Big Data for Big Profits?
In recent years there has been a data explosion. Back in 2011 an IBM study reported that a colossal 2.5 quintillion bytes of data are produced every single day and that over a period of just 2 years, 90% of all data ever generated was created. The trend has continued, giving rise to the new phenomenon of Big Data and is largely accredited to the invention of the internet which has allowed data to be created in thousands of ways not previously thought possible – notably through social media. Big Data’s popularity continues to increase and its current applications appear endless – from making suggestions on Netflix to monitoring the spread of disease.
But what actually is it? Specifically, Big Data is the use of large data sets which are processed and then analysed in order to find links and correlations. In the past, investigations have always been about finding causal links to explain human behaviour and the world around us. Big Data on the other hand, due to its size and nature, allows relationships to be spotted without an apparent cause. In modern society, a strong correlation between two data sets is often enough evidence upon which to act when making decisions. So, Big Data now has the potential to change the world in which we live in more ways than we could imagine.
Arguably one of the most well-known business uses for Big Data is the loyalty card scheme used by many supermarkets and other large retailers. These schemes aim to make predictions about the products certain consumers will demand - and at what rate - and send out promotions accordingly. Pioneered by Tesco in 1995, detailed data about the consumption patterns of their customers allowed the supermarket to increase their market share in just one year – by 1996 Tesco Clubcard holders were spending 28% more in Tesco and 16% less in Sainsbury’s. Coupon redemption has also increased from 3% to 70% due to the personalisation of such rewards and Tesco currently receive data on about two-thirds of all shopping baskets.
Based on relatively simply models relating past demand to projected future demand but on a very large scale, these systems have been fairly common in a variety of industries for the best part of 20 years and for those that have utilised it, it has paid off. In fact, it has been shown that those firms which use these predictive analytics techniques have profits, on average, that are 73% higher than those who do not. Yet, in the current economic climate where barriers to entry in many industries are at an all-time low through the expansion of the online market, it is essential that the power of Big Data is utilised further in order to not only maximise profits but also to survive in this increasingly competitive world.
Some firms have caught on to this and retailers have started to use Big Data in the operations of their firms in ways aside from just predicting demand. This aims to minimise costs, resulting in a boost to their level of competitiveness and ultimately their profit margin. Going back to the Tesco example, they have developed a system to reduce their spending on energy through monitoring levels of heating, lighting and refrigeration across their stores (gathering 70 million refrigerator data points) to work out the minimum cost involved in optimising each of these variables. Similarly, a top biopharmaceuticals company capitalised on the power of Big Data to analyse the interdependencies between each process involved in the production of one of their vaccines and their impact on the yield and therefore profit margin of said vaccine – saving the company between £5 million and £10 million annually. Lastly, an unnamed fast food company has taken vast sets of past data to train cameras on drive-thru lanes to determine how busy it is and then display adverts for different products accordingly.
Many firms are already harnessing the benefits of analysing large sets of data in order to make predictions about demand for their products, whether that be through a loyalty card scheme or using sentiment analysis of social media to gather the opinions of the general public. However, as data is becoming more and more accessible in forms never before thought possible, it is perhaps true that Big Data will become increasingly indispensable in also minimising costs in order to earn big profits.