Spring 2027

Operations Analytics

Operations Analytics applies descriptive, predictive, and prescriptive methods to real industry data and case problems in operations and supply chains.

offering recorded3 credits
Recorded instructors · Spring 2027 Greg DeCroix3.9/5

Summary

1 / 6

Past student reviews · Greg DeCroix

Assignments were rated as fair, but the workload involved many group projects, which was a notable aspect of the course structure.

What you’ll be able to do

  • Recognize patterns and relationships that provide insights into business problems.

  • Choose and apply data-based forecasting methods, and evaluate the performance of such methods to inform operations decisions.

  • Engineer spreadsheet models for decision-support leveraging optimization and simulation tools.

  • Apply critical thinking to complex real-world problems by formulating appropriate questions, making implementable assumptions, and interpreting results of analyses.

  • Work effectively in teams on analytics projects.

  • Communicate analytics and insights through presentations and written reports.

  • Develop basic skills using Tableau visualization software and the statistical software R.

  • Develop intermediate skills using Excel.

Source: UW Guide

Grade history

↗
average GPA
letter grades
A
AB
B
BC
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All recorded terms · compare terms & instructors

Prerequisites

Course map

OTM 300 and (GEN BUS 306,ECON 310,MATH 331,MATH/​STAT 309, 409, or 431), or declared in undergraduate Business Exchange program

OTM 453

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Spring 2027
Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 5.00/5 from 4 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

For this course: 5.0/5 raw quality · 3.0/5 difficulty · 1 reviews

RMP profile ↗ · All captured review dates; profile matched by name.

Past student reviews · Greg DeCroix

Greg DeCroix was described as kind and compassionate, with fair assignments that the reviewer enjoyed. The course featured many group projects, which the student noted as a key aspect of the workload. The reviewer ultimately loved the class and found the experience positive.

Recent recorded grades — Spring 2024: 3.68 GPA, 90.9% A/AB (n=66 letter grades); Spring 2025: 3.51 GPA, 84.6% A/AB (n=78 letter grades); Spring 2026: 3.52 GPA, 79.2% A/AB (n=53 letter grades).

Historical instructors & teaching patterns

GREGORY DECROIX is recorded teaching in Spring 2023, Spring 2024, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 450
LEC 002Classroom Instruction0 / 450

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records
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Student experience

the class

Past student reviews · Greg DeCroix

Students found the class enjoyable under Greg DeCroix, who was described as kind and compassionate. The course featured fair assignments that students genuinely liked.

Recent recorded grades — Spring 2024: 3.68 GPA, 90.9% A/AB (n=66 letter grades); Spring 2025: 3.51 GPA, 84.6% A/AB (n=78 letter grades); Spring 2026: 3.52 GPA, 79.2% A/AB (n=53 letter grades).

difficulty & workload

Past student reviews · Greg DeCroix

Assignments were rated as fair, but the workload involved many group projects, which was a notable aspect of the course structure.

Past student reviews · Greg DeCroix

The student experienced a positive environment, even noting a personal touch when they saw the professor's dog, Mabel, during the course.

Topics

  • Descriptive, predictive, and prescriptive analytics.
  • Case-based problem solving in business operations.
  • Forecasting methods for operations decisions.
  • Spreadsheet modeling with optimization and simulation.

Skills

  • Apply and evaluate data-based forecasting methods for operations decisions.
  • Build spreadsheet decision-support models using optimization and simulation.
  • Use Tableau and R for data visualization and analysis.
  • Apply intermediate Excel skills to analytics tasks.
  • Present and write up analytics findings.

Grades

Latest available · Spring 2026— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Spring 2026 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1280 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

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Selected offering source records
OTM 453 · Spring 2027

Operations Analytics

Recorded 2026-10-14
Raw records 
[
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:238:025940",
    "course_id": "OTM 453",
    "course_uid": "course_98d3b88fef60209ab5b8bac5",
    "term_id": "1274",
    "source_course_id": "025940",
    "source_subject_id": "238",
    "title": "Operations Analytics",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Not Applicable"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "b06944d2f144582ffd121bab7cfb8ee41bba9dad37de17518f807470bb69860a",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}