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Sue Abdinnour, Ph.D.

Dr. Sue Abdinnour

Dr. Sue Abdinnour

Professor, Department of Finance, Real Estate & Decision Sciences
Omer Professorship, Barton School of Business
President, Advanced Operations Consulting & Training

Education

Ph.D. Operations Management, Indiana University
Master of Science Operations Research, Southampton University in England

Experience

Operations Management

Supply Chain Management

Business Analytics

Enterprise Resource Planning (ERP)

Dr. Sue Abdinnour is a Professor and holder of the Omer Professorship in the W. Frank Barton School of Business at Wichita State University. She received her Ph.D. in Operations Management from Indiana University, Bloomington and her Master of Science in Operations Research from Southampton University in England.

Her teaching specialties include operations, technology, and decision making. In addition to teaching undergraduate and graduate students, she  conducts workshops and seminars for executives and employees from various organizations focusing on continuous improvement, Six Sigma and lean principles.  Dr. Abdinnour research interests include Operations Analysis and Improvement, Supply Chain Management, Enterprise Resource Planning (ERP), and Technology Use in Organizations.

She has published her research in top tier academic and practitioner journals including Decision Sciences, International Journal of Production Research, Journal of Engineering and Technology Management, and Production and Inventory Management Journal. Dr. Abdinnour has won several awards of excellence for her teaching and research.  Finally, she aided companies with some major projects such as the redesigning of an assembly line and the implementation of new technology.

Dr. Sue On-Site Operations and Analytics sessions bring the learning directly to your team, service division, manufacturing cell or office department.  The learning is enhanced when exercises, models, and games are used that are directly related to your company, your industry and your issues.  Give us a call today, and we will create a path to strengthen your organizations foundation.

Software Skills and Business Analytics:

Description:

Today, we have access to more data and information than ever before, but how do you use any of it to make the best decision?  This course teaches you how to put information and data to work when making business decisions.

What you will learn:

Most workplaces have dozens of Excel spreadsheets full of the critical numbers that drive every aspect of the organization, whether it be finance, production, sales, marketing, engineering, etc.

In your day-to-day functions, regardless what they are, you have access to more data and information than you know what to do with.   You know all of it is valuable, but you are not sure how to use it effectively and efficiently. You are expected to interpret the data and make projections that keep the organization successful.  How do you begin to take advantage of the data and information at your disposal to make good decisions?

Dr. Sue will help you use common business tools and real world examples, that exist in Excel, to model the outcomes of different applications and help you make better choices.  Excel has allowed individuals and companies to explore and make informed decisions without having to wait weeks or months for information.  You will be able to take Excel from the simple usage of tables and charts to a powerful decision-making tool that works for you.

You will learn the practical steps to gather data and organize it, then analyze it in Excel’s basic and advanced tools. This will help you understand historical trends, diagnose the current situation, predict the future with accuracy measures, and find better metrics to measure the Key Performance Indicators (KPIs) of your business.  Don’t continue making decisions in the dark, when this course will give you the tools to make better decisions.

This class will demonstrate all the Excel tools using practical examples from numerous functional areas of the business, including Operations/Production, Supply Chain, Marketing, Finance, Sales, Marketing, Information Technology, Management, Human Resources, R & D, and many others. You will come out of this workshop with knowledge of many tools that help you harness the power Excel for analyzing data and information to make better decisions.

 

Designed for:

If you are an analyst, or responsible for data management or reporting, you will gain additional skills and have cutting edge expertise when you experience this class.  Regardless of your industry (service, aerospace, health, government, education, finance, non-profit, etc.).

 

Required skills:

It is recommended that each participant have the skills below.

  • Familiar with the Excel main menu ribbon options.
  • Creating a new spreadsheet, with multiple sheets.
  • Inserting, deleting, copy, move and rename sheets.
  • Comfort with rows, columns, inserting, deleting, hiding.
  • Cell and range copying, pasting, paste special, select non-adjacent ranges.
  • Relative, absolute and mixed references, and the impact of copying each to different cells in rows and columns
  • Excel functions:  SUM, AVERAGE, COUNT, MAX, MIN, SUMPRODUCT, VLOOKUP, IF
  • Formatting numbers, text, ranges with color, decimals, $, % etc.
  • Comfortable creating basic charts and format them as a histogram, line, pie chart, etc.

 

Outline:

Excel, Data, Databases, and Data Analytics

    • Sources of Data – Big and Small
    • Collecting, Organizing, and Cleaning Data
    • Spreadsheets vs, Databases for Data Analysis
    • Role of Enterprise Resource Planning (ERP)
    • Data Analytics – The Next Competitive Advantage

Build an Excel Spreadsheet Model

    • Review basics of Data Analysis in Excel
    • The 7-step Spreadsheet Modeling Process
    • Excel Tips and Best Practices in Excel
    • Key Excel Tools: Goal Seek and Data Tables
    • Breakeven Analysis What-if Example
    • Cash Flow Analysis What-if Example

Optimize the Excel Spreadsheet Model

    • Optimization vs. What-if Models
    • Importance of Optimization Models
    • The Basic Excel Optimization Model
    • Key Excel add-ins: Solver and Solver Table
    • Product/Marketing Mix Example

Develop Advanced Excel Optimization Models

    • Capital Budgeting Example
    • Workforce Scheduling Example
    • Product/Service Pricing Example
    • Extra: Portfolio and Investment Examples

Use Network Optimization Models in Excel

    • Network Model – A Specific Optimization Model
    • Excel vs. Microsoft Project for Network Models
    • Project Scheduling Example
    • Transportation / Supply chain Example
    • Job or Machine Assignment Example

Description:

In today’s competitive landscape, high-performing companies go beyond merely collecting and storing data or generating reports. They leverage analytics to craft robust competitive strategies. By harnessing data-driven insights, these companies distinguish themselves in a crowded market of similar products and services.

Globalization and technological advancements have intensified the challenges of competition and growth, leaving no room for “gut-feel” decisions. To remain competitive, analytics must permeate all aspects of the business, including operations, marketing, finance, customer service, IT, and human resources.

Cultivating a culture of analytics is the key to sustaining profitability and ensuring long-term success.

If you seek to improve your data-driven decision-making skills in Excel, this session is designed for you.

 

Designed for:

This course is tailored for analysts across various functions, including marketing, operations, quality, customer service, IT, finance, accounting, and human resources. Analysts at all organizational levels, from account representatives and specialists to managers, directors, and executives will find this class relevant.

The course will focus on hands-on exercises that show how to apply different types of Analytics in Excel. Any employee who uses Excel to manage data, perform analysis, or generates reports to enhance their decision-making will benefit from this class.

If you seek to improve your data-driven decision-making skills in Excel, this session is designed for you.

 

OUTLINE:

  • Business Analytics and its Scope
  • Why is Business Analytics important?
  • Data, Metrics, and KPIs for Analytics
  • Examples of Business Analytics in Excel
    1. Data Collection and Preparation
    2. Descriptive Analytics & Visualization
    3. Predictive and Prescriptive Analytics
    4. Building a Dashboard in Excel
  • A Data-Driven Culture with Analytics

Operations and Supply Chain Management

Inventory and Supply Chain Management

 Description:

Maintaining excess inventory is expensive; however, insufficient inventory can turn away valuable customers and even stop production. This puts your organization in the middle of a dangerous balancing act.  This program gives you the essentials of inventory management and useful decision making models you can apply to better manage inventory in your organization. You’ll have the opportunity to examine the distinction between independent and dependent demand inventory (MRP – Material Requirements Planning) and will come away from the program equipped with useful methods for controlling inventories in your area.

Managing inventory is part of the larger practice of supply chain management, which has been widely adopted in recent years by companies worldwide. Your company is as strong as the weakest link in its supply chain. Today, competition is supply chain against supply chain, rather than company against company. In this seminar, you will learn the basics of supply chain and how to mitigate problems that commonly accompany an integrated supply chain. You’ll also have the opportunity to see supply chain play out in a simulated environment through the widely recognized MIT “Beer Game” which helps illustrate critical supply chain concepts.

OUTLINE:

Inventory management

  • Types of inventory
  • Inventory cycle
  • Inventory costs

Inventory models

  • ABC analysis
  • EOQ model
  • MRP model

Supply chain management

  • Definition
  • Critical decisions
  • Bullwhip effect

The MIT Beer Game

  • Game rules
  • Play the game
  • Collect data
  • Analyze the data
  • Discuss the results

Description:

Lean principles focus on increasing efficiency while reducing expenses to deliver the maximum return-on-investment.  Through the introduction of lean, many organizations have enjoyed lower costs, higher profits, superior quality, shorter order-to-delivery time, greater flexibility and improved response to changing client demands by introducing lean principles into their organization.

Benefits:

The ability to quickly respond to market demand and prevent over-capacity within your company requires the adoption of lean principles.  Lean techniques allow you to lower costs, improve efficiency, reduce overhead, and eliminate activities that are not value added.

This course is designed to introduce participants to the fundamentals of lean using a hands-on simulation exercise with multiple runs.  Plant managers, operations managers, business owners, shift supervisors, HR professionals, quality control personnel, engineers and anyone wanting an understanding of the use & application of lean principles will benefit from this program.

Outline:

An introduction to lean

  • Evolution of lean
  • Types of wastes
  • Value stream mapping
  • Simulation round ONE

First improvement phase

  • Batch size
  • 5S system
  • Visual controls
  • Dept layout
  • Cellular flow
  • Simulation round TWO

Second improvement phase

  • Pull system
  • Kanban
  • Teamwork
  • Quality at the source
  • Total productive maintenance
  • Simulation round THREE

Management readiness for lean

Review & discuss principles of lean

Description:

Numerous companies are investing in improving their operations by starting with the basic question: what is our operations strategy? Regardless if your company is service or manufacturing, private or public, small or big, etc. it is critical to assess your operations strategy to get good performance and experience growth. Without a proper assessment and reassessment of your operations strategy, a company ends up making random and uncoordinated decisions that may help in the short term, but are detrimental in the medium and long run.

This seminar gives you a quick introduction to three key respectable operations-based strategies that have helped many companies become competitive in the global marketplace. You will be exposed to the theory, how it is applied in service and manufacturing, common tools, and many other useful topics. At the end of each strategy, there will be a discussion and an assessment of how the strategy applies to your company. Every executive, manager, supervisor, and employee can benefit from this seminar.

 

What is an operations strategy

  • Why is it important to have one
  • Setting competitive priorities

 

Three main types of operations strategies

 

Quality-based strategy

  • Is there one definition of quality?
  • Quality and profitability
  • Quality in service vs. manufacturing
  • Dimensions of quality
  • Costs of quality
  • Brief introduction to Six Sigma
  • Common quality tools

 

Lean-based strategy

  • Evolution of lean
  • The seven wastes of lean
  • Logic of pull vs. push
  • Lean in service vs. manufacturing
  • Brief introduction to value stream mapping
  • Common lean tools
  • Related Topics: lean supply chain, Lean Six Sigma

 

Theory of Constraints-based strategy

  • Goldratt’s iconic “The Goal” book
  • Watch the movie (based on the book)
  • Learn the steps of Theory of Constraints (TOC)
  • Find the bottleneck in an operation
  • Drum, buffer, rope

 

Comparison of Six Sigma, Lean, and TOC

 

Role of metrics in an operations strategy

Numerous companies have proven that improved quality is a significant factor in reducing costs and producing stronger profits. This is even more critical in today’s marketplace with the challenge of controlling quality along a global supply chain. A single quality incident, regardless of its source, can inflict huge financial loss and ruin a company’s reputation.  In this program you will learn the most effective quality tools including flowcharts, Pareto Analysis, and many others. You will apply what you learn by playing the famous “Deming’s Red Bead Experiment.”

 

This seminar will also give you an introduction to the fundamentals of Six Sigma and its five-step quality improvement cycle – DMAIC, which is a systematic problem-solving approach for improving business processes in both manufacturing and service organizations. Driven by data, it applies proven techniques to streamline processes, improve efficiency, and cut costs. Thousands of companies around the world have discovered the far-reaching benefits of Six Sigma and have posted huge savings after implementing it.

The Basics of Quality

    • Do we still care?
    • The costs of poor quality
    • Metrics to track quality

 

The Quality Toolbox

    • Process flowcharts
    • Pareto analysis
    • Fishbone diagrams
    • Scatter diagrams
    • Quality Control Charts
    • Process capability

 

Deming’s Red Bead Experiment

    • Game rules
    • Play the game
    • Collect data
    • Analyze the data
    • Discuss the results

 

 

Six Sigma and DMAIC

    • What is Six Sigma?
    • D- Define
    • M-Measure
    • A-Analyze
    • I-Improve
    • C-Control

Description:

 

This session will review two of the most critical decisions in any business: forecasting demand and managing capacity. While managerial judgment and experience is still required for forecasting demand, managers today are aided by different decision making models that help them improve their forecasts. In this class you’ll learn how to use a number of effective forecasting approaches.

 

This program also gives you essential tools required to effectively plan for appropriate capacity in your operations. In class many of these tools will be hands-on exercises done with EXCEL on a laptop.  You’ll also gain valuable understanding of useful capacity measures, like utilization and efficiency; and you’ll look at two key strategies that can be applied to match the forecasted demand to the available capacity.

Operations management

  • What is operations management?
  • Critical decisions in operations
  • Products vs. services

 

Forecasting models

  • Qualitative vs. quantitative
  • Time series analysis
  • Moving average
  • Exponential smoothing
  • Regression analysis
  • Forecast errors

 

Capacity planning

  • Capacity measures
  • Forecasts vs. capacity
  • Chase strategy
  • Level strategy
  • Yield management
  • Scheduling strategies
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