Barry Render and Chuck Munson invite you to a special session at DSI-Orlando Monday, Nov. 24th at 10am in Magnolia 10. Here is the title: “An Exciting New Way to Teach (and Learn) Operations Management.”
To help you start the day, we will be serving fresh Krispy Kreme donuts and coffee in the session room. Or stop by the Pearson booth to say hello.
We know our students need to think critically in an AI age to be productive and engaged future employees. One solution, writes Faculty Focus (July 9, 2025), to the triple challenge of fostering critical thinking, meaningful learning, and academic integrity is to double down on transparency. We can emphasize the why we want responsible AI use: why we want students to use their own cognitive abilities for some tasks, why using AI could be helpful at times, and why we’ve crafted AI-integrated assignments in the ways we have.
Here are five steps to update assignments in the AI age:
Step 1: Take a critical look at your current syllabus. If AI can easily complete a task (try running your instructions through ChatGPT to find out), maybe it’s no longer a relevant measure of authentic learning. Add new instructional practices (like modelling AI use) and new components of the assignments you update or keep.
Step 2: Consider whether and how students should use AI on the assignments. Students want to know exactly what is appropriate for AI use in your class. A helpful tool for this process is the 5-level AI Assessment Scale (AIAS). The levels range from No AI, AI Planning, AI Collaboration, Full AI, and AI Exploration. Each one identifies and sanctions different ways students can use AI in appropriate and meaningful ways to support their learning.
Step 3: Discuss and model your expectations. Students are not sure what is acceptable in this current moment. What better way to help them feel confident while developing the AI skills they need than modelling what you’re looking for? Take class time or record a video for your online class to teach your students what you expect them to do with AI for each assignment, what not to do, and what you’ll be looking for in their finished product.
Step 4: Ask students to disclose their AI use. One approach is to use the AI Disclosure (AID) framework to document how students used AI, or add an appendix to each assignment, or add comments or footnotes to make transparent what they wrote and what AI wrote.
Step 5: If you suspect inappropriate use of AI, don’t accuse students of cheating. Instead, have a conversation with them. A primary goal of the AIAS is to facilitate discussions about AI use.
As I pointed out in a recent blog, our author team can help. We have developed AI exercises for each chapter of the new 15th edition.
Prof. Andrew Stapleton, at U. Wisconsin-La Crosse, provides another interesting exercise to liven up your OM class.
The Fibonacci sequence, introduced by mathematician Leonardo Fibonacci from Pisa, Italy in the 12th century, is a number sequence where each term is the sum of the preceding ones. A typical Fibonacci sequences looks like: 1, 1, 2, 3, 5, 8, 13, 21, 34, and so on. While this is the most well-known version, Fibonacci numbers can begin with any two numbers on the number line as long as they follow the same pattern of addition.
The sequence is closely related to the Golden Ratio, a concept that appears frequently in nature (e.g., in the spiral pattern of shells or of sunflowers) and art (e.g., proportions in Renaissance paintings).
Interestingly, the Fibonacci sequence also has practical applications in Operations and Supply Chain Management. It can be applied in areas such as supply chain network design, forecasting inventory fluctuations, resource allocation, and even in facility layout optimization.
Fun Math Trick using Fibonacci Sequence
Here is an engaging way to explore Fibonacci numbers with your students:
1. Have a student pick any two numbers, say 5 and 4.
2. Add the numbers together (5+4=9).
3. Now, take the second and third numbers (4+9=13)
4. Continue the process for ten steps and calculate the sum.
For example, start with 5 and 4. These yields: 5, 4, 9, 13, 22, 35, 57, 92, 149, 241.
Now calculate the sum of the sequence. The sum is 627.
How to Predict the Sum:
Before calculating, you can impress your students with a neat trick! Here’s how:
Instead of adding all of the numbers manually, look at the fourth number from the bottom of the list. In this case, it is 57.
Multiply the number by 11.
57 x 11 = 627 – this gives you the total sum without having to add them up.
This works because the Fibonacci sequences follow a predictable pattern:
This is what the list of numbers will be:
a
b
a + b
a + 2b
2a + 3b
3a + 5b
5a + 8b
8a + 13b
13a + 21b
21a + 34b
The sum is 55a + 88b, which is 11 times the seventh number. Since multiplying by 11 is a relatively simple calculation, this creates a fun and useful math trick to amaze your students and connect math concepts to OM.
Prof. Andrew Stapleton teaches OM at U. Wisconsin-LaCrosse
Many of us have experienced the anxiety some of our students feel whenever we teach OM techniques. I have found a very effective manner to alleviate it by beginning my lectures with Math Magic.
First, start off the semester with the Phone Number. Tell your students to: (1) Grab a calculator; (2) Key in the first three digits of their phone number (NOT the area code); (3) Multiply by 80; (4) Add 1; (5) Multiply by 250; (6) Add the last four digits of the phone number; (7) Add the last four digits of their phone number again; (8) Subtract 250; (9) Divide by 2. Recognize the number?
Here is why it works:
X = first three digits of your phone number
Y = last four digits of your phone number = [250(80x+1) + (2y-250)]/2 = [20000x + 250 +2y -250]/2 = [20000x + 2y]/2 = 1000x + y = your phone number (this trick doesn’t work if the first digit of the last four is a zero).
Hers is another one: The Rope Around the World. Imagine an un-stretchable rope wrapped completely around the Earth at the equator. Imagine the Earth is as smooth as a cue ball. Here is the question: If you lift that rope exactly one foot above the earth’s surface (ignoring gravity), going all the way around the planet, how much extra rope will you need? The answer is amazing. Students may think they need to Google the diameter of the Earth to figure this one out. Surprisingly, you don’t need to know the Earth’s diameter or radius. You only need to know the formula for the circumference of a circle, i.e., Circumference = 2πr, where the value of π is approximately 3.14 and r stands for the radius.
Answer: You realize you can plug in that extra foot into the circumference formula. When the rope was wrapped around the Earth at the surface, you just have 2πr. When you add in the extra foot, it extends the radius of the Earth by one foot, so you now have 2π(r+1). If you want to find out the difference between the lengths of the two ropes, you subtract the shorter rope on the Earth’s surface from the longer rope suspended one foot above the Earth. 2π(r+1) – 2πr or 2πr + 2π – 2πr = 2π. The two circumferences in the equation cancel out, which leaves just the 2π. Really? It’s true! The rope that is suspended a foot higher all the way around our planet only needs to be 2π or 6.28 feet longer than the rope lying flat on the Earth’s surface.
Challenges like these take help take students’ minds off anxiety they may have felt when we go over a new OM model, making them more receptive to learning a new technique.
In the latest podcast, Barry Render, coauthor of the #1 Operations Management textbook on the market, interviews Dr. Andy Johnson, who teaches Operations Management and Supply Chain to over 1,000 students a semester at University of Central Florida. Andy and Barry discuss the unique way UCF’s course is set up, and the OM Simulations the course is centered around, which bring an essential real world, engaging hands-on element to the course.
Did you know our podcast is now available on Apple podcasts? Just go to your Apple podcasts app, search “Heizer Render OM Podcast,” and subscribe to get all our podcasts on your mobile device as soon as they come out!
A Word document of this podcast will download by clicking the word Transcript above. Instructors, assignable auto-graded exercises using this podcast are available in MyLab OM. See our earlier blog post with a recording of author and user Chuck Munson to learn how to find these, or contact your Pearson rep to learn more! https://www.pearson.com/en-us/help-and-support/contact-us/find-a-rep.html
Prof. Howard Weiss’s suggestions may help you teach your OM course this semester.
As the developer of POM for Windows and Excel OM for the Heizer/Render/Munson text, I am naturally biased about the use of software in an OM class. In
my opinion, students in an OM course, as opposed to an Operations Research course, should not be bogged down in the mechanics of computation but rather should understand the model concepts, inputs and outputs. There are four categories of problems that are strong candidates for assigning students to use POM, Excel OM or Excel.
Problems with a large data set There is no reason to ask students to solve PERT/CPM models with a large number of activities by hand. It makes much more sense to have the students enter the data and solve the problem using software, and then stress the concepts such as slack or crashing. In forecasting, students should understand the meaning and use of the trend and the error measures rather than spending time computing the intercept and slope. For control charts, if a student has computed results for 5 samples by hand does it really make sense to ask the student to compute the results by hand for 30 samples rather than using software to perform the computations and instead ask the student about his or her conclusions. There are many more examples of topics that include numerous computations – factor rating, center of gravity, assembly line balancing, ABC analysis, MRP, Lot-sizing and one machine sequencing come to mind. (Also, for models with much data, students should not spend a great deal of time entering data. It is very easy to copy and paste the data tables from MyOMLab to the software).
Iterative Models The discussion of LP, transportation, assignment and 2 machine scheduling, should focus on the formulation of the problems, the inputs, the goals and the interpretation of the results.
Models with multiple methods Some models have more than one approach. It is useful for the students to compare the results of these different methods without having to try every method by hand themselves. Obvious models are time- series analysis, assembly line balancing, aggregate planning and one-machine scheduling.
Models for which the software goes a step further than the text. In a few cases the software presents methods or results that are not part of the textbook. In one machine scheduling, Moore’s method is available to minimize the number of late jobs. Wagner-Whitin is included in the software for lot-sizing. Pairwise comparison is available to determine the layout with the minimum amount of movement.
Dr. Jonathan Jackson is Associate Professor of SCM at Providence College.
Preparing for an upcoming semester is a challenging task for educators in normal circumstances, but infinitely harder when facing the largest disruption in education since the internet. The introduction of generative artificial intelligence (AI) and large language models (LLMs) like ChatGPT have caused us to rethink an entire course.
While AI will inevitably cause challenges, it also provides great opportunity to improve higher education. Here are 4 opportunities to make your teaching easier and more impactful using AI:
1. We have all been in the situation where no matter how we try to explain a challenging topic (e.g., the bullwhip effect), it still isn’t “clicking” for our students. This is where AI can help. By prompting an LLM like ChatGPT with a topic (say, bullwhip) and an audience (business students), it can help generate alternative explanations at varying levels of complexity to help improve student understanding.
2. Relevant and interesting examples help keep students engaged, but coming up with good examples is no easy task. Similar to generating alternative explanations, AI can provide various examples to help students connect a topic (e.g., inventory management) to things they see in their day-to-day lives.
3. While your Heizer/Render/Munson OM text has an amazing set of questions that can be auto-graded through MyLab, sometimes we need additional questions for a particular topic or class session. For example, before introducing SPC in Supplement 6, we may want to devise a low-stakes quiz to refresh students on topics from their previous statistics course such as central limit theorem and Normal distribution. AI can not only develop the questions, but also provide an answer key and explanations.
4. Short feedback mechanisms like “1-minute paper” and “muddiest point” are excellent tools to help gauge student understanding and gaps in knowledge. Unfortunately, they can be cumbersome for us to administer on the back end. Specifically, AI can help in summarizing the responses from the 25+ students into important points (understanding) and areas of confusion. By inputting all student responses into the LLM, it can provide prevalent key points and areas of confusion in a matter of seconds.
Much of the discussion around AI and education comes in an adversarial tone, but these opportunities are framed around leveraging this new technology for the betterment of our courses (and to save us a little time!).
Note: Generative AI and LLMs are not foolproof and should be carefully vetted using your content expertise.
Today’s Guest Post comes from Dr. Albena Ivanova, who is Professor of OM at Robert Morris University in Pennsylvania.
Excel OM software, which comes free with your Heizer/Render/Munson text, is an excellent tool for students to learn the various concepts of Operations Management. I have been using this software in conjunction with MyOMLab ever since I started teaching. I have found that using this software has not only made the homework completion process smoother but also helped students gain a better understanding of the course concepts.
The first thing that I do is show students how to arrange their tabs so they can have the two screens open at the same time next to each other. I usually pick algorithmic problems for class practice, where we are all working on the same problem, but with different numbers. I use the Study Plan for class practice and then give similar questions (but with different numbers) for homework and for the exam. My homework is not time limited, however, the students have only one (1) attempt. If they need to practice, they can do that in the Study Plan before completing the homework.
In the attached video I explain the process of using the Excel OM software to complete an Aggregate Problem homework in MyOMLab. The software has been slightly modified, and I have explained these modifications in detail in the video. I think that these small edits provide additional learning experience for the students, as they can see how to create or edit their own templates.
Overall, using Excel OM software has been a game-changer in my classroom. It has helped students better understand the course concepts. I hope my experience and the attached video will be helpful to fellow operations management professors in their efforts to enhance the learning of their students.
Readers may have noticed, that in the 14th edition of our OM text, we have continued to add to the rich selection of solved problems and end-of-chapter problems (which now comprise about 1,000 static problems). When the multitude of algorithmic versions are added, the number of problems may exceed 10,000! (We have actually not tried to count them).
In addition to the end-of-chapter problems, MyLabOperationsManagement also includes a number of problem variations noted as ‘brief’, ‘alternate’, and ‘extension’.
‘Brief’ problems are designed to allow faculty to assign problems with a smaller data set (see Problems 4.3, 4.6). These may be especially useful for time-constrained testing situations or with assignments containing a number of other problems. In these situations, students focus a larger percentage of their time on applying the technique a few times rather than generating “busy work” by repeating the same technique over and over. While the problem should take less time to solve, the ‘brief’ problem may have a data set that is smaller than should be used for a reasonable sample in the real world. Faculty may want to note this for students.
‘Alternate’ problems are variations of the text problem(s) (see Problems 15.24, 15,25 and 15.26) to enhance the variety of problems available to assign to students.
Finally, ‘extension’ problems enrich the comprehensiveness of the problem, as in Chapter 15, for example, where the critical ratio option has been added as an ‘extension’ of the scheduling problem (see Problems 15. 25, 15.27)
In all cases these problems can be accessed by the instructor by ‘clicking’ the “Show other custom questions” in the Assignment Manager, under Instructor Tools.
Our Guest Post today comes from Dr. Misty Blessley, who is Associate Professor of Statistics, Operations, and Data Science at Temple University
Astonishment best describes my initial reaction to hearing about ChatGPT, but this was mostly due to the reaction of all those people who asked me what I thought about ChatGPT in the month of December, 2022. “What do you think about ChatGPT?!!!”, I was asked, and this was not by people in our academic circle. Fresh off of the Annual DSI Conference and Thanksgiving, I was waist deep in all things December (i.e., wrapping up the semester, holidays, family, and etc.), but I could not shake the astonishment in everyone’s voices. Curious, I looked into what OpenAI, a San Francisco based firm with connections to Elon Musk and Microsoft Corporation, who launched the ChatGPT chatbot on November 30, 2022, had generally accomplished for the masses.
This month, ChatGPT hit close to home when I learned that it passed Wharton Professor Christian Terwiesch’s final exam in his MBA level operations management class. To be clear, “An AI bot passed this Wharton professor’s exam,” writes the Philadelphia Inquirer (January 25, 2023). As mirrored by an OM colleague, my astonishment turned to excitement and terror. Digging into Terwiesch’s article (cited below), ChatGPT “has shown a remarkable ability to automate some of the skills of highly compensated knowledge workers”. However, it has also failed to handle some complex problems, made mistakes in simple math and benefitted by having a human to prompt after a failure.
Open AI states that: “Our mission is to ensure that artificial general intelligence benefits all of humanity.” This chatbot can be used in many academic disciplines. A Wharton faculty member in innovation and entrepreneurship requires its use (see NPR, January 26, 2023). Let those of us in operations use it as a teaching tool, such that OpenAI’s mission is accomplished.
Here is the link to read the full article: Christian Terwiesch, “Would Chat GPT3 Get a Wharton MBA? A Prediction Based on Its Performance in the Operations Management Course”, Mack Institute for Innovation Management at the Wharton School, University of Pennsylvania, 2023
Classroom discussion questions:
1. How can students use ChatGPT to score big on operations exams taken on their own?
2. Given that ChatGPT benefits by having a human to provide hints after failing to solve a problem, what nuances do humans bring to the table that may be difficult to incorporate into a chatbot?
Although universities’ end-of-term evaluations are important, they are often too generic to guarantee detailed insights into our OM classes and our teaching. If we want to get specific feedback from students—about our assignments, MyLab, case studies, guest speakers, projects, readings—we must ask specific questions. And the best way to do that is by issuing our own surveys as well.
Harvard Business School’s Faculty Lounge (Nov. 15, 2022) has 3 suggestions to consider:
1. Ask specific questions to yield actionable feedback– including feedback on the materials you use, the approach you take, or the subjects you cover. Perhaps even ask what students would have done differently if they had been in your shoes and what topics they wished you had time to explore. You might also be wondering whether a particular guest speaker resonated with your students. And while you’re at it, list all the guest speakers in a survey question and request that students rate each one on a 1–5 scale, explaining their rating. You can ask similar questions about assignments, case studies, readings, and projects. Perhaps ask: “What are you most proud of achieving this term?”
2. Share the why—and be mindful of the when and how. You want students to understand that their feedback really means something to you—and that you’re thinking through what will lead to their most candid responses. To ensure that students will give your survey their full attention, let them know the “why”—that you’re including your own survey because their specific feedback is incredibly valuable and that you’d appreciate honesty, thoughtfulness, and thoroughness. If you’re worried about survey fatigue, keep your questionnaire short. Also, anonymous surveys build trust and inclusion. Online tools like Google Forms, Qualtrics, and Canvas offer anonymous survey options.
3. Learn to shrug off unproductive comments. Anonymous feedback can improve teaching—but also destroy educators’ confidence and innovation. If all your students think your course was wonderful, easy, and absolutely what they expected, it may be a sign that perhaps you’re not challenging students and pushing them beyond their comfort zones. Still, take some comments with a grain of salt, narrowing in on the feedback that is most productive and adjusting accordingly. If you end up surprised by some of your students’ responses, take opportunities to ask for feedback earlier in future terms.
The advantages of creating your own end-of-term survey are plentiful. But an important benefit is that it gives your students a voice.
When preparing a slide presentation for an OM lecture, we’re not always thinking about the most compelling way to deliver it, says Harvard’s Faculty Lounge (Sept. 13, 2022). We load up our slides, and then sometimes read them aloud to our students.
But no one—especially a student—is wired to engage with bullet points on a slide. They’re wired for story, a narrative that has a theme, attention-grabbing moments, and a satisfying conclusion. On their own, presentation programs like PowerPoint or Google Slides are not storytelling tools. So we need to be the inspiring narrators.
Understanding the difference between presenting and storytelling is critical to our ability to engage students and stir their excitement. Here are 4 strategies to help grab your students’ attention and ensure they are retaining what you’re teaching.
1. Craft a narrative that brings the topic to life. There’s absolutely nothing wrong with using PowerPoints for classroom learning, but slides shouldn’t be designed to replace the instructor—the storyteller. The narrative must come first, and slides should complement the story. First identify a story that brings the topic to life and then create or select the slides. It can be a consulting experience, a blog from this site, a WSJ article, or a case study.
2. Animate your story with pictures or videos. Students recall only 10% of the content they hear. But if you add a picture, they’ll retain 65%. So use one of our 50+videos, a YouTube clip, graphics, or photos to help bring the stories to life.
3. Add a few surprises. Some PowerPoints are boring because they’re predictable. Your students know what comes next—another slide of bullet points, followed by another. A good story, however, has the element of surprise. The human brain pays attention to novelty—twists and turns and unexpected events. This means your students will perk up when they detect something that breaks a pattern.
4. Rehearse the story before sharing with your class. A great lecture should inform, inspire, engage, and entertain, and should therefore be rehearsed–out loud. While it’s not realistic or necessary to practice every minute of a 1-hour lecture, at least rehearse the opening, conclusion, and stories you plan to share. Students won’t recall every piece of information they heard in class, but they’ll remember the moments you choose to spotlight.
We all strive make our OM course topics compelling–and we are lucky that ours is a field that allows us to bring teaching to life.
Lack of student engagement is one of the biggest challenges OM educators face. And whether you’re teaching in person or online seems to make little difference. As educators, it’s difficult to be sure why students are disengaged unless you ask them directly. To help, Harvard Business Publishing (Aug., 2022) reached out to four students to learn: What is something a professor does that makes you disengage, and what can they do to improve your engagement?
First student (from London): “I disengage in classes where the professors just lecture with no energy or passion for the topic. I would feel more engaged if professors relied less on lectures and leaned into more opportunities that allow students to actually apply the learning to projects or case studies.”
Second student (from India): “Some professors read the content directly from the presentation slides without explaining it further. This can make for a boring lecture. My three ideas are: (1) Make room for breaks during longer lectures so students can refuel.; (2) Crack some jokes to grab students’ attention; (3) Use real-world activities that allow students to apply their knowledge and solve problems.
Third student (from UNC): “Rather than extensive reading assignments and large cumulative tests, professors should consider integrating timely current events or discussions into their material. Courses can also be taught more effectively through project-based application. Also, provide help sheets, links, online videos, and recommendations for external resources so there are various methods for learning the material. This shows that professors are intentional about wanting students to have opportunities to succeed in their courses.”
Fourth student (from Portland State U.): “I disengage when a professor hasn’t introduced or taught concepts during lectures that are included in homework. I’m more engaged with professors who seem like real people and who have global awareness. The best professors speak to their lives outside of the classroom.”
Based on these responses, it appears that for students to care about what we are covering in our OM class, there needs to be less focus on the grades and more on the learning, as well as ample opportunities for course concepts to be applied to the real world–such as the simulations in MyLab. We will want to stay up to speed on new teaching methodologies and be realistic about what our students value.
The fall semester is almost upon us, and Jay, Chuck, and I wanted to share some of the important new MyLab for OM features:
Many of the recent updates to MyLab have been back-end changes that focus on improving stability, accessibility functions, and enabling a better LMS-integration experience. One notable enhancement is in the assignment manager. The user experience has been updated to look more modern, and is easier to navigate and manage assignments throughout the semester with improved functions like updating due dates, unassigning activities, and filtering to specific chapters. Here is a screen shot of what the UI looks like:
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Whether you’re a veteran or new OM educator, Harvard Business Publishing (June 21, 2022) offers the following syllabus checklist to ensure you set clear, measurable course objectives that align with your graded assignments and instruction topics. Answer yes to the 5 questions below and you’ll have a well-designed course that will more 
effectively teach students what you want them to learn.
1. Are my course objectives clearly defined and relevant? Take a fresh perspective every semester.
2. What do your students want? Try a pre-course survey. Ask: “Where do you want to work? What do you want to do? What are your goals and aspirations for your career?” Perhaps use some of our text’s 100+ case studies that relate to specific goals.
3. What do businesses want? Try connecting with people in the field and asking, “What do you wish you’d learned when you were an undergrad or grad OM student?” Ask the same of your alumni.
4. Do your assessments adequately measure student progress? Find a way to measure whether students are grasping the material and meeting their goals. Try giving quick, ungraded assessments consisting of a few short questions. Or do entry tickets before students sit down or exit tickets at the end of class, depending on whether you want to assess how well they grasped the reading assignment or what they just learned in class.
5. Do instructional experiences align with the objectives? Students don’t like busy work. So when you’re planning out assignments, discussion topics, lectures, and guest speakers, be clear about how they all align with the course objectives. For example, if you’ve assigned a group project for a case study or a MyOMLab simulation, explain to your students how this will help them learn. Let them know this exercise is teaching them to collaborate, work in teams, and be a leader—skills they will need in their future careers.
One big complaint from students is that we can go off on tangents with topics that don’t end up on tests or graded assignments. This occurs when there’s a lack of alignment between your course objectives and your instruction, assignments, and assessments. If you use your end goals as drivers for planning, your syllabus will have purpose, structure, and transparency—and your students may be more willing and active participants in your class.