Ngonidzaishe Makaha and Adrian Mapiye
Data analytics has shaken our everyday perspective and decisions over the recent years. It has realised exponential growth and sophistication with the advent of new algorithms, computations and storage systems. Big data, unlike statistical data is found everywhere including business administrative systems, social networks and the internet of things. In this era of information overload where approximately 2.5 quintillion bytes of data is created every single day, according to DOMO’s Data Never Sleeps report, there is a traceable link between data and innovations in businesses, education, health and even improvements in sport. Data has changed the conventional and traditional methods and brought about waves of disruption that have enhanced livelihoods and altered policy discourses for economies.
Number crunching has for long been associated with computer scientists, engineering and mathematics. In business, data has been applied less often but faced with new challenges stemming from increased competition, the need for new inventions and changing consumer behaviours and needs, the emphasis on data analytics has grown rapidly. In advanced economies, the use of analytical tools to decipher raw data has helped businesses gain greater efficiency and preserve shareholder value. Economists in rich economies have built algorithms that can warn them of a recession whilst traders on the high end financial districts of London, Frankfurt and New York have found data analytics much useful in structuring their bids and asks as opposed to gamble and rogue trading.
One thing that has kept the developing world apart from the efficiencies that economies and businesses in the developed world have accrued lately is failure to embrace data analytics.
Of most significance is the need to exploit big data to come up with robust economic policies that have positive correlation to growth and development. Most advanced economies have placed high priority in data analysis as a tool of shaping economic policy and driving growth. Instead of exploiting data to justify aid or external debt the developing world must mine, process and execute its data to achieve prosperity and growth,
In business and finance, data analytics has played a much bigger role in detecting consumer behaviour, human capital decisions, drafting marketing models and business improvement strategies. Businesses from the developing world can accrue economies of scale and make informed decisions that can improve efficiency through embracing data analytics.
Exploring big data analytics can also work in advancing social and health programs that can enhance livelihoods. There is urgent need to do away with mass social programs that do not speak to the needs of communities. With data analytics employed in healthcare facilities there could be proper management of various epidemics through predictive analysis, alerts which could be real time and secure electronic health registers that can guide governments on health spending and insurance. The same can be done for education where big data analytics can define curriculum needs for specific student groups.
In data analytics however, there is need to pay attention to data integrity. Big data has multiple sources and as such there is no guarantee to quality. It is thus imperative for businesses and policy makers to focus on clean, useful and dependable data whose analytical results can lead to decisions that can be relied upon. With data transforming into a pot of gold, cyber-criminals are on the prowl using some of the sophisticated attacks to siphon data. To preserve data integrity there is need for intelligent systems and skills to source, analyse and protect data.
Its intriguing and remarkable how analytics has influenced sport with a recent feature in theNew York Times Magazinedetailing how Liverpool FC just ended remarkable season was not just a result of coach Jurgen Klopp tactical ingenuity or the athletes creativity but also a factor of the club’s research director Ian Graham algorithms and data models that were very insightful in guiding player acquisitions, defining tactical approaches in the field of play and even directing corporate decisions of the club. Successes for baseball club Boston Red Sox, e-commerce giant Amazon and some of the largest financial institutions in the world is attributable to clean data analytics such that its time corporate functions and policy makers from the developing world invest in big data.
Ngonidzaishe Makaha and Adrian Mapiye write blogs which cover financial analysis, equities, financial inclusion, development finance, analytics and Cybersecurity. They write in their personal capacities.