Operational Efficiency and Process Improvement

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.