There is a battle for data collection in every industry. Not only tech giants but other sectors like governments, insurances, logistics, retailers and financial institutions etc are accumulating information and are also gearing up in this domain. Organisations artistically demonstrate their product features and loyalty programs around their app or website so that they can engage their customers digitally as well, which certainly allows them to collect data.

An article appeared in The Medium, an online publishing platform, which stated that Clive Humby, a British Mathematician, was the first to coin the phrase “Data is the new oil”. He elaborated on the concept by saying that, oil when refined becomes a valuable entity similarly, the true value of data gets unlocked after its processing. However, data also has many other properties which requires the analogy to be broken down to a more detailed inspection. Data processing is simply the conversion of raw data in meaningful information through a process. Oil refining requires significant amounts of resources. On the other hand, data can be replicated at low cost and can be re-used, re-engineered and is subject to time sensitivity. But one of the key components is utilising data; due to a lack of awareness, most of organisations have completely confused the concept of data utilisation with data reporting.

Since organisations have already witnessed that data-driven decisions led them to the top and data doesn’t lie, perhaps that’s the reason that they have started rushing to collect data. But unfortunately, most of them are under the impression that data can only assist them to measure historical performances and trends or so on. This is where potential opportunities go to waste. Your business data are your assets and your competitors don’t have access or visibility on this; you can use data to improve and narrow down your future decisions and predict the consequences of your calculated actions.

The example of highest data/tech academic control ever analysed and utilised by China may help to understand the effective utilisation of data. Following the current circumstances of coronavirus crisis, China has managed to control the situation very quickly since they have considered several precautions but they have also taken advantage from the data perspective.

The Chinese government has done two things in particular to control the crisis. The Chinese government collects massive amount of data, which includes but is not limited to, images from CCTV cameras; which means if you are caught on camera, they recognise you, they know who you are and where you are. Another big source of data is WeChat, (a Chinese social media and debit card all rolled in one super app) which also tracks where you are, what you are up to and what you’re saying to your friends. China used this big data in a novel way to tackle the coronavirus. If an individual’s (say Mr A’s) COVID-19 test is positive, then authorities would run algorithm(s) that enables them to identify all the different places Mr A has been visiting during the last fourteen days and all the people who might have been in contact with him during that time. Then the authorities would notify potentially infected people to quarantine themselves. This could help understand that China not only collected but also utilised that data in the right way.

Conclusively, institutes should aim to focus on analytics, artificial intelligence and machine learning etc as well, as collecting data on its own will not help. They need to understand that organising themselves around individuals is important instead of products or channels, developing the ability to view an individual as one segment, recognising their uniqueness, and tailoring their offerings so that the individual view is meeting their needs, not pushing products. Develop a customer-centric business model, analyse and act upon the insights from the ever-increasing mass of data. Technology will continuously change everything – we need to adopt the right approach.