Digital Transformation
Digital transformation for managers in Canada, with examples from Canadian retail, health care and manufacturing and the rules of PIPEDA and Quebec's Law 25: what digital transformation is and why programs disappoint, with maturity assessment and the productivity J-curve, digital strategy and business model innovation with subscription and service economics, platforms, ecosystems and network effects with two-sided pricing and governance, data as a strategic asset with governance, quality, lakehouse architecture and privacy, analytics and controlled experiments with prediction thresholds set by the cost of errors, machine learning and generative AI with retrieval-augmented generation, AI business cases and AI governance, automation and the future of work at the level of tasks, cloud decisions, the shared responsibility model and cybersecurity oversight, omnichannel customer experience and the inventory accuracy it depends on, technology business cases with staged investment, agile delivery and product management, and leading adoption, change and digital culture, ending in a capstone digital roadmap for Cedarline Outdoor, with runnable Python examples.
MBA-603 3 credits 12 lessons · 4 h 29 min ▶ Video lessons coming soon
Offered by HSM University · MBA Core
This is the Canadian version of this course. See the American version.
What you'll learn
- Distinguish digitization, digitalization and digital transformation, assess an organization's digital maturity and explain why transformation programs often disappoint.
- Connect digital initiatives to business strategy and evaluate new digital business models, such as subscriptions, services and retail media, with simple unit economics.
- Analyse platforms and ecosystems using network effects, two-sided pricing, multi-homing and governance, and judge when an established firm should build a platform.
- Treat data as a strategic asset by assigning ownership, measuring and improving quality, choosing a fitting architecture and respecting privacy law and consent.
- Use analytics to change decisions, design and interpret controlled experiments, and set prediction thresholds from the business costs of errors.
- Explain how machine learning and generative AI work at a manager's level, identify valuable uses, build an AI business case and apply AI governance and regulation.
- Analyse the effects of automation and AI on tasks and roles, decide what to automate or augment, and plan workforce transitions responsibly.
- Make cloud decisions using total cost and capability, apply the shared responsibility model, and oversee cybersecurity and digital risk in business terms.
- Design omnichannel customer experiences, evaluate fulfilment options and the inventory accuracy they depend on, and align measures and incentives across channels.
- Build honest technology business cases, value staged investments, choose between building and buying, and apply agile delivery and product management.
- Lead technology adoption and change, diagnose stalled rollouts, and build a digital culture, skills and governance for transformation.
- Integrate the course into a board-ready digital roadmap with a diagnosis, guiding policy, sequenced initiatives, economics, owners, risks and measures.
Course content
12 lessons · 4 h 29 min total · final exam
- 1 What digital transformation is: technology, strategy and organization 23 min · quiz
- 2 Digital strategy and business model innovation 23 min · quiz
- 3 Platforms, ecosystems and network effects 23 min · quiz
- 4 Data as a strategic asset: governance, quality and architecture 22 min · quiz
- 5 Analytics and data-driven decision making 22 min · quiz
- 6 Artificial intelligence and generative AI in business 24 min · quiz
- 7 Automation and the future of work 21 min · quiz
- 8 Cloud, cybersecurity and digital risk 23 min · quiz
- 9 Digital customer experience and omnichannel 21 min · quiz
- 10 Technology investment: business cases, agile delivery and product management 22 min · quiz
- 11 Leading technology change and digital culture 22 min · quiz
- 12 Capstone: Cedarline's digital roadmap 23 min · quiz
- E Final exam 20 questions
Requirements
Recommended background. You can start any course at any time.
Description
Digital transformation for managers in Canada, with examples from Canadian retail, health care and manufacturing and the rules of PIPEDA and Quebec's Law 25: what digital transformation is and why programs disappoint, with maturity assessment and the productivity J-curve, digital strategy and business model innovation with subscription and service economics, platforms, ecosystems and network effects with two-sided pricing and governance, data as a strategic asset with governance, quality, lakehouse architecture and privacy, analytics and controlled experiments with prediction thresholds set by the cost of errors, machine learning and generative AI with retrieval-augmented generation, AI business cases and AI governance, automation and the future of work at the level of tasks, cloud decisions, the shared responsibility model and cybersecurity oversight, omnichannel customer experience and the inventory accuracy it depends on, technology business cases with staged investment, agile delivery and product management, and leading adoption, change and digital culture, ending in a capstone digital roadmap for Cedarline Outdoor, with runnable Python examples.