Executive Briefings

How Big Data and Analytics Are Reshaping Industrial Manufacturing

Analyst insight: As the global competitive landscape evolves, businesses are looking to gain an edge by leveraging big data, using sophisticated analytics to uncover insights and help drive performance. One industry that is behind the curve is manufacturing – primarily automotive, mining, life sciences and consumer packaged goods. But that may be changing as a result of a rekindled focus on improving operational efficiency and the necessity for organizations to utilize their supply chains as a competitive advantage. – Amber Morgan, Senior Manager, Supply Chain Analytics Lead, EY

How Big Data and Analytics Are Reshaping Industrial Manufacturing

Multiple tools, multiple functions: Forward-thinking manufacturing organizations are applying advanced analytics tools over a range of functions. For example, they can be used to:

• Statistically determine the optimal target run rate for a line or unit operation based on its current loss profile and business strategy

• Classify top losses on a line-by-line category (planned and unplanned) and analyze equipment failure profiles using statistical analysis

• Prioritize improvement opportunities that deliver the maximum benefit using minimum effort – and statistically quantify the impact of improvement actions.

Production line data analysis: A critical source of enterprise data that is traditionally underutilized comes from the production line. The technology that gathers this data is called manufacturing line event data systems, i.e., LEDS or MES. Many companies do not take full advantage of the potential insights that this data can provide. However, leading-edge organizations are finally beginning to make better use of it.

A global CPG company, for example, is leveraging production data systems to drive plant throughput and, thus, alter the competitive landscape of its industry. Partnering with a world-renowned science lab, the company is using advanced computational technologies to develop new manufacturing tools, which have been successfully applied in environments ranging from continuous chemical processing to high-speed discrete packaging. These deployments have driven measurable and sustainable results for organizations around the globe.

These advanced analytics tools can also use data gleaned from production runs to learn and adapt. With these acute and timely insights, manufacturers can analyze and reduce failures on the production line. The resulting performance improvements include better throughput and higher quality – and possibly save billions of dollars.

Packaging knowledge, improving performance: Today’s manufacturers face human capital constraints and lack the time to develop analytics tools internally. Fortunately, management consulting firms are aggregating industry knowledge and delivering performance improvement programs to their clients. In many of these programs, the manufacturers already use LEDS, but are not leveraging it to provide maximum benefit. Substantial value can be achieved by refining existing, languishing data from production lines and other operations.

The Outlook

Leading manufacturers are equipping their plants with the tools and skills to reshape the industry. Using existing data to shape strategic decisions enables plants – and supply chains as a whole – to become more flexible and responsive. The key is for manufacturers to invest resources and leverage these tools for competitive advantage. Data analytics are expected to become accessible across multiple organizational functions, and analyzed for insights that contribute to more informed business decisions.

The views expressed herein are those of the authors and do not necessarily reflect the views of Ernst & Young LLP.

Multiple tools, multiple functions: Forward-thinking manufacturing organizations are applying advanced analytics tools over a range of functions. For example, they can be used to:

• Statistically determine the optimal target run rate for a line or unit operation based on its current loss profile and business strategy

• Classify top losses on a line-by-line category (planned and unplanned) and analyze equipment failure profiles using statistical analysis

• Prioritize improvement opportunities that deliver the maximum benefit using minimum effort – and statistically quantify the impact of improvement actions.

Production line data analysis: A critical source of enterprise data that is traditionally underutilized comes from the production line. The technology that gathers this data is called manufacturing line event data systems, i.e., LEDS or MES. Many companies do not take full advantage of the potential insights that this data can provide. However, leading-edge organizations are finally beginning to make better use of it.

A global CPG company, for example, is leveraging production data systems to drive plant throughput and, thus, alter the competitive landscape of its industry. Partnering with a world-renowned science lab, the company is using advanced computational technologies to develop new manufacturing tools, which have been successfully applied in environments ranging from continuous chemical processing to high-speed discrete packaging. These deployments have driven measurable and sustainable results for organizations around the globe.

These advanced analytics tools can also use data gleaned from production runs to learn and adapt. With these acute and timely insights, manufacturers can analyze and reduce failures on the production line. The resulting performance improvements include better throughput and higher quality – and possibly save billions of dollars.

Packaging knowledge, improving performance: Today’s manufacturers face human capital constraints and lack the time to develop analytics tools internally. Fortunately, management consulting firms are aggregating industry knowledge and delivering performance improvement programs to their clients. In many of these programs, the manufacturers already use LEDS, but are not leveraging it to provide maximum benefit. Substantial value can be achieved by refining existing, languishing data from production lines and other operations.

The Outlook

Leading manufacturers are equipping their plants with the tools and skills to reshape the industry. Using existing data to shape strategic decisions enables plants – and supply chains as a whole – to become more flexible and responsive. The key is for manufacturers to invest resources and leverage these tools for competitive advantage. Data analytics are expected to become accessible across multiple organizational functions, and analyzed for insights that contribute to more informed business decisions.

The views expressed herein are those of the authors and do not necessarily reflect the views of Ernst & Young LLP.

How Big Data and Analytics Are Reshaping Industrial Manufacturing