Mapping global seasonality: national times of abundance and scarcity?

Connecting some dots made me think of this exercise. If national governments are increasingly looking at ways to bridge the informal economy with the formal, in order to provide more inclusive benefits to their citizens and at the same time there’s an increasing focus on providing inclusive financial services to those outside of the formal economy, then why don’t the overly large global institutions consider mapping national seasonality as a way to track regional abundance and scarcity?

Rather than applying existing metrics which result in a significant portion of the population slipping between the cracks, there is scope to develop measures of assessment where it is known that incomes are irregular, and tend to display seasonal patterns. This mapping need not be too granular in the first instance, even at country level it may be of help as another layer of information over the various surveys conducted.

India, for example, has long known the linkage between the state of her monsoon season and that year’s economic performance, even for organizations and people who are not directly connected to the land and its produce.  Recently, I did something similar for Kenya, mapping the ebb and flow of local income in three different regions and was able to arrive at a rough estimate for a nationwide time of abundance – a peak sales season, if you will.

Highly industrialized nations have detached themselves from the land and the natural seasons, thus the impact of the rains or the dry season on economic activity are barely perceived. In emerging economies and still developing nations where a greater proportion of the population is rural based and food security more vulnerable to weather changes, these elements can influence national GDP or consumer durable sales.

Whether its segmentation of rural markets for companies or policies of financial inclusion on a global scale, I believe this additional layer of information has the potential to provide some crucial nuances to information currently being analyzed, and found wanting.

This entry was posted in Africa, ASEAN, Assumption filter, Banking, Base of the Pyramid, Business Models, Cashless transactions, China, Consumer Behaviour, Culture, Economy, global, Income, India, Indigenous & Traditional, Informal & Flexible, Kenya, Migrant worker, Philipines, Research, rural, Senegal, South Africa, South Asia, Strategy, Sub Saharan Africa, User research. Bookmark the permalink. Post a comment or leave a trackback: Trackback URL.

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