Defining a New Era in Automotive, Industrial, and High-tech Manufacturing

Industrial, automotive and high-tech manufacturers use Big Data to design and test new products, optimize research and development, improve yields and reduce defects, and optimize the supply chain, marketing and services and finance.

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Winning a High-Stakes Game

In the high-stakes, high-profile game of 21st-century manufacturing, Big Data and advanced analytics are critical competitive weapons. That’s true of both the established global giants that set the pace and emerging innovators and dynamic disrupters who seek to transform the industrial, automotive and high-tech sectors.

For years, manufacturers have used Big Data to improve supply chain visibility, productivity and resiliency – requirements for a just-in-time world, where margins are tight and expectations are high. Sales and marketing programs, as well as field service operations, have been made intelligent and highly personalized. Finance teams pored over operational, sales and trends data to find an edge when making resource allocation decisions. Big manufacturers were among the first to use predictive analytics and condition sensors on key equipment to avoid the risk of breakdowns and bottlenecks in production.

But manufacturing leaders are now going farther. Big Data drives research and development programs and the endless quest for better products, like autonomous vehicles. Telematics are revolutionizing both the customer experience and exponentially increasing data flows. Virtual design and testing capabilities mean manufacturers explore next-generation products today – and much more precisely and cost-effectively than in the past. Sensor data from the plant floor, which changes constantly and can’t be supported with traditional database structures, helps increase outputs, boost yields and eliminate defects in increasingly high-tech and automated environments.


Prepared and Proactive with Big Data

From the Internet of things to integrated fields of data, manufacturers are consistently on the leading edge of Big Data. In considering how Big Data drives the business forward, the questions to ask include:

  • Is the right architecture in place to take advantage of real-time sensor data in monitoring quality and outputs?
  • Is all potentially valuable data from the plant floor captured and monitored appropriately?
  • What are the implications of integrated field data for operations?
  • How can we gain predictive insight into what customers want tomorrow and next year?
  • How can data from a diverse supplier base and outsourced operations be integrated to meet strict requirements for regulatory reporting?
  • What tools and data streams are necessary to virtualize new product design and development processes?
  • Can we proactively identify potential issues with manufacturing equipment and processes before production delays occur?
  • What is the right architecture to link forecasting and planning toolsets with production systems?
  • How do we focus field service efforts on the highest-value customers?

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Big Data in action for Manufacturing

High-tech leaders are embracing advanced analytics and comprehensive Big Data strategies in a range of high-impact initiatives: 

  • Building the Factory of the Future: Increasing visibility into “dark data” and achieving “insight for all” with the right analytical toolsets is the way forward for high-tech manufacturers.
  • A Data-Driven Transformation at High-Tech Leader: Disruption is the key to innovation as Dell reinvents itself for a new era – Dell 2.0 is all about the power of data to reduce complexity and deliver more of what consumers want.
  • IoT at Industrial Scale: Valmet uses data and analytics to boost revenue and strengthen long-term agreements with key customers and partners.
  • From Transactions to Transformation: NCR provides data-driven insights to quantify the value of its offerings and enhance service levels.
 
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Breaking through with Big Data

In large and complex manufacturing enterprises, there are abundant Big Data opportunities. The highest impacts returns often come from: 

  • The Right Big Data Strategy: Effective strategies start with understanding how Big Data and advanced analytics can drive tangible performance gains in everything from marketing campaigns, plant floor outputs and supply chain efficiency.
  • A Holistic Ecosystem Approach: Diverse data sets – including sensor, third-party and supplier data – must be integrated in well designed data and analytics ecosystem.
  • Data-Driven Culture: Data-driven decision making and broad-based analytics thinking is a way of life and should be pervasive across the enterprise – Big Data is truly everyone’s job.