TRACK Workshop: Digital Business Models for Industrial Companies
Day one: Business Model Archetypes (4/20/22)
Day two: Developing Business Model (4/27/22)
Value is migrating from traditional industrial business models to digital business models at a rapid pace. These new business models are complex, and often depend on new corporate capabilities. It can be mystifying to identify the digital business model that is most appropriate for a particular industrial context, however. This course is designed to provide enough background for participants to identify and begin developing and testing digital business models.
The course is divided into two parts. In the first part, we will discuss the digital business model archetypes that are most appropriate to industrial companies. For each, we will discuss the model, who uses it today, why it works, and the key assumptions underlying the model. The second part of the course will discuss how to develop, test, and introduce a new business model. It is based a model for doing business model innovation called the Business Model Pyramid). We will also discuss the challenges of doing business model innovation in large companies and how to build internal support for your business.
The course will feature practical illustrations based on the real-world experiences of the instructor. It will include hands-on break-out sessions that will give participants confidence in applying the concepts. Upon completion, participants will be able to identify digital business model options for their companies, assess them, and begin to do the work to bring a new concept to market.
Who should attend:
The course is designed for those in innovation functions or within businesses who have responsibility for developing and bringing new business concepts to market or for managing their company’s digital transformation. It is useful both for practitioners developing new business concepts and for those who manage the innovation and digital functions. This course covers a broad range of business issues and can be viewed as a springboard to the participant’s professional advancement.
IRI Members: $295
Non Members: $395
Due to limited seating, we request that you cancel at least 48 hours before a scheduled class. This gives us the opportunity to fill the class. However, if you do not cancel prior to the 48 hours, you will lose the payment for the class.
All IRI events are broadcast in Eastern Standard Time
Outside Consulting, LLC
Jim Euchner is Honorary Professor at Aston Business School (UK) and Editor in Chief of Research-Technology Management, a peer-reviewed journal for practitioners of innovation, technology and research management. He was previously Vice President of Global Innovation at Goodyear Tire & Rubber Company, where he led the development of new businesses and helped launch five businesses on three continents. Prior to his work at Goodyear, Jim held positions as Vice President of Growth Strategy and Innovation at Pitney Bowes, Inc. and Vice President, Network Systems Advanced Technology at Bell Atlantic (now Verizon). Jim has worked in the field of intelligent systems for over 25 years. In his consulting practice, he helps companies to implement businesses enabled by emerging technologies, including AI, the Internet of Things (IoT), automation, and predictive analytics. He helps companies to move quickly and in a disciplined way from concept to cash. Areas of focus include the use of lean startup approaches in large organizations, business model innovation, and the challenges manufacturers confront in moving to services-led business models. Jim is a member of the Scientific Advisory Council for the Nissan Autonomous Vehicle program and industry co-chair of the Aston Advanced Services Partnership. He is also a co-founder of the MIT Innovation Laboratory, a consortium to nurture innovation in organizations. Jim has published and spoken extensively on innovation and technology management. His google scholar page can be found at http://tinyurl.com/google-scholar-JimEuchner. Jim received his Bachelor of Science degree from Cornell University in mechanical and aerospace engineering and his Master of Science degree from Princeton University, where he was a Guggenheim Fellow. He also holds an MBA from Southern Methodist University. He has received several awards for his work in AI, including two selections as Innovative Applications of AI, the Carnegie Mellon University/AMS Award for Managing Information Systems, and the Franz Edelman Award (finalist).