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Innovation management

01TXISM

A.A. 2020/21

2019/20

Innovation management

Innovation management

Digital technologies are improving the capability of organizations and individuals of accessing, storing and analyzing information (cloud computing, big data and artificial intelligence), of making things in a smarter, more efficient and safer way (augmented and virtual reality, additive manufacturing), and of connecting things (Internet of Things - IoT). There are certain dimensions in which digital technologies transform industries and processes in ways that replicate and extend transformations of the past. For example, IoT, big data and artificial intelligence offer new ways of implementing continuous improvement and lean thinking methods. However, there are other ways in which digital technologies transform industries that are fundamentally new (e.g. smart connected products and product-service systems), create new approaches to design and management, expose organizations to new sources of uncertainty, risk and competition, and require new approaches to decision-making, design and engineering. Both the “old” revisited approaches and the more radical transformations have in common the need to develop job positions characterized by technical skills on data science and managerial skills and attitudes needed to understand with a business and an operational engineering lens how big data can be used. Such T-shaped profile of skills will allow data scientists to work in cross-functional teams and have effective coordination with business domain experts. The course intends to explore the main challenges and perils produced at three levels. At the macro level, the course provides an interpretation of the social and economic implications of big data and it will offer a comparative analysis of its characteristics and effects across industries, within and outside the manufacturing world. Contextual factors will be considered. While digital transformation and big data enable global innovations, economic regulations and institutions are still at a local level. This implies an understanding of the factors that can facilitate or hinder the success and the replicability of digital transformation initiatives across different industries. At the meso level, big data raise fundamental questions on the underlying processes, routines, capabilities and structures by which organizations innovate and build their organizational learning mechanisms, in processes like product and service development, manufacturing and customer relationship management. At the micro level, the simultaneous introduction of Artificial Intelligence, Big Data, algorithms and virtual reality challenges existing skills and capabilities into the organization. This raises several points for organizations related to how the new digital skills should be acquired and combined with “analog” legacy skills of an organization.

Innovation management

At the end of the course, students will have acquired a concrete ability to analyze and manage business decisions related to big data in both strategic and operational terms.

Innovation management

At the end of the course, students will have acquired a concrete ability to analyze and manage business decisions related to big data in both strategic and operational terms.

Innovation management

For an easier acquisition of the course contents, it might be useful for students to know the fundamentals of Economics and Business Organization, as well as the basics of Business Strategy.

Innovation management

For an easier acquisition of the course contents, it might be useful for students to know the fundamentals of Economics and Business Organization, as well as the basics of Business Strategy.

Innovation management

1. Technological Innovation, companies and sectors: Determinants, taxonomies and dynamics of innovation, dominant design and standard. Innovation in business models. Technological forecasting. 2. Big Data as a strategic resource of competition: the use in incremental vs. radical innovation; big data and business model innovation; big data and its relation with a firm’s core competencies 3. Big data and industry-level changes: how big data and the related digital technologies require new core competencies and new alliances between firms 4. Big Data and new organizational architecture: what type of organizational changes and configurations are needed to deploy big data and data scientists effectively 5. Big Data and AI and their role in the decision-making processes at the individual and organizational level.

Innovation management

1. Technological Innovation, companies and sectors: Determinants, taxonomies and dynamics of innovation, dominant design and standard. Innovation in business models. Technological forecasting. 2. Big Data as a strategic resource of competition: the use in incremental vs. radical innovation; big data and business model innovation; big data and its relation with a firm’s core competencies 3. Big data and industry-level changes: how big data and the related digital technologies require new core competencies and new alliances between firms 4. Big Data and new organizational architecture: what type of organizational changes and configurations are needed to deploy big data and data scientists effectively 5. Big Data and AI and their role in the decision-making processes at the individual and organizational level.

Innovation management

Innovation management

Innovation management

The course consists of lectures, with extensive use of case studies drawn from experience and empirical research, and practices.

Innovation management

The course consists of lectures, with extensive use of case studies drawn from experience and empirical research, and practices.

Innovation management

Texts, readings, handouts and other learning resources

Innovation management

Texts, readings, handouts and other learning resources

Innovation management

Modalità di esame: Prova scritta (in aula);

Innovation management

Innovation management

Exam: Written test;

Innovation management

Exam: written test; individual project Assessment will be based on a written exam and on assignments handed in during the course.

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