BigDataFr recommends: Buried treasure: Advanced analytics in process industries
[…] The full power of advanced analytics requires not only acquiring new technology and analytics solutions, but also helping people improve their expertise and adopt new ways of working.
The Internet of Things (IoT), industry 4.0, advanced analytics, digital technologies, and big data have all generated enormous hype for their potential to transform every facet of business. To date, the dialogue around these tools has focused primarily on consumer-facing industries, such as retail and financial services; on large industrial companies, such as GE; and on leading digital players, including Amazon, Google, and Netflix. Beyond the spotlight, however, manufacturers in process industries—also commonly referred to as heavy or capital-intensive manufacturing—have been early to adopt many of the latest advances. For decades the sector has not only generated large amounts of data but also combined science, engineering knowledge, classical statistics, and powerful modeling into advanced-process-control (APC) systems that run key assets efficiently.
Since APC systems are expensive to develop and historically have been effective only for well-understood, less-complex processes, APC usage has generally been limited to the largest, most critical ones. Smaller, as well as secondary and more-complex processes have been left without suitable process controls (see sidebar, “The processes of heavy manufacturing”). And while process industries generate huge volumes of data, their process-management and information-technology capabilities are not as advanced as those of other industries. As a result, thus far manufacturers have lagged behind in systematically deploying data analytics to extract the substantial value hidden in the insights they contain.
The good news is that over the past several decades, entirely new and more affordable manufacturing analytics methods and solutions have emerged, and they are now reaching market maturity as part of Industry 4.0. These solutions—which provide easier access to data from multiple data sources, along with advanced modelling algorithms and easy-to-use visualization approaches—could finally give manufacturers new ways to control and optimize all processes throughout their entire operations.
But new technology is just one part of the equation. To achieve a strong financial impact from improvements in analytics, manufacturers must also consider the human factor. As in previous efforts to optimize production, such as lean manufacturing or ISO quality standards, change-management capabilities will be crucial. The new horizon in analytics will achieve its full impact only when manufacturers enhance skills across the entire organizations so that the new methods and solutions become a part of the day-to-day routine. […]
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By Robert Feldmann, Markus Hammer, Ken Somers, and Joris Van Niel
Source: mckinsey.com