How East Africa can unlock Big Data

In this era of Big Data, characterized by radical customization, constant experimentation; unique business models are the new hallmarks of achieving competitive advantage. Organizations that analyze huge volumes of data have the edge. East Africa should not be left behind; below are recommendations that companies within the region should pay attention to.

  • Increase the variety of data collected by your company but start with questions and be aware of the mountains of data available in your organisation. Pay attention to department “silos” that exist within organisations which can impede timely exploitation of data. We are in the digital age or as some call it;  ‘the Internet of things’ (IoT). Internet of things is the concept of connecting any device with an on and off switch to the Internet (and/or to each other). This includes everything from cell phones, coffee makers, washing machines, headphones, lamps, wearable devices and almost anything else you can think of also applicable to components of machines, for example, a jet engine of an airplane or the drill of an oil rig. In digital data exist customer behavior, answers that can achieve operation efficiency and unknown or underdeveloped knowledge that can improve awareness, understanding, and forecasting. Some companies today can process satellite imagery analyse it and find clues about a competitor’s physical facilities. These satellite sleuths can provide insight into expansion plans or business constraints as revealed by facility capacity shipping movements and the like. Nonetheless, for this to occur data has to move cross department for some institutions and the hierarchical nature of some organisation leads to silos. The UK government with its early Big Data efforts set a coalition of police departments and hospitals to share data on violent crimes but there has been reported failure due to a lack of communication among participating organizations. Organizations need to break silos and develop efficient control towers to regulate data collection within their organisations.

 

  • Invest in Big Data technology software and modeling able to handle the growing volumes of data. Investing in software such as Hadoop can easily accommodate access, protection and security while supporting large numbers of files. Its distribution of data in clusters ensures business continuity and data can be mirrored between different clusters so data loss is not an issue. However, since it is new technology it needs to train staff new computer skills that need serious commitment and investment for the long term. This cost may block organisations from investment in Big Data software like Hadoop. When it comes to the analytics side, algorithms have helped companies save money and time, organisations in East Africa should pay attention. Some manufacturers, for example, use algorithms to analyse sensor data from production lines, creating self-regulating processes that cut waste, avoid costly (and sometimes dangerous) human interventions to ultimately lift output. By the same token, one beverage company integrated daily weather forecast from an outside partner into its demand and inventory planning process by analysing three data points – temperatures, rainfall levels, and the number of hours sunshine on a given day and the company was able to cut its inventory while improving forecast by about 5% in a key European market. This improved performance, better risk management and the ability to unearth insights that would otherwise remain hidden.

 

  • Radically move away from the highest paid opinion (Hippo) decision-making model to a state where data and human experience work together strategically to produce desired results. Ipsos Uganda revealed that some organisations might fail to act on insights brought to the table through data analysis. An investment in Big Data analytics also signal that a firm is accepting data as a source for decision making. “You can’t manage what you don’t measure”, should be the new manifesto to improve business performance in the region. This can be achieved with constant testing of decisions using controlled and uncontrolled experiments where companies can tests hypothesis and analyses results to guide investment decisions and operational changes. Leading online companies are continuous testers, in some cases, they allocate a certain portion of their Web page views to conduct experiments that reveal what factors drive higher engagement or promote sales. Constant testing can also help formulate scalable data analytics procedures that can be used in different environments.