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Online executive education, designed in Montreal

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Mini-MBA Innovation Management

Categories: English, Gestion, Mini-MBA

About Course

Program overview

Online, self-paced · 37 hours · 11 modules

Designed for managers who have to turn ideas into results, this 37-hour online program covers the full innovation cycle, from customer discovery to financing and scaling. It is grounded in Canadian and American realities in 2026 (agentic AI, the SR&ED reform, new data rules) and draws on real cases, plus a running case followed from one module to the next. Each module ends with a deliverable applied to your own organization. You leave with a 90-day roadmap, ready to present to your leadership team.

What Will You Learn?

  • Diagnose your organization's innovation maturity and find what is really holding it back
  • Build and manage a stage-funded innovation portfolio with clear stopping criteria
  • Run customer interviews that produce facts, and test your assumptions at low cost
  • Redesign workflows with generative and agentic AI while keeping the risks under control
  • Build a business model and a value-based pricing strategy
  • Mobilize partners, public programs and tax credits (SR&ED, Québec's CRIC)
  • Present a convincing investment case and measure what innovation actually delivers

Course Content

Module 1 : Innovation in 2026: what managers really need to steer
By the end of this module, you will be able to: tell the difference between innovation activity and innovation results; position your organization against the four forces reshaping innovation in Canada and the United States in 2026; produce a maturity diagnostic you can defend in front of your leadership team.

  • 1.1 An uncomfortable starting point
  • 1.2 A definition that helps you decide
  • 1.3 Four forces changing the game in 2026
  • 1.4 Innovation theatre
  • 1.5 Case study: BlackBerry, reading a failure through a manager’s eyes
  • 1.6 Case study: Shopify and the AI memo
  • 1.7 Composite case: Usinage Laurentien
  • 1.8 Tool: the innovation maturity diagnostic
  • 1.9 Module deliverable
  • 1.10 Key takeaways

Module 2 : Innovation strategy and portfolio: what to bet on, with what money, for how long
By the end of this module, you will be able to: write an innovation intent that genuinely helps sort projects; map your current projects by level of ambition and spot the imbalances; propose stage-based funding, with stopping criteria set before any money is spent.

Module 3 : Finding the problems worth solving
This module is different from the first two. It is shorter on reading and longer on practice: you are going to leave your office (or pick up the phone) and talk to customers. Half of the planned time is devoted to that. If you do not do the interviews, you will have read a module, but you will not have taken it. By the end of this module, you will be able to: tell a real problem apart from a solution dressed up as a need; run a customer interview that produces facts rather than polite opinions; synthesize several interviews to bring out the opportunities worth investing in.

Module 4 : Experimenting and deciding under uncertainty
By the end of this module, you will be able to: identify the assumptions a project really depends on, and choose which ones to test first; design a test that measures behaviour, not opinion; decide whether to persevere, pivot or stop, based on criteria set in advance.

Module 5 : Generative and agentic AI: innovating with it, innovating on it
This module has two parts. The first looks at AI as a lever: how it changes the way your organization works. The second looks at AI as the object of innovation: the new offers it makes possible for your customers. The two call for different decisions, and many organizations mix them up. By the end of this module, you will be able to: break down a workflow and decide, task by task, how much autonomy to give AI; explain why most agent projects never get past the pilot stage, and what sets apart the ones that succeed; position your projects within the Canadian and American regulatory framework as it stands in September 2026; shape an AI-based offer that cannot be copied in two weeks.

Module 6 : Business models, pricing and monetization
By the end of this module, you will be able to: describe an innovation’s business model, separating value created from value captured; calculate the unit economics of an offer and spot the figure that makes it fragile; build a pricing hypothesis from the value to the customer, then test it.

Module 7 : Open innovation and North American ecosystems
By the end of this module, you will be able to: choose between building, partnering, buying or acquiring, depending on the cost, speed and control you are after; identify the players your innovation’s adoption depends on, even when they are not your customers; set up a partnership with a start-up, a university or a college without bureaucracy killing it before it starts; use the main Canadian and American public programs that fund collaboration.

Module 8 : Financing innovation: tax credits, public programs and the business case
By the end of this module, you will be able to: identify the funding sources for an innovation stage, distinguishing money that dilutes from money that does not; assess whether a project can qualify for SR&ED credits, and estimate their order of magnitude after the 2026 reform; understand what is changing in the United States and in Quebec for R&D spending; present an investment case that a chief financial officer will take seriously. A word before we start: this module gives management benchmarks, not tax advice. The rules are technical and change often. Any estimate must be validated by a tax specialist before it goes into a budget.

Module 9 : Organization, culture and leadership for innovation
This is the most uncomfortable module in the program, because it is about you. The previous modules gave you methods. This one explains why they often fail in real organizations, even when everyone knows them. By the end of this module, you will be able to: identify the mechanisms that kill good ideas in your organization, beyond the official explanations; choose where to place innovation in the structure, depending on how much it conflicts with existing activities; distinguish a culture that tolerates failure from one that tolerates incompetence; change three leadership behaviours that, without your knowing it, send signals that work against innovation.

Module 10 : Measure, govern, protect
By the end of this module, you will be able to: build an innovation dashboard of eight indicators that measures results, not just activity; clarify who decides what in the governance of innovation and AI; choose the right way to protect a knowledge asset: patent, secret, contract or speed; avoid leaks of confidential data through AI tools.

Module 11 : Capstone project: your 90-day roadmap
This last module brings almost no new content. Its purpose is to turn ten separate deliverables into a single document you can present to your leadership team and, above all, put into practice. This is often where the difference lies between a program you attended and a program that changed something. By the end of this module, you will have: redone the Module 1 maturity diagnostic, and measured what has changed in your reading of the organization; chosen a precise, measurable 90-day objective; built three initiatives at most, with their milestones, owners and stopping criteria; prepared what you are asking of leadership, and the three things you will do on Monday.

Assessment