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3 Industries Turned On Their Heads By Data

The work being done has changed significantly thanks to data

16May

We now live in a data-driven world, where everything we do creates data or is based on decisions informed by data.

From the way we use the heating in our homes, through to the information pilots flying planes across the world can receive, it is omnipresent in almost everything we do. Despite this, the changes have been minimal for many in terms of their daily lives.

In the business world though, the use of data has had a huge impact, revolutionizing several industries and changing the face of many others. Below, we look at three of those that have had been impacted the most.

Sports

The sports industry has always been data hungry, but the data revolution has given them a totally new dimension to how they view their sport. Data was being used in sport well before Billy Beane and the Oakland A's began to turn heads, but that was arguably the moment when people began to see the genuine impact it could have on the field.

James Bunce, Head of Sport Science, Premier League said about the change 'The use of technology has gone through the roof... Originally we were using things like heart rate monitors and now it's GPS and motion systems where you're tracking a player's movement.' Essentially, the use of analytics and the new technologies surrounding its collection have changed the way that players play and coaches coach.

Simon Jones, The Head of Innovation at the Team Sky cycling team, also believes that data has pushed cycling upwards - 'Now we can measure things like power, then once you start gathering this information, using coaching tools and analysis then brings about new questions and it moves the sport forwards.'

But is not only during a performance that sport is being impacted by data. We have seen it being used to change the way that new athletes are found and recruited, how teams can engage with their fans, and even down to the level of making sure that enough stock is being held in Stadium bars and shops during a match.

Insurance

It is no surprise that insurance is dependent on data. They are essentially making bets against you crashing your car, becoming ill, or having your possessions stolen. The more data they can create around this area, the better idea they will have around whether or not they should offer a low or high rate of premiums.

However, what is currently revolutionizing the industry is the ability to personalize an insurance policy. Aviva, the UK insurer, has launched an app that tracks how people drive and rewards them accordingly with lower premiums. A driver who scores over 7.1/10 'could save an average of £150 on Aviva comprehensive car insurance'. This app not only makes sure that their customers are fairly treated, but also that the company can collect significant amounts of information about their customers at the same time.

It is not only in making their customers use their phones that insurance can be more personalized either. The ability to segment and test on more targeted audiences is having a big impact on premiums across the board. We all know that male drivers between 18-25 have very high premiums because statistically speaking, they are the most likely to have a crash. However, this isn't true of every male driver in this category. Through looking at hundreds of data points and making decisions for subsections of these groups rather than the group as a whole, the company creates fairer pricing for everyone.

This kind of approach is working for the industry, with the world seeing a growth of 2.5% in direct premiums in 2015.

Oil & Gas

As one of the richest industries in the world, it is no surprise that oil and gas has seen significant benefits from the use of data.

Having been hit hard by the recent slump in oil prices, the importance of reducing costs and increasing efficiency has been their number one priority. Big data has a huge impact on this capability. The digital oilfield is now a data-driven enterprise, a far cry from the comparatively basic fields only 10 years ago.

We have seen predictive analytics, image analysis and the internet of things becoming the key drivers for finding new sources of oil, which has seen companies save billions of dollars on often expensive and unnecessary exploratory work. For instance, it is possible to look at topography and seismic activity combined with data from similar sites, all without leaving the office. Once a site is found, sensors can be placed that communicate back to a central office, meaning less manpower is needed. Using similar analytical techniques, it is possible to start the more extensive parts of the process with a considerably higher chance of success.

Once the well is tapped, data is also significantly impacting on its upkeep and running costs.

This is generally being done through the use of the Internet of Things and thousands of sensors. Every single element of a pipeline is now connected to a central monitoring station, allowing them to see exactly what is happening at any moment anywhere in their pipelines and manufacturing facilities. It also shows wear on parts, allowing pre-emptive action to be taken to prevent further damage. This has seen a significant reduction in the cost of maintenance with research from Accenture showing that predictive maintenance alone generates savings of up to 12% over regular maintenance. It also allows for considerable reduction in down-time, which loses companies millions of dollars every time they happen and this same Accenture survey showed that data led to a 70% reduction in down time.

With these kinds of data initiatives, the safety of pipelines, shipping and manufacture of oil has become considerably safer. From an environmental standpoint alone, when we look at the average number of oil spills every year in the 1970's (24.6) compared to 3.3 in the 2000's (we don't currently have the data for more recent trends), we can see an 86% decrease despite an increase in sea-borne oil transport. This has coincided with an increase in the use of data to measure safety elements, track routes, and create better safety processes. With the Internet of Things telling us about a potential issue before anybody would notice, we have the opportunity to reduce this even further.

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