The future of manufacturing is iterative, collaborative and data-driven
At its core, digital transformation means investing in people
In association withRaytheon Missiles & Defense
Digital transformation has been positioned as a cure-all to many of the challenges today’s enterprises face. But to fully reap the benefits of a digital transformation, businesses need to do more than just adopt the latest tools and apps. They also have to change their attitudes, practices and processes around data and technology, throughout their own organization and in their interactions with partners and customers.
“Digital transformation requires a jump on the technology side, but it requires a leap on the people side,” says Bill Gundrey, executive director for digital engineering and operations at Raytheon Missiles & Defense. “At Raytheon, digital transformation is a team sport. It impacts every function in our company, as well as customers and suppliers. We had to change the way people think about data and technology.”
Changing the way we work
Globally, covid-19 played a major role in shifting collective attitudes toward technology, particularly in the ways people do business. At Raytheon, it helped fast-track the cultural side of digital transformation, changing the way internal teams interacted with vendors, customers, and government partners.
“We learned a lot during the pandemic. We proved we could work and collaborate virtually,” says Gundrey. “In the end, digital transformation is all about people. It’s about being able to work from anywhere and to leverage new tools to improve how we collaborate.”
Now, as organizations transition back to in-office or hybrid work arrangements, businesses need to use the lessons learned during the pandemic to permanently change operational attitudes toward technology for good, says Gundrey. Business leaders now face an unprecedented opportunity to embrace digital transformation and the business practices that support it.
An iterative and interactive approach
Perhaps the biggest opportunity for cultural transformation is replacing the traditional waterfall approach to project management — a linear process that front-loads the project with detailed planning and meticulous documentation — with a more agile methodology, says Gundrey.
Agile processes are more iterative. Customers and end users are directly involved in the development cycle, with their feedback incorporated in every iteration, or sprint. This approach to project management improves success rates by creating a space for continuous innovation and improvement, even if project specifications evolve during the course of development. As organizations adopt agile methodologies, they also start to become learning organizations, with the team learning as much as they are developing during each sprint. This then better positions subsequent sprints.
Before digital transformation, the development process at Raytheon could take months, says Gundrey. The requirements-gathering process alone involved creating hundreds of pages of PowerPoint charts before the customer could even view a preliminary design.
Now, with a more agile approach leveraging digital transformation, customers have greater visibility into the system earlier in the process, can see the relationship of requirements, and get a better view of preliminary designs. They can give feedback on designs and models in real time, requesting changes before Raytheon engineers invest time and money in building out prototypes that aren’t quite right. No PowerPoints required.
“We don't have to stop our work to allow time for extensive formal checkpoints,” Gundrey says. “Instead, our team and our customers become incrementally smarter day by day because the process allows for a more continuous flow of iterations.”
Another key digital transformation practice is integrating artificial intelligence (AI) and machine learning (ML) to automate, or at least streamline and simplify, product development. At Raytheon, teams leverage model-based engineering to predict complex fluid, structural, and thermal interactions in missile systems so engineers can better understand how a product will operate at hypersonic speeds. But any industry can use AI and ML to help teams make better and smarter design choices and, ultimately, better products and experiences for customers and end users.
Natural language processing technology, a branch of AI that trains machines to understand human speech and writing, for example, can improve everything from customer support operations to e-commerce product descriptions. AI and ML can also be used to streamline and automate warehouse operations and data entry and processing. During the early days of the pandemic, some banks relied on AI-powered robotic process automation to respond to the massive influx of Paycheck Protection Program applications and rapidly file submissions to the U.S. government.
A central goal of many digital transformations is connecting the data stored throughout the organization, making it easier to discover, access, and leverage. This often is achieved via a federated data model, an approach to data management that creates a centralized view of the organization’s data, though it resides in disparate locations. By aligning data that was formerly siloed, while storing it at its source, data federation provides simple access to up-to-date data, allowing diverse teams to collaborate throughout the development, manufacturing, and testing processes.
At companies like Raytheon, where security and safety are a top concern, the data must be organized and firewalled to ensure that only those with proper access can view classified information. But once implemented, a modern data architecture has also helped Raytheon’s teams navigate a global supply chain that continues to face challenges caused by the pandemic and ongoing political strife.
“We had data stored in multiple systems. There was data in our procurement system and data in our risk management system. There was data stored in each program’s master schedule,” says Gundrey. “Now, our supply chain team is able to pull all of this data together and use AI and ML to better predict material lead times and help us better plan our program activities.”
These transformative technologies and all-important data can all be linked via “digital thread,” a communications architecture that runs through the manufacturing process. By capturing and streaming data throughout the product lifecycle, the digital thread integrates disparate digital technologies in a holistic view. People and process, of course, remain central to this transition. As Gundrey says, “I want folks to know that as we’re building out this digital thread, it’s all about the people and the work processes that come along with it.”
The benefits of digital transformation
For today’s companies, the benefits of digital transformation are extensive. In addition to connecting and speeding up the product development cycle and giving teams richer and more relevant data, it can also help reduce risk.
At an individual business level, this could mean reducing the risk of disappointing an end user because the agile methodology helped teams identify potential issues early in the design process. Using these iterative and collaborative approaches gives teams the ability to tackle complex design issues early on, preventing the risk of costly reworking later, and gives managers more foresight about how separate components will work together.
At a global level, reduced risk could help enterprises roll out new technology that helps combat everything from climate change to national security concerns. Raytheon, for example, is using digital transformation to help speed up how it works with government partners. The goal is to reduce an acquisition, development, and production process that currently takes 10 years to an astonishing 18 months, helping the company’s partners get new capabilities into the field faster.
But the ultimate goal of digital transformation is not just to digitize and streamline internal processes. It’s to improve the experience of the people who use the technology and rely on the processes to do their jobs. They now have more time to do what machines can’t do: find out what’s keeping customers awake at night, develop innovative solutions to customers’ problems, and collaborate with internal and external teams to make better business decisions.
“When we talk about digital transformation, ultimately, we're investing in people,” says Gundrey. “We're taking the monotony out of their jobs. We're making it easier for them to put their brain power on the challenging analysis and the design, and the real problem solving we need people to focus on.”
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.
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