How Applications of Big Data Drive Industries

Article Index

5. Manufacturing and Natural Resources

Industry-Specific challenges

Increasing demand for natural resources including oil, agricultural products, minerals, gas, metals, and so on has led to an increase in the volume, complexity, and velocity of data that is a challenge to handle.

Similarly, large volumes of data from the manufacturing industry are untapped. The underutilization of this information prevents improved quality of products, energy efficiency, reliability, and better profit margins.

Applications of big data in manufacturing and natural resources

In the natural resources industry, big data allows for predictive modeling to support decision making that has been utilized to ingest and integrate large amounts of data from geospatial data, graphical data, text and temporal data. Areas of interest where this has been used include; seismic interpretation and reservoir characterization.

Big data has also been used in solving today’s manufacturing challenges and to gain competitive advantage among other benefits.

In the graphic below, a study by Deloitte shows the use of supply chain capabilities from big data currently in use and their expected use in the future.

Big Data Providers in this industry include: CSC, Aspen Technology, Invensys and Pentaho

 

6. Government

Industry-Specific challenges

In governments the biggest challenges are the integration and interoperability of big data across different government departments and affiliated organizations.

Applications of big data in Government

In public services, big data has a very wide range of applications including: energy exploration, financial market analysis, fraud detection, health related research and environmental protection.

Some more specific examples are as follows:

Big data is being used in the analysis of large amounts of social disability claims, made to the Social Security Administration (SSA), that arrive in the form of unstructured data. The analytics are used to process medical information rapidly and efficiently for faster decision making and to detect suspicious or fraudulent claims.

The Food and Drug Administration (FDA) is using big data to detect and study patterns of food-related illnesses and diseases. This allows for faster response which has led to faster treatment and less death.

The Department of Homeland Security uses big data for several different use cases. Big data is analyzed from different government agencies and is used to protect the country.

Big Data Providers in this industry include: Digital Reasoning, Socrata and HP

 

7. Insurance

Industry-Specific challenges

Lack of personalized services, lack of personalized pricing and the lack of targeted services to new segments and to specific market segments are some of the main challenges.

In a survey conducted by Marketforce challenges identified by professionals in the insurance industry include underutilization of data gathered by loss adjusters and a hunger for better insight.

Applications of big data in the insurance industry

 

Big data has been used in the industry to provide customer insights for transparent and simpler products, by analyzing and predicting customer behavior through data derived from social media, GPS-enabled devices and CCTV footage. The big data also allows for better customer retention from insurance companies.

When it comes to claims management, predictive analytics from big data has been used to offer faster service since massive amounts of data can be analyzed especially in the underwriting stage. Fraud detection has also been enhanced.

Through massive data from digital channels and social media, real-time monitoring of claims throughout the claims cycle has been used to provide insights.

Big Data Providers in this industry include: Sprint, Qualcomm, Octo Telematics, The Climate Corp.

 

8. Retail and Whole sale trade

Industry-Specific challenges

From traditional brick and mortar retailers and wholesalers to current day e-commerce traders, the industry has gathered a lot of data over time. This data, derived from customer loyalty cards, POS scanners, RFID etc. is not being used enough to improve customer experiences on the whole. Any changes and improvements made have been quite slow.

Applications of big data in the Retail and Wholesale industry

Big data from customer loyalty data, POS, store inventory, local demographics data continues to be gathered by retail and wholesale stores.

 

In New York’s Big Show retail trade conference in 2014, companies like Microsoft, Cisco and IBM pitched the need for the retail industry to utilize big data for analytics and for other uses including:

 

  • Optimized staffing through data from shopping patterns, local events, and so on
  • Reduced fraud
  • Timely analysis of inventory

Social media use also has a lot of potential use and continues to be slowly but surely adopted especially by brick and mortar stores. Social media is used for customer prospecting, customer retention, promotion of products, and more.

Big Data Providers in this industry include: First Retail, First Insight, Fujitsu, Infor, Epicor and Vistex

 

9. Transportation

Industry-Specific challenges

In recent times, huge amounts of data from location-based social networks and high speed data from telecoms have affected travel behavior. Regrettably, research to understand travel behavior has not progressed as quickly.

In most places, transport demand models are still based on poorly understood new social media structures.

Applications of big data in the transportation industry

Some applications of big data by governments, private organizations and individuals include:

  • Governments use of big data: traffic control, route planning, intelligent transport systems, congestion management (by predicting traffic conditions)
  • Private sector use of big data in transport: revenue management, technological enhancements, logistics and for competitive advantage (by consolidating shipments and optimizing freight movement)
  • Individual use of big data includes: route planning to save on fuel and time, for travel arrangements in tourism etc.