In this expert interview, University of Wollongong lecturer Mostafa Khatami reveals his passion for system optimization and details how Business Analytics empowers data-driven decision-making across Finance, Supply Chain, Marketing, and Agriculture.
He also explores the critical importance of data storytelling, the transformative impact of generative AI on academic assessment, and why foundational coding and Machine Learning proficiency are essential in the modern workforce.
Key takeaways:
- Easily understand what Business Analytics is through simple examples that explain the key concepts.
- Machine Learning is now a basic skill in Business Analytics, no longer a special advantage but a core expectation for all students.
- Find out why context matters when interpreting data, and how AI is reshaping assessments and future skills.
Mostafa Khatami’s professional trajectory blends Engineering, Mathematics, and applied problem-solving. After earning his Bachelor’s and Master’s degrees in Industrial Engineering in Iran, he relocated to Australia to pursue a PhD in Mathematics specializing in Operations Research, followed by academic research positions at the Queensland University of Technology.
Currently a Lecturer in Business Analytics at the University of Wollongong, Khatami focuses on solving complex operational challenges, including resource scheduling, service facility location, and logistics network optimization. His research appears in top-tier academic journals, and in 2023, he received a national Rising Star Award for his significant contributions to the field.
Online Result: How did you find your passion for business analytics?
Mostafa Khatami: During my final year of high school in Iran, I was researching university degrees. While I initially gravitated toward Mechanical Engineering, I discovered the Industrial Engineering curriculum. The concept of "optimization" really resonated with me. I completed my Bachelor’s and Master’s in Industrial Engineering before moving to Australia.
In Australia, the discipline is integrated into Operations Research, which represents the mathematical optimization aspect of industrial engineering. Consequently, I completed my PhD in Mathematics—as Operations Research is situated within Mathematics departments here—before continuing into a postdoctoral role and, eventually, a lectureship at Wollongong.
Online Result: Looking back, what early experiences shaped your interest in maths and technical education?
Mostafa Khatami: I have always had an aptitude for numbers. I knew I wanted to pursue Engineering, but I was also deeply interested in Economics. Industrial Engineering—what we now define as Business Analytics—emerged as the perfect bridge between engineering principles and economic logic.
What Business Analytics really means in simple, real-world examples
Online Result: Many high school students struggle to choose a degree. What advice would you give them?
Mostafa Khatami: I always tell students that longevity in a career depends on passion. Research what the daily routine of a professional in your chosen field actually looks like. Whether it’s an industrial engineer or a business analyst, visualize your day-to-day responsibilities. You have to love the work, because it will be your path for the rest of your life.
Research what the daily routine of a professional in your chosen field actually looks like. See if you enjoy that lifestyle, because it will be your future. You have to love what you do.
Online Result: How would you explain business analytics to a high school student exploring different study options?
Mostafa Khatami: At its core, Business Analytics is the science of predicting the future using data-driven insights.
Consider a coffee shop: by tracking daily cappuccino sales, you can forecast future demand. To make that prediction, we utilize three distinct branches of Business Analytics.
The first is "descriptive analytics," which involves examining historical data to understand past trends and patterns.
The second is "predictive analytics," where we project future outcomes—such as next week's customer volume—based on those historical insights.
The final and most crucial step is "prescriptive analytics," which focuses on decision-making. We use our predictions to determine how many staff to hire or how much inventory to purchase, essentially using data to optimize operational outcomes.
Learning to work together with experts from different industries
Online Result: How is business analytics used across different fields and industries?
Mostafa Khatami: Business Analytics is a universal toolset applicable to any discipline—from Human Resources and Marketing to Supply Chain and Finance—to solve complex, real-world problems.
In finance, we use it to forecast market trends and optimize investment portfolios. In supply chain management, it minimizes fuel costs and delivery times through route optimization. In agriculture, analytics helps optimize crop selection and resource allocation across vast farmland. [MK1]
Online Result: Do students need prior experience in these fields before joining a Business Analytics degree?
Mostafa Khatami: Business Analytics is inherently collaborative. A client brings deep domain expertise to a problem, and the analyst brings the tools to solve it. It’s not about being an expert in every industry, but about being an expert in decision-making methodologies.
Online Result: What makes this collaboration work well?
Mostafa Khatami: I emphasize context-awareness to my students. You can perform complex data analysis in Excel, but without domain context, your results may be theoretically sound yet practically useless, or even damaging to the business.
We must interpret the "story" behind the numbers. This requires partnering with industry experts who understand the nuances of what is operationally significant versus what is mere noise.
Context is everything. You might reach a conclusion through data, but if you don't understand the context, you risk proposing solutions that are inapplicable or counterproductive in the real world.
Online Result: What hands-on learning do your students experience to prepare for jobs after graduation?
Mostafa Khatami: Our capstone subjects provide students with the freedom to explore industries they are passionate about. Since many students pursue double majors—for instance, Business Analytics paired with Finance—they often bring specific cross-disciplinary problems to solve using our analytical framework.
Over the course of a semester, students identify a business, define a core problem, and apply both predictive and prescriptive analytics to develop a comprehensive solution.
Why Business Analytics is for students who love working with numbers
Online Result: Do you have many international students in your programme?
Yes, our undergraduate program is highly international, with approximately 95 percent of our students joining us from diverse backgrounds across Asia, Europe, Africa, and South America.
Online Result: What technical skills should students have before starting a Business Analytics degree?
Mostafa Khatami: Business Analytics is inherently quantitative. If you don't enjoy working with numbers, it might not be the right fit. We also incorporate coding, though it is less intensive than a Computer Science degree.
While we utilize the same Machine Learning [MK2] tools as engineering disciplines, our focus is on using them to drive business decisions. Today, Machine Learning literacy is a baseline requirement for everyone in the industry—it is no longer just a competitive advantage; it is a fundamental skill set.
Machine Learning literacy is a fundamental requirement for anyone in Business Analytics. It has moved beyond being just a "competitive edge" to becoming an essential, universal skill.
Online Result: AI and machine learning are evolving fast. How has AI changed Business Analytics in recent years, and what changes do you expect next?
Mostafa Khatami: Generative AI has caused a major paradigm shift. We are seeing a significant, year-over-year increase in its adoption among both students and staff.
It has fundamentally altered how we structure our curriculum and assessments. Since Business School projects are often research-heavy, the temptation to use AI for drafting is high, as the technology handles writing tasks effortlessly.
I advise my students to develop their own voice first and use AI as an iterative editing tool, rather than relying on it to generate content. Foundational writing and critical thinking remain indispensable.
We are now prioritizing the assessment of critical thinking over rote output. While some institutions are retreating to old-school, pen-and-paper examinations, I believe we need to evolve our assessments to verify a student’s genuine thought process and intellectual contribution when using AI tools.
Online Result: What makes your Business Analytics programme stand out from others in Australia?
Mostafa Khatami: Our program is distinguished by its balanced integration of methodology. While many institutions focus heavily on predictive analytics, we place an equal emphasis on prescriptive analytics, ensuring our graduates possess the comprehensive skill set needed for a distinct competitive edge.