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INTEGRATING BIG DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE INTO MONITORING AND EVALUATION (M&E) IN A FAST-CHANGING DEVELOPMENT LANDSCAPE

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INTEGRATING BIG DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE INTO MONITORING AND EVALUATION (M&E) IN A FAST-CHANGING DEVELOPMENT LANDSCAPE

Abstract

Various trends are regarded to affect the field of monitoring and evaluation within the scope of international development. Resources allocated towards development have become more scarce, while the expectations for their input towards development is increasing drastically. A search for more efficient systems to evaluate the impact of these changes is currently being developed. The state governments have also put a considerable effort into enhancing their evaluation capabilities. Additionally, substantial demand from the international community is increasing to ensure that meaningful participation in evaluation is achieved. The efforts aim at improving the accountability from both the development agencies as well as the recipient countries. These factors have pushed the donors as well as the evaluators to seek more rigorous systems to monitor and evaluate the human interventions as well as development approaches.

Information technology has fostered several web-based services that affect every aspect of today’s development activities. These generate large quantities of data, often referred to as big data. These data are made in real-time and in varying formats and from a wide range of sources. African and the global context faces a surge in evaluation data sets, reflecting large and increasing monitoring and evaluation records. This condition can enhance the analysis to improve decision making by providing more granular data as development indicators.  To facilitate this factor, techniques like big data analytics, as well as artificial intelligence, are being developed to provide more holistic data analysis. An increasing number of donor agencies have developed big data approaches to explore these concerns.

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Introduction

Over the years, there has been a high competition for the limited resources allocated for the international development aid, alongside the vast growing expectation of what ought to be achieved through these projects. This factor has facilitated the immense demand for systems that can effectively evaluate performance as well as the effect of development programs initiated. The developed countries have also increased their commitment to developing systems that can effectively evaluate the performance of the national projects. Additionally, the civil society and the local organizations argue that there is a high demand for assessing the participatory, humanitarian as well as the aspect of equity associated with development to enhance monitoring and evaluation processes. Furthermore, the growth in crisis incidents has led to an increased demand for evaluating the effect of development during the occurrence of such events.

The factors given above have led to high demand for more rigorous and flexible epic leadership developmentto monitor and evaluate development as well as human interventions. A critical evaluation of strengths epic leadership developmentassociated with the current monitoring and evaluation (M&E) processes identifies that the current conventional M&E approach faces two broad sets of challenges (Acevedo, Rivera, Lima, and Hwang 2010). The first set is regarded as the operational challenges, while the second is referred to as methodological challenges. The former includes the cost of data collection, the complexity of relevant data as well as difficulties in obtaining up to date data. Conversely, the methodological challenges include the problem of construct validity, challenges in developing theories of change as well as insecurity. However, new ICT tools and applications can help address some of the difficulties given as well as contribute towards overcoming a real-world challenge.

The rise in Disruptive Technology

New technology virtually affects every aspect of an individual in the universe. For example, a 40 percent rise in the usage of mobile phones was recorded in 2011 at the global index. Similarly, the growth in the usage of tablets was discovered to have increased steadily. In a recent study, nearly 7 billion individuals had subscribed to a mobile cellular network in 2013. Hence, international development is developing a myriad to utilize the chance generated by this growth. The field of ICT for development is also growing to accommodate rapidly growing technology. Conversely, ICT gained popularity when the public sector began to use information management systems to facilitate the administrative processes (Segal, van Wayk, O’Flaherty, Simmons, Osinubi, Yaiche 2016). In the 1980s, international corporations utilized computers to spur economic development in the private sector. In the 1990s, the internet was hugely used in technology development. In 2000, technology revolved around integrations of ICTs. The year was characterized by development of mobile phones.

As technology advances, the field of ICT4D has also developed. Currently, ICT4D places a significant emphasis on participation, flexibility, improvisation, learning, as well as local capacity. The initiatives were designed for the poor in a laboratory (Heeks 2009). The ICTs are found throughout the development process in every field of development. The latter facilitates development organizations in improving their information management, advocacy as well as public outreach.  The ICTs are also used directly in programs, where they enable individuals to access information, markets, financial service as well as healthcare (Heeks 2009). The latter would allow individuals to connect with friends as well as families and augment the overall participation in the development process (Segal, van Wayk, O’Flaherty, Simmons, Osinubi, Yaiche 2016). Furthermore, ICT facilitates enhanced feedback as well as participation from a population being served by a particular agency. ICTs have facilitated new innovative approaches in the collection of data, new methods of data combination and analysis, as well as faster data processing to enable planning and decision making.

The new technology, as well as the software devices, developed over the past years, plays a significant role in the rise of new strategies to M&E. For example, a mobile phone can facilitate communication via text, besides facilitating voice calls. Additionally, a more advanced mobile phone will provide for the installation of applications, image capturing as the ability to locate and deliver location tracking using global positioning systems. Smartphones, as well as tablets, can enhance data collection and make it easier and intuitive. In a steady network, data can be regularly uploaded to cloud storage, which allows applications to be updated more easily (Segal, van Wayk, O’Flaherty, Simmons, Osinubi, Yaiche 2016). Additionally, a rise in mapping tools, software, platforms as well as data visualization options provides for the capability to combine sophisticated data sets and support more informed decisions and implementation of programs as well as resource utilization. Technologies are being developed to ensure real-time availability of information to program managers, the community as well as other frontline staff. Finally, new tools are designed to enable the evaluators to manage M&E processes and outcomes.

The social media is also developing to enable a lengthy discussion as well as the engagement with the information being shared. The ability to manage social media using big data analysis provides for a powerful assessment tool. Some evaluators are also using social media to conduct focus group conversations or monitor how the perceptions of participants about a certain initiative (Segal, van Wayk, O’Flaherty, Simmons, Osinubi, Yaiche 2016).. Currently, ICT offers a wide range of possibilities, including program planning, data visualization, sharing evaluation outcomes as well as capacity building in the field of M&E. Additionally, different technologies combined to facilitate the efficiency of the existing data collection methods. These advancements aim at facilitating new notions about M&E. Conversely, ICTs are being integrated into various monitoring systems, which can enable evaluators to enhance the quality of data collected.

Big Data and Artificial Intelligence

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. Additionally, it alludes to policymaking insights extracted from the data as well as the tools used (Raftree, L. and Bamberger 206). Big data is currently being used to perform predictive modeling as well as forecast systemic changes on a large scale. Additionally, big data can be used to determine the idiosyncratic shocks as well as processes. Mostly, big data exists in high volumes, varies greatly, and has a fast velocity (Raftree, L. and Bamberger 206). More often, the data originates from a variety of sources such as news sites, records of online transactions, and mobile signals. The growing capability to collect data associated with people’s actions has prompted efforts to utilize the data generated, predict and track behaviors, and schedule timely interventions.

Large organizations use large sets of marketing as well as the data on behavior to shape their efforts in marketing and increase the revenue generated. However, recently, humanitarians, as well as other development agencies, have begun to make explorations regarding the usage of big data to predict as well as track behaviors of individuals living beyond the poverty lines (Raftree, L. and Bamberger 206). Big. One of such organizations includes the Global Pulse, which aims at establishing connections between the data generated by web users and possible development interventions. Additionally, a Computing Research in Qatar aims at filtering social media traffic to enhance the disaster response (Raftree, L. and Bamberger 206). Big.  However, there are concerns about the privacy of big data due to the increased capacity to identify the behaviors 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 sifting across the 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 (Russel and Norvig 2016). The ability of the AI to be integrated well with big data has made the two technologies inseparable. Currently, the AI machine learning, as well as in-depth learning, are utilizing inputs to generate new rules for future organizational analytics (Analytics 2018). 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.

The fourth Industrial Revolution

Most organizations are amid significant technology disruptions. These transformations have been hugely driven by the recent technological changes that entail big data and artificial intelligence, robotics, as well as the internet of things (Manyika, Chui, Bughin, Dobbs, and Marrs 2013). The revolution is developing at a dizzying speed with its impacts being evident across many sectors, such as intense internal competition within an organization. However, the underlying challenge is how to utilize these technological advances to ensure success in the performance (Nalubega and Uwizeyimana 2019). The fourth industrial revolution of digital analytics can facilitate productivity leap since it is associated with a wide range of distinct opportunities. These opportunities include faster acceleration, a factor that enables changes to be effected more quickly. Additionally, the higher efficiency associated with the fourth industrial revolution ensures that the changes enacted consume fewer resources while giving a considerable effect. Thirdly, the enhanced predictability allows firms to schedule their activities consistently. Finally, deeper engagement at all levels leads to more extensive resource networks to reinforce the new behaviors.

As essential product functions become progressively commoditized, product design emerges as one of the crucial aspects of differentiation. However, some of the best countries have already utilized this advantage. Hence, the next level of product optimization combines both the latest design thinking with various data sources, as well as exploits the advanced analytics techniques to gain an understanding of possible cost and value improvements (Nalubega and Uwizeyimana 2019). The. For instance, a computer-aided design tool can be associated with various pools of procurement data and social media activities to enable a firm to identify designs that optimize profitability. These signs of progress are not only meant for consumers but also for utilities whose traditional business models have been upended by more sophisticated clients. Conversely, in manufacturing and other sectors such as banking, lean management has facilitated firms to focus more on activities that create value, which clients are willing to meet its cost. New technologies are successfully enabling the attainment of these elements.

In the recent past, the zero-based budget has proved to be worthy and played a significant role in cost reductions. However, due to slow growth, some of the high-profile companies have built speed, scale as well as sustainability around a ZBB process to facilitate cost saving of about 10 to 25 percent. Conversely, most of the companies in the world have focused their attention on new manufacturing technologies (Nalubega and Uwizeyimana 2019). The development has been spurred by emergence of cheap internet-linked sensors as well as availability of user-friendly tools for data analysis. These technologies enable individuals to have a high level of understanding as well as control over the complex processes, leading to a substantial economic impact.

Shifts in Global Development Priorities

There is a sense in which projects in a global landscape are ever-changing. The development agencies are ever generating new reports and drafting new policies to increase the scope of the projects. The biggest concern is the scope of the changes and the extent to which foreign aid contributes towards the development. Furthermore, the form of the relationship existing between the development agencies and the recipient states is a major concern(Harman and Williams 2014). From the argument, we can identify four shifts in global development priorities. The first is the shift in thinking, which emphasizes the role played by the state in the development process. The second, return on big and small projects, whereas the third demonstrates a set of changes within a donor environment that has led to the choice for aid recipient state based on both pluralism and autonomy (Harman and Williams 2014). Finally, there is a change in the relationship between aid recipient countries, reinforcing the independence and the development agencies.

Recently, there has emerged a debate over the roles of states as and markets within a development process, taking place within the World Bank. One aspect of the discussion has been a reflection on the record of development for the last 15 years. The World Bank has maintained that progress can only be achieved if growth exceeds the efficient use of the allocated resources  (Harman and Williams 2014). The institution suggests that development can only be realized if economic policies are associated with profound changes in social relations as well as the patterns of production and consumption. This factor demonstrates a recognition that development policies should adapt to changing the prevailing external circumstances (Kharas and Rogerson 2017). Nonetheless, there have been notable changes concerning patterns of the funding of development projects, which can be associated with the debate concerning the development policy.

Secondly, there is a considerable shift in the donor priorities towards infrastructure and investment in middle-level states. The emphasis of this factor has been to determine the role of the recipient country as the driver of the respective projects. The change has been propagated by the classification of projects as big or small, as defined by the World Bank (Harman and Williams 2014). The latter suggests that big projects require a hefty investment on roads, ports, agriculture, public health, finance, and justice. The vision involves assistance from the private sector. However, its functionality hugely depends on a legitimate institutional arrangement to ensure that interests of elites, general citizens as well as the local entrepreneurs are considered (Kharas and Rogerson 2017). Conversely, small developments are influenced by fewer change visions for a country, and more by the material plight of individuals. Mostly, donors are channeling their aid towards the significant development policies.

Thirdly, the volume of financial aid has increased dramatically over the last two decades. However, there has been a significant change in the donor’s landscape facing the assistance recipient countries. There has been a growth in the number and the weight of the non-traditional donors increased significance of the regional development banks as well as the emergence of philanthropists, which have spurred changes in challenges posed by the development landscape  (Harman and Williams 2014). These factors indicate a new form of pluralism as well as dispersal of authority in terms of which an agency sets the agenda of development in developing countries (Kharas and Rogerson 2017). These shifts are significant since they might change the relationship the donors and the recipient states. Finally, the new pluralism existing among the donors provides an opportunity for developing countries to choose from the available aid providers. This factor also minimizes the leverage that some donors have over development policies in developing states.

Effect of Above Developments in the Field of Evaluation in Africa and Globally

Technologies such as satellite imagery, geo-engineering, and smartcards comprise of discoveries that have a high possibility of disrupting global development. The technology professionals are working hard towards enhancing development interventions. However, there are similar advances within the field of business, which are hugely influenced by the availability of big data. Nonetheless, some of the disruptive technologies such as automation threaten a lack of jobs, mostly in the production sector globally and in Africa (Manyika, Chui, Bughin, Dobbs and Marrs 2013). Some of the technologies, such as virtual reality, can be used in building empathy and support for global development projects. Furthermore, they can be used in evaluation and monitoring in the aid agencies to track the progress of the global developments both in Africa and in the worldwide context. Additionally, some technologies can be used to influence evaluation 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). For example, the use of remote reporting digital sensors for evaluating the use of water filters in Rwanda can be used to collect objective data to enhance control of sustainability interventions. Conversely, other projects can track real-time occurrences by analyzing online content. This factor is necessary for providing a baseline for a current incident, updating this with current snapshots to monitor how a situation transforms, which can be used in the program interventions (UNDP 2013). Additionally, the Un Global Pulse operates several projects which utilize social media to monitor the social environment. This factor provides a baseline of how a public discourse changes over time to facilitate monitoring and evaluation of effectiveness.

The fourth industrial revolution (4IR) poses a challenge to the traditional monitoring and evaluation in public as well as the private sector in Africa and globally. The technological advancements brought forth by the fourth industrial revolution is changing how various societies conduct their daily operations (CEPAL 2018). However, besides the numerous opportunities associated with (4IR), it also poses a risk to the regulatory framework of the countries most in data and cybersecurity as well as consumer protection. Hence, this factor necessitates call to address effects of 4IR for monitoring and evaluation in both Africa and the global context. Monitoring and assessment have a high likelihood of growing and adapting to a changing environment while addressing the worldwide public demands. Hence, this factor necessitates enhancement in the intellectual capabilities of practitioners to utilize the opportunities brought forth by the technological advancements to develop sustainable solutions to monitoring and evaluation issues in Africa and the world (Rogerson 2014). The 4IR provides for vast opportunities for customizing M&E into the African and global development policies as well as the program evaluation approaches.

Presenting international assistance as aid as the expansion of the recipient nation investment opportunity has become an essential aspect in enhancing the defense for the budgetary aid allocations. The policies for spending federal aid inspire conflicting self-interest rationality. This factor prompts considerable shifts in the field of architecture, which can be attributed to this change. Conversely, the recipient countries are required to enact stringent measures to ensure that financial aid granted by the donors is used efficiently and resources are fully utilized. Additionally, the recipient country is expected to present project insights that will ensure that fields with a high level of urgency are considered to enhance the smooth running of the country.

 

 

 

 

 

Reference List

Raftree, L. and Bamberger, M., 2016. Emerging Opportunities: Monitoring and Evaluation in a Tech-Enabled World https://www. rockefellerfoundation. org/report/emergingopportunities-monitoring.

Kharas, H. and Rogerson, A., 2017. Global development trends and challenges: horizon 2025 revisited. Overseas Development Institute.

Segal, J., van Wyk, A., O’Flaherty, M., Simmons, M., Osinubi, F. and Yaiche, N., 2016. Disrupting Africa: Riding the wave of the digital revolution. In PwC.

Harman, S. and Williams, D., 2014. International development in transition. International Affairs90(4), pp.925-941.

CEPAL, N., 2018. Emerging challenges and shifting paradigms: New perspectives on international cooperation for development.

Nalubega, T. and Uwizeyimana, D.E., 2019. Public sector monitoring and evaluation in the Fourth Industrial Revolution: Implications for Africa. Africa’s Public Service Delivery and Performance Review7(1), pp.1-12.

UNDP (2013) Discussion Paper: Innovations in Monitoring and Evaluation. Retrieved from http://www.outcomemapping.ca/download/UNDP%20Discussion%20Paper%20Innovations%20in%20Monitoring%20and%20Evaluation.pdf

UN Global Pulse (2012). Big Data for Development: Challenges & Opportunities [White Paper]. Retrieved from http://www.unglobalpulse.org/sites/default/files/BigDataforDevelopment-UNGlobalPulseJune2012.pdf

Analytics, M., 2018. Analytics comes of age. McKinsey & Company: New York, NY, USA.

Rogerson, A., 2014. Financing the post-2015 Sustainable Development Goals: a rough roadmap. Overseas Development Institute.

Manyika, J., Chui, M., Bughin, J., Dobbs, R., Bisson, P. and Marrs, A., 2013. Disruptive technologies: advances that will transform life, business, and the global economy.[Sl]: McKinsey Global Institute.

Acevedo, G.L., Rivera, K., Lima, L. and Hwang, H., 2010. Challenges in monitoring and evaluation: an opportunity to institutionalize M&E systems. Washington, DC: The International Bank for Reconstruction and Development/The World Bank.

Russell, S.J. and Norvig, P., 2016. Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited,.

Heeks, R., 2009. The icT4D 2.0 Manifesto: Where next for icTs and international development? (Development informatics Group, Ed.). Manchester, uK: Development informatics.

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