EXECUTIVE EDUCATION

Technology and Innovation Acceleration Program

Manage both people and technology with excellence.

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Course Dates

STARTS ON

June 30, 2021

Course Duration

DURATION

6 months, online
4-6 hours per week

Course Duration

Leading Into the Next Frontier

Just as technology and business have joined forces to co-create value, technology and leadership have conspired to require a new kind of leader. The skills required of leaders to achieve breakout performance have shifted—dramatically. Now is the time to step out of your comfort zone and prepare for the next frontier.

In order to support technology professionals on this journey, more than 15 MIT faculty have distilled their expertise on key technology accelerators, along with principles of organizational strategy and leadership, into the six-month Technology and Innovation Acceleration Program online.

Being a future-ready leader is about managing both technology and people with excellence. That’s the MIT way.

Organizing Principle: The Six Pillars of Technology Management

Pillar 1: Critical thinking
Analyze the evidence, consider alternate solutions, solve complex problems

Pillar 2: System thinking
Understand how the components of a system interact with each other, identify interdependencies, solve more problems

Pillar 3: Creating value through emerging technologies
Evaluate what technologies can solve your problems and pay off

Pillar 4: Radical innovation
Establish the ground rules for exponential growth

Pillar 5: Organizational strategy
Identify how technology impacts your organizational structure and strategy

Pillar 6: Leadership
Mobilize the people and resources needed to achieve breakthrough performance

Who Is This Program For?

Every industry is prone to disruption. This program is ideal for individuals who are seeking to be on the leading edge of technology innovation while also applying organizational strategies to bolster success. Representative roles include:

  • Mid- to senior-level managers preparing for technology leadership roles
  • Functional department heads and business leaders looking to drive tech innovation and strategy across their organization
  • Senior technology leaders seeking to lead technology innovation, build high-performing teams, and develop strategies for achieving organizational alignment
  • Consultants seeking to explore emerging technologies, such as AI and AR/VR tools for enabling innovation, and business applications in order to offer cutting-edge solutions for clients

Key Takeaways

  • Implementing system thinking and architecture to analyze complex systems or processes, create new models, and utilize strategic decision-making
  • Exploring emerging technologies and their business applications, including artificial intelligence, augmented reality, virtual reality, and quantum computing
  • Identifying core features and strategies to execute various forms of radical innovation
  • Aligning organizational strategy to products and teams
  • Creating and reinforcing a culture of innovation within the organization through advanced leadership strategies

Program Modules

Over the course of six months, you will examine the range of capabilities, from critical thinking to emerging technology to managing technology and innovation, to help you lead with excellence.

Module 1:

Introduction to Critical Thinking

Get introduced to the concept of critical thinking and meta-cognition, the processes used to plan, monitor, and assess one's own understanding. Learn to implement critical thinking for solving complex problems by analyzing alternative solutions critically and identifying types of evidence for or against the alternative solutions.

Module 2:

Critical Thinking in Context

Receive an introduction to the concept of information literacy and various research techniques to help you form conclusions. Assess the strength of evidence and relate evidence to different social and technical factors.

Module 3:

Structured Decision Processes

Practice group decision-making processes that focus on convergence and gathering information by using the Pugh Matrix and the Evaluation Matrix. Learn how MIT’s D-Lab applies these matrices into their research to develop and advance practical solutions to global poverty challenges.

Module 4:

Foundations of System Thinking

Understand the elements of system thinking through a diverse set of self-assessment activities and learning scenarios. Apply these concepts to a personal activity system and a professional activity system of your choice.

Module 5:

Supply Chain and Computational Approach of System Thinking

Learn how system thinking is applied to a diverse array of applications, including logistics, transportation systems, and computational systems.

Module 6:

Modern System Architecture

Describe the architecture of a system and identify both architectural decisions and non-architectural decisions. Identify the various elements in architecture representations and place these in the context of the overall documentation of the system.

Module 7:

Modeling with the Design Structure Matrix (DSM) and Modularization

Learn to construct a DSM, either by analyzing the design or by converting a graph of the system. Construct a process architecture DSM and identify how it is different from a design DSM.

Module 8:

Value-Oriented Decision-Making

Understand the process of tradespace exploration by defining value, a key metric by which designs are compared. Develop a model of value by characterizing a design using attributes and organize these attributes into hierarchies for evaluation and summation.

Module 9:

Creating AI-Based Products and Services

Get acquainted with the stages involved in the design process for AI-based products and services with a focus on cost metrics and technical requirements of an AI software development plan.

Module 10:

Machine Learning

Identify various machine learning algorithms and study the different approaches, such as Bayesian and regression models. Learn about unsupervised and semi-supervised methods of machine learning algorithms. Run and analyze the results from various machine learning algorithms.

Module 11:

Deep Learning

Building on the knowledge of machine learning fundamentals gained in module 10, explore the basics of deep learning. Topics include neural networks, artificial neurons, and simulation of complex networks.

Module 12:

Designing AI Machines to Solve Business Problems

Identify superhuman intelligence used in an AI product. Compare and contrast the advantages and disadvantages of using an AI technology.

Module 13:

Introduction to Augmented Reality and Virtual Reality (AR/VR)

Discover immersive media, including augmented reality, and virtual reality. Learn to differentiate the unique elements of AR, VR, and mixed reality and learn about the software and hardware requirements of each.

Module 14:

Future of AR/VR

Understand the applications of AR/VR in diverse fields such as medicine, military, and education. Learn about AI-enhanced augmented reality and drive innovation using AR/VR powered solutions. Analyze the impact of 5G on AR/VR experience and the long-term impact of COVID-19 on remote and virtual experiences.

Module 15:

Introduction to Quantum Computing

Learn about the core concept of quantum computing, its origin, and how it is different from other forms of computing. Compare and contrast classical computers (desktops, laptops, tablets, cloud servers, etc.) with quantum computers. Learn about the timeline for quantum computing and explore the types of problems that are a challenge for classical computers, but can be efficiently solved on a quantum computer.

Module 16:

Introduction to Radical Innovation

Get an introduction to radical innovation, a concept that is diametrically opposed to incremental innovation. Learn the core features of technical innovation in the modern world and the philosophy and strategies needed in an organization to execute various forms of innovation.

Module 17:

Urgency and Spirit of Radical Innovation

Understand the factors that pose a threat to innovation, both internal and external. Explore concepts such as super technologies, business model innovation, and developing your innovation pipeline.

Module 18:

Leading in Innovation

Understand the most important elements of how to innovate. Explore different methodologies such as Lean and Agile for executing innovation, and learn about testing, rapid prototyping, and design to lead innovation within your organization.

Module 19:

Technical Changes and Its Impact on Organizational Strategy

Recognize the key elements of strategy, the precursors to strategy, and the influence of strategy on products. Analyze the impact of technological changes on organizational strategy and apply strategic thinking for gaining competitive advantage.

Module 20:

Building High-Performance Teams

Learn how to create, staff, and mobilize the people and resources needed to effectively launch new project teams and improve existing ones. Examine strategies for managing three main types of group conflict: task-related conflict, relational conflict, and process conflict.

Module 21:

New Perspective of Leadership in Technical Teams

Explore different strategies to increase effectiveness and to build teams in a productive way. Learn to architect an effective organization that supports teams and teams' success. Implement post-mortems to capture lessons learned and build future capability in teamwork.

Module 22:

Navigating and Leveraging Networks

Get introduced to organizational networks and learn about the different categories of networks like social network, closed network, and open network. Identify the key players, their roles, and importance while leading change within an organization.

Module 1:

Introduction to Critical Thinking

Get introduced to the concept of critical thinking and meta-cognition, the processes used to plan, monitor, and assess one's own understanding. Learn to implement critical thinking for solving complex problems by analyzing alternative solutions critically and identifying types of evidence for or against the alternative solutions.

Module 12:

Designing AI Machines to Solve Business Problems

Identify superhuman intelligence used in an AI product. Compare and contrast the advantages and disadvantages of using an AI technology.

Module 2:

Critical Thinking in Context

Receive an introduction to the concept of information literacy and various research techniques to help you form conclusions. Assess the strength of evidence and relate evidence to different social and technical factors.

Module 13:

Introduction to Augmented Reality and Virtual Reality (AR/VR)

Discover immersive media, including augmented reality, and virtual reality. Learn to differentiate the unique elements of AR, VR, and mixed reality and learn about the software and hardware requirements of each.

Module 3:

Structured Decision Processes

Practice group decision-making processes that focus on convergence and gathering information by using the Pugh Matrix and the Evaluation Matrix. Learn how MIT’s D-Lab applies these matrices into their research to develop and advance practical solutions to global poverty challenges.

Module 14:

Future of AR/VR

Understand the applications of AR/VR in diverse fields such as medicine, military, and education. Learn about AI-enhanced augmented reality and drive innovation using AR/VR powered solutions. Analyze the impact of 5G on AR/VR experience and the long-term impact of COVID-19 on remote and virtual experiences.

Module 4:

Foundations of System Thinking

Understand the elements of system thinking through a diverse set of self-assessment activities and learning scenarios. Apply these concepts to a personal activity system and a professional activity system of your choice.

Module 15:

Introduction to Quantum Computing

Learn about the core concept of quantum computing, its origin, and how it is different from other forms of computing. Compare and contrast classical computers (desktops, laptops, tablets, cloud servers, etc.) with quantum computers. Learn about the timeline for quantum computing and explore the types of problems that are a challenge for classical computers, but can be efficiently solved on a quantum computer.

Module 5:

Supply Chain and Computational Approach of System Thinking

Learn how system thinking is applied to a diverse array of applications, including logistics, transportation systems, and computational systems.

Module 16:

Introduction to Radical Innovation

Get an introduction to radical innovation, a concept that is diametrically opposed to incremental innovation. Learn the core features of technical innovation in the modern world and the philosophy and strategies needed in an organization to execute various forms of innovation.

Module 6:

Modern System Architecture

Describe the architecture of a system and identify both architectural decisions and non-architectural decisions. Identify the various elements in architecture representations and place these in the context of the overall documentation of the system.

Module 17:

Urgency and Spirit of Radical Innovation

Understand the factors that pose a threat to innovation, both internal and external. Explore concepts such as super technologies, business model innovation, and developing your innovation pipeline.

Module 7:

Modeling with the Design Structure Matrix (DSM) and Modularization

Learn to construct a DSM, either by analyzing the design or by converting a graph of the system. Construct a process architecture DSM and identify how it is different from a design DSM.

Module 18:

Leading in Innovation

Understand the most important elements of how to innovate. Explore different methodologies such as Lean and Agile for executing innovation, and learn about testing, rapid prototyping, and design to lead innovation within your organization.

Module 8:

Value-Oriented Decision-Making

Understand the process of tradespace exploration by defining value, a key metric by which designs are compared. Develop a model of value by characterizing a design using attributes and organize these attributes into hierarchies for evaluation and summation.

Module 19:

Technical Changes and Its Impact on Organizational Strategy

Recognize the key elements of strategy, the precursors to strategy, and the influence of strategy on products. Analyze the impact of technological changes on organizational strategy and apply strategic thinking for gaining competitive advantage.

Module 9:

Creating AI-Based Products and Services

Get acquainted with the stages involved in the design process for AI-based products and services with a focus on cost metrics and technical requirements of an AI software development plan.

Module 20:

Building High-Performance Teams

Learn how to create, staff, and mobilize the people and resources needed to effectively launch new project teams and improve existing ones. Examine strategies for managing three main types of group conflict: task-related conflict, relational conflict, and process conflict.

Module 10:

Machine Learning

Identify various machine learning algorithms and study the different approaches, such as Bayesian and regression models. Learn about unsupervised and semi-supervised methods of machine learning algorithms. Run and analyze the results from various machine learning algorithms.

Module 21:

New Perspective of Leadership in Technical Teams

Explore different strategies to increase effectiveness and to build teams in a productive way. Learn to architect an effective organization that supports teams and teams' success. Implement post-mortems to capture lessons learned and build future capability in teamwork.

Module 11:

Deep Learning

Building on the knowledge of machine learning fundamentals gained in module 10, explore the basics of deep learning. Topics include neural networks, artificial neurons, and simulation of complex networks.

Module 22:

Navigating and Leveraging Networks

Get introduced to organizational networks and learn about the different categories of networks like social network, closed network, and open network. Identify the key players, their roles, and importance while leading change within an organization.

Program Highlights

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Live sessions with MIT faculty

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Individualized feedback on assignments

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Weekly live office hours with Q&A (learning facilitator led)

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Access to cutting-edge technologies and concepts from MIT

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Application of learning through a final capstone project

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Certificate of Completion from MIT xPRO

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Optional on-campus event to network and celebrate program completion

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Fireside chats with technology leaders

Capstone Project

The capstone project uses the six pillars as the cornerstone of an authentic technology management project aligned to your current or aspirational technology leader role. The final capstone applies learning from each pillar to solve a challenge with practical applications. You will be able to design a project that can be integrated into your real-world setting.

Select Case Studies

Logo for JumpToPC

JumpToPC

For many in developing countries, personal computers are out of reach. MIT D-Lab is collaborating with partners to develop a platform that uses a household’s existing smartphone or television to offer at-home computing solutions. Examine the strategic decisions made along the development journey.

Logo for Toyota

Toyota

Were sticky pedals and floor mats to blame for the "unintended acceleration" issues on many Toyota vehicles, or was it a problem with the sensors or software? Peer into the investigation and explore how critical thinking and decision-making were used and abused.

Logo for The Robot Compiler

The Robot Compiler

Take a system-thinking tour of how making a custom robot is made possible by compiling parts from a database. Examine each of the computation-driven steps in the process of fabricating a robot—so easy, anyone can have a personal robot.

Logo for The Apollo Mission

The Apollo Mission

With countless decisions to be made and competing priorities, how does a team organize a mission to the moon? Examine the decision-making process that the Apollo team used, distinguishing between the architectural decisions that needed to be made first and those decisions that could be made downstream.

MIT Instructors

Faculty Member Deborah Ancona

Deborah Ancona

Seley Distinguished Professor of Management, Professor of Organization Studies, and Founder of the MIT Leadership Center at the MIT Sloan School of Management

Anaconda’s pioneering research into how successful teams operate has highlighted the critical importance of managing outside, as well as inside, the team’s boundary. Ancona’s work also focuses on the concept of distributed leadership and on the development of research-based tools, practices, and teaching/coaching models that enable organizations to foster creative leadership at every level.

Faculty Member Hamsa Balakrishnan

Hamsa Balakrishnan

Professor and Associate Department Head of Aeronautics and Astronautics at the Massachusetts Institute of Technology

Balakrishnan’s current research interests are in the design, analysis, and implementation of control and optimization algorithms for large-scale cyber-physical infrastructures, with an emphasis on air transportation systems. Her research spans theory and practice, including both algorithm development and real-world field tests.

Faculty Member Duane Boning

Duane Boning

Clarence J. LeBel Professor in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology

Boning's research is focused on the modeling and control of variation in manufacturing, including IC, photonics, and MEMS processes, devices, and circuits. His research interests include statistical and machine learning methods for design and manufacturing in advanced technologies.

Faculty Member Bruce G. Cameron

Bruce G. Cameron

Director of the System Architecture Lab at the Massachusetts Institute of Technology

Cameron’s research interests include technology strategy, system architecture, and the management of product platforms. He has supervised over 50 graduate students and has directed research projects for Amazon, BP, Sikorsky, Nokia, Caterpillar, AMGEN, Verizon, and NASA.

Faculty Member Edward Crawley

Edward Crawley

Professor of Aeronautics and Astronautics and Ford Professor of Engineering at the Massachusetts Institute of Technology

Crawley’s research focuses on the design of complex systems, and he is the author of this text: System Architecture. He is a fellow of the AIAA, and a member of the NAE, as well as national academies in the UK, Sweden, Russia, and China.

Faculty Member Olivier de Weck

Olivier de Weck

Professor of Aeronautics and Astronautics and Engineering Systems at the Massachusetts Institute of Technology

De Weck’s research focuses on how complex man-made systems such as aircraft, spacecraft, automobiles, printers, and critical infrastructures are designed and how they evolve over time. His main emphasis is on strategic properties that have the potential to maximize lifecycle value.

Faculty Member Steven Eppinger

Steven Eppinger

General Motors LGO Professor of Management; Professor of Management Science and Innovation; Co-Director, SDM and IDM Programs at the Massachusetts Institute of Technology

Dr. Eppinger is one of the most highly recognized scholars in the area of product development and technical project management. His research is applied to improving complex design processes in order to accelerate industrial practices. He is a pioneer in development of the widely used Design Structure Matrix (DSM) method for managing complex system projects.

Faculty Member Dan Frey

Dan Frey

MIT D-Lab Faculty Director for Research, Professor of Mechanical Engineering at the Massachusetts Institute of Technology

Frey is actively involved in design of engineering devices for the developing world, and has worked intensively with colleagues, administrators, and the Singapore Ministry of Education to establish a major new research center for engineering design.

Faculty Member D. Fox Harrell

D. Fox Harrell

Professor of Digital Media & Artificial Intelligence and Director of the MIT Center for Advanced Virtuality

Harrell’s research explores the relationship between imagination and computation, and it involves developing new forms of virtual reality, computational narrative, video gaming for social impact, and related digital media forms based in computer science, cognitive science, and digital media arts.

Faculty Member Bruce Lawler

Bruce Lawler

Managing Director of MIT Machine Intelligence for Manufacturing and Operations

Lawler is a technology entrepreneur and executive leader with consecutive public and private exits, and early-stage investing success with leading venture firms including Accel, CRV, KPCB, Redpoint, Sequoia, and Softbank. He has development expertise in mobile applications, SaaS, artificial intelligence systems, and video distribution networks. He is currently the managing director of MIT MIMO (Machine Intelligence for Manufacturing and Operations).

Faculty Member David Niño

David Niño

Senior Lecturer, Gordon Engineering Leadership Program at the Massachusetts Institute of Technology

Niño heads leadership education for graduate students across the institute. He is strongly committed to the development of leadership among engineers and other professionals in technology and is active in an international consortium of engineering leadership centers. He is also a founding officer of the Engineering Leadership Development Division of the American Society of Engineering Education.

Faculty Member Will Oliver

Will Oliver

Professor of the Practice of Physics, Associate Director of the Research Laboratory of Electronics (RLE), and Laboratory Fellow at MIT Lincoln Laboratory

In these roles, Oliver provides programmatic and technical leadership targeting the development of quantum and classical high-performance computing technologies. His research interests include the materials growth, fabrication, design, and measurement of superconducting qubits, as well as the development of cryogenic packaging and control electronics involving cryogenic CMOS and single-flux quantum digital logic.

Faculty Member RAY REAGANS

RAY REAGANS

Alfred P. Sloan Professor of Management, Professor of Work and Organization Studies, and Associate Dean for Diversity, Equity, and Inclusion at MIT Sloan School of Management

Reagans studies the origin and influence of social capital on knowledge transfer, learning rates, and overall team performance. More specifically, he examines how demographic characteristics such as race, age, and gender affect the development of network relations.

Faculty Member Adam Ross

Adam Ross

Research Scientist, Systems Engineering Advancement Research Initiative, Engineering Systems Division at the Massachusetts Institute of Technology

Ross has research interests and advises students in ongoing research projects in advanced systems design and selection methods, tradespace exploration, managing unarticulated value, designing for changeability, value-based decision analysis, and systems-of-systems engineering.

Faculty Member Daniela Rus

Daniela Rus

Professor of Electrical Engineering and Computer Science, and Director of CSAIL at the Massachusetts Institute of Technology

Rus’ work is focused on developing the science and engineering of autonomy, toward the long-term objective of enabling a future with machines pervasively integrated into the fabric of life, supporting people with cognitive and physical tasks. Her research addresses some of the gaps between where robots are today and the promise of pervasive robots. The applications of this work are broad and include transportation, manufacturing, agriculture, construction, the environment, underwater exploration, smart cities, and medicine.

Faculty Member Brian Subirana

Brian Subirana

Director of Auto-ID Laboratory at the Massachusetts Institute of Technology and Accenture Convergence Initiative for Industry and Technology

Subirana’s research centers on IoT and AI, and focuses on manufacturing, e-learning, the creative industries, and digital health. He is developing a voice name system that can help humans talk to any object in an IoT environment. He has over 200 publications, including three books.

Faculty Member Sanjay Sarma

Sanjay Sarma

Vice President for Open Learning and Professor of Mechanical Engineering at the Massachusetts Institute of Technology

Sarma is co-founder of the Auto-ID Center at MIT and developed many of the key technologies behind the EPC suite of RFID standards now used worldwide. He was the founder and CTO of OATSystems, which was acquired by Checkpoint Systems (NYSE: CKP) in 2008. His research includes sensors, the Internet of Things, cybersecurity, and RFID.

Certificate

Example image of certificate that will be awarded after successful completion of this program

Certificate

Get recognized! Upon successful completion of this program, MIT xPRO grants a certificate of completion to participants. This program is graded as a pass or fail; participants must receive 75% to pass and obtain the certificate of completion.

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