
The lecture starts with real work: you take one system you are rolling out, or one that is already running badly, and go through nine checks that decide whether people will use it.
This course is built from six disciplines: operations management, system selection, change management, knowledge management, surveys and performance management.
The map of the course
A simple dictionary for reading lectures from other fields as rollout work
Three questions to ask after every lecture
A short self-diagnostic that shows which sections to watch first
Download the Rollout Readiness Check and fill in one line after each lecture.
Why a business needs this function once it passes fifty employees
How it differs from project management
The key areas of responsibility
The typical mistakes and false expectations
End-to-end thinking, and mapping the key processes
Where formalisation is needed and where it does harm
The minimum sufficient regulation
The cost of over-bureaucratising before you automate
Why metrics fail in most companies
Input, output and outcome indicators
Leading against lagging, and who owns each
The operational dashboard
Bottlenecks and system constraints
Queues, downtime and context switching
Quick wins, standardising and simplifying
When automation is genuinely needed, and when it is not
Why teams fail to connect
Cross-functional processes, and reducing friction
Operational meetings and status updates
Weekly, monthly and quarterly rhythms that stay useful
Why order keeps breaking down
Managing change through the process itself
Resistance, sabotage and inertia
Prioritising changes, and knowing when to stabilise against rebuild
Process and workflow systems
Metrics, dashboards and where the data comes from
The cases where a spreadsheet is the correct answer
The typical automation mistakes, and designing the target system
Who ends up owning this work
Treating it as a management role rather than admin
Return on operational management
Building the case, and a personal roadmap
How systems in this space are classified, and how they evolved
Where to look for providers, and an overview of who exists
What to automate first
Writing your selection criteria before you see a demonstration
The types of tracking system, and what separates them
Selection criteria for one specifically
An overview of the popular solutions
How to negotiate with providers and get the maximum discount
Whether to implement the practice first or choose the system first
An overview of the solutions
Continuous feedback functions
From a simple form to an advanced system, and how to roll it out
The basics of online learning delivery
The types of platform, and an overview
How to start
How to integrate the systems with each other successfully
What collaboration tooling actually covers
An overview of the systems
Organising the work inside them
Getting everyone involved, with practical experience
How chatbots evolved, and an overview of solutions
What you can build yourself
Low-budget platforms
Where AI fits into them
What the current capabilities actually are
An overview of existing solutions
Application across the process
Systems with AI built in rather than bolted on
How people usually react to a change
The eight mistakes companies make when implementing one
The consequences of each
What determines success, and Kotter's model
Splitting a large project into smaller ones
The role of managers
The role of leaders, and how it differs
Creating a sense of urgency
Reinforcing the sense that this is necessary
The role of leaders in the introduction
Building the change team
Why the rational case is not enough on its own
Guiding the rider
Motivating the elephant
Simplifying the path
Developing the strategy and the picture of after
Promoting it among the people who have to change
Creating the conditions that make it possible
Achieving quick wins early
Finalising the change rather than letting it drift
Fixing it into the company's culture
A worked model of how a large company does this
What knowledge management is, and why it matters here
Explicit knowledge against tacit knowledge
The main challenges companies hit
Cases from companies that solved it
Capture methods: interviews, surveys, working groups
Structuring it into bases, wikis and ontologies
The tools that hold it
Protecting what should not be public
The ways knowledge moves, and what blocks each
Building a sharing culture
The platforms
Communities of practice, and knowledge leaders
This course contains the use of artificial intelligence.
The system is bought, paid for and configured. Six months later half the department is still keeping the spreadsheet, because it is faster.
Choosing was the easy fifth of the job
You compared providers, sat through the demonstrations, negotiated something off the price and signed. That part went fine. What nobody planned was everything after: the process the system was meant to serve was never written down, so the configuration encodes whatever the person setting it up assumed. That person has since left and no one knows why a field is named the way it is. Nobody ever asked users where it is awkward, so the workarounds spread quietly. And nothing in anyone's objectives says they have to use it, which means the ones who dislike it simply do not.
What this course covers
Forty-one lessons across the whole implementation, not just the purchase. The process first, because automating a broken one only makes it faster: what a process actually is, mapping the ones that matter, where formalisation helps and where it does damage, input against output against outcome measures, bottlenecks and context switching, quick wins, and specifically when a spreadsheet is the correct answer and when automation is genuinely needed. Then the choice: how systems in the category are classified, where providers are found, what to automate first, writing selection criteria before you watch a single demonstration, selection criteria for a tracking system, negotiating with a provider and getting the discount that is actually available, goal and feedback tooling, learning platforms, collaboration tools, chatbots you can build yourself, systems with intelligence built in, and integrating any of it with the rest. Then the rollout: how people react, the eight mistakes companies repeatedly make, Kotter's eight steps, creating urgency, building the change team, the rider-and-elephant model for why a rational case is not enough, vision and quick wins, and fixing the change into the culture rather than letting it drift. Then survival: capturing how the thing works so it outlives whoever configured it, wikis and knowledge bases, retrospectives on what went wrong, and measuring whether anyone reads any of it. Then honesty: designing a survey people answer truthfully, the length at which answers stop being honest, response rates, reading the open answers, and an action plan with interim measurement. Finally the standard: performance agreements, objectives and cascading, check-ins, four ways to evaluate results, the review meeting, and what follows from it.
Why the examples are people-function systems
The system-selection, knowledge, survey and performance blocks were recorded for that audience, and the categories used as examples are tracking, learning and review systems. That is a working example rather than a limit. Selection criteria, provider comparison, discount negotiation, integration, user resistance and adoption measurement behave identically for any category of software. These particular systems make good examples for one reason: almost every company installs them, and they fail more often than most, because unlike an accounting system nobody is forced to use them.
Who is teaching this
I am Mike. I built the people system at Preply as it became a unicorn, and I have worked at Wargaming, iDeals and Alfa-Bank. More than 1.6 million students have enrolled in my courses across 185 countries, and over 150,000 specialists have gone through my programmes. I hold PHRi and SHRM-CP certifications and represent HRCI in more than ten countries.
What is included
Lifetime access to all 41 lessons
Active instructor support in the Q&A section
A Udemy Certificate of Completion
Working material: process mapping, the input-output-outcome model, selection criteria, the provider negotiation approach, integration planning, the eight implementation mistakes, Kotter's steps, the rider-and-elephant model, knowledge capture methods, questionnaire design, and the performance agreement
The four fifths of an implementation that come after the signature
Where to start
Find one spreadsheet in your company that duplicates something a paid system already does. Ask the person keeping it why. That answer is the whole course in one sentence. Enrol now and start today.