Paving the way for Big Data analytics in Sri Lanka

BY Zahir Fuard 

Sri Lanka is a land which is well acquainted with the concept of precognition, and a persistent desire to predict the future. Even the most rational among us cannot help but be tempted by the idea. 

If you knew what was coming tomorrow, would you act differently? What would you do? How would things change? Naturally, many have tried to step in and fulfill this latent demand for a more certain future. We see it in horoscopes, and in the confident proclamations of astrologers. Yet time and again, these intermediaries fall woefully short of providing any real insight to what lays ahead.

Tools change with the times, and today’s technological innovations are rapidly enabling a brave and exciting new world of possibilities, one in which data becomes a catalyst for an economy, a society, and a nation that is free to unleash its true potential. Across the globe, we see numerous examples of predictive analytics enabled by rapid advances in the ability of a given organization to collate and analyze massive quantities of data – essentially enabling a given macro-situation to be analyzed simultaneously at face value, down the most minute, granular level. This approach is capable of driving entirely unprecedented paradigms of development in nearly every facet of life. 

From the way we grow our food, to the way we run our businesses; from the treatment of disease, to the development of breakthrough products and services in the banking and financial sector; from predicting natural disasters to developing smarter financial models, change is coming, and big-data is the key. Our emerging digital economy will ultimately operate according to a drastically different set of rules, and success in this new environment boils down to how we frame an issue, and how intelligently we respond to the insights we are given.  

The devil is in the details 

While the general approach of how big-data works is fairly consistent, its application and integration into different industries can be a bit more complex. Consequently, specific approaches must be tailored for each sector. 

Generally speaking, big-data is simply a catch-all term used to describe a process by which predictive mathematical algorithms are applied to very large, complex, rapidly-changing datasets in order to extract precise, reliable insights into what is most likely to happen next, based on a complete analysis of every such situation in the past. 

As is often the case, it is the banking, financial services, and insurance (BFSI) that is often the first adopter of cutting-edge technologies and Though many BFSI organizations are beginning to disrupt their analytics landscapes by gathering immense volumes of data assets, these companies are at varying levels of Big Data maturity. As customer volume increases, it dramatically affects the level of services offered by the organization. 

Existing data analytics practices have simplified the process of monitoring and evaluation of banks and other financial services organizations, including vast amounts of client data such as personal and security information. But with the help of Big Data, banks can now use this information to continually track client behavior in real time, providing the exact type of resources needed at any given moment. This real-time evaluation will in turn boost overall performance and profitability, thus thrusting the organization further into the growth cycle.

In agriculture too, Big Data is taking a figurative sledgehammer to centuries old inefficiencies. Globally, it is estimated that US$ 940 billion every year as a result of inefficiencies in planting, harvesting, water use and trucking, as well as uncertainty about weather, pests, consumer demand, all of which contribute to greater uncertainty, which further compromises the ability of the sector to be responsive to change. 

Once again, it appears that Big Data will play an increasingly vital role in resolving these challenges. Through the deployment of purpose designed sensors, farmers are gaining granular visibility into oil conditions, as well as detailed info on wind, fertilizer requirements, water availability and pest infestations. GPS units on tractors, combines and trucks can help determine optimal usage of heavy equipment. Data analytics can help prevent spoilage by moving products faster and more efficiently. Unmanned aerial vehicles, or drones, can patrol fields and alert farmers to crop ripeness or potential problems.

One common thread that runs through all of greatest success stories in Big Data is found in the structured approach taken to adoption. It is simply not enough to implement these solutions simply because the competition is doing the same. Rather, each step into the world of big-data must be calculated, precise, and based on the fundamental question: what will this information do for my organization?

Potential for Big Data in Sri Lanka 

Currently, the Sri Lankan market is already playing host to several important experiments into the field of Big Data, however the reason for their importance is more to do with the fact that these are historic first steps, rather than the fact that they are revolutionary steps forward. Nevertheless, we must learn to crawl before we can learn to walk, and in Sri Lanka, we see some extremely encouraging signs with regard to the uptake of Big Data. 

Often times, Sri Lankan companies are unaware of the wealth of data that they possess or have easy access to base on procedural records generated by the business over time

Often times, Sri Lankan companies are unaware of the wealth of data that they possess or have easy access to base on procedural records generated by the business over time. Simply by being a little more precise about what how they analyze their data, companies can gain unprecedented insights into employee performance, operational efficiency, product popularity, and customer preferences. Equipped with this knowledge, organisations can categorize their customers into distinct segments defined by their demographics, regular transactions, and any other fields relevant to a given business. Such businesses can tailor their service offering, products portfolio and marketing campaigns to have the most impact on customers including through the use of personalized marketing. 

As with most international cases, in Sri Lanka too, we anticipate the banking and finance sector to lead country into the field of big data, and already the first tentative steps in this direction have been taken by leading financial institutions in the country, however, the true potential of big data in this sector remains largely untapped. This potential can be directed towards internal improvements to processes such as in areas of fraud detection to ensuring compliance with regulatory and statutory requirements, but can also be utilized towards driving a deeper understanding of the customer, a factor essential to success in any service industry. 

My analyzing social media, transaction histories and comparing such behavior with customers in similar categories, Sri Lankan banks will be able to deploy predictive analytics to determine with unprecedented accuracy what a given customer will do, and what type of services they will require, even before the customer realizes their own need.

Such techniques can be similarly utilized in the retail sector, or the leisure sector to deliver targeted promotions based on criteria such as customer preferences and stock availability in order to ensure optimized sales.

 
 A single bill might not reveal much, but the entirety of an organisation’s billing records can be mined for invaluable data. In retail, it could be deployed to determine at what times of the day, week, month or year a particular product reaches peak popularity.    

In the public sector, these technologies can be utilized to save lives, predicting future natural disasters and helping to mitigate them both through the ability to provide longer warning periods for evacuation and in terms of assisting in the coordination of relief efforts. Most importantly, while the functionality of big-data is growing at an exponential rate, the costs associated with them are not. Indeed the big data analytics tools of today are available at a fraction of the cost and ultimately, we are confident that it is not necessarily the size of the investment, but the intelligence behind it that will determine who emerges as the next generation of business and corporate leaders. In the age of information, knowledge is power.

(Zahir Fuard is a co-founder of TYE Solutions, Sri Lanka’s fastest growing open source analytical solutions provider. Having worked with a diverse range of clients including large telecommunications, logistics, banks, agro ,MNC’c and production houses.  For more info visit www.tyesolutions.com.lk)