South Africa has 532 African, Asian and Coloured townships that have a larger geographic area than both Johannesburg and Durban combined. In 2019, there were 21.7 mil people living in these townships. Gauteng with 8.9 mil people living in them has the largest township population followed by the Western Cape with 3.2 mil people.
The impact of COVID-19 on people living in townships has been dramatic and has been described by some as an “perfect storm”. The greatest impact has been the increase in unemployment and poverty. Between February and June 2020, labourers were 10 times more likely to have lost their jobs. During this period there was a 2.2 million decrease in employment countrywide.
Much of the job losses (515 000) were in community and social services and in the trade sector (373 000), all of which would have impacted on the economy of townships. As a consequence, there was a 4.4 million increase in social grants to 14 - 18 million recipients. This increase in grants is larger than the four million grants issued between 2009 and 2019. The R350 grant allocated to people is highly likely to become a permanent feature to assist people overcome the long term impact of the pandemic.
This is exacerbated by the fact that nearly all local municipalities did not receive a clean audit because of aspects such as corruption. What this means is that funding that could have been made available to township communities to address the impact of the pandemic would not be available. Add to this is the many townships (eg Khayelitsha) that are impacted by violent crime and others have high levels of property and social fabric crime.
To be able to understand these trends and to develop appropriate interventions to bring about change in the lives of people living in townships as well as to develop appropriate policies, requires access to a single source of granular geospatial data layers. This is the idea behind the Township Potential Atlas that will provide a wide range of comprehensive geospatial data.
These data layers would include the boundaries of townships , primary, secondary and tertiary datasets that will include point data, such as malls, retail outlets and government service points. Current demographic data and information on housing, especially backyard dwellings are vitally important. Backyard dwellings play a critical role in the socio-economic character of townships but also have a significant impact on bulk services. Economic data, especially income, is critically important to understand the potential of townships, the viability of communities and opportunities for businesses. To be able to communicate with township communities requires an understanding of all forms of media covering them.
A critical layer of information is retail data and a census of 150 857 FMCG retail outlets was conducted in the major metropolitan and urban areas of South Africa in 2019. It is anticipated that the actual size of the FMCG market in South Africa is between 280 000 and 370 000 outlets. This partial census of the country included informal and formal businesses from table tops to brick and mortar outlets in 11 different trade channels with data collected on 16 major product categories. In the 318 townships that this data covers, a total of 73 795 FMCG retail outlets can be found. A recent audit of 1 000 of these retail outlets has shown a potential attrition rate of 6% during the time of the pandemic.
Similar censuses have been conducted in the major urban areas of 18 African countries and data on a total of 450 000 FMCG retail outlets collected. The long term strategy is to increase the number of retail outlets and to update the information on an annual basis through the conducting of censuses as well as using other innovative techniques. This information on retail outlets in South Africa and other African countries is critically important to understand the multiple routes to market, especially in townships.
Geospatial data of this nature is an asset especially when it can be used to implement appropriate strategies and policies. Innovative web mapping technologies provide easy access to this data and tools to visualize and analyze the information. For example, it can be used to visualize the data on small enterprises in townships to get a thorough understanding of the different business segments that they fall into and what are the positive and negative characteristics associated with him. This allows different strategies to be developed for the diversity of small businesses.
The various primary, secondary, tertiary and point datasets can be overlaid and used to create informative “heatmaps” and dashboards that can used to filter the data and provide summary statistics. Importantly, this comprehensive source of geospatial data is foundational in being able to develop optimized retail and service networks in the townships. The value of this geospatial data, especially in a web mapping format, is to allow route to market planning, policy development, identification of new market opportunities and the development of sustainable businesses and markets. It also facilitates the building of partnerships with township entities, the development of planning norms and standards for the provision of services, the implementation of CSI and community projects in the townships.