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The SAS Analytics Simulation Game, called Cortex, turns predictive modeling into a business decision exercise. Learners work with data, choose whom to contact or serve, account for costs and consequences, and compare results with other players. SAS developed Cortex with HEC Montréal for classroom and business use. No verifiable recording or transcript for the specific DSC Podcast episode named in the original title is available, so this article does not attribute comments, speakers or conclusions to that recording.
What Cortex is
Cortex is an online simulation game from SAS, developed in collaboration with HEC Montréal. Its purpose is to let participants apply predictive-modeling methods inside a defined business scenario rather than study models only as abstract techniques.
The game combines a case study, a dataset, SAS software access, instructional resources and, in some implementations, a leaderboard. Players make decisions, observe the commercial or operational implications, and can compare their outcomes with classmates or teammates.
How the simulation turns modeling into a decision
Fundraising scenario
In the fundraising exercise, a learner acts for a nonprofit. The task is to use available data and predictive models to decide which potential donors to contact while considering the cost of each contact. The 2019 SAS conference paper describing the design uses a simulated population of one million potential charity members; that figure describes the game dataset, not a measured learning result.
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Credit-risk scenario
The credit-risk version centers on loan-approval decisions. Participants apply predictive analysis to determine how risk information should influence lending choices.
Customer-retention scenario
The customer-retention version asks players to identify customers to invite to a loyalty event, with the aim of reducing churn. The scenarios make model output consequential: a prediction must lead to a resource-allocation decision.
Why the game format can support learning
Practice with a concrete objective
Cortex gives learners a defined goal, data and constraints. Instead of stopping at model construction, they must connect a prediction to an action such as contacting a donor, approving a loan or targeting a customer.
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Feedback through outcomes and comparison
The fundraising design includes contact costs and a live scoreboard. A leaderboard can show how different strategies perform, creating an immediate reason to inspect assumptions, revise a model or reconsider a targeting rule.
Adjustable scaffolding
The 2019 design account says instructors could provide prebuilt modeling diagrams so beginners could obtain predictions quickly and spend more time exploring data and models. More advanced groups can work further into model building or adjustment.
Collaboration and competition
SAS describes Cortex for individual, team and group activities. Friendly competition can make trade-offs visible, while discussion among participants exposes different interpretations of the same data.
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These are design mechanisms and vendor-described uses. SAS’s published descriptions do not report a quantified evaluation showing that Cortex produces a particular gain in grades, retention or predictive-modeling skill, and they do not establish that it outperforms lectures or another teaching method.
Where educators and business teams can use it
Academic courses
SAS presents Cortex as a component of business-analytics teaching. Instructors receive instructional materials, and students use the associated software while working through the game. A class can begin with a demonstration, use prepared models for rapid orientation, and then move toward independent exploration.
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Business workshops
SAS describes formats that can run for a single day or across several weeks, either in person or remotely, with difficulty adjusted to the team’s skill level. Those descriptions support Cortex as a workshop or team-learning format, but they are vendor claims about intended use rather than independent evidence of business impact.
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What an implementation needs
- A selected scenario and a clear decision objective.
- Access to the required SAS software or the SAS-and-Python arrangement offered for the chosen edition.
- Time for orientation, analysis, decisions and debriefing.
- An instructor or facilitator who can connect model performance with business costs, risks and ethical considerations.
- A plan for using the leaderboard appropriately: as feedback and discussion material, not as a substitute for understanding the analysis.
The strongest instructional value comes from the debrief. Learners should explain why they targeted particular records, how costs changed the decision, what assumptions their model made and how a different threshold might change results.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Cortex access variants and regional pricing
A SAS Taiwan academic page lists the following options. The amounts are page-specific, geographically scoped offers and may change; verify current terms, software support and licensing with SAS before purchase.
| Option listed by SAS Taiwan | Access or requirement | Scenario availability | Listed price |
|---|---|---|---|
| Enterprise Miner | 20 hours of cloud software access | As specified on the regional page | $100 |
| Cortex Desktop | Requires an existing Enterprise Miner installation | As specified on the regional page | $50 |
| SAS and Python | Uses the stated SAS-and-Python setup | As specified on the regional page | $35 |
These figures are not a universal SAS price list, and the SAS Taiwan page does not establish that they remain current outside that regional page.
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How to compare Cortex with another teaching approach
The documented materials support comparison by design, not by measured outcomes. Ask:
- Audience: Is the activity for an academic class, an executive workshop or a mixed-skill team?
- Scenario fit: Does fundraising, credit risk or retention resemble the decisions learners need to understand?
- Scaffolding: Will participants use prebuilt diagrams, adjust existing models or build models themselves?
- Delivery: Is a one-day intensive or a multi-week sequence more suitable?
- Access: Which software, cloud hours and installation requirements apply?
- Assessment: How will the facilitator judge reasoning, not just leaderboard position?
No published source establishes that Cortex is superior to lectures, conventional case studies or another simulation. Its defensible distinction is that it combines predictive modeling with an explicit, cost-sensitive decision and rapid feedback.
What is known—and not known—about learning results
SAS’s product and course materials describe engagement, practice and instructional flexibility, while a SAS-hosted testimonial calls the integrated case study, data, models and platform an excellent teaching tool. Those statements are promotional or testimonial evidence. The cited SAS product, course and testimonial materials do not provide a named quantitative study of Cortex learning outcomes, a controlled comparison or a validated effect size.
For that reason, an accurate description is that Cortex is designed to support experiential learning through applied prediction and decision-making—not that it has been proven to deliver a specific improvement.
Bottom line for prospective adopters
Cortex is a credible simulation format for teaching the link between predictive models and real allocation choices. It is most useful when the scenario matches the audience, the software access is confirmed, and a facilitator turns scores and model outputs into a structured discussion. Treat SAS’s format and benefit statements as vendor descriptions, check regional licensing directly, and avoid presenting the unverified DSC Podcast as evidence about the game.
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