Paper Example. The Decomposing Framework

Recent advances in information technology resulting from the fourth industrial revolution and associated disruptive innovations, has created vast quantities of big data, generated in real-time and in various formats. Associated developments, such as artificialas artificial intelligence, have contributed to strengthen the field of monitoring and evaluation. Big data analytics and artificial intelligence technologies as a result are playingare playing a significant role in monitoring and assessment by increasing efficiency, reducing evaluation costs, and redefining the field of M&E. This paper applies a decomposition framework to clarify big data analytics and artificial intelligence as determinants of monitoring and evaluation. The decomposing framework is a methodology used for research whereby a single problem is broken down into several subcomponents. It does so within the broader framework of disruptiveof disruptive technologies and the fourth industrial revolution and how they are shaping monitoringshaping monitoring and evaluation.

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Summary of Key Messages

Big data and artificial intelligence have facilitated various capabilities that can be used to enhance the monitoring and evaluation of development operations.Big data and artificial intelligence are being employed to promote monitoring and evaluation processes such as predictive modelling and even forecasting certain changes in systems on a large scale. are currently being used to perform predictive modeling as well as forecasting systemic changes on a large scale.The availability of large scalelarge-scale data is what has triggered the improvements in artificial intelligence. The explosion of data has facilitated the development of artificial intelligence.Big data analytics and artificial intelligence are important factors that will contribute to the 2030 Agenda for sustainable Development. no doubt prerequisites for the realization of the ambitious global goal of 2030 Agenda for Sustainable Development, since almost everything will be handled through technologyThe fourth industrial revolution of digital analytics can facilitate productivity leap since it is associated with a wide range of distinct opportunities that can be used to enhance monitoring and evaluation.Disruptive technologies are evolving rapidly while presenting a high level of performance to be utilized.Big data and artificial intelligence have facilitated various capabilities that can be used to enhance the monitoring and evaluation of development operations.Shifts in global productivity can be enhanced to ensure that the existing challenges existing the global development projects are resolved. Introduction

Over the yearspast 10 years, there has been increased competition for the limited resources allocated to international development, as opposed to the growing expectation of what ought to be achieved through such development assistance (Raftree and Bamberger, 2016). This has facilitated the demand for systems that can effectively evaluate performance as well as the effect of development programs. The rise of big data analytics and artificial intelligence resulting from the fourth industrial revolution (4IR) and associated boom in disruptive technologies are helping to provide platforms and tools that enables participation in decision making, and in turn, allows citizens to access services and increase transparency and accountability. Big data is a broad term used to refer to trends such as the volume of digital data produced daily as a result of high usage of digital services, new technologies, tool as well as methods to analyze large data sets. In addition, it alludes to policy-making insights extracted from the data as well as the tools used (Raftree & Bamberger 2016). Conversely, artificial intelligence alludes to a branch of computer science that facilitates the development of machines that are capable of performing tasks that require human intelligence. In artificial intelligence, machines analyses data and adjust to new inputs. Accordingly, this paper analyzes how big data analytics and artificial intelligence impact the process of monitoring and evaluation through a decomposing framework. The decomposing framework is a methodology used for research whereby a single problem is broken down into several subcomponents (McIntosh & Sajda, 2020). The paper suggests that these tools have managed to shape the process of monitoring and evaluation by triggering the development of more effective procedures; and, concludes that big data analytics and artificial intelligence are essential for the future of M&E since the landscape is changing at a fast pace.

Fourth Industrial Revolution & Disruptive Technologies

The Fourth Industrial Revolution refers to technological innovations characterized by a fusion of a series of technologies, which are blurrblur the lines between the physical, digital, and biological spheres.

The 4IR It speedsupspeeds up innovations, making information access faster, more efficientefficient, and more widely accessible than before. Technology in the era of 4IR is also increasingly connected, enablingconnected, enabling societal shifts by influencing policy-making, economics, values, identities, and possibilities for future generations. Central to the 4IR are bigare big data and artificial intelligence (Manyika et al. 2013). However, an underlying challenge of 4IR is how to effectively utilize these technological advances to ensure success in the performance of an organization (Nalubega & Uwizeyimana 2019).

Disruptive technologies on the other hand, refer to forms of innovations that tend to impact significantly and alter the traditional approach through which consumers, industries, and businesses behave(behave (Segal et al. 2016).. The disruptive technologies developed over the past yearslast 10 years plays a significant role in the rise of new strategies that influence M&E. For example, mobileexample, mobile telephony has facilitated communication via text, besides facilitating voice calls (Segal et al. 2016). Additionally, mobile phones are increasingly being utilized effectivelyutilized effectively as part of large-scale data collection efforts in many sectors, including education. Also, given the widespread availability of these phones with a growing number of functionalities and decreasing acquisition and operating costs, this technology is increasingly being employedbeing employed to aid data collection efforts. Smartphones, as well as tablets, enhance data collection and data can be regularly uploaded to cloud storage, which allows applications to be updated more easily (Segal et al. 2016).

Artificial Intelligence. It refers to the human intelligence simulation in machines which have been designed to mimic specific aspects of humanity (Russell and Norvig, 2016). It focuses on essential human traits, such as learning and problem-solving. Big Data and Artificial Intelligence

In artificial intelligence, machines analyses data and adjust to new inputs. Big data is a broad term used to refer to trends such as the volume of digital data produced daily as a result of high usage of digital services, new technologies, tool as well as methods to analyze large data sets. In addition, it alludes to policy-making insights extracted from the data as well as the tools used (Raftree & Bamberger 2016). Conversely, artificial intelligence alludes to a branch of computer science that facilitates the development of machines that are capable of performing tasks that require human intelligence. In artificial intelligence, machines analyses data and adjust to new inputs. xxxxxxThat is what enables the technology to be designed into specific interventions that will enhance the process of evaluation (McKenzie, 2018). Hence, the latter performs human-like duties such as decision making.

Big data and artificial intelligence are currently being used to perform predictive modelingmodelling as well as forecasting systemic changes on a large scale. The growing capability to collect data associated with people's actions has prompted efforts to utilize the data generated, predict and track behaviorsbehaviours, and schedule timely development interventions.

It is widely agreed that high-quality development data are critical as it informs development impact. Consequently, high quality of development data is the foundation for meaningful strategies that support policy-making, efficient resource allocation, and effective public service delivery in the developing countries. However, development practitioners have begun to explore the use of big data to predict as well as track behavior of individuals (Raftree & Bamberger 2016). One of such organization is the United Nations Global Pulse, which aims at establishing connections between the data generated by web users and possible development interventions. Additionally, Qatara Computing Research Firm/Organization/Instituteion in Qatar is filtering social media traffic to enhance the disaster response (Raftree & Bamberger 2016). However, there are concerns about the privacy of big data due to the increased capacity to identify the behaviorsbehaviours of individuals and trends in geographic locations. This factor should be carefully considered when working with big data.

The explosion of data has facilitated the development of artificial intelligence. The IT professionals have quickly realized that scrutinizing data and analyzing it to improve decision making is tedious (Analytics, 2018). Hence, they have developed intelligent algorithms to achieve the task of deriving insights from the vast data sets collected. Using the data generated from various sources, AI facilitates the building of a store of knowledge to enable accurate predictions (Russell & Norvig 2016). The ability of the AI to be integrated well with big data has made the two technologies inseparable. However, the success of AI depends on the quality of data integrated into big data. Nonetheless, AI has become a cyclical process with big data, and thus, less effort is required to enhance these processes.

Shifts in Global Development PrioritiesThe Effect of Big Data and Artificial Intelligence on Monitoring and Evaluation in Africa and Globally

Big data analytics and artificial intelligence are no doubt prerequisites for the realization of the ambitious global goal of 2030 Agenda for Sustainable Development, since almost everything will be handled through technology. IndeedIndeed, related technologies such as satellite imagery, geo-engineering, and smartcards comprise of discoveries that have a high possibility of disrupting global development (Manyika et al. 2013). Other related technologies, such as virtual reality, are also being used in building modelsbuilding models to support the monitoring and evaluation of development projects and programs, as well as tracking the progress of development interventions both in Africa and in globally. Similarly, theseSimilarly, these technologies care being used to evaluate interventions and facilitate service delivery as well as policy strengthening.

In the field of monitoring and evaluation, big data has a high potential for complementing traditional data sources. The latter is accomplished by enhancing uniqueness as well as providing an up to date information that can be utilized to present a comprehensive outlook of a situation ("UN Global Pulse," 2012).