Few things in my life have shaped who I am today, including graduating from MIT’s Leaders for Global Operations (at the time, Leaders for Manufacturing) program. So, when an opportunity arose for me to talk with Dr. Duane Boning, Co-Director, MIT Leaders for Global Operations Program, about the future of leadership in manufacturing and operations, I took it.
After all, part of the program’s stated mission is “to educate leaders to address the world’s most challenging operations and high-tech problems.” As I’ve written about here a lot, capitalizing on the next wave of innovation in manufacturing (fueled by complex advances like artificial intelligence, machine learning, and advanced analytics) is no easy feat.
Here, Dr. Boning shares his perspectives on the challenges and opportunities for developing leaders who can thrive in the digital age of operations.
What is MIT’s Leaders for Global Operations (LGO) program?
The program began about 30 years ago, with the vision of offering dual master’s degrees in management and engineering to prepare leaders for the unique challenges found in manufacturing and operations.
In collaboration with some of the world’s largest high-tech, manufacturing, pharmaceutical, energy and global supply chain industries, LGO brings together the best and brightest in academia and business. LGO Fellows apply the latest thinking in technology and management best practices to the real-world. Pushing the limits of what’s possible, MIT’s LGO Fellows tackle the most intractable problems in manufacturing and operations today and position companies for better performance tomorrow.
How has the LGO program changed or adapted to students and industry?
At the outset of the program, it was focused on manufacturing at the shop floor and plant level. We quickly learned that focusing on any one silo was not enough so, 10 years ago, we shifted to a broader focus on challenges manufacturing and operations firms face. Today, our member companies include Amazon, Verizon, and National Grid, as well as more-traditional manufacturers.
More recently, we’ve expanded the curriculum to align more closely with the leading edge of digital transformation, equipping future leaders with the necessary skills to harness advances in analytics and data-rich problem-solving. All 50 students in the incoming class now also complete intense training in programming skills and machine learning. Through this, they gain an understanding of how these will affect their chosen industry – characterized by fast-moving, data-intensive environments.
What are some of the operational challenges facing your member companies today?
You won’t be surprised to learn classic manufacturing/operations problems still exist: Quality, statistical process control, etc. In operations and supply chain, the basic principles will take you a long way, but it really is about best practices. While those have been defined, they are hard to implement and sustain – it takes knowledgeable and skilled leaders to make that happen.
The emerging problems involve more data and more-sophisticated data analytics. Machine learning is a great example because this field of computer science provides the ability to extract insights from data and learn. Though not a new field, machine learning has been advancing rapidly, and helping companies apply the technology – from predicting problems before they happen, to optimizing performance beyond what has been possible with traditional analytics, to integrating insights to enable better and faster response to market opportunities – that’s new.
The level of sophistication required to apply machine learning in manufacturing is very challenging. Take, for example, determining whether a product is good or bad: we need to use machine learning to make decisions across many levels of classification, but we may not have the same huge volume of images as are used in learning if an image is one of a dog or a cat.
How are you preparing the future leaders in manufacturing and operations for these challenges?
Well, fundamentals are key. Like I said, the problems in manufacturing and operations aren’t easy ones to solve. Reinforcing those basics and making sure best practices around them are cemented, is a major focus for us at MIT.
At a broader level, the LGO model — synthesizing management perspectives (the MBA) with deeper analytical and engineering skills (the MS in one of six engineering disciplines) – gives students a different way of thinking about their roles.
One of the most important lessons our students learn is an appreciation of management challenges. Most come to LGO with four or five years of work experience. Then through the internship model, they not only come face-to-face with an operational challenge, they learn to work through it through the management lens. That appreciation of the management challenge is essential.
At the very heart of all these challenges, we’re talking about the transformation of operations. And transformation requires change. LGO graduates understand that and appreciate what it requires to bring about change and implement it.
What’s next for the LGO program?
We talk with the COOs and CEOs of our member companies in great depth to understand what keeps them – as leaders – awake at night. One thing 100 percent of them have shared with us is that they believe talent – or the lack thereof – is a real challenge.
One of the biggest challenges of a huge transformation, like the digital age of operations, is that you need more people, not fewer. While we’re extremely proud of the 1,200+ alumni who’ve gone on from LGO to become agents of change around the world, we realize that’s a very small population. Companies need more people with a broader and deeper set of skills. So we’ve got to do something to close the gap.
To that end, MIT has developed the Principles of Manufacturing MicroMasters, a set of online courses on edX.org. This program is designed to give new talent an easy and accessible way to explore fundamental skills needed for global excellence in manufacturing and competitiveness. In this way, we hope to extend the learning and experience that defines leadership to help a vitally important industrial sector thrive.
Dr. Boning’s insight into the challenges of integrating data and analytics to drive operational excellence and his perspective on the talent gap are familiar topics here. Which do you find to be the most vexing? Are there others? Share your thoughts with me @jim_lawton.