Toby Ingleton |
This article first appeared in the Spring 2017 issue of The Record.
Analytics has become an absolute necessity throughout the business world, but its penetration has seen more traction in certain areas.
Morgan Zimmermann is CEO of the EXALEAD brand at Dassault Systèmes, which enables organisations to gather, align and harness the power of big data. He says that in the enterprise resource planning and customer relationship management spaces, companies have been willing to make significant investment in analytics. In product lifecycle management (PLM) however, this has not been the case.
“There is no massive analytics technology that is being deployed yet into the PLM space,” he says. “Traditional analytics doesn’t work with PLM because it has been built to manage transactions, which in most cases are characterised by numbers. When you go into PLM, you are not managing transactions but configurable product structures. So it’s not a number, but a graph.”
Zimmermann says that in the PLM space, a different type of technology is required.
“It’s one thing to be able to have a dashboard showing issues, but what people want to see is the issue in the engineering, design and 3D context,” says Zimmermann. “They also want to be able to collaborate on the issues and their resolution workflows. Analytics in the product space, more than anywhere else, requires collaboration and the ability to take action from every insight.”
Enabling decisions to be made within the PLM system, and for analytics to be close to the authoring system when designing a product, is key.
“We help deliver tangible output and benefits in product execution, cost reduction, resource allocation and quality,” Zimmermann says. “PLM is all about being able to manage the performance of the product programs. How do we enable this? At any stage, we can find out what the risks, costs and issues that are delineating from the initial targets are. From an early stage, the right decision can be made to optimise costs, tackle issues and ensure quality.”
Zimmermann says that without the ability to monitor all stages of a product’s development, problems can arise. In addition, data extracted into static spreadsheets is immediately outdated and tempting to manipulate. PLM analytics offers a single source of truth.
“Take the quality and issues space for example,” Zimmermann explains. “Thanks to the openness of Dassault Systèmes’ 3DEXPERIENCE platform, we provide an analytics application that can bring in product managers for warranty issues, identify the field issues as extracted from open source web or social media, and engineering issues. That information is then in a single application, which can link these issues to the 3D and the virtual mock-up. Anyone working on a model can identify the optimum failure modes, resolution paths, or risks. This has a major impact on the ability to drive down cost of quality and time-to-market.”
Zimmermann adds that moving forward, analytics applications in PLM will have more built-in content and machine learning algorithms to help boost risk identification and, ultimately, make tasks easier.