Exploring the Transformation to the Digital Enterprise: 4 Key Takeaways

Digital transformation has changed how engineering teams design, manufacture, launch, and service products. Many of these teams build and release products at an unprecedented speed — all while adhering to more stringent requirements and regulations than ever before.

To balance velocity and quality, today’s engineering teams are turning to new methods for connecting data and fostering cross-disciplinary collaboration. The digital thread framework — linking product data gathered from across the product lifecycle and its associated manufacturing systems — is becoming especially important. By connecting data from all corners of the manufacturing process, organizations can better collaborate, make intelligent decisions, and meet growing requirements.

In the first episode of Pulling the Digital Thread, Aras’ thought leadership speaker series focused on exploring the digital enterprise’s transformation from the perspective of the digital thread, four industry leaders share their thoughts on facilitating an enterprise-level digital thread. The panel included Lionel Greaulou, managing director and founder of Xlifecycle Ltd.; Oleg Shilovitsky, cofounder and CEO of OpenBOM; Brion Carroll, CEO and board member of Sabrion Digital Group; and Aras CTO Rob McAveney. I moderated the discussion.

Here are four of their recommendations for organizations that want to better adapt to today’s fast-paced product lifecycles and high consumer expectations.

1. Break from document-based processes and prioritize data

Historically, organizations have almost exclusively used document-oriented processes. Engineers use computer aided design (CAD) documents, compliance teams use audit-ready documentation, etc. However, today’s digital threads must follow a data-oriented approach to succeed. Documents tend to create silos, making it challenging to see a product from the beginning to the end of its lifecycle. On the other hand, a data-driven approach promotes efficiency and collaboration.

According to Oleg Shilovitsky: “It’s getting to the point where [a document-based process] prevents companies from becoming more efficient…We need to break the boundaries of documents, be more granular, start operating with data, and see how we can use data for process management and decision support.”

A data-first approach allows an organization to collect holistic analytics and identify ways to improve processes and resource usage over time. For example, Lionel Grealou says teams can use data analytics to help with supplier selection in procurement or to make financial decisions about which products should be decommissioned or replaced.

2. Build a digital thread with your unique priorities in mind

While there are some standard best practices for building a digital thread (e.g., connecting siloed technology like BOMs and CAD), the specifics of how you develop your digital thread should revolve around solution ideas that empower what makes your business unique – your differentiation, goals and operational structure — which tool connections are most important, which downstream engineering practices your organization uses, etc.

Brion Carroll recommends creating a detailed deployment plan before starting: “It’s all based on priority. You have to sit down and come up with a playbook: ‘Who’s ready to start adopting this connectivity?’ Where is the value?’ ‘What are the business imperatives, the strategic advantages?’…You don’t need to boil the ocean; you just need to know where to fish.”

3. Leverage the cloud for better collaboration and innovation

Businesses should use cloud-hosted solutions as they build out a digital thread as they are essential to support collaboration with internal and external stakeholders. Why? They increase accessibility allowing teams to collaborate, in real-time, anywhere with an internet connection. These solutions are highly scalable enabling the ability to share complex designs and handle the velocity of change with many stakeholders accessing, visualizing, and commenting simultaneously. Additionally, integration with other productivity tools is seamless enabling teams to connect and share information vs working in disparate tools.

Rob McAveney explains how the cloud allows for greater agility and even innovation:

“We can bring supply chain partners and other business partners into the mix and connect their data to the digital thread. We can also link our data through AI and cloud-based analytics services. Those things are going to provide a lot of value over time. We can bring in external data sources for component libraries and regulatory compliance kinds of requirements, material databases — all these things that can augment our existing digital thread with new data that’s out there on the cloud.”

4. Build AI into your digital thread for specific use cases

Today’s manufacturers face unprecedented requirements — whether from societal pressures, sustainability initiatives, market feedback, or internal process changes. They must identify ways to respond to these ever-changing requirements with a cross-disciplinary strategy for the digital thread.

Organizations can turn to emerging AI technology to help them parse through static requirements documentation and decipher which ones apply to which aspects of the product lifecycle.

“This is where AI technology can help us make sense of regulations and their changes,” says Grealou. “It can give humans the right information for making decisions… it brings the ability to compute large data sets across functions and suppliers.”

While AI technology can help organizations better understand and prioritize the right requirements, teams must also use it cautiously. For example, organizations should verify AI output, as many of these tools haven’t been adequately trained.

“Everyone likes to speak about the opportunities of AI these days, but then you go to someone and say, ‘Can I get your data and do some experiments?’ Everyone gets cold feet, right?” says Shilovitsky. “If someone is trying to sell AI, the first question I always ask is, ‘Where did you get the data for your AI?’”

In McAveney’s words: “We should be more concerned about methods to ensure that whatever is produced by this new technology can actually be verified to meet the requirements that we’ve set out for it. So, let’s not be afraid of it — let’s utilize it where it works best. But let’s also trust but verify.”

Listen to the full conversation about digital thread

Building a foundation for your digital thread with data-driven approaches, organization-specific prioritization, robust cloud connectivity, intelligent strategy for meeting requirements, and proper usage of AI technology can prepare your organization for existing and upcoming challenges and opportunities.

Watch the full Pulling the Digital Thread: Exploring the Transformation to the Digital Enterprise presentation on-demand to learn more.