Data and Development Planning

THE creation of a dense network of technologies and radical shift in the volume, variety, quality, and speed of data generated on people, governments, economies, and environment has led to a salvo of new information (and techniques of storage, access and analysis) without precedent in history (UNDP 2016). Data is rapidly transforming society and the way in which the world functions. It requires enormous opportunities – as well as challenges – to improve the livelihoods of people around the world (UNDP 2016). Access to data and data analytics has the potential to radically improve service delivery, public administration and accountability of governments and businesses (Sachs, 2015). According to the UNDP, it is estimated that governments worldwide already posted over one million datasets on the Internet (IDRC 2013). However, only a small fraction of these datasets is from developing countries. This points to the lack of knowledge in some parts of the world, despite a data surge in others (UNDP 2016).

New data collection and monitoring technologies are becoming rapidly available. These innovations will dramatically advance national statistical offices’ and the international community’s ability to monitor the impacts of development programmes, in addition to informing the way they are designed and implemented.
Critical data for global, regional and national development policymaking are still lacking. Many governments still do not have access to adequate data on their entire populations. While most data are typically public, assessing it is not always easy, and mining it for relevant insights can require technical expertise and training. Making good use of big data will require collaboration of various actors including data scientists and practitioners, leveraging their strengths to understand the technical possibilities as well as the context within which insights can be practically implemented (Maroof, n.d).

Effective application of big data would require changes in decision-making process, which customarily relies on traditional statistics. Given the high frequency of big data, a more responsive mechanism will need to be put in place that allows the government to process information and act quickly in response (Maroof, n.d).
Moreover, it must be acknowledged that data are an essential for the delivery of the 2030 agenda for Sustainable Development. The Development Co-operation report (2017) produced by OECD highlights the importance of data for development because of the quality, timely and disaggregated data that are crucial for achieving the ultimate goals of development – improving welfare of people and fighting poverty.

Investing in statistical systems needs to become a strategic priority for developing countries like Guyana and providers of development cooperation alike. Development cooperation can help developing countries produce and use more and better data in a responsible and transparent manner for good policy outcomes (OECD, 2017).
The OECD has put forward six concrete actions that can bridge the data divide for sustainable development which includes making statistical laws, regulations and standards fit for evolving data needs; improving the quality and quantity of financing for data; boosting statistical capacity and data literacy through new approaches; increasing efficiency and impact through data compacts or other coordinated, country-led approaches; investing in and use country-led results data to monitor progress towards the Sustainable Development Goals and produce and use better data to help understand the overall state of SDG financing.

Guyana is about to enter an era of transformational development of its economic landscape and is ripened to be positioned as the number one investment destination in the Latin America/Caribbean and South America, if not the Western Hemisphere.
As a signatory to the United Nations 2030 Agenda on Sustainable Development Goals, it is imperative that the development path undertaken by the policymaker is aligned to the SDGs. Guyana has a huge gap to fill where data-driven policy is concerned; there is a lack of data collection to aid in this regard. The data is not necessarily unavailable, but rather, lack of compilation owing to most agencies still largely manual.
It is crucial, therefore, that going forward, data for development planning needs to be tied to a national digital transformation strategy and / or an ICT strategy which needs to be implemented quickly. More so, agencies such as the Bank of Guyana, and the Guyana Revenue Authority that sits on an abundance of data, and the Guyana Bureau of Statistics, need to work collaboratively in these respects.

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