Learning outcomes

At the end of the course the student will be able to : • Designing and developing a digital product • Design and develop a digital functionality to an existing physical product • Designing a business model for new digital products • Designing a servitization model for an existing physical product • Develop a strategy for bringing a digital product to market

Goals

The course deals with the design, development and marketing of digital products (software/SaaS/API/Mobile Apps) and digital smart products (digitalisation of physical products): • Understand what a digital product is and how to digitise a physical product (smart product) • Mastering the different possible valuations of digital and smart products (data valorisation, digital servitisation, digital business models) • Mastering the development of such products • Develop a go-to-market strategy for such products: • Designing and developing a smart product from an existing physical product (digitalisation) • Develop a business model and a go-to-market strategy for this smart product The course will focus on techniques and approaches to digital product design: • Lean Startup • Value Proposition Canvas • Minimal Viable Product (MVP) • Digital Product/Service design • Smart product design and industrialization (industrialization-ready) • Hyper-scalability & Micro-caring • Growth Hacking

Content

Part 1: Digital products and digitisation of physical products • Digital innovation • Digital products: software, SaaS/Cloud, mobile applications and APIs • Smart products: digitalisation of physical products • Digital business models Part 2: Design and development of digital products • Agile & iterative design: lean startup principles • Design tools: value proposition canvas, business model canvas • Development of a Minimum Viable Product • Data-driven product management • Design of specific digital products: API & Smart Products Part 3: Gotomarket of digital products • Digital marketing • Growth hacking • Data usage • Pricing

Assessment method

The evaluation will be based on class participation (20%) and group work (80%) around a real case of digitisation of an existing physical product. The case will be common to the different groups. Students will apply the concepts & techniques learned in the course to the case. They will submit a report at the end of the year (+/- 50 pages) and present their work in class.

Sources, references and any support material

Scroll down to the WebCampus page of the course.

Language of instruction

French
Training Study programme Block Credits Mandatory
Master 120 en sciences de gestion, à finalité didactique Standard 0 5
Master 120 en sciences de gestion, à finalité spécialisée en Business Analysis & Integration Standard 0 5
Master 60 en sciences informatiques Standard 0 5
Master 120 en sciences informatiques, à finalité spécialisée en software engineering Standard 0 5
Master 120 en ingénieur de gestion, à finalité spécialisée en data science Standard 0 5
Master 120 en sciences de gestion, à finalité spécialisée en Transformation Digitale de l’Entreprise Standard 0 5
Master 120 en sciences informatiques, à finalité spécialisée en data science Standard 0 5
Master 120 en ingénieur de gestion, à finalité spécialisée en Analytics & Digital Business Standard 0 5
Master 120 en sciences de gestion, à finalité spécialisée en Business Analysis & Integration Standard 1 5
Master 60 en sciences informatiques Standard 1 5
Master 120 en ingénieur de gestion, à finalité spécialisée en data science Standard 1 5
Master 120 en sciences de gestion, à finalité spécialisée en Transformation Digitale de l’Entreprise Standard 1 5
Master 120 en ingénieur de gestion, à finalité spécialisée en Analytics & Digital Business Standard 1 5
Master 120 en sciences de gestion, à finalité didactique Standard 1 5
Master 120 en sciences de gestion, à finalité didactique Standard 2 5
Master 120 en sciences informatiques, à finalité spécialisée en software engineering Standard 2 5
Master 120 en sciences de gestion, à finalité spécialisée en Transformation Digitale de l’Entreprise Standard 2 5
Master 120 en sciences informatiques, à finalité spécialisée en data science Standard 2 5