes also preclude state/region level data aggregation and cannot highlight regional imbalances.
Another problem with the metric is that more than two-thirds of the score is based on statistics on children. Elderly hunger is indirectly attributed through data on food supply shortages. Many countries that rank high in the global hunger index recognize that undernutrition and food insecurity among older adults, especially after COVID-19, is now at epidemic levels.
In the same report, Sri Lanka ranked 64. It showed a positive trend with improvement over previous years. As recent events in Sri Lanka have shown, the index is neither predictive nor prescriptive.
From Vanity to Actionable Metrics
A given metric can be categorized as vanity or actionable. A vanity metric looks good on the surface but offers limited value. Actionable metrics tie actions to observed results and provide the needed insights to make informed decisions that get you closer to your goals. A positive trend of the metric will indicate that policies, investments, and actions are working and a negative trend of the metric informs the corrective actions that can improve outcomes.
An actionable metric can track targets, identify gaps, and provide a standard way to benchmark and compare status across regions and nations. It allows for transparency in policy-making and guides in directing investments that can have the maximum impact on the most vulnerable populations. Once the investments are made, the same metrics can now quantify the impact and the return on investments.
Measuring Social Impact
The UN Sustainable Development Goals (SDG) provide a shared aspirational blueprint for achieving economic prosperity for all nations and a sustainable future for the planet. The goals recognize that ensuring economic prosperity and preserving the environment starts with removing inequities, creating opportunities, and making sure that basic needs like food, health, and education are available to all.
To measure SDG progress, we introduced a facility-based data model and a set of actionable metrics for each of the SDGs. For SDG 2 (Zero Hunger), instead of looking at household hunger, we look at the availability and accessibility of food and whether it meets the needs of vulnerable populations. We have shown that a facility-based data model is far less expensive than household enumeration and last-mile accurate as compared to randomized household surveys.
For SDG 2, we surveyed PDS outlets and community kitchens and measured them on service availability, service accessibility, and service quality. The facility-based model enables tools and dashboards to visualize geospatial information, which provide the needed transparency and the necessary actionable insights for local and regional officials to light their paths to zero hunger. Open data and apps ensure that the information about access and availability of food is available to all who need it.
Towards Zero Hunger
India has a fairly effective food security program through its PDS outlets. The PDS outlets distribute foodgrains and other commodities at affordable prices and have been effective in ensuring access to food. During the COVID-19 lockdowns, it was recognized that a large number of the population that included the homeless, migrant workers, elderly, and other marginalized groups, without access to or not able to utilize a kitchen, were excluded from its benefits.
Community kitchens are key to providing universal food security. They serve localized, healthy, and inexpensive food, which keep street food prices in check, and extends benefits beyond the marginalized communities to the daily-wager and the urban poor. The challenge now is to plug the gaps, scale, remove regional imbalances, and create a national food grid that is responsive, maintains service quality, and provides food security for all.
Methodology matters, but more than that, it is the quality of the data that determines the quality of the results. Data scientists use the term GIGO (garbage in, garbage out) when nonsense input data produces nonsense output data. It is time to move from GIGO to actionable metrics and chart our path towards zero hunger.
A longer version of this article, that referred the GHI 2021 report, is available at Towards Zero Hunger.
* Header image uses photos by Loren Joseph | Unsplash, Jacopo Maia | Unsplash, Sreehari Devadas | Unsplash