Upcoming Webinars

IISE webinars are FREE one-hour presentations by knowledgeable professionals and experienced volunteers who provide deeper insight into topics and issues involving industrial and systems engineers and ISE-related disciplines.

You must be able to view Windows Media Files to watch. If the recording does not start automatically, download this codec.

IISE will award continuing education units (CEUs) if you attend the entire webinar. Send your request to IISE customer service at cs@iise.org.

IISE members and others qualified to view designated webinars can also review the webinar archive and access past presentations.

Webinar Recordings

Business Process Improvement Portfolio Management: Picking the Right Projects to Drive Enterprise Value Better and Faster

An IISE Performance Excellence Webinar
11:30 a.m. ET Nov. 29

Join Jared Frederici and Scott Sink as the continue to build on the three webinar series we did in September and October (links to these presentations can be found when you register at the button below).

In this fourth session in the series, Jared and Scott will zoom in on a strategy and approach for selecting the right business processes and projects to systematically grow enterprise business process maturity and in doing so drive greater enterprise value better and faster.


#HSPI2023 Pre-Conference Workshop Overview

Presented by the Healthcare Systems Process Improvement Conference 2023
1 p.m. ET Dec. 1

Enjoy this preview of each #HSPI2023 pre-conference workshop in this webinar! Each workshop leader will give a brief overview of what to expect, how to prepare and the type of activities planned. Click here to read more about the scheduled pre-conference workshops.


Causal Inference Methodologies in Healthcare Policy Evaluation

Presented by the Society for Health Systems
1 p.m. ET Dec. 8

In the public health domain, it is difficult or prohibitively expensive to design controlled studies to evaluate effective public health policies. Therefore, the use of observational studies is increasing, mostly due to the wider adoption of information technology in management systems, social media, and smart electronic device usage. Current methods underlying causal inference suffer from several fundamental challenges that may lead to sub-optimal policy decision.

This webinar will discuss how we can use optimization and data analytics to facilitate better policy decision making. To show the efficacy of the proposed methods, the following two important healthcare policy evaluation case studies will be discussed:

  1. Evaluating the causal relation between Hospital Readmission Reduction Program (HRRP) and readmission to different hospital (non-index readmission) using the State of California Patient Discharge Database.
  2. Evaluating the effect of Opioid Use Disorder (OUD) on suicidal behavior using SAMHSA’s National Survey of Drug Use and Health (NSDUH).


Dynamic Characterization and Optimal Self-Management of the Emergence Trajectories of Multiple Chronic Conditions

Presented by the IISE Quality Control and Reliability Engineering (QCRE) Division
1 p.m. ET Dec. 6
Dr. Adel Alaeddini

More than a quarter of all Americans and two out of three older Americans are estimated to have at least two chronic health problems. Treatment for people living with multiple chronic conditions (MCC) consume an estimated 66 percent of U.S. healthcare costs, and as the population ages, the number of MCC patients will increase. However, fundamental knowledge gaps remain in our understanding of how MCC evolves at the individual and population levels. This presentation introduces functional and deep continuous time Bayesian networks to model the relationship among MCC and non/modifiable risk factors to characterize major patterns of MCC emergence in individuals based on a dataset from the US Department of Veteran Affairs.


Data Science for Wind Energy

Presented by the IISE Energy Systems (ES) Division
3 p.m. ET Dec. 9
Dr. Yu Ding

Wind energy is one of the fastest-growing clean energy sources. Despite the significant growth in the past two decades, wind energy missed some intermediate goals set forth earlier. In his book, Data Science for Wind Energy, Dr. Yu Ding demonstrates how statistical and machine learning methods can help address research needs in wind energy applications. Dr. Ding will discuss some challenges encountered in wind applications and present use cases in which statistical/machine learning models and solutions make sensible impacts.


Strategic Performance Improvement Planning in Periods of Economic Disruption

11 a.m. ET Dec. 13

In periods of disruption, as we have shared, Insightful Leadership is required to skillfully guide the challenging path to sustained "performance excellence." Price Recovery has been and will continue to be a "solution" that is constrained, limited in effectiveness—many firms just cannot increase prices fast enough to offset rising costs in the supply chain.

As such, effectively planning to improve productivity and quality faster and better is the name of the game.

This webinar will outline a process, method for doing Process and Performance Improvement Planning we have developed over the past 30 years. We will overview the method and provide specific examples of how it plays out in different types of organizations. Join us to learn about how to drive Productivity Faster, Better in Disruptive, Difficult Economic times.