Data has long been part of the business decision-making process but in the past the use of data was typically reflective, looking back over time and determining trends that could be incorporated into planning for the next sales or business cycle. Nowadays, with real-time access and advances in technology, data is being harnessed in a way that enables businesses to be more agile, shifting strategy and operational execution in real-time, taking advantage of opportunity and mitigating risk.

Time to shift seats?

Although the use of this real-time data for insightful decision-making is becoming more widely recognised as a must-have, rather than a nice-to-have, the Big Data teams are still effectively backseat drivers. Some forward-thinking companies have taken the leap to enable Big Data to take a driving position at the Executive table, creating roles such as Chief Data Officer.

Let’s take a quick look at how big data is changing mainstream industries today.


Insurers have long relied on data to analyse risk and determine their products and pricing. However, today they have access to a plethora of information, particularly real-time data, that helps to improve their pricing accuracy, develop highly customised products and services, prevent fraudulent claims and grow stronger relationships with customers.

Technology advances have enabled insurers to capture a continuous stream of real-time data from various sources, including vehicle sensors, wearable fitness trackers, smartphones and others. By combining this with behavioural models of customer profile data, insurance data scientists can develop more accurate analysis to mitigate risk and in so doing, develop personalised products and pricing.


Access to real-time global data has led to the surge in demand for data scientists in the finance sector to capture and analyse this information to build predictive models capable of running live simulations of market events.  With markets driven ultimately by sentiments (the opinions and feelings of people who invest and consume) there is an upsurge in the construction of algorithms to collect sentiment data, primarily from social media feeds, to determine the impact of natural disasters, political events (including terrorist attacks) and other seemingly unrelated issues.


With escalating costs in healthcare, medical insurers are harnessing data to improve efficiencies and reduce costs. By accessing a cross-analysis of data from medical trials, personalised patient records and real-time efficacy stats, doctors are now able to offer a more accurate diagnosis and recommend a suitable corrective (or preventative) treatment plan. One of the more exciting areas for data scientists in the healthcare sector is that of disease modelling and mapping. This is the work towards better understanding the causes (or linkages) of certain diseases to ultimately prevent them.


Retailers have been harnessing consumer data for years and as far back as 2011, McKinsey in their report Big Data: The next frontier for innovation, competition and productivity, suggested that retailers who used big data could raise their operating margins by as much as 60%.  Within the fast-moving consumer goods environment, big data makes a significant impact across the business. From logistics and supply chain, through merchandising and marketing, to creating a personalised customer experience.


As robotics begin to take over within the manufacturing sector, access to data increases. This data can be used to improve efficiencies, identify risks and reduce costs. Particularly industries like motor manufacturers, where safety standards are exceptionally high, the opportunity to identify a mistake (such as a single bolt not tightened sufficiently) that is potentially life-threatening in real-time is paramount. Analysis of production data can also be used to determine better ways of manufacturing, reducing energy costs and improving quality.

The high pace of business is fuelling the demand for skills and expertise to analyse the myriad of data being captured and to turn the numbers into stories that provide clear opportunities for improvement and greater profitability. In the 21st century economy, it makes perfect sense to shift big data into the driving seat.