2026 Community of Human and Organizational Learning 32nd Annual Conference

Note:  There is an afternoon offering of the same session.

A highly interactive workshop where participants practice Humans at Work tools to redesign systems, improve planning, and learn from everyday work—moving beyond concepts to real-world application


This four-hour workshop is designed as a hands-on, project-based learning experience where participants practice Humans at Work (HAW) methods, apply tools, and leave with tangible skills they can use immediately.


Participants will explore ten key philosophical and practical shifts that distinguish the Humans at Work approach from traditional performance improvement processes, and will actively connect organizational practices—planning, learning, controls, and leadership behaviors—to the principles that drive them. Through guided exercises, small-group projects, and real-world scenarios, participants will redesign tasks, surface system constraints, map gray zones, and practice everyday learning and error management methods.


The workshop emphasizes learning how to do, not just learning what to remember. Participants will work with tools for improving planning prior to task execution, learning from everyday work, identifying performance-influencing factors and latent organizational conditions, and applying the Control Paradox to organizational design.


Exercises will focus on discovering structural blind spots, redesigning defenses, and shifting from person-focused fixes to system-focused improvements.

Note:  There is a morning offering of the same session.

A highly interactive workshop where participants practice Humans at Work tools to redesign systems, improve planning, and learn from everyday work—moving beyond concepts to real-world application


This four-hour workshop is designed as a hands-on, project-based learning experience where participants practice Humans at Work (HAW) methods, apply tools, and leave with tangible skills they can use immediately.


Participants will explore ten key philosophical and practical shifts that distinguish the Humans at Work approach from traditional performance improvement processes, and will actively connect organizational practices—planning, learning, controls, and leadership behaviors—to the principles that drive them. Through guided exercises, small-group projects, and real-world scenarios, participants will redesign tasks, surface system constraints, map gray zones, and practice everyday learning and error management methods.


The workshop emphasizes learning how to do, not just learning what to remember. Participants will work with tools for improving planning prior to task execution, learning from everyday work, identifying performance-influencing factors and latent organizational conditions, and applying the Control Paradox to organizational design.


Exercises will focus on discovering structural blind spots, redesigning defenses, and shifting from person-focused fixes to system-focused improvements.

Description.
The availability of data to frontline managers in an organization has the potential to be a powerful way to improve performance of clinical teams.  Often, data platforms provide aggregated data that allows senior leaders to monitor (and fret about) the status of a problem.  Our prior platforms did not prioritize the day-to-day and week-to-week needs of our frontline leaders in managing the performance in their clinical area.  We developed a data platform specifically designed to support the work of frontline clinical managers in improving the reliability and resilience of the delivery of care of evidence-based bundle elements.  Displayed data elements are actionable and clearly communicate current system conditions at the local level. 7-day rolling bundle compliance is clearly displayed in order to create a rapid-cycle feedback loop for teams and allow early detection of a change in performance. 
Clinical outcome data is displayed using run charts to denote performance over time, as these are easier for frontline leaders to interpret when compared to more traditional process control charts. The design is simple and uniform across all hospital-acquired conditions (HACs).  Performance data are aggregated to communicate broader organizational performance to the executive team in a simple display that communicates current performance and highlights ongoing challenges.  We also made the platform available to all team members as a large interactive display to generate engagement with the data and foster a commitment to data transparency across the organization.
We have seen dramatic improvements in compliance with evidence-based bundles and reductions in hospital-acquired conditions since the data platform was deployed 18 months ago. The data platform operationalizes multiple principles of resilience engineering and joint cognitive system design.

Three key takeaways / learning objectives

• Designing a platform that prioritizes and supports the work of frontline clinical managers effectively is an important means of driving broad improvement across a large organization.
• Displaying data by clinical unit in a way that is transparent leverages the pride that people take in the areas in which they work to drive and manage local performance.
•  The integration of rapid feedback loops (7-day rolling data) supports local learning and allows teams to rapidly detect and respond to drift in performance.  Moving from statistical process control displays to 12-month rolling outcome data allows progress to be easily communicated rapidly across the organization.

 
Measurable results
We have seen dramatic increases in local compliance with evidence-based bundles and reductions in hospital-acquired conditions in the 18-months since the platform was deployed. Our 12-month rolling HAC rates are currently amongst the lowest since they began to be tracked in the organization, despite record-setting clinical volumes. We would be happy to share performance data during the presentation.

Description.
The availability of data to frontline managers in an organization has the potential to be a powerful way to improve performance of clinical teams.  Often, data platforms provide aggregated data that allows senior leaders to monitor (and fret about) the status of a problem.  Our prior platforms did not prioritize the day-to-day and week-to-week needs of our frontline leaders in managing the performance in their clinical area.  We developed a data platform specifically designed to support the work of frontline clinical managers in improving the reliability and resilience of the delivery of care of evidence-based bundle elements.  Displayed data elements are actionable and clearly communicate current system conditions at the local level. 7-day rolling bundle compliance is clearly displayed in order to create a rapid-cycle feedback loop for teams and allow early detection of a change in performance. 
Clinical outcome data is displayed using run charts to denote performance over time, as these are easier for frontline leaders to interpret when compared to more traditional process control charts. The design is simple and uniform across all hospital-acquired conditions (HACs).  Performance data are aggregated to communicate broader organizational performance to the executive team in a simple display that communicates current performance and highlights ongoing challenges.  We also made the platform available to all team members as a large interactive display to generate engagement with the data and foster a commitment to data transparency across the organization.
We have seen dramatic improvements in compliance with evidence-based bundles and reductions in hospital-acquired conditions since the data platform was deployed 18 months ago. The data platform operationalizes multiple principles of resilience engineering and joint cognitive system design.

Three key takeaways

• Designing a platform that prioritizes and supports the work of frontline clinical managers effectively is an important means of driving broad improvement across a large organization.
• Displaying data by clinical unit in a way that is transparent leverages the pride that people take in the areas in which they work to drive and manage local performance.
•  The integration of rapid feedback loops (7-day rolling data) supports local learning and allows teams to rapidly detect and respond to drift in performance.  Moving from statistical process control displays to 12-month rolling outcome data allows progress to be easily communicated rapidly across the organization.

 
Measurable results
We have seen dramatic increases in local compliance with evidence-based bundles and reductions in hospital-acquired conditions in the 18-months since the platform was deployed. Our 12-month rolling HAC rates are currently amongst the lowest since they began to be tracked in the organization, despite record-setting clinical volumes. We would be happy to share performance data during the presentation.

Elite athletes visualize failure before it happens, yet most organizations wait for an incident to learn. What if frontline workers were trained like top performers instead of compliance check boxes?


Organizations invest significant time and resources in training yet many struggle to prove how learning translates into real-world performance and measurable risk reduction. Completion rates and certifications may demonstrate participation, but they rarely indicate readiness decision quality or the ability to perform under pressure.


High-performing athletes do not rely on repetition alone. They use visualization to mentally rehearse high-risk scenarios anticipate mistakes and execute effectively when it matters most. This session challenges leaders to apply the same performance principle to frontline work where the cost of failure includes injuries downtime regulatory exposure and reputational risk.


The session explores how organizations can move beyond compliance-based learning by connecting training visualization and operational data. By linking learning programs with incidents, near misses, audits, human performance indicators and making risk visible organizations can enable frontline teams to mentally rehearse the scenarios they are most likely to face. This approach transforms training from a static event into a dynamic system that reinforces critical behaviors before incidents occur. Attendees will learn practical executive-relevant approaches for aligning learning investments with real operational risk improving frontline adoption and creating continuous feedback loops between learning EHS and operations. The session highlight show connected systems allow leaders to measure what truly matters preparedness performance and risk reduction.


Key takeaways include:

1. How to shift learning from a compliance requirement to a performance and risk management lever
2. Why visualization is a proven but underutilized capability in frontline safety and operations
3. How to connect training with real-world safety and operational data to drive relevance
4. Strategies for improving frontline engagement without adding burden
5. Metrics that reflect readiness behavior change and impact on risk 

Artificial Intelligence is already drafting risk assessments, analysing incident data, generating safety communications, and automating assurance workflows. But does that trajectory end with AI supporting safety practice—or replacing it? This double breakout session uses a structured, high-energy debate format to test that question in real time, separating hype from operational reality and exposing what “replacement” really means in complex sociotechnical systems.
In the first 50-minute session, participants will nominate as speakers and be randomly allocated to either the Affirmative (“AI will replace the Safety Practitioner”) or the Negative (“AI will not replace the Safety Practitioner”). Teams will rapidly build their case using guided prompts and fast research, while the rest of the room engages in a facilitated, interactive discussion to surface assumptions, evidence, risks, and ethical boundaries. Together we will map the strongest arguments on both sides—covering capability, accountability, regulation, human judgement, leadership, organisational learning, and the messy realities of work-as-done.


In the second 50-minute session, the room becomes a formal debating chamber. Teams deliver timed opening statements, structured rebuttals, and closing arguments, supported by a timekeeper and clear rules of engagement. The audience acts as adjudicators, voting on the winner and sharing the reasoning behind their decision. The facilitator will officiate, synthesise themes, and provide feedback—connecting debate insights to practical implications for the safety profession: what to automate, what to augment, what to protect, and what new capability the next generation of safety practitioners will need.


Participants will leave with a sharper, evidence-informed view of AI’s realistic role in safety—and a clearer line between tasks that can be mechanised and responsibilities that must remain human-led.

Artificial Intelligence is already drafting risk assessments, analysing incident data, generating safety communications, and automating assurance workflows. But does that trajectory end with AI supporting safety practice—or replacing it? This double breakout session uses a structured, high-energy debate format to test that question in real time, separating hype from operational reality and exposing what “replacement” really means in complex sociotechnical systems.
In the first 50-minute session, participants will nominate as speakers and be randomly allocated to either the Affirmative (“AI will replace the Safety Practitioner”) or the Negative (“AI will not replace the Safety Practitioner”). Teams will rapidly build their case using guided prompts and fast research, while the rest of the room engages in a facilitated, interactive discussion to surface assumptions, evidence, risks, and ethical boundaries. Together we will map the strongest arguments on both sides—covering capability, accountability, regulation, human judgement, leadership, organisational learning, and the messy realities of work-as-done.


In the second 50-minute session, the room becomes a formal debating chamber. Teams deliver timed opening statements, structured rebuttals, and closing arguments, supported by a timekeeper and clear rules of engagement. The audience acts as adjudicators, voting on the winner and sharing the reasoning behind their decision. The facilitator will officiate, synthesise themes, and provide feedback—connecting debate insights to practical implications for the safety profession: what to automate, what to augment, what to protect, and what new capability the next generation of safety practitioners will need.


Participants will leave with a sharper, evidence-informed view of AI’s realistic role in safety—and a clearer line between tasks that can be mechanised and responsibilities that must remain human-led.