Written by

Bernard Marr

Bernard Marr is a world-renowned futurist, influencer and thought leader in the fields of business and technology, with a passion for using technology for the good of humanity. He is a best-selling author of 20 books, writes a regular column for Forbes and advises and coaches many of the world’s best-known organisations. He has over 2 million social media followers, 1 million newsletter subscribers and was ranked by LinkedIn as one of the top 5 business influencers in the world and the No 1 influencer in the UK.

Bernard’s latest book is ‘Business Trends in Practice: The 25+ Trends That Are Redefining Organisations’

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Bernard Marr ist ein weltbekannter Futurist, Influencer und Vordenker in den Bereichen Wirtschaft und Technologie mit einer Leidenschaft für den Einsatz von Technologie zum Wohle der Menschheit. Er ist Bestsellerautor von 20 Büchern, schreibt eine regelmäßige Kolumne für Forbes und berät und coacht viele der weltweit bekanntesten Organisationen. Er hat über 2 Millionen Social-Media-Follower, 1 Million Newsletter-Abonnenten und wurde von LinkedIn als einer der Top-5-Business-Influencer der Welt und von Xing als Top Mind 2021 ausgezeichnet.

Bernards neueste Bücher sind ‘Künstliche Intelligenz im Unternehmen: Innovative Anwendungen in 50 Erfolgreichen Unternehmen’

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How Is Big Data Transforming Business?

2 July 2021

When new technologies become cheaper and easier to use, they transform industries. That’s what is happening with Big Data right now. Let’s take a look at some key industries and explore how data is driving performance and competitiveness.





Healthcare

Big data in healthcare is transforming the way we identify and treat illnesses, improve quality of life and avoid preventable deaths. The drive now is to understand as much about a patient as possible, as early in their life as possible – hopefully picking up warning signs of serious illness at an early enough stage that treatment is far simpler, and less expensive.

For example, in one specialist premature and sick baby unit, Big Data techniques have been used to monitor the babies’ heartbeats and breathing patterns. Using this data, the unit was able to develop algorithms that predict infections 24 hours before any physical symptoms occur.

Retail

The way we buy and sell is evolving fast. Both online and offline, those retailers that are embracing a data-first strategy towards understanding their customers, matching them to products and parting them from their cash are reaping huge rewards.

This means that data analytics is now being applied at every stage of the retail process – working out what the popular products will be by predicting trends, forecasting where the demand will be for those products, optimising pricing for a competitive edge, identifying the customers likely to be interested in certain products, working out the best way to approach those customers, taking their money and, finally, working out what to sell them next.

Manufacturing

Data plays a hugely important role in modern manufacturing processes. Advances in robotics and increasing levels of automation are dramatically changing the face of manufacturing. Adidas is one big name investing heavily in automated factories, for example.

Even in a more traditional manufacturing environment, data is still making its mark. By embedding sensors into their equipment, manufacturers are capturing valuable data that helps them monitor the health and efficiency of those machines. Sensors are also increasingly being installed into a wide range of products, from jet engines to yoga mats, allowing manufacturers to gather valuable data on how those products are performing and being used.

Financial services, banking and insurance

The applications of data go far beyond high-tech, big-money trading. For example, data is helping credit card companies like American Express detect fraudulent transactions and expand into trend analysis services for businesses.

In insurance, data is already being used to help insurers set fairer and more accurate policy premiums, identify fraudulent claims and improve their marketing efforts. Companies like Progressive and Aviva are taking data collection a step further by offering discounts to drivers who allow them to monitor their driving via smart phone apps and in-car devices, allowing the insurer to observe how safe a person’s driving really is.

Education

Increasingly large amounts of data are being generated about how we learn, and education establishments are now beginning to turn this data into insights that can identify better teaching strategies, highlight areas where students may not be learning efficiently, and transform the delivery of education. In one example, in Wisconsin’s Menomonee Falls School District, data has been put to use for everything from improving classroom cleanliness to planning school bus routes.

Of course, these days, not all education takes place in the classroom. The boom in online courses is providing a wealth of insights into the ways that people learn, and leading to huge advances in personalised, adaptive learning.

Transportation, supply chain management and logistics

In warehouses, digital cameras are routinely used to monitor stock levels and the data provides alerts when restocking is needed. Forecasting takes this a step further – the same camera data can be fed through machine learning algorithms to teach an intelligent stock management system to predict when a resupply will be needed. In the not-too-distant future, warehouses and distribution centres will effectively run themselves, with very little need for human interaction.

And in the world of transportation, companies are collecting and analysing telematics data from their vehicles and using this data to improve driving behaviour, optimise transport routes and improve vehicle maintenance.

Agriculture and farming

Even very traditional industries are embracing the power of data. US agricultural manufacturer John Deere has enthusiastically adopted Big Data practices, launching several data-enabled services that let farmers benefit from crowd sourced, real-time monitoring of data collected from its thousands of users.

Myjohndeere.com is an online portal that allows farmers to access data gathered from sensors attached to their own machinery as they work the fields, as well as aggregated data from other users around the world.

Energy

The costs of extracting oil and gas are rising, and the turbulent state of international politics adds to the difficulties of exploration and drilling for new reserves. In the face of big problems, the energy industry is turning to data for solutions. Royal Dutch Shell, for example, has been developing the “data-driven oilfield” in an attempt to bring down the cost of drilling for oil.

And on a smaller but no less important scale, data and the Internet of Things (IoT) is disrupting the way we use energy in our homes. The rise of “smart homes” includes technology like Google’s Nest thermostat, which helps make homes more comfortable and cut down on energy wastage.

Government and public sector services

A number of cities are currently piloting data analytics with the aim of turning themselves into “smart cities”, where data collection, analytics and the IoT combine to create joined-up public services and utilities.

My home town of Milton Keynes is one that’s already using smart, connected, data-driven technology to help improve public services. For example, a sensor network has been rolled out across all 80 of the council’s neighbourhood recycling centres to help streamline collection services, so wagons can prioritise the fullest recycling centres and skip those with almost nothing in them.

Hospitality

Hotel and leisure operators are turning to advanced analytics solutions for clues about how to keep their customers happy.One common use of analytics in the hotel industry revolves around yield management. This is the process of ensuring that each room attracts the optimal price – taking into account troughs and peaks in demand throughout the year as well as other factors, such as weather and local events, that can influence the number (and type) of guests checking in.

Of course, the traditional hospitality industry is also facing stiff competition from data-enabled services like Airbnb, which helps travellers find unique accommodation all around the world.

Professional services

When you read or hear news stories about the imminent takeover of robots and algorithms that will eliminate jobs for human workers, many times the first examples given are blue-collar jobs like factory workers and taxi drivers. But even highly skilled professional services – like accounting, law and architecture – are seeing massive change thanks to advances in data, analytics, machine learning, robotics and artificial intelligence.

In accounting, for example, software can automatically import transactions, keep track of digital receipts, automate payroll and keep track of taxes. But even more complex tasks like auditing, regulatory compliance and trend analysis can be carried out by computers these days.

Sports

Most elite sports have now embraced data analytics. In Premier League football, a set of cameras installed around the stadiums now track every player using pattern recognition generating over 25 data points per player every second! NFL players have installed sensors in shoulder pads to gather data on their performance, and analytics helped British rowers row their way to Olympic gold. Data has even unlocked the secrets of the perfect golf swing.

In fact, it’s hard to think of any area of sport that isn’t embracing data and analytics these days. Many elite sports teams go so far as to track athletes outside of the sporting environment – using smart technology to track nutrition and sleep, as well as social media conversations to monitor emotional wellbeing.

Businesses built on data

Increasingly, data is becoming a key business asset in its own right, and platform businesses that are entirely fuelled by data are among the most successful companies in the world. Apple, for example, is using data right across its business to drive success. And Google arguably knows more about us than our loved ones – knowledge it uses to provide a highly personalised service and to help other businesses target customers effectively.

Data is also at the heart of the sharing economy, including businesses like Uber. These companies represent a new way to use data effectively to provide services to people when and where they want them.

Conclusion

It’s very clear that we’re well passed the time when businesses should be wondering if they have to worry about Big Data. As these examples show, Big Data is already revolutionising just about every industry and those companies with a clear data strategy are becoming the leaders in their fields.

Business Trends In Practice | Bernard Marr
Business Trends In Practice | Bernard Marr

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