Market-entry decision
Module 4 · Entry strategy
Which decision it covers, the kind of reasoning it uses, and whether learners have to master it.
Name
Market-entry decision
Purpose
Choose how to enter a new market: wholly owned, joint venture or licensing.
Framework Type
Decision Tree
Nature
Qualitative
Requirement
Core
What the assistant has to know about the learner's case, asked outright or picked up from the conversation, and what the learner leaves with.
Outputs: Recommended entry mode, Rationale
The questions you'd ask, in your order. The assistant takes the learner through them one at a time.
What it builds on, what it leads to, and the course files it draws from, so a learner meets your frameworks in the order you teach them.
Builds On
Market attractiveness
Leads To
Competitive response
Alternatives
None
Files
The situations it's meant for, and the ones where it doesn't hold.
When to Use: choosing how a firm enters a market it doesn't operate in yet.
Invalid When: the firm already sells there and is deciding how to grow.
Sophia drafts frameworks like this from your materials. You review, edit and approve every one.
Name it, describe it, and paste your syllabus. Your modules come straight from the syllabus.
Add PDFs, Markdown, text and images to each module, mark each file Required or Optional, then sync.
Press Update frameworks and Sophia, SLAN's co-pilot, reads your modules and proposes frameworks: the decisions, criteria and steps you teach. Nothing changes until you review.
3 of 4 modules read · 2 ways of deciding so far.
Each framework arrives as Pending review. Edit it, decline it, or approve it. Every framework records the documents it came from.
Choose Single stage for Q&A and coaching, or Multi stage for lessons and case walkthroughs. Link frameworks to each stage, preview it, then deploy.
Create a cohort and set it to Private, Registration Code, or Public. Learners join with the code, or you add them by email.
Start with context
The learner picks their course's assistant and describes what they're working on. Nudge starts by gathering context.
Work each stage
Decision checks and structured questions at every stage, held to the criteria you set for when a stage is done.
Reach a decision
Finish with a recommendation, plan, or checklist the learner can defend, because they built it step by step.
Generative AI executive programme, first three pilot cohorts.
“Half the [in-class exercise] debrief used to be me answering questions they should have already worked through. Now, the conversation focuses on what is important.”
Your expertise stays yours. You keep the IP, nothing goes live without your approval, and access is scoped per course, assistant and cohort.
We'll walk through course creation, framework extraction, assistant building and cohort access, using your materials.