Finding and Breaking the Bottleneck: Theory of Constraints

Stop improving everywhere at once. Find the one constraint that governs your system — and manage it so the whole thing delivers more.
  • Author: Dr. Zitianellis

  • Level: Foundational
  • Study Mode: Self-paced
  • Recommended Period: 1 Week
  • Estimated Learning Time: ~7 Hours
  • Proficiency: 1 Graded Assessments
  • Award: 1 Certificate
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To ensure the best continuity in your learning, we recommend completing the course within the recommended completion period. The course is self-paced, so you can adapt your learning schedule around work and other commitments.
Course overview
Finding and Breaking the Bottleneck is a one-week applied micro-course on the Theory of Constraints. It teaches a single, practical skill: viewing an organization as a system limited by one constraint, identifying that constraint rather than chasing symptoms or local inefficiencies, and managing it to increase the system's overall throughput. In the opening lesson, you choose one real process or system you own and carry it through all six lessons, learning to locate its constraint, measure whether the whole system is really improving, exploit the constraint and subordinate the rest of the system to it, and judge when to add capacity. By the end of the week, you will have a defended plan that raises what your system delivers rather than how busy its parts are.

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  • Operations Management
  • Process Improvement
  • Systems Thinking
  • Leadership & Decision-Making

Your Instructor

Taught by a practitioner. Moderated by the same.
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Dr. Zitianellis brings broad data science and analytics experience across financial services, retail, supply chain, operations, and pharmaceutical manufacturing. She has worked with SubjectWell, IQbusiness, PBT Group, Sanlam, and Standard Bank Group, delivering forecasting, segmentation, anomaly detection, data quality, credit analytics, and reporting solutions.
At Monarch, she is Director of the Doctor of Applied Behavioral Data Science program and supports curriculum development, instructional design, and program operations across Bachelor, Master, and Doctoral programs.
As an educator, she contributes to academic and executive data education. She is Head Tutor for the Economist Education course Data Storytelling and Visualization, supporting data communication and analysis. Currently assesses work for the University of Cape Town Data Skills Accelerator program, focusing on fair evaluation, feedback and student outcomes.
Dr. Zitianellis holds a Doctor of Business Administration and M.Phil. in Business Research from Monarch Business School Switzerland, an MSc in Data Analytics and Operations Management from Arden University, and a postgraduate diploma in Data Science and Business Analytics from the University of Texas at Austin.
Her doctoral work examined AI and machine learning to improve clinical trial patient recruitment, integrating health behaviour theory, NLP and predictive modelling. Broader interests include ethical data analysis, machine learning in business, data visualisation, operations and supply chain analytics, risk analysis and mixed-methods research. 
She is committed to ethical data use, affiliated with the Algorithmic Justice League’s Agents for Change, and supports animal welfare and education community projects. Her research covers big data analytics and supply chain management, as well as AI/ML applications in clinical trial recruitment. She has presented at the Applied AI Summit and the 21st Century Women’s Entrepreneurship and Leadership Conference.