Events that include:

Leadership by Design will help both individuals and teams understand and practice human-centered design. Participants in this program will learn both strategic and hands-on techniques for structured exploration through prototyping. They will also learn how to enable an action-based organizational culture in which empathy is generated, trial and error is encouraged, and failure is celebrated as a source of learning, all resulting in successful innovation. It is intended to introduce the concepts of human-centered design to individuals and teams who are not already familiar with these design-based concepts and their application.

Drawing on the resources of MIT?s Integrated Design & Management curriculum and its new Integrated Design Lab (ID Lab), this program combines the inspired, intuitive methods taught in the world?s best design schools with the systematic, analytical methods for which MIT is world-renowned. This program is led by Matthew S. Kressy, creator and Director of Integrated Design & Management (IDM).

Course content includes:

• Discussions on expression and culture
• Field exercises in observation, exploration, and user empathy
• Lectures on concept generation
• Studio exercises in persona development and storytelling
• Lectures and case studies pertaining to design leadership
• Hands-on sketch modeling and rendering exercises
• Functional prototyping workshops
• Opportunities to build, test, and iterate prototypes in teams
• Concluding discussions on process and leadership

The tools presented in the program can be applied to any range of human-centered innovation problems and opportunities including products, services and social/societal challenges.

By applying a design-centered approach to leadership, you?ll be able to conceive of radically innovative solutions to multifaceted problems, create a vision that gets buy-in from senior management and colleagues, avoid hazards, and create solutions that people love both emotionally and intellectually.

Innovation is a driver of productivity, comparative advantage, economic growth, and enterprise value. But innovation does not happen in a vacuum. It requires a network of participants—entrepreneurs, corporate managers, investors, researchers, university faculty, venture capitalists, government officials, suppliers, and customers—who comprise the ecosystem. Innovating in such ecosystems creates a new set of challenges for organizations and their leaders. Executives often find it hard to get beyond the buzzwords to harness the power of this phenomenon for their organizations.

This new course draws on MIT research to provide an introduction to innovation ecosystems, to demystify this important concept, alongside the broader topics of innovation and entpreneurship, and to explain how the right ecosystem can provide both an inspiration for innovation and source of competitive advantage. Participants will learn to understand their role as stakeholders in innovation ecosystems. They will learn ways to assess both their local and other ecosystems (including Boston and elsewhere) as potential locations for innovation centers, etc. And also to partner with startup entrepreneurs, research universities, ‘risk capital’ providers and other corporate/government stakeholders, on on accelerators, prizes, and hackathons.

Participants in the program need not aim to become corporate entrepreneurs or intrapreneurs themselves, but they should want to understand—as leaders and managers—how to access external innovation from the ecosystem, and how to lead on internal innovation.

New digital technologies have fundamentally reshaped marketing theory and practice the last decade alone. Technology has changed the modes of communication through which firms engage with consumers. Moore's law has made the storage and analysis of consumer data scalable, creating opportunities for fine-grained behavioral analytics. New monitoring tools have fostered precise and personalized customer relationship management practices. The rise of mobile phones and tablets has enabled location based messaging and reciprocal communication. The ubiquity of video content has promulgated rich, native advertising programs. The global emergence of social networking has enabled networked based predictive modeling and new forms of targeting and referral strategies based on the preferences of consumers' peers. And finally, new social media have brought all of this onto the public stage, with word-of-mouth conversations driving brand awareness and brand loyalty, and user-generated content on review and ratings sites making or breaking demand for products or services.

This two-day course provides a detailed, applied perspective on the theory and practice of digital marketing and social media analytics in the 21^st century. We will cover concepts such as the difference between earned and paid media, predictive modeling for ad targeting and customer relationship management, measuring and managing product virality, viral product design, native advertising, and engaging the multichannel experience. Throughout the course we will specifically stress the theory and practice of randomized experimentation, AB testing and the importance of causal inference for marketing strategy.

Topics covered in this course include:

• Search marketing
• Social network marketing
• Social media analytics
• User generated content management and marketing
• Mobile advertising and commerce
• CRM strategy in the age of big data and digital advertising
• Earned vs paid media
• Predictive modeling for ad targeting
• Viral product design
• The multichannel experience
• Randomized experimentation
• A/B testing

Upon completion of this course you should have a fundamental understanding of:

• The digital advertising ecosystem and attribution and pricing models for digital advertising
• The fundamentals of web and app analytics and KPIs for web traffic and commerce
• Search engine marketing, search engine advertising, ad auctions, and strategies for optimizing search engine advertising
• Social network marketing and social network targeting
• Predictive analytics using social network data, peer-to-peer marketing and personalized social advertising
• Targeting and segmentation, specifically demographic targeting and segmentation, behavioral targeting and segmentation, social targeting and segmentation
• Social listening?analysis of user generated content, reviews, ratings and their effects on consumer demand
• Mobile commerce and analytics

Technical professionals' goals and incentives are often different from those of other employees, and so are the management challenges that arise. Drawing on the wealth of research and industry experience of faculty and leading practitioners, Managing Technical Professionals and Organizations explores proven, practical, and innovative strategies for maximizing the contribution of technical professionals. This intensive program focuses on the management and motivation of technical professionals in the innovative organization, and in particular:

• How creative individual contributors work together on risky projects, processing information under conditions of uncertainty;
• How to address critical problems and issues dealing with staff professionals and members of project teams, including cross-functional teams;
• How to work effectively with prima donnas and independent spirits.

The Learning Experience
Organizations that are designed and managed for doing the same things well repetitively, as in manufacturing and operations, are not particularly appropriate for doing something well once, as in R&D. Running a technical organization presents a unique set of management problems. How do you motivate and reward technical professionals to maximize their performance and creativity? How do you create an organizational structure that will contribute to success, not inhibit it? How do you deal with creative individual contributors, project teams, and innovative professionals? How do you build and sustain high motivation and vitality while preventing complacency? How do you utilize "marshaling" events for building more collaborative, innovative activities? And how do you move information and technology effectively across organizational structures?

This unique two-day program focuses on issues critical to the effective management of technical professionals and cross-functional teams. Its principles and strategies can be applied in any organization where research, development, engineering, or computer-related technology developments need to take place in a timely, effective, and successful manner.

Participants will learn principles and strategies of crucial importance to any organization where R&D, engineering, and/or computer-related technologies lie at the core of the business. Upon completing this program, participants will gain a thorough understanding of the following subjects:

• Managing risk taking and uncertainty in technical projects
• Managing and motivating your technical professionals
• Developing effective reward and incentive systems for technical professionals
• Creating a highly motivating work environment
• Managing and leading creative individual contributors
• Maximizing the technical productivity and vitality of teams
• Leading and managing more effectively across organizational structures
• Leading system change within established corporate cultures
• Transferring technology and information flows between and within organizations
• Organizing for innovative product development
• Managing the tensions among development efforts and cost/schedule pressures

This course aims to teach a suite of algorithms and concepts to a diverse set of participants interested in the general concept of fitting data to models. It starts with mostly simple linear algebra and computational methods, and introduces some more difficult mathematical concepts towards the end. This method also, by design, fits in with our approach of morning lectures and afternoon practice on personal computers. The combined teaching system provides opportunities for much hands-on learning and participants leave the course with practical knowledge of the basic algorithms.

The course is very broad and is primarily intended to cover the fundamentals of each technique we address. Consequently, the major gain is that we can cover many different approaches. Think of it this way: we cover the first chapter or two of a specialized "book" on a given method. We therefore get you through the many fundamentals, which then allow you to dig further through the book on your own. Another way of thinking of our approach is the analogy of a carpenter?s tools?the goal is for participants to understand the utility of each tool and not to become specialists in any one method. In that sense the course is introductory and general. The course taps into material from a very wide selection of literature in many disciplines involving computation, including but not limited to: statistics and applied mathematics, science, engineering, medicine and biomedicine, computer science, geosciences, system engineering, economics, insurance, finance, business, and aerospace engineering. More specific areas in which you might come across relevant books are: Regression, non-linear regression, linear and non-linear parameter estimation, inversion, system identification, econometrics, biometrics, etc. The diversity of the past participants and their fields has always provided many perspectives on our common interest in data and models. Please note that we do not specifically cover non-parametric statistics, principal component analysis, or Big Data.

Who Should Attend: Anyone who fits data to models. This course is truly broad-based and participants from vastly differing fields are envisioned and encouraged to attend. Some of these fields are engineering, business, natural sciences, geoscience, medicine, statistics, and economics. Familiarity with computing and statistics is desirable. A fair background in linear algebra is highly recommended. The course is a condensed version of a regular MIT class with the same title, taught by Professor Morgan. The course has also been given at NASA, the University of the West Indies in Barbados, Sakarya University in Turkey, Stanford University, University of Science and Technology of China,the Cyprus Institute, and Texas A&M University.

We live in an age of exponential change in which rapid innovation is disrupting and unseating incumbent products and industries, creating new technological frontiers, and challenging nearly everything we think we know about business. For instance, think Uber and the end of the medallion taxi industry. Think Airbnb in twice as many countries as Hilton in less than 5 percent of the time. Think Tesla. Think Oculus. But beyond using the "buzzword," can you really define innovation?

In this course, which is centered on the concept of Design Thinking, your answer to that question will come from actually involving yourself in the activity of innovating.

The course will include lectures from faculty and guests, discussions of case studies in innovation models and methods, and learning expeditions on and beyond the MIT campus. But it will also go beyond these traditional classroom activities to include hands-on experiences with some cutting-edge innovations as well as group work and a class hackathon to engage in genuine innovating ? and through that, to gain an understanding beyond the buzzword. Participants will emerge as more critical thinkers, knowledgeable about what innovation is (and is not), how it happens, how to discern meaningful trends in design and technology, and how to identify opportunities and propose innovative products, services, and experiences. Active class participation, a willingness to engage with others in a creative process, and a recognition that you might have a lot to learn about innovation are all prerequisites for the course.

Who Should Attend: To facilitate the cross-pollination of ideas, approaches, and critical thought, professionals from all industries are welcome. People from across the functional business spectrum will find the course valuable, including strategy leaders, directors of innovation and technology, product managers, engineers, marketers, and R&D personnel. All participants must come with a willingness and enthusiasm to engage and be ready to share their particular passions and expertise.