Finding Operational Efficiency in a Covid-19 World and Beyond
by Alexis Fiore, Consultant, Integrated Insight
Published October 21, 2020
Many businesses planning reopening strategies have approached our team at Integrated Insight for help understanding how they can reopen safely while remaining profitable. In most cases, we find operational and design efficiencies that allow our partners to increase their capacity over their original plan.
This is usually followed by the question, “Why weren’t we always running this way?” Major business disruptions like the current pandemic usually result in businesses taking a good look at their operation to try and find ways to do more with less. This has never been truer than now, when space is at a premium, and governments are placing arbitrary limits on the capacity of attractions.
This article follows one of our recent projects where we used agent-based simulation to find a 14% increase in capacity for our client while still maintaining social distancing simply by redesigning the event.
A client came to us seeking operational advice on how to re-open a long running walk-through attraction in a COVID-19 world. The initial scope of the project was to model the attraction as previously designed and then simulate the impact of changes to determine a layout that followed social distancing guidelines, while also optimizing attendance and revenue.
Data is not always available due to closures or inaccurate representations of capacity. Because of this, we use a combination of operational subject-matter experts, available data, and our industry experience to develop detailed assumptions for group demographics, arrival rates, overall length of stay, operational flow, way-finding decisions, and dwell times throughout the attraction. All of these inputs, and making solid assumptions, are critical to building a robust model.
Throughout the development of the model we received great input from the client operations team to ensure that the model accurately depicts the attraction experience. Once a valid model was created, we used our main evaluation metrics – instantaneous guest counts and time in queue – to determine that the points of interest (POI) in the attraction were front loaded. In previous years, up to 50% of the show content was placed in the first 30% of the experience. This created several problems:
1. Overcrowding at the beginning of the show became a bottleneck.
2. This bottleneck caused the queue to back up quickly.
3. The unbalanced experience caused reduced capacity in the overall venue.
Working closely with the operations team, our goal was to determine a few POI from the front of the experience that could be moved to a less crowded location without creating other unintended bottlenecks.
To decide which POIs to move, and their new locations, we analyzed guest density heat maps from the simulation model. The images below show heat maps of original layout and the new layout of both the first and final segments in the attraction. The areas circled in red highlight the change in guest density with our recommended operational improvements.
These changes substantially improved operational efficiency and we were able to run higher demand scenarios with the new layout. In addition, guests were able to spend a balanced amount of time throughout each house in the event. Based upon our estimated time in queue, we determined that additional queuing was not required as the current queue layout held up to 30 minutes of demand. With timed-ticketing, the client would be able to ensure the queue never exceeded the available space.
Making sure to maintain guest experience with the new layout of the event, the recommended daily capacity is ~40% of their pre-COVID peak day due to social distancing. This finding is notably lower than the typical government regulations mandating 50% capacity for an attractions operation. Opening at 50% of their peak capacity with no operational changes would likely have caused a public health hazard that could have produced negative press. Making these small operational improvements allowed the client to safely maximize their profits without impacting guest experience. Below is a clip of the simulation showing the attraction with the changes that improved operational efficiency.
Even with these operational improvements, we identified some areas of high guest density in the event where additional measures may be needed to mitigate congestion. By identifying these ahead of time, inexpensive strategies can be implemented to address these problem areas. This includes use of signage or ground markings guiding people where to view or wait for a popular attraction, designating a pathway through the experience where guests may pass other groups, or an employee monitoring the flow of guests through a high congestion area.
Simulation modeling helped this client in a set of complementary ways to maximize event experiences for their guests. The advanced analytic techniques helped them better understand the capacity at which they can safely open their experience. The analysis also allowed them to increase their total revenue, via increased throughput, relative to their plan by making minor layout changes. While this work was needed because of COVID-19, the operational improvements have been available for years; we just needed the right tools to find them.
Alexis Fiore specializes in simulation modeling and industrial engineering. Prior to joining Integrated Insight, Alexis had years of experience in healthcare and manufacturing industries.
Her prior projects include the study of operational efficiencies in the operating room at the Medical University of South Carolina and Prisma Health. In manufacturing, she worked on a team developing simulation models to identify bottlenecks and areas of improvement for factory throughput for Samsung.
While studying at Clemson University, she also completed internships at Walt Disney World Industrial Engineering, Southwest Airlines, Bosch Rexroth, and Design Interactive. During these internships she focused on inventory management, dashboard creation, database programming, and back of house capacity analyses. Each of these projects contributed to notable operational improvements and cost-avoidance for the organization.