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!
References
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