Leverage Big Data Analytics to Enable Digital Business Transformation

Big data has always been a part of the manufacturing industry, albeit limited to certain aspects of the decision-making process. "Manufacturers were using data mostly to understand and optimize their operations," explained Julien Calviac, NETVIBES Strategy Director at Dassault Systèmes. He added, "But if we want to increase our ability to manage the unexpected, we need to raise our expectations of what's possible."

Before manufacturers take that step of expanding their decision-making process, three fundamental questions need to be addressed:

• Do they have access to the right information data sets?
• Do they have the right decision process in place to make the most beneficial decisions?
• How long does it take before a business decision influences operations?

"Our customers realize that they can't go back to normal and just catch up or do things faster," said Julien. "We need to shift to a brand new way of envisaging industrial innovation, enterprise agility and resilience."

Even though the implementation of smart technologies like the industrial internet of things (IIoT) have exponentially increased, the rate of data collection, analysis and decision-making quality is still sub-optimal. "The data being collected is still missing contextual information, and that limits the manufacturers' ability to get the right answers," explained Julien. "Where's the data coming from? What are the data sources that you need to connect to? If you want to engage in a true digital transformation, you have to get this part right."

It is not only about capturing real-time data and information but also about discovering patterns from data that has already been captured. "The decisions that you've made in the past will help add context, facilitate effective analytics and guide future decision-making," Julien highlighted.

To help our customers address all these different points and successfully execute their digital transformation, we've developed a new collaborative data intelligence capability.

Collaborative data intelligence is purpose-built to connect multiple data sources while managing and manipulating data at scale. In this fully-featured collaboration environment, multidisciplinary stakeholders can work together to accelerate innovation.

"The foundation of collaborative data intelligence is the 3DEXPERIENCE® platform," said Julien. "The key outcome of this is the virtual twin experience of your operations based on a combination of input models — 3D simulation data, behavioral models or even physical models — to help contextualize real-world data and inform better business decisions."

Having access to the same knowledge base across every stage of the product development process allows stakeholders to access the same source of truth and streamline information sharing. "For example, product engineering and service teams have access to the same description of the products and the same description of services that can be applied to those products," explained Julien.

Collaborative data intelligence is not a one-and-done affair. It is a continuous process that creates a real-time bridge between the real world and design, engineering and manufacturing. By combining big data with contextual information, manufacturers can anticipate future decisions based on past results. With the 3DEXPERIENCE platform, manufacturers can now make it happen in real time. This is the secret to an agile and resilient supply chain — and a sustainable competitive advantage.