The Need for Fellows Analytics
The COVID-19 pandemic has been a reminder that management in times of crisis must be based more than ever, on reliable and credible statistics (African Union, 2022). The lack of quality data in Africa not only limits the continent’s ability to generate a pertinent body of knowledge but also prevents analysts from generating the evidence that policymakers need to make proper decisions in influencing the development of the continent (Kinyondo & Pelizzo, 2018).
The ability to generate data systematically outpaces the ability to store it (Mellado, 2015). Africa’s structural problems are better solved or avoided with quality statistical data (African Union, 2022). Data, and especially data of good quality, are essential for national governments and institutions to accurately plan, fund and evaluate development activities. Solutions to social and economic problems are often inseparable from statistics (Donatien, 2016). The African continent often lags behind the rest of the world when it comes to embracing innovation in the field of data. Africa needs specialists who are proficient in big data techniques (Mellado, 2015).
You cannot build schools without knowing how many children need to be enrolled. Private investors need to know what resources are available in a given country before putting in their money. A country needs to know what it grows and where to prevent famine. Donors can only know whether their aid is changing lives if they have data (Donatien, 2016).
In 2015, 65% of the Millennium Development Goals indicators for countries in Central Africa were either estimated, derived from statistical models, or were last measured before 2010. Data in Africa are not produced on time, are not frequently produced, are of poor quality and are not accurate. Limited access to and usability of data. This makes it difficult to make data-driven decisions (Donatien Beguy, 2016). The problem of data quality in Africa is due to the lack of research culture rather than just scarcity of resources, as argued in the literature (Kinyondo & Pelizzo, 2018).
One of the problems that scholars encounter when conducting research is that data from Africa are poor (Kinyondo & Pelizzo, 2018). The paucity of accurate, reliable and timely data has been a recurring issue. It continues to be a major constraint to the effective monitoring and evaluation of interventions and development programmes across countries in Africa (Donatien Beguy, 2016). Indeed, they either do not exist in a complete sense or are not of good quality in the sense of lacking validity and reliability (Kinyondo & Pelizzo, 2018).
African governments and their development partners need good data on basic development metrics. To be of value, such data must be accurate, timely, disaggregated and widely available. This is not the case in many African countries (Donatien, 2016). Most data are based mostly on estimates & conflicting (Muzenda, 2010)
There have been gains in the frequency and quality of censuses and household surveys over the past 30 years or so. But the building blocks of national statistical systems on the continent remain weak (Donatien, 2016). There is world’s growing need for statistics and the widening gap between developed and developing countries regarding access to information – the data gap (Bédécarrats et al., 2016).
Data is the first step – but then you need analysis. Development decisions should be informed by data. But more importantly this data must be turned into information that is easy to understand and useful to end users. Data is the first, crucial step. Then you need smart, objective analysis to make sense of the data and shape the narrative. Once the data supply side is up to par, the hope is that decision-makers at all levels will increasingly demand relevant information to lay the foundation for policymaking and budgeting (Donatien, 2016).
These are the issues that African countries should address to drastically improve data systems and the quality of data needed for development (Donatien, 2016). Much of the economic and structural problems that Africa faces today and, in the past, could be better resolved or avoided altogether if quality statistical information was available (African Union, 2022). There is, therefore, a need for contributions to data quality, the evolution of data over time, and the role of innovations, especially new technologies (Bédécarrats et al., 2016).
We cannot afford to continue with business as usual. We want to help modify the relationship between donors, governments, and statisticians to work in harmony with statistical priorities (Donatie, 2016). Data, and especially data of good quality, are essential for national governments and institutions to accurately plan, fund and evaluate development activities. To build an institution that can produce accurate, unbiased, big, and open data was a task at hand. As a result of all the above-mentioned issues, Fellows Analytics was founded!
Donatien B. (2016, August 18). Poor data affects Africa’s ability to make the right policy decisions. The Conversation. https://theconversation.com/poor-data-affects-africas-ability-to-make-the-right-policy-decisions-64064
Kinyondo, A., & Pelizzo, R. (2018). Poor Quality of Data in Africa: What Are the Issues? Politics & Policy, 46(6), 851–877. https://doi.org/10.1111/polp.12277
Mellado, B. (2015, November 19). The big data challenge and how Africa can benefit. The Conversation. https://theconversation.com/the-big-data-challenge-and-how-africa-can-benefit-50664
African Union. (2022). Africa’s structural problems are better solved or avoided with quality statistical data | African Union. Au.int. https://au.int/en/pressreleases/20201221/structural-problems-are-better-solved-or-avoided-quality-statistical-data
Muzenda, D. (2010). Challenges in Data Collection: China’s Engagement with Africa, OECD -DAF -Investment Africa’s Emerging Partnerships, Expert Meeting; 12 Oct 2010. In oecd.org. https://www.oecd.org/dev/46295687.pdf
Bédécarrats, F. C. J. P. & Roubaud, F. (2016). The Data Revolution and Statistical Challenges in Africa: Introduction to the Special Report. Afrique Contemporaine, 258(2), 9–23. https://www.cairn-int.info/article-E_AFCO_258_0009--the-data-revolution-and-statistical.htm