Data: is bigger really better?

When the concept of big data was first discussed more than 70 years ago, it wasn’t taken very seriously, as many didn’t know how to use it. One of the earliest examples came from American writer, inventor and genealogist Fremont Rider, who in 1933 was appointed a librarian at Wesleyan University. He estimated that US college libraries were growing two-fold in size every 16 years, and therefore predicted that Yale University’s library alone would require a 6,000-strong staff by the year 2040.

Today, thanks to technology, there is little escape from the big data phenomenon, particularly as we head deeper into the age of information. However, despite its potency, is big data the ‘one-size-fits-all’ answer it is often touted to be? Moreover, is it a solution that is relevant for your company? Let’s take a closer look at where big data has been useful, examine potential gaps and share insights and tips on how your business can make the most of big data.

How does big data work, and why do we use it?

Data collection methods have come a long way in enabling the capture of information in a variety of formats. Large technology companies already have access to huge pools of data as a result of their business functions, while other companies opt to use third party sources as an alternative to collecting the data they need.

Now that all this information is at our fingertips, how do we define what big data is and conversely what it isn’t? Here are two scenarios to help determine big data diamonds from duds.

Firstly, if you capture the number of customers and resulting sales volumes and use this information for your monthly sales reporting, these figures alone do not qualify as big data. They are not complex, varied or voluminous enough to tell a story, which is the fundamental purpose of big data.

On the other hand, if your store footprint has 1,000 outlets with a million customers each, and could capture sales volume every hour while also monitoring chatter and sentiment on social media on what is trending, then the data collected is reliable and high in volume, variety and frequency. This is big data.

In short, big data can be defined as business intelligence. As a term, it helps to describe our ability to understand the growing volumes of data in the world. The possibilities offered by big data are endless. From optimising business performance to hyper-targeting customers, big data provides business with the insights needed to stay ahead in a fast paced, ever-evolving world.

Is bigger always better?

The key to unlocking the power of big data lies in the ability to analyse the findings and use them to tell a story. In a world where consumers are saturated with news and offers they care little for, well analysed, purposeful data enables businesses to detect and drive trends in order to cut through the marketing noise.

To make big data work, companies first need to have a clear understanding of what they want to achieve with the data they capture. Additionally, one of the biggest challenges that businesses face today is knowing how to leverage big data in a way that improves business performance. Quite often, most companies have vast oceans of information that are often left underutilised, resulting in what is known as ‘dark data’.

Enter big data analytics, which extract and provide meaningful sound bites that form the basis of consumer insights. For example, Mastercard Advisors uses anonymised real-time retail spend data to provide clients with market trends, consumer preferences and characteristics. This knowledge enables businesses to make precise, data-driven decisions in order to streamline and optimise their businesses.

A key example of big data in action is a digital monitoring tool that enables the company to create and track campaigns and offers in real-time. Each activity and promotion is based on empirical anonymised data mined through social listening and analysing data from cardholder transaction habits. While it seems technical, the combination of technology, creative thinking and strong partner relationships allows creation of special, once-in-a-lifetime moments for cardholders.

The insurance industry is another example of where big data plays a pivotal role, where it is applied to helping determine premiums and payouts as a result of collecting and analysing data on personal driving habits. For example, Aviva, a leading insurance provider in Singapore, found that car accidents were most likely to occur on Fridays. If a driver was unfortunate enough to meet with an accident then, they may find they receive a different level of compensation than one who did on another day. 

So is bigger data really better? Not necessarily – only if it fits in with your business objectives and operations. If you are not already collecting data on a regular basis, then it will be beneficial to start small by leveraging existing data. Once you have optimised the collection process, you’ll need to add layers of external data that will give variety and depth to your existing data sets.

How can companies make best use of big data?

With the sheer amount of organisation that big data requires, upkeep can be expensive. Few small and medium enterprises (SMEs) can afford to hire chief information officers (CIOs), or spend time and effort analysing and percolating their data. Instead, they often settle for regular reporting of cash flows, inventories or customer tracking.

This is not to say smaller enterprises can’t grab a bite of the big data pie. In March this year Mastercard Advisors announced a partnership with IBM to provide merchants with access to anonymised, real-time and analytics-based market insights on revenue, market share, customer demographics and competitors in a particular location and across multiple ones. Such insights help merchants understand their consumers, opportunities and challenges on a deeper level, and make thoughtful and informed business decisions that work to their upmost advantage.

Like most things worth investing in, big data is a journey and a long-term venture. Only by having clear business objectives and building systematically to scale can your businesses achieve the best use of the powerful tool that is big data.

 

 

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