I believe Poor data hurts African countries’ ability to make good policy decisions. I also believe in the power of information. To improve economic and community development in Africa; All our sectors will need to take advantage of significant performance data.
To improve production and quality we would need to prioritize accuracy, timeliness, relevance and availability in data, especially data of good quality for National Governments and Institutions to accurately plan, fund and evaluate development activities.
Take for example the problem of low wages. How can we increase pay more effectively above the subsistence wage levels to produce the greatest beneficial impact on those at the base of the wage pyramid? Subsistence wage levels are calculated locally and must consider all kinds of things particular to the specific circumstances of individual workers so that they have real meaning. What data science can do is improve predictive power by injecting the much-needed human dimension; for example, beyond the simple increase in wages, which combinations of actions can be undertaken by a company and in which communities, to generate the most lasting positive impact on the lives of employees and their families.
How do you know, for example, if a company really pays a fair salary? Does it help the communities in which it operates to be strengthened so that working families can build a better future? Information on community health, economic and county-level income, local environmental conditions and pollution vectors, job quality and working conditions, and a host of other aspects of socio-economic conditions in African countries are becoming more widely available. Many companies are taking the initiative to make data available. All of this is raw material for impact-oriented data science.
Using science data and data to shed light on how companies can better address the real priorities of African people, including: investing in building healthy communities, improving social outcomes and financial performance, alleviating pressures on poor people, addressing the environmental problems while creating jobs and isolation of social impact metrics that are more powerful in predicting future business performance. The industries in the continent can help to supply the necessary raw materials. And from the crowdsourcing, the best talents in the field of data science, data science and data analysis can turn those raw ingredients into a truly valuable analysis that, hopefully, will bend the curve of economic and community development in Africa in the right direction.