Since the big data explosion in recent years, the value of data itself has risen exponentially. Its potential to reveal valuable business intelligence and create new sources of revenue has made it a major global economy in its own right. Hailed by many as a disruptive force comparable in its impact to the Industrial Revolution, big data has now been named as a more valuable resource than oil.
While quality data is no doubt high in worth, its true value could be seen to lie in the ability to process and extract meaning from it – a skill known as data analytics. As such, those with an understanding of data analytics are greatly in demand.
The ways in which companies have turned data into a ‘product’ capable of creating new business opportunities demonstrates why skills in data analytics have become so marketable.
The ‘data-network’ effect
Each interaction a consumer has with a business creates data, so the more customers a company has, the more their data sets grow. Data scientists can then examine this accumulated data for patterns in consumer behaviour that indicate where service improvements can be made, using machine learning to reveal trends no human could ever spot.
Improved services help to attract more customers, who in turn create more data, and the cycle continues. Bigger data sets also provide more training material for machine learning algorithms, helping to make them more ‘intelligent’ as they analyse the information.
This process has become known as the ‘data network effect’. It’s how search engines like Google continue to develop; the more searches users perform, the more data Google has to work through and the more refined their search results become.
What’s more, big data collected in this way can benefit other companies too, as the following examples show.
Commodifying big data for business
Many companies now build means for data capture into their products. The reasons for this are two-fold; firstly, it helps them better understand how the products are used by their customers, and secondly, it creates a data set with its own unique value.
Electric car manufacturer Tesla includes data-gathering sensors in all of its cars, which record everything from how drivers grip the steering wheel to how the cars themselves perform over time and distance. Based on the data they collect, these sensors enable Tesla to keep refining its vehicles to better suit drivers, not just for new models but for those sold years previously, thanks to software updates capable of fixing performance issues remotely. Tesla’s ‘crowd-sourced’ data continuously edges the company closer to its ultimate aim; designing the world’s first fully autonomous ‘self-driving’ car.
Crucially, it’s not only Tesla that could use the information it’s collecting. The company is amassing one million miles of new data every 10 hours, which could be used to help design safer and more efficient road networks, for example. McKinsey estimates that the market for vehicle-gathered data will be worth $750 billion a year by 2030.
In a similar way, sportswear giant Nike are starting to harvest data from ‘smart’ clothing and wearable tech; creating data sets from its millions of customers on variables like heart rate and blood pressure. As the smart clothing market develops, this technology will enable Nike to stay ahead of curve, and give them a source of constantly updated health data that could help health insurance companies understand and predict their customers’ health needs.
Although no longer a popular social network, search-and-discovery service Foursquare still boasts one of the most comprehensive sources of location data available, built up by its millions of users over the years. Recognising the value of this data, Foursquare now enables partner businesses to enhance their location services through its own data sets, and offers the ability to identify groups of users by the types of business they like to visit regularly, creating a new service for advertisers.
Understanding the emerging data economy
Of course, none of the examples we’ve mentioned would be possible without people who know how and why to apply data for different objectives; the value of data is dependent on those who can extract it. That’s why understanding data analytics is set to become a highly sought-after skill with IBM predicting that the demand for data analysts will increase by 28% by 2020. As data continues to enable new commercial opportunity, those with the ability to understand it will find themselves key to the future of business.
Combining core business and data analytics expertise, our Online MBA with Data Analytics offers a stepping stone to launch or develop a data-focused career. The course can help you understand the importance and value of data in the emerging data economy, as well as the significance of big data, data analytics and machine learning for business strategy, competitive advantage and technological innovation.
To find out more about this course and how it can help you decipher data for business gain, request more information today.