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Innovation Insights
by Stephen Shapiro


My Baggage Claim Story and ChatGPT

Like millions of others, I have been playing around with ChatGPT. In an earlier post, I asked it some generic questions and got some generic responses. So I decided to put it to the test and see how it would do with my Invisible Solutions content. Can the AI system reframe problems better than the 25 lenses?

To put it to the test, I decided to ask it to solve the baggage claim problem. If you are not familiar with it, be sure to watch this video. The short version of the story is, to reduce wait time, instead of speeding up the bags, the airport slowed down the passengers.

Solutions to the Baggage Claim Problem

I asked ChatGPT:

Q: I work for an airport. People are complaining about how much they have to wait at baggage claim for their checked bags. Is there a better way to look at this problem? Are there good solutions?

A: There are a few ways you can approach this problem. Here are a few ideas:

  1. Analyze the baggage handling process: Look at how bags are being sorted and delivered to the baggage claim area. Are there bottlenecks or inefficiencies in the process that could be causing delays?
  2. Monitor baggage claim wait times: Keep track of how long it takes for bags to arrive at the baggage claim area, and use this data to identify patterns or trends. This can help you identify problem areas and come up with solutions.
  3. Communicate with travelers: Make sure travelers know what to expect when it comes to baggage claim wait times. Provide information about average wait times, and let travelers know if there are any delays or issues that may affect their experience.
  4. Consider implementing technology solutions: There are a number of technology solutions that can help improve the baggage handling process, such as RFID bag tags and automated sorting systems. These can help reduce wait times and improve the overall experience for travelers.
  5. Work with airlines and other partners: Collaborate with airlines and other partners to find ways to improve the baggage handling process. This could involve coordinating baggage handling procedures or implementing new technologies.

Not bad. Logical. But nothing overly insightful.

So I asked it a follow on question:

Reframing the Baggage Claim Problem

Q: Is there a way to reframe the original problem?

A: Yes, it may be helpful to reframe the problem in terms of how to improve the overall experience for travelers at baggage claim. Rather than focusing solely on reducing wait times, you could consider a more holistic approach that addresses the various factors that contribute to travelers’ satisfaction at baggage claim. This could include improving communication with travelers, providing amenities and services to make the wait more comfortable, and addressing any other issues that may arise. By taking a more holistic approach, you may be able to better address the root causes of travelers’ complaints and create a more positive experience for all travelers at baggage claim.

Meh. Basically said the same thing in a different way. However, I do like the “experience at baggage claim” as that is one of my reframes. So I decided to see if it could take the bait and look at both aspects of wait time – speed of bags and speed of passengers.

Q: What if the original problem was about reducing wait time. Would you have different answers?

A: If the primary goal were to reduce wait times at baggage claim, there are a few additional strategies you could consider:

  1. Increase staffing levels: If staffing levels are inadequate, it could be causing delays in the baggage handling process. Increasing staffing levels may help to speed up the process and reduce wait times.
  2. Streamline the baggage handling process: Look for ways to streamline the process of sorting and delivering bags to the baggage claim area. This could include implementing new technologies or optimizing current processes to improve efficiency.
  3. Reduce the number of bags that need to be handled: One way to reduce wait times is to reduce the number of bags that need to be handled. This could involve encouraging travelers to use carry-on luggage or implementing a baggage fee to discourage travelers from checking bags.
  4. Work with airlines and other partners: Collaborating with airlines and other partners to coordinate baggage handling procedures can also help to reduce wait times. This could include implementing new technologies or standardizing procedures to improve efficiency.

Didn’t seem to help. It didn’t realize that wait time is comprised of both the speed of passengers and speed of the bags. I thought #3 and #4 had some potential though. #3 is a use of the REDUCE lens while #4 is an application of the REASSIGN lens.

Not giving up, I decided to force feed it the answer. I pasted in the entire baggage claim story from the book and asked the AI to learn it.

Teaching AI to Learn My Baggage Claim Story

What I asked it what it learned, it responded with:

A: It sounds like the airport learned that the key to reducing wait times at baggage claim was not just about speeding up the bags, but also about slowing down the passengers. By reconfiguring the airport to take longer for passengers to walk from the plane to baggage claim, they were able to ensure that the bags and passengers arrived at baggage claim at the same time, improving the overall experience for travelers. Additionally, the airport realized that they could ask different questions, such as “How can we improve the waiting experience?” to consider a wider range of solutions to the problem. This approach can be seen in other industries, such as theme parks, where leaders are always looking for ways to improve the experience for visitors, even when they have to wait in line.

It seemed to summarize the story quite nicely. No new insights. But it still was a useful way to pull out the interesting concepts. What if you had a Zoom call and got the recording transcribed? You could feed it into the AI and get the key learnings. I may play with this at some point. But back to baggage claim.

Asking the AI to Ask me Questions

After feeding it the story, I asked it to ask me some questions. Here’s what I got in response:

  1. How do airlines typically restrict carry-on luggage?
  2. What was the biggest complaint of passengers at the small U.S. airport mentioned in the text?
  3. How did the airport initially try to solve the problem of long wait times at baggage claim?
  4. What did the airport eventually realize was the key to reducing wait times at baggage claim?
  5. What approach did the theme parks mentioned in the text take to improve the waiting experience for visitors?
  6. How did the designers of the “Race Through New York Starring Jimmy Fallon” ride at Universal Studios approach the problem of wait times?
  7. What did the airport do to reconfigure the airport and reduce wait times at baggage claim?
  8. How did changing the question from “How can we reduce the wait time?” to “How can we improve the waiting experience?” impact the range of solutions considered by the airport?
  9. How did the airport’s solution to the problem of long wait times at baggage claim also benefit the airport financially?
  10. Can you give an example of an industry other than the airline and theme park industries where minimizing wait times or improving the waiting experience is important?

Most aren’t that interesting on the surface, but if you use your imagination, it might generate some new ideas.

For example, #1 might lead to, “How can we allow more carry-on luggage on the plane?” Or maybe even, “How can we allow EVERYONE to carry on all of their luggage?” Maybe that a bit extreme (using the STRETCH lens from Invisible Solutions), but still thought provoking.

After Learning, Can it Reframe Better?

Now that it has had time to digest the content and look at it from different angles, I asked it one final question:

Q: Given what you now know, please reframe the original problem “How can we speed up the bags?” 7 different ways.

A: Sure! Here are 7 different ways to reframe the original problem of “How can we speed up the bags?”:

  1. How can we reduce wait times at baggage claim?
  2. How can we improve the overall experience of waiting for luggage at the airport?
  3. How can we ensure that bags and passengers arrive at baggage claim at the same time?
  4. How can we minimize the time it takes for luggage to be transported from the plane to the baggage carousel?
  5. How can we streamline the process of handling and transporting luggage within the airport?
  6. How can we optimize the speed and efficiency of the baggage handling system?
  7. How can we reduce the amount of time it takes for travelers to receive their luggage after arriving at their destination?

#1 and #2 are straight out of the baggage claim story. It still didn’t pick up on slowing down the passengers, although #3 hints at it. #4 – $7 are really just the original “speed up the bags” problem.

Overall, I am impressed. Although it can’t really think on its own, it is still a useful tool for brainstorming ideas. You might have to dig to find the nuggets. But it’s pretty good and can be a helpful sounding board. If you combine this with my 25 lenses, it can definitely help you. In fact, one of my next experiments will be to teach ChatGPT my 25 lenses and see if it can learn them and then use them effectively to reframe. Stay tuned!

So what do you think?

h/t to Adam Leffert for suggesting I use the “learn:” feature in ChatGPT.