MAP Dec 2021 | Managing Effective Operations

This Course shows a new entrepreneur the inside workings of a business process, viewed with precision. Professor Rajaram begins with a scientific understanding of operations management, demonstrating the steps in process analysis, and then discusses variability and its impact on a process, using Little’s Law to illustrate the assessment, and shows how and when to use work-in-progress buffers. He completes the course by addressing various ways to reduce process variability and its effect on lead times.

Faculty

Professor Kumar Rajaram

Professor Kumar Rajaram

Professor

Kumar Rajaram is a Professor of Operations and Technology Management at the UCLA Anderson School of Management. Professor Rajaram’s current research interests include improving operations in the health care industry, non-profit sector and in the process manufacturing sectors including food processing, pharmaceuticals and the petrochemical industry. He has focused on developing analytical models of complicated systems with a strong emphasis on practical implementation. His work has been published in leading research journals such as Operations Research, Management Science, Manufacturing and Service Operations Management, Marketing Science and the European Journal of Operational Research. He has been awarded the Eric and ‘E’ Juline Faculty Excellence in Research Award at the UCLA Anderson School.

Professor Rajaram has developed a new control paradigm called “Robust Process Control” to increase the productivity of large-scale industrial processes. By focusing on the design and control of these processes in operational environments, this technique has resulted in four-fold increases in productivity in several types of industrial processes. These methods have been implemented at several process companies worldwide. This work was awarded the prestigious Franz Edelman finalist award for outstanding applications of operations research and management science techniques to practice by the Institute for Operations Research and the Management Sciences (INFORMS). He has also developed techniques to better balance supply with demand for products with short life cycles and highly unpredictable demand. This work has been applied at several large fashion retailers in Europe and North America and has resulted in substantial improvements to profitability at these sites.

At the UCLA Anderson School, Professor Rajaram teaches the MBA core course on operations and technology management, various Executive Education courses and doctoral level courses on operations management and models for operations design, planning and control. He has been awarded the George Robbins Award, the Citibank Award and the Neidorf “Decade” Award for excellence in teaching at the UCLA Anderson School.

Education
Ph.D. Operations Management, 1998, The Wharton School, University of Pennsylvania
M.A. Managerial Science and Applied Economics, 1997, The Wharton School, University of Pennsylvania
M.S. Industrial Engineering and Operations Research, 1993, University of Massachusetts at Amherst
M.Sc. Mathematics, with Honors 1991, Birla Institute of Technology and Science, Pilani, India
B.E. Electrical and Electronics Engineering, with Honors 1991, Birla Institute of Technology and Science, Pilani, India

Course Learning Objectives:

  • Analyze a process scientifically to find its bottleneck/s and evaluate options for improving and balancing the process.
  • Integrate buffers appropriately into your work processes to maximize smooth production output.
  • Use Little’s Law to investigate the impact of variability and cycle times on lead times and bottlenecks, then systematically reduce those impacts.
  • Explain basic process analysis terms to a novice in operations management.
  • Create a logical operational process in its correct order, labeling each step as input, tasks, flow, storage, and output.
  • Using a logical process, correctly calculate/determine its bottleneck, idle time, direct labor content, direct labor utilization, and whether the process is “in balance.”
  • Use data to describe a current process in terms of its efficiency and its economic measures.
  • Analyze an existing process to find options for improving its efficiency and related economic measures.
  • For one change option, analyze the data to determine if it would or would not be an improvement to the existing process and make a recommendation.
  • Calculate the range and the standard deviation of the variability in an existing process.
  • Evaluate the value of incorporating a work-in-progress buffer into an existing process and recommend for/against it.
  • Evaluate each of the managerial levers that can reduce variability to determine its suitability for addressing a problem with variability in a process.
  • Calculate the lead time for a process, using Little’s Law and provided data.
  • Follow the directives of the P-K Formula to focus on reducing variability to remove some of the randomness of the arrival of orders, thus reducing lead time; consider each of the three main types of managerial levers: external policies, internal polices, and technology.

 

Syllabus

Learning Objectives: 
  • Explain basic process analysis terms to a novice in operations management.
  • Create a logical operational process in its correct order, labeling each step as input, tasks, flow, storage, and output.
  • Using a logical process, correctly calculate/determine its bottleneck, idle time, direct labor content, direct labor utilization, and whether the process is “in balance.”
  •  
Module Components:

Video Lectures:

  • Introduction to Operations Management
  • What is Business Process?
  • Basic Definitions and An Illustrative Example

Readings:

  • Introduction to Business Process Improvement
  • Unblocking Bottlenecks
  • How to Manage Bottlenecks in Operations Management

Case Study:

  • Case Study: Ultimate Teeth

Quiz:

  • Operations Management and Business Process Improvement – Quiz
Learning Objectives:
  • Use data to describe a current process in terms of its efficiency and its economic measures.
  • Analyze an existing process to find options for improving its efficiency and related economic measures.
  • For one change option, analyze the data to determine if it would or would not be an improvement to the existing process and make a recommendation.
Module Components:

Video Lectures:

  • Process Analysis – An Illustrative Example
  • Improvement Mechanisms – An Illustrative Example
  • Framework for Process Analysis

Readings:

  • Improving Business Processes
  • Handbook for Basic Process Improvement
  • Business Process Management – A Comprehensive Survey

Case Study:

  • Case Study: Ultimate Teeth (Continued – Part 1)

Quiz:

  • Operations Management – Modeling, Analyzing and Optimizing Processes – Quiz
Learning Objectives:
  • Calculate the range and the standard deviation of the variability in an existing process.
  • Evaluate the value of incorporating a work-in-progress buffer into an existing process and recommend for/against it.
  • Evaluate each of the managerial levers that can reduce variability to determine its suitability for addressing a problem with variability in a process.
Module Components:

Video Lectures:

  • Fundamentals of Managing the Impact of Variability
  • How Variability Affects the Process
  • How Variability Affects Operations and How to Reduce Variability

Readings:

  • Minding Manufacturing Peeves and Queues
  • Secrets to Variability Reduction
  • Analysis & Control of Variation

Case Study:

  • Case Study: Ultimate Teeth (Continued – Part 2)

Quiz:

  • Operations Management – Variability – Quiz
Learning Objectives:
  • Calculate the lead time for a process, using Little’s Law and provided data.
  • Follow the directives of the P-K Formula to focus on reducing variability to remove some of the randomness of the arrival of orders, thus reducing lead time; consider each of the three main types of managerial levers: external policies, internal polices, and technology.
Module Components:

Video Lectures:

  • Managing the Impact of Variability on Lead Times
  • Managing Lead Times in Processes
  • Action Planning for Effective Operations Management

Readings:

  • Manufacturing Lead Time – What is it?
  • Manufacturing Critical-path Time – A Measure of True Lead Time
  • Lead Time Reduction Methods

Case Study:

  • Case Study: Ultimate Teeth (Continued – Part 3)

Quiz:

  • Operations Management – Managing Lead Times – Quiz

Support

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