Pre-conference Workshops

Attend the conference. Network with colleagues. Update your skills and put yourself ahead of the game.

Pre-conference workshops offer in-depth, skill-building tools and focus on the topics that you will require for career advancement and professional development. Enhance your learning experience and maximize your networking opportunities by attending one of our pre-conference workshops.

  • Continuing education units (CEUs) are available.
  • You must register for the full conference to participate in a pre-conference workshop.
  • Advance registration accompanied by the additional registration fee is required to reserve a pre-conference workshop seat. 

Saturday, May 30

8 a.m. - 5 p.m.

Improving the Effectiveness, Efficiency, and Quality of Organizations as Systems by Leveraging Disappointment

Kevin Nortrup, Sugar Creek Solutions LLC, Principal

Course Description

Organizations are the meta-systems within which all Industrial and Systems Engineering takes place.  Against ever-increasing complexity of products, services, requirements, constraints, building-blocks, and tools, it is essential that organizations be intentionally designed, implemented, operated, and improved as the sociotechnical systems that they are.  Failure to approach and to accommodate complexity systemically can compound it unintentionally, causing many of the problems that face companies and institutions today.

Unfortunately, genuinely systemic treatment of organizations is not the norm.  Many initiatives for improving organizations tend to optimize locally where problematic symptoms are observed, in relative isolation from context and interdependencies..

Many rely upon individuals with specialized skillsets in separatist departments whose objectives may not align with those of other departments.  Many improve metrics without improving the overall wellness of an organization or the quality of its results.

This innovative, interactive workshop explores a holistic, systemic model and approach for organizations.  It explains how five subsystems – culture, structure, process, technology, and training – must be designed, implemented, operated, and improved as interdependent components of the larger sociotechnical system.  It investigates common problems in organizations and illustrates their systemic identification and remediation.  It contrasts centralized, episodic intervention with distributed, inherent wellness.  Finally, it explores a mindset and a methodology that enables everyone throughout the organization to be ongoing agents of positive change and of improved quality, by leveraging disappointment as a trigger and focus of inquiry.

Learning Objectives

  • Explain the need, and demonstrate the ability, to apply systems thinking and systems engineering to the intentional design and cultivation of organizations
  • Describe the top-level interdependence and the respective operation of Culture, Structure, Process, Technology, and Training, within the presented model for organizations as systems
  • Analyze problematic symptoms within the multi-dimensional framework of that model
  • Illustrate advantages of distributed, inherent wellness over centralized, episodic intervention
  • Adapt, prepare, and perform inquiry into disappointment as a trigger and focus for organizational improvement


(Interactive applications and individual/group exercises are distributed throughout)

  • Introduction
    • Practical theory and theoretically sound practice
    • The universal problem: management of growing complexity
    • Sociotechnical systems
  • A five-part model for exploring and improving organizations as systems
  • "The quality problem"
    • Episodic intervention versus inherent wellness
    • Centralized versus distributed models
    • Qualitative quality
  • Disappointment-driven system-improvement
    • Rationale
    • Preparation
    • Sample protocol
  • Conclusion

Who Should Attend?

Level: Everyone – novices will be introduced to new concepts; experts will find novel interpretation & application of established concepts  

Responsibilities: Everyone – C-suite, directors, managers and ME/PI professionals; individual contributors; anyone wanting to improve the process of process-improvement by extrapolating it into system-improvement, for their company, their group, or just for themselves

Industries/markets: Everyone – Healthcare and manufacturing will be used as primary examples, but the principles and methods are universally applicable to any purpose-driven collaborations of people, process, and technology – companies, hospitals, institutions, even professional societies, in any industry, market, vertical, or skillset.

8 a.m. - 5 p.m.

Creating a Business Case for Artificial Intelligence using Design Thinking

Ben Amaba, IBM, Global Chief Technology Officer
Michael Testani, Binghamton University, Director of Industrial Outreach & Continuing Professional Education  

Course Description
This pre-conference workshop is intended for business leaders and employees to help explain the many benefits of Artificial Intelligence (AI) and how it can help their specific business.  This hands-on workshop applies important AI practices; like Machine Learning and Natural Language Processing (NLP) to help orient participants to the powerful capabilities of AI.  Design Thinking practices will also be used to help participants discover and document the potential for business value AI can bring to their business.

Learning Objectives

At the completion of this workshop, the participants will be able to:

  • Discuss the business benefits of Artificial Intelligence (AI)
  • Describe the 6 strategic intents of AI
  • Understand key capabilities of AI: Machine Learning, Deep Learning and Natural Language Processing and apply these techniques with actual data
  • Explain and apply key Design Thinking practices
  • Explain how AI can lead to business value
  • Build a business case for AI in your organization  


  • What is Artificial Intelligence (AI) and why is important for business?
  • What benefits being realized across industries using AI?
  • Hands-on application of AI using Natural Language Process to perform sentiment analysis for unstructured data (text)
  • Hands-on application of AI using Machine Learning and Deep Learning models to make accurate predictions from complex data sets
  • What is Design Thinking and why is it invaluable for visualizing the future of AI?
  • Apply powerful Design Thinking practices to create a business case for AI adoption in each participant’s organization  

Who Should Attend?
Business leaders, engineers, transformation consultants, data scientists, continuous improvement practitioners and academia.