• December 14, 2015

Five Industries Where Big Data is Making a Difference

To understand how Big Data can transform businesses, we have to understand its nature. Although there are numerous definitions of Big Data, many will agree that it is characterized by the 3 V’s: volume, velocity and variety.

Volume: This refers to the ability to process a vast amount of information available. This also refers to the proliferation of data that is produced, from social media to transactional records, from system logs to the Internet of Things. The greater the volume, the more data points are available to enable systems to identify patterns and predict future outcomes based on historical records. This creates challenges in storing and managing these vast amounts of data and demands innovative approaches to manage the spiraling investments that big data demands.

Variety: Enterprises are used to managing and processing a limited set of data types, such as transactional records and logs generated by the business systems. In today’s world, there is value from data created both inside and outside the enterprise. Social media platforms such as Facebook and Twitter generate a huge amount of traffic that could significantly impact business performance. Advances in technology have enabled the analysis of unstructured data, including images, voice recordings, videos and text to deliver insights. The enterprise now has to answer the question of what is relevant and what is not. As technology improves, data that cannot be used today may become useful sources of information in the very near future.

Velocity: The rate at which data is created has increased significantly, with digitisation a major contributor to more data being tracked and logged. The Internet of Things has opened a new floodgate of data being created, and rapid adoption of social media and advances of technology has made previously useless data useful. The list is endless. This data can be useful only if it is ingested rapidly and, more importantly, delivers meaningful outcomes within a practical time frame. For example, recommending the right product to an online shopper must be done in a split second—otherwise, the window of opportunity will be shut. The rise of Big Data poses a significant issue for enterprises, but it also is a major opportunity to transform and change the rules of the game. Making sense of Big Data can transform data into valuable insights and help organizations accomplish the following business goals:

  • Increase revenue, profitability, and market share. Customers have more information than ever before to help them compare products and services. Companies that understand that can respond quickly to changes in the marketplace. This allows them to meet their customers’ needs quickly, gain market share and increase profits.
  • Ramp up efficiency. Improved access to information will enable the enterprise to analyze and review its processes and identify room for improvements to increase efficiency and reduce cost.
  • Improve customer experience. Social media will provide marketers with word of mouth sentiment that was unattainable in the past. Big Data enables more accurate profiling of customers and enable enterprises to meet their needs more effectively.
  • Manage risks. Big Data transforms information archival and retrieval, facilitates control over data and demonstrates compliance to customers and regulators.
  • Monetize information assets. Information is key to improving competitive positions. Big Data allows enterprises to deliver undiscovered insights and reveal new growth areas.

Big Data technologies are enabling opportunities that were not considered even remotely possible just a few years ago. Technology advances have coalesced to create solutions that are helping businesses in a wide variety of industries. While Big Data solutions are taking hold across all industries, enterprises can look at early adopters of the technology and identify similar opportunities for their industries.

Telecommunications

Telecommunications service providers have a high incentive to improve quality of service at all times. Advanced analytics helps telecom providers smooth out service performance by spotting patterns in potential traffic bottlenecks, ensuring that suppliers meet service level agreements and offer even better service-level agreement (SLA) guarantees that generate more revenue.

Big Data solutions are helping companies identify potential customers for incremental revenue opportunities such as mobile usage plans, unified communications and business videoconferencing. Sophisticated analytics tools are helping companies customize their promotional offers to conform to unique characteristics of individual customers based on usage patterns, service call histories and social media interactions. This has helped service providers increase revenue even as profit margins come under pressure with intensified competition from non-traditional segments such as voice over IP.

Travel and transportation

The airline industry has had to deal with new government regulations, pricing pressures, industry consolidation and the ups and downs of the general economy. As a result, carriers have placed even greater emphasis on generating the highest possible revenue and profit from each passenger (as well as from commercial freight customers). Big Data provides airlines with instantaneous information on seating capacity and matches availability with historic trends on passenger booking patterns to determine the ideal pricing offers that fill as many seats as possible, and as profitably as possible.

It also has become increasingly important in determining the scale and scope of frequent flyer programs in order to identify the best ways to incentivize reward the most profitable customers without burdening the program with excessive administrative costs. Analytics helps build customer segmentation models in alignment with business goals, such as increasing market share, improving per-customer profitability and generating new revenue streams.

Health and life sciences

Healthcare and life sciences are two high-growth industries that also are characterized by extensive regulatory and compliance requirements. Big Data solutions are surfacing essential data to help improve patient care and ensure confidentiality and privacy, while at the same time helping to increase profitability by rooting out potentially fraudulent claims and applying the appropriate treatment codes for swifter reimbursement.

Advanced analytics also is helping to foster collaboration and information sharing among caregivers in different departments in healthcare organization, especially as hospitals increase their use of such data-generating devices as “smart beds,” purpose-built tablets, RFID-based admitting tags and pharmacy shelf sensors. The business implications are immense: “If (United States) healthcare were to use big data creatively and effectively to drive efficiency and quality, the sector could create more than $300 billion in value every year,” according to consulting firm McKinsey Global Institute.¹

In the life sciences industry, important strides have been made in such initiatives as the Human Genome Project, which has created an unprecedented opportunity to “read nature’s complete genetic blueprint for building a human being.”² Because of advanced analytics software, combined with powerful yet affordable computer hardware, the National Human Genome Research Institute is able to continue mining extremely large amounts of data in order to learn more about how genetics affects everything from health to human behavior.

Consumer industry and retail

Recent years have seen important technical advances in how retailers create, share and use data to improve their competitiveness and business operations. Traditional bar-coding and fixed point-of-sale terminals are giving way to technologies such as RFID and mobile computing to improve the customer experience and enhance the all-important merchandize availability. In doing so, stores are generating significantly higher volumes of data from numerous new sources in their supply chain, in their inventory centres, on their show floors and at the checkout counter.

Big Data solutions are helping retailers identify the location of their merchandize down to the item level in order to support such important shopping trends as mobile shopping, omni channel retailing and “showrooming.” Smart shelves, which identify when specific SKUs are in low quantity or out of stock, automatically trigger reordering from suppliers and distribution centres, and send signals to store associates to help shoppers locate an out-of-stock item in another nearby store.

Big Data is helping retailers and their consumer packaged-goods suppliers by generating and analyzing large volumes of consumer behavior intelligence based on factors such as social media activity, website visits or in-store shopping. Sophisticated analytics also is helping them to analyze the performance of their many promotional and marketing campaigns in order to determine how to tailor different programs for different audiences in different locations, even for different days of the week or times of the shopping day.

Financial services

Two recent industry developments are reshaping how financial services company use the vastly expanded information created in their businesses: government regulations and competition for an increasingly discriminating customer’s “share of wallet.”

The financial services industry is under pressure from government regulators to become more vigilant in curbing crimes such as money laundering, and Big Data is playing an important role in spotting possible instances of fraud through transaction analysis. International antiterrorism efforts also are being aided by financial institutions’ ability to sift through huge amounts of data, often obscured by a litany of confusing transactions among partner companies and affiliates, to determine the funding sources for terrorist organizations.

At the same time, financial institutions are working hard to expand their product lines, and advanced analytics is helping them understand customers’ willingness to purchase such products as insurance, brokerage services, commercial loans and credit cards. Analytics tools are helping banks, credit unions and other financial organizations augment traditional data sources such as third-party credit reports with social media analysis and other behavioral data to identify the best possible candidates for their new services.

HPE Big Data Discover Experience

Even though Big Data has the potential to transform the business, it does require significant investments. Making the right investments to maximize ROI has proven to be tricky. Many organizations understand the importance of developing ways to identify new insights and turn them into actionable business steps but may lack the expertise in either understanding how to apply it to their business or how to develop and deploy those solutions. There are many Big Data ideas, but there is a need to separate the wheat from the chaff and make the right investments.

HPE Big Data Discovery Experience Services is designed to assist enterprises in identifying, exploring, proving and implementing Big Data analytics and insights to improve decision making and drive business innovation and growth.

Enterprises can validate their Big Data initiatives and prioritize their projects based on the projected returns on investment. HPE Big Data Discovery Experience Services leverages a secure HPE cloud analytics environment based on the HPE HAVEn Big Data platform, as well as advisors with extensive knowledge of complex data integrations and data environments.

The result is a solution that is based on ready-to-use technology platforms to rapidly capture the value of Big Data and analytics, along with flexible delivery and commercial models that minimize investment risk.

¹“Big data: The next frontier for innovation, competition and productivity,” McKinsey Global Institute, May 2011
²“Life Sciences and Big Data: What’s the Big Deal?” Science Buddies, April 9, 2014