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At the center of data-driven digital transformation, Engineering and Tech professionals are increasingly ascending to the Boardrooms and C-suites of modern-day companies. Beyond that, executives and shareholders are increasingly coming under pressure to incorporate safety, sustainability, DEI, and ethics into their business models and strategies, instead of focusing solely on shareholders’ financial returns. In other words, companies must consider the broad set of stakeholders, not just the shareholders, impacted by the product or service. The best outcomes occur when diverse teams of engineers consider factors such as sustainability, safety, and ethics, early on during the design phase. This exciting “engineering first” renaissance requires a renewed and expanded focus on engineering management as a discipline in its own right.
Engineering management and leadership is a “broadly integrative and synthesis-focused enterprise engineering discipline”1, where, akin to mechanical engineering and civil engineering, design and synthesis are key elements of the engineering work. Engineering management covers the gap between engineering and business management, namely the combination of technical and economic decision-making with analytical skills, optimization capabilities, and technical product development.
When industrial revolutions emerge, engineering innovation is essentially causing the production of goods and services in a society to be accelerated due to a general-purpose ‘power’. For example, the first revolution was powered by steam; the second one by electricity; and the third one by computing. This new and fourth industrial revolution, as many believe, is being powered by data and AI. Companies who are restructuring or building themselves to thrive in it form what we call, Industry 4.0.
Increasingly, all industries are becoming more data-driven and thus are basing their business decisions on all the digital data collected across the supply chain. Because of the speed of innovation in this new era, engineers are being increasingly brought to the decision table to analyze and interpret the massive amounts of data to help make fast, robust economic decisions, and to apply engineering management skills to better lead engineering teams to exploit new opportunities and develop smarter products, platforms, and services. With the rise of Industry 4.0, where technologies combine human, machines, and data, a modernized form of engineering management has arisen. In this new era, engineering management must have their decision making supercharged by data and artificial intelligence (AI).
At its fundamental core, the field of engineering management combines technical engineering expertise, human leadership, specific business management concepts, and advanced technologies. Today’s engineering managers must be skilled Industry 4.0 practitioners and leaders who can guide diverse engineering teams and oversee complex service or product development that always leverage and consider the role of data. Their responsibilities include safety, sustainability, resource allocation, team building, project planning, budgeting, and product development linked with economic and financial outcomes. They must also oversee execution in terms of technology deployment.
Effective engineering management matters enormously. It influences an organization’s financial outcomes (revenue growth, profitability and operational efficiency) and impacts engineering facilities, largescale projects, clients, workers, and the public. The focus is on effective implementation of best practices to lead engineering teams with knowledge spanning the gap between business management and engineering.
Engineering managers serve as the interface between the business and technical sides of a project, translating business-oriented goals and needs into actionable engineering strategies and projects. They direct teams to ensure they stay motivated, focused, and efficient. Their joint knowledge of certain key aspects of business management and technical engineering concepts allows them to proactively make balanced decisions that will mitigate project risks, efficiently allocate resources, and consistently deliver high-quality products within the project budget and schedule.
Engineers are good at solving technical problems. However, they're often not as strong at leveraging data science techniques to make evidence-based decisions, or leading and inspiring diverse teams with empathy and inclusiveness.
- C. Fred Higgs, III, Faculty Director, Master of Engineering Management & Leadership (MEML) Degree Program
Within the field of engineering management, roles vary by specialization. Here are some of the fields within engineering management and the specific responsibilities in each role:
- Mechanical engineering managers lead teams, projects, and innovations in the design and improvement of mechanical systems, typically in specialized areas like automotive, robotics, and electronics.
- Bioengineering managers lead teams, projects, and innovations in the interface of medicine and engineering. They participate in the design of medical and diagnostic devices, biocompatible materials, and advance biomedical engineering, ecological engineering, and orthopedic medicine.
- Chemical and Biomolecular engineering managers lead teams, projects, and innovations in chemical plant operations, waste management, life sciences, and the production of items such as medicine and plastics on a large scale. Their work focuses on the study and manipulation of chemicals and biological molecules, which often finds applications in materials and nanotechnology, engineered biological systems, energy, sustainability and the environment. When chemical-based innovations emerge, these managers lead engineering teams to scale them up.
- Civil and Environmental engineering managers lead teams, projects, and innovations related to societal infrastructures. Projects can include bridges and roadways, and ecological improvements, like contamination remediation, green energy, and infrastructure for smart cities.
- Electrical and Computer engineering managers lead teams, projects, and innovations in the study, design, and development of electricity, electronics, electromagnetism, and computer hardware and software, ranging from electrical components and information technology hardware to supercomputers and cloud-based hardware and cyber-infrastructure. Semiconductor manufacturing is another area that is filled with these engineering managers.
- Industrial and Systems engineering managers lead teams, projects, and innovations in the optimization and development of industrial and manufacturing systems, processes, machines, and organizations.
- Materials Science and Nanoengineering managers lead teams, projects, and innovations in the study, discovery, creation, testing, and use of materials (like advanced plastics and graphene) by understanding their behavior from the the atomic to macroscopic scale. This is done in order to create tools and materials solutions for industry or human problems.
- Software engineering managers lead teams, projects, and innovations in the development of advanced software systems and computer programs, many of which are cloud based, platform based, and increasingly incorporating AI and machine learning.
As undergraduates, engineers are expected to pass rigorous math, science, and engineering classes in order to learn the “hard skills”, or technical skills, required to become an individual contributor in their chosen specialization. For many engineers, working as an expert in their field–whether Aerospace or Mechanical, Environmental or Chemical–is the end goal and a fulfilling career.
But for those engineers who feel called to lead engineering, becoming an Industry 4.0 engineering manager and business leader can be a difficult and confusing path for three main reasons:
1. The Chicken-or-Egg Dilemma: Many companies will only consider candidates with demonstrated managerial/leadership experience, but the only way to get this experience is by managing and leading teams. Where is an engineer supposed to start?
2. Hard Skills Now Include Industry 4.0 AI and Data Science Skills: AI is a general-purpose technology that will transform every industry. Every engineering discipline will be deeply impacted by it, from molecular dynamics in chemical engineering, to smart buildings and infrastructure in civil and environmental engineering. Opportunities presented by big data and AI are increasing exponentially, and the engineer who expects to have a thriving career will not be able to sit on the sidelines. Data is the ‘blood’ that connects both devices in the Internet of Things and technologies such as 3D printing, digital twins, and autonomous vehicles. Today’s engineering managers and leaders must understand the strategic, economic and operational benefits of these advances, while communicating the value of them to the internal gatekeepers over the resources--the business executives.
3. Soft Skills and Emotional Intelligence are Core to Effective Leadership: Being an effective engineering manager requires not just the technical skills they learned as undergraduates, but a new toolkit of soft, human leadership skills that don’t always come naturally to more systematic, logical thinkers. These include: motivating and inspiring employees (“EQ” or emotional intelligence), persuasion, servant leadership, communication, project management, and more. Most MSEs (Master’s or M.S. Degrees in Engineering) typically won’t focus on these important human leadership areas; instead, they'll push engineers deeper into their chosen area of specialization.
An engineering management graduate degree can help engineering professionals more easily and confidently transition from being an individual contributor to an engineering manager and leader. The engineering master’s degree (often called a “MEM” degree, or Rice “MEML” degree) is ideal for individuals with existing engineering educational and work/business experience who want to advance their careers and take on leadership roles.
The MEM degree is not merely a combination of engineering and management, it bridges the gap of information between engineering and business management in order to train engineers to lead technical teams and units. The Master of Engineering Management and Leadership (MEML) degree at Rice University is a MEM degree, yet it is supplemented by a focus on educating engineers to lead within this exciting, fast-evolving Industry 4.0 (I4) landscape.
In an engineering management master’s degree program, professionals can learn and apply both the I4 technical skills (for example, augmented reality or additive manufacturing) and soft skills that one often can’t acquire through work experience alone. These programs are designed to sharpen your leadership skills while broadening your business, managerial, technical engineering, and advanced tech knowledge, so you’ll be prepared to manage engineering teams and projects of any size or level of complexity.
While there are many ways to learn related skills like communication and project management, an advanced engineering management program provides a holistic, all-in-one curriculum and a unique experience to learn in personalized, smaller class sizes from industry experts who have been on the frontlines of data-driven digital transformation. For example, the MEML@Rice degree program has one of the highest numbers of engineering professors in the practice, a title for reserved for engineering professors with 10+ years of industry experience. The MEML curriculum allows students to gain invaluable experience that will help them reskill and upskill through the Capstone project, where students develop I4-relevant technological solutions to their industry’s latest engineering and business problems.
Whichever business engineering management role you pursue, the Master of Engineering Management and Leadership (MEML) program at Rice will help you develop the skills you need to succeed. With specializations in computer and data science, skill sets designed to develop Industry 4.0 and data-driven leaders, a world-class faculty, and a robust curriculum, the program is designed to prepare you for a successful engineering management or technical leader career.
Sources: 1Bozkurt, Ipek. "Quantitative analysis of graduate-level engineering management programs." 2014 IEEE
International Technology Management Conference. IEEE, 2014.
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