Curriculum

This course will provide students with a high-level introduction to the role of digital product management in organizations and why this role is so important to pursue new strategic opportunities, change business models and transform the way people work. At the core of this course is the reality that despite a plethora of investment in innovation, organizations are struggling to translate their digital aspirations into valuable business results. Students will develop a comprehensive understanding of the entire life cycle of a product (from cradle-to-grave), key activities within each phase, and the ability to manage a digital product management lifecycle in a way that aligns the product strategy to the business strategy, incorporates key activities across business functions, scales the product into operation, and thoughtfully plan for the product’s end-of-life.

This course introduces students with best practices in navigating the problem space. Building on the digital value drivers (business, user, technical) introduced in MDPM 800, students will learn best practices in divergent and convergent thinking to create the first iteration of the product strategy: the Digital Product Opportunity (DPO). Students will work in sub-teams to explore each driver in isolation, then work to converge perspectives to clarify the problem. Miro will be used to provide students with a structured approach to exploring the problem from different perspectives. All perspectives will be taught in a learn-by-doing environment. We will begin by defining the core concepts that underlie each perspective and transition into an exploration of the tools and frameworks that can be used to analyze the perspective and desired outcomes. Students will learn about common methods (e.g., digital business models, digital capabilities, jobs-to-be-done, and customer journey mapping) and apply this knowledge to create the Digital Product Opportunity (DPO) that will become the input into the next stages of the digital product management lifecycle.

Emerging technologies are greatly changing the way that computing is performed. People acting in product management roles need to be aware of these technologies, their potentials, and their weaknesses and be able to communicate about them with technical experts (i.e., tech fluency). This course will cover key technologies that are revolutionizing digital products. For example, how Artificial Intelligence (AI) and Machine Learning (ML) are being used in a broad range of products ranging from recommender systems, help systems, through autonomous vehicles. How cloud-based computing provides a new model for delivery of services, where sophisticated code and data reside in the cloud, allowing simpler creation and use of more robust and available products. How Internet of Things (IoT) makes use of sensors and devices in the broader environment, ranging from cameras, microphones, and stress sensors, and uses them to provide services to people without requiring use of traditional computing devices. Specific emerging technologies discussed in this course may evolve year-over-year. Learning about technologies is important, but the primary learning outcome in this course is to provide students with a comprehensive approach for evaluating emerging technologies that is important for making design decisions, assessing product feasibility, and scaling digital products for growth.

In this course, students will learn how to design and build proof-of-concept prototypes within a user-centred design process. Students will be introduced to interaction design as a practice for designing digital products informed by the needs of users, organizations, and technological context. Students will gain hands-on experience using concrete tools for design such as scenarios, task models, and requirements documents and well as low-fidelity prototyping methods including paper prototyping and wireframe tools. The course addresses equity in user interface design, specifically addressing techniques for increasing the accessibility of interactive systems to persons with disabilities.

This course will introduce students to the importance of both linear and systems thinking as knowledge foundations for digital product management. At the macro level, both types of thinking are necessary, but they offer different benefits and challenges. Students will learn how linear thinking is necessary when developing process and task models and systems thinking is important to extend the design of a digital product for a specific context. When both thinking approaches are applied, significant benefits emerge such as increased user adoption rates, improved technical feasibility, cost reduction, and revenue generation. Case studies will be used to demonstrate the unintended consequences that emerge when product teams apply linear practices that overlook a systems-view. The concepts, theories, and tools introduced in this course will be applied to navigating the problem space, however they can also be applied to different phases of the digital product management lifecycle.

This course introduces students to established and novel practices in designing innovation. Building on the notion that innovation value is derived from a collective set of needs that span across market, business, and user perspectives, students will develop critical thinking skills related to design thinking (outside-in), capability analysis (inside-out) as well as divergent and convergent design cycles. As this is a project course, students will develop these skills using a learn-by-doing approach to clearly define the problem and identify the innovation opportunity. The course will begin by defining the core concepts that underlie each perspective and then students will learn about different methods and techniques used to conduct research and analysis. Once the basics have been covered, the course will transition into an exploration of the tools and frameworks (e.g., jobs-to-be-done, customer journey mapping) that can be used to analyze each perspective as well as how to frame perspectives to identify the opportunity for innovation. Brainstorming and creativity (e.g., Miro) as well as artificial intelligence (e.g., GenAI) tools will be used to provide students with a structured yet modern approach to designing innovation.

This course introduces the notion of software architecture as a core concept that serves as the blueprint for implementing a digital product. The course shows how software architectures can fit within existing legacy (technical and business) systems and business processes, while also leveraging emerging technologies. Architectural trade-off analysis is taught as a key tool for digital product managers to allow them to assess how development choices impact a product’s non-functional requirements. All digital product managers need to have a high-level understanding of software architecture in order to cooperate with software and system architects, to make informed product design decisions, and to tailor products and implementation approaches to specific business and user needs. Course topics include: Software Architecture, Architecture Styles, Architecture Recovery, Big Data, and Architecture Trade-off Analysis.

Usability has become critical to distinguishing products in the marketplace. This course teaches the fundamentals of product usability, including models of how people interact with systems, design techniques, and evaluation techniques. An emerging area within usability is persuasion, which is used to nudge people to specific behaviours, as diverse as stopping smoking, filing expense reports on time, or returning to an e-commerce website. Gamification is a technique supporting persuasion where game-like elements are used to increase engagement with an interactive product. The course covers the psychology of persuasion, specific gamification techniques, and gamification case studies.

This course examines the implications of digital innovation on people, business and society by exploring a number of examples of how innovative products and services can create harm without due ethical considerations. As innovators, it is imperative that both the benefits and limitations of new innovation be explored. Throughout this course, students will be required to identify and evaluate the ethical underpinnings of design choices, formulate ethical design principles and learn to effectively embed ethical implications into the innovation management lifecycle. Furthermore, while other courses prepare you to unleash your creativity and the possibilities of digital technology in coming up with great digital innovations, this course calls for a reflection on the silent but salient essence of ethical considerations and implications of your design choices. In other words, it is aimed to make you pause and ponder simple but profound questions such as — because we can, should we?

This course equips learners with the strategic mindset and design tools to architect digital innovation by integrating linear and systems thinking approaches. While linear thinking emphasizes goal-oriented planning, sequencing, and efficiency, systems thinking enables a holistic understanding of interdependencies, feedback loops, and emergent behavior within complex digital environments. Students will explore how to balance structured problem-solving with adaptive innovation across the innovation lifecycle — from ideation and development to implementation and scale. The course applies both modes of thinking to challenges such as platform design, user experience innovation, and change management. Students will explore case studies that demonstrate how when both thinking approaches are applied, significant benefits emerge such as increased user adoption rates, improved technical feasibility, cost reduction, and revenue generation. Artificial intelligence tools will be used to develop systems (context) maps to provide students with a structured yet modern approach to architecting innovative solutions.

Security breaches take place almost on a daily basis, threatening the correct operation and privacy of digital products. This course covers the fundamentals and best practices for building and maintaining secure software systems including an overview of other important non-functional challenges regarding dependable software solutions. It will first introduce the basic concepts of dependable and secure computing, general methods and tools for quality software systems, threats to dependability and security, their attributes, and general techniques to achieve these attributes. Students will learn how to develop a security plan cataloguing threats and assets and techniques for threat mitigation. Overall, the course will provide comprehensive knowledge about security engineering principles that are applied in the design and implementation of security-aware software systems.

This course is intended to introduce students to the types of decisions that entrepreneurs and corporate innovators are faced with as they launch their new product or service. Core to this course is the notion of demonstrating proof beyond promise, where a successful launch is increasingly tied to growth, scalability, and defensibility metrics. Specific attention will be paid to developing an understanding of how customer/user market characteristics shift dramatically between the introduction and growth phases, and the implications of this shift for both marketing and sales strategies and tactics. Students will also learn to understand and appreciate the critical role of sales in launching innovation and scaling for growth. Specific topics include managing the interplay between the marketing and selling functions, setting and evaluating sales strategy, managing the day-to-day sales functions including recruitment, training, compensation and performance management as well as the evaluation and control of professional selling methodologies and activities.

This course will expose students to the main kinds of analytical techniques that can help improve their capacity in making decisions based on data. Such techniques are of two major kinds: predictive modeling techniques (which use data to predict what is otherwise unknown), and prescriptive modeling techniques (which use data, including the predictions made using data, to advise on the best course of action). This course will give an introductory understanding of both kinds of techniques, including models for predicting quantities (such as regressions), models for predicting events (such as classification and regression tree, random forests, and the likes), decision tree and Monte Carlo simulation models, and optimization models (linear programming). The focus will be made not on the technical issues, but rather on the conceptual understanding and the ability to implement these models using the examples of software and case studies provided during the course.

This course introduces students to the process of gathering and transforming user-level data into insights that reveal how customers interact with the digital product. Students will learn how product analytics enables organizations to track and analyze its users’ journeys from user activation through all other phases of use. Product analytics is a powerful way to understand what makes users engage with the product, enable product improvements, and evaluate the benefit the digital product provides to customers and other business performance indicators. Students will learn how to capture trace data (e.g., average time users spend on specific features, how many times users return in a day/week), build a simple analytical model, and use insights to improve user experiences (UX).

In this course, students apply the fundamentals and best practices in human-centered, accessible, and inclusive design to translate product design into an operational solution that is highly usable across a diverse population. Students will learn techniques for advanced design of digital products’ user interface and evaluation techniques suitable for high-fidelity prototypes. Theory and concepts introduced in MDPM-826 will be applied in this course.

This course will integrate course-level learning objectives related to the product development phases of discovery and design. Student groups will complete work associated with two experiential learning milestones. Grading for each milestone will be pass/fail as all learning outcomes are evaluated in associated co-deliverables from other courses in the program. Where students are expected to apply knowledge beyond the scope of existing courses, additional concepts, theories, and practices will be introduced in this course. Sessions will also provide students with an overview for each milestone and a formal review completed by practicum faculty advisors. Required outputs of this course include the Digital Product Opportunity, Product Vision, and the first iteration of a digital product prototype. This is a project course running through the first half of the degree program.

This course will integrate course-level learning objectives related to the product development phases of build, scale, operate, and exit. Student groups will complete work associated with two experiential learning milestones. Grading for each milestone will be pass/fail as all learning outcomes are evaluated in associated co-deliverables from other courses in the program. Where students are expected to apply knowledge beyond the scope of existing courses, additional concepts, theories, and practices will be introduced in this course. Sessions will also provide students with an overview for each milestone and a formal review completed by practicum faculty advisors. Required outputs of this course include the technical feasibility report, product marketing plan, digital product roadmap and two iterations of the digital product prototype developed in MDPM 900. This is a project course running through the second half of the degree program. It follows the MDPM-900 project course, in which students discover, design, and build a digital product prototype.