Industry 4.0 Is Enabling A New Era Of Manufacturing Intelligence And Analytics

Industry 4.0 Is Enabling A New Era Of Manufacturing Intelligence And Analytics

September 2016

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  • 72% of manufacturing enterprises predict their use of data analytics will substantially improve customer relationships and customer intelligence along the product life cycle.
  • 86% of manufacturers surveyed expect to secure simultaneous gains from both lower costs and added revenue in the next five years.
  • 35% of companies adopting Industry 4.0 expect revenue gains over 20% over the next five years.
  • Japan and Germany are the furthest along in digitizing internal operations and partnering across their value chains.
  • Data analytics and digital trust are the foundations of Industry 4.0.

These and many other insights are from the recently published Price Waterhouse Coopers (PwC) report, Industry 4.0: Building The Digital Enterprise (PDF, no opt-in, 36 pp.).  PwC has also provided an online summary of their study here.  PwC’s Industry 4.0 survey is the largest of its kind globally, with over 2,000 participants from nine major industrial sectors including aerospace, defense & security; industrial manufacturing; engineering & construction; chemicals; electronics; transportation & logistics; automotive; metals and forest-based paper & packaging.  The study’s scope also included 26 countries. For additional information on the methodology, please see page 33 of the study.  PwC found that over the next five years, the companies surveyed expect to increase annual revenues by an average of 2.9% and reduce costs by an average of 3.6%.

Key takeaways from the study include the following:

  • Industry 4.0 focuses on the end-to-end digitization of all physical assets and integration into digital ecosystems with value chain partners encompassing a broad spectrum of technologies. PwC found that generating, analyzing and communicating data seamlessly underpins the gains promised by Industry 4.0, which networks a wide range of new technologies to create value. Three key attributes of Industry 4.0 include digitization and integration of vertical and horizontal value chains; digitization of product and service offerings; and digital business models and customer access. The following graphic explains PwC’s framework for Industry 4.0:


Industry 4 framework

  • Investing in greater digitization and support for enterprise-wide integration is predicted to increase 118% by 2020 in support of Industry 4.0. 33% of manufacturers surveyed report they have a high level of digitization today, projected to increase to 72% by 2020.  The leading areas of these investments include vertical value chain integration (72%), product development and engineering (71%), and customer access including sales channels and marketing (68%).


Double spending on digitization with Industry 4.0

  • 83% expect data to have a significant impact on their decision-making in five years; only about half are currently using data to drive decisions. Getting beyond analytics as a means to track historical performance and making use of advanced techniques including machine learning and predictive algorithms to assess future outcomes, all industrial sectors interviewed see strong upside to analytics and manufacturing intelligence through 2020. Given the complexities of managing large-scale transportation and logistics systems, respondents from this industry predict a 90% increase in the importance of analytics in their decision-making. Electronics (89%), Chemicals and Industrial Manufacturing (both 88%) also are predicting their reliance on manufacturing intelligence and analytics will increase through 2020.


data and analytics

  • New product development and optimizing existing products and services are the greatest areas of growth potential for analytics in manufacturing by 2020. Industry 4.0 is revolutionizing the use of analytics and manufacturing intelligence, setting the foundation for greater optimization of overall business and control, better manufacturing, and operations planning, greater optimization of logistics and more efficient maintenance of production assets and machinery. By better orchestrating these strategic areas, manufacturers are going to be able to attain levels of accuracy and responsiveness to customers not achievable before.


understimating analytics

  • Manufacturers expect to reduce operational costs by 3.6% while increasing efficiency by 4.1% annually through 2020. PwC found that high levels of cost reduction are expected across the series of industry sectors studied.  By relying on integrated planning & scheduling across manufacturing centers, making full use of the data captured by sensors monitoring machine reliability and performance, and tracking asset utilization more effectively, the cost reductions manufacturers expect to achieve are attainable. Forward-thinking manufacturers are piloting machine learning applications and algorithms to interpret asset-level reliability and performance data, leading to more accurate asset-level predictive maintenance and repair schedules.


cost reduction by industry

  • Globally, manufacturing enterprises expect to gain an additional 2.9% in digital revenues per year through 2020, with digitizing their existing product portfolios (47%) leading all other strategies. Introducing an entirely new digital product portfolio is the second most common strategy (44%) followed by creating and offering new digital services to external customers (42%). Just over a third (38%) plan to create and sell big data analytics services to external customers.


revenues digital

  • 72% of manufacturing enterprises predict their use of data analytics will substantially improve customer relationships and customer intelligence along the product life cycle. Key areas of focus include basing a new product or service development effort on customer specifications, using data analysis to meet customer requirements and improve operational performance, and taking steps to build a more customer-focused supply chain. 69% say increasing in-house data analytics technology and skill levels is the top route to boost data analytics capabilities.


customer data

 

This article was written by Louis Columbus from Forbes and was legally licensed through the NewsCred publisher network.

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