Accelerating Innovation and Increasing Quality in the Age of Big Data
By Valérie Nedbal and Ian Cox
“Big Data” is characterised by ever increasing volumes and varieties of potentially useful data. For companies involved in making tangible goods, the Industrie 4.0 framework has allowed some to seize the resulting opportunities, but for others, confusion remains. Buzz words like “machine learning” and “artificial intelligence” abound and add to the bewilderment about the potential benefit of starting such an initiative, and how to get started.
A December 2016 report by McKinsey & Company estimated that product development costs can be cut by up to half by embracing these new data-driven approaches. Furthermore, the primary obstacles to adoption are lack of appropriate combination of skills and the means to distil and adequately communicate the insights that come from potentially complex analyses.
In this video, we use real-world case studies to show how JMP can help engineers, scientists and technicians work with big data methods to better discover actionable insights and more effectively communicate their findings to stakeholders. The examples cover the whole product life cycle, and also show how to augment initiatives like Six Sigma that rely on the simple analysis of relatively small data, making them better suited to this new age.
You will see how JMP can empower your existing workforce to embrace the data analytics revolution, helping your colleagues combine their existing subject matter expertise with new data analytic capabilities to drive better decisions faster. So, whether you compete on time to market, quality or both, reserve your place now.