My Baggage Claim Story And ChatGPT

Like hundreds of thousands of others, I’ve performed with ChatGPT. In an earlier submit I requested it some common questions and received some common solutions. So I made a decision to place it to the take a look at and see how it might do with my Invisible options contents. Can the AI ​​system reframe points higher than the 25 lenses?

To put it to the take a look at, I made a decision to ask it to resolve the bags declare drawback. If you are not aware of it, do it Watch this video. The brief model of the story is, to shorten the ready time, as a substitute of dashing up the baggage, the airport slowed down the passengers.

Solutions To The Bags Declare Drawback

I requested ChatGPT:

Q: I work for an airport. People complain about how lengthy they’ve to attend on the baggage carousel for his or her checked baggage. Is there a greater approach to have a look at this drawback? Are there good options?

A: There are just a few methods you’ll be able to method this drawback. Here are just a few concepts:

  1. Analyze the bags dealing with course of: see how baggage are sorted and delivered to the bags carousel. Are there bottlenecks or inefficiencies within the course of that would trigger delays?
  2. Monitor baggage declare wait instances: monitor how lengthy it takes for luggage to reach on the baggage declare space and use this information to establish patterns or developments. This can assist you establish drawback areas and provide you with options.
  3. Communicate with vacationers: Make positive vacationers know what to anticipate in the case of baggage declare maintain instances. Provide details about common wait instances and let vacationers know if there are any delays or points that would have an effect on their expertise.
  4. Consider implementing know-how options: There are various know-how options that may assist enhance the bags dealing with course of, equivalent to RFID baggage tags and automatic sorting techniques. These can assist cut back ready instances and enhance the general expertise for vacationers.
  5. Work with airways and different companions: Work with airways and different companions to seek out methods to enhance the bags dealing with course of. This could contain coordinating baggage dealing with procedures or implementing new applied sciences.

Not dangerous. Logically. But nothing overly enlightening.

So I requested it a follow-up query:

Reformulation Of The Bags Declare Drawback

Question: Is there a method to reframe the unique drawback?

A: Yes, it may be useful to reframe the difficulty by way of the right way to enhance the general expertise for vacationers at baggage declare. Rather than focusing solely on lowering ready instances, take into account a extra holistic method that addresses the varied components that contribute to traveler satisfaction with baggage retrieval. This consists of bettering communication with vacationers, providing services and providers to make ready extra comfy and fixing every other issues. By taking a extra holistic method, you might be able to higher tackle the foundation causes of traveler complaints and create a extra constructive expertise for all vacationers on the baggage carousel.

Meh. Actually, he stated the identical factor differently. I do just like the “baggage claim experience” although, as a result of that is one in all my reframes. So I made a decision to see if it might take the bait and have a look at each facets of maintain time: baggage velocity and passenger velocity.

Question: What if the unique drawback was about lowering the ready time? Would you’ve gotten different solutions?

A: If the first aim had been to scale back baggage declare ready instances, there are just a few further methods you might take into account:

  1. Increase the workforce: If the workforce is insufficient, it could possibly trigger delays within the baggage dealing with course of. Increasing the workforce can assist velocity up the method and cut back ready instances.
  2. Streamline the bags dealing with course of: Look for tactics to streamline the method of sorting and delivering baggage to the bags carousel. Think of implementing new applied sciences or optimizing present processes to enhance effectivity.
  3. Reduce the variety of baggage to be dealt with: One method to cut back ready instances is to scale back the variety of baggage to be dealt with. This might embrace encouraging vacationers to make use of hand baggage or introducing a baggage surcharge to discourage vacationers from checking in baggage.
  4. Collaborate with airways and different companions: Collaborating with airways and different companions to coordinate baggage dealing with procedures may assist cut back ready instances. Think of implementing new applied sciences or standardizing procedures to enhance effectivity.

It did not appear to assist. It failed to appreciate that ready time consists of each passenger velocity and baggage velocity. However, I believed #3 and #4 had some potential. #3 is a use of the REDUCE lens, whereas #4 is an utility of the REASSIGN lens.

I did not quit and determined to drive the reply. I pasted the entire story on the bags declare from the e-book and requested the AI ​​to study it.

Learning AI To Study My Baggage Declare Story

What I requested it what it realized, it answered with:

A: It appears the airport has realized that the important thing to lowering ready instances on the baggage carousel isn’t just dashing up the baggage, but additionally slowing down the passengers. By designing the airport to take passengers longer to stroll from the plane to the bags carousel, they had been in a position to make sure that baggage and passengers arrived on the baggage carousel on the identical time, bettering the general expertise for vacationers. In addition, the airport realized that they may ask a number of questions, equivalent to “How can we improve the waiting experience?” to think about a wider vary of options to the issue. This method can be seen in different industries, equivalent to amusement parks, the place leaders are at all times in search of methods to enhance the expertise for guests, even when they’ve to attend in line.

It appeared to sum up the story properly. No new insights. But it was nonetheless a helpful method to extract the attention-grabbing ideas. What in case you had a Zoom name and transcribed the recording? You might feed it into the AI ​​and study a very powerful classes. I’ll play with this sooner or later. But again to the bags carousel.

Asking The AI ​​to Ask Me Questions

After giving him the story, I requested him to ask me some questions. This is what I received in response:

  1. How do airways sometimes restrict hand baggage?
  2. What was the largest passenger grievance on the small US airport talked about within the textual content?
  3. How did the airport initially attempt to remedy the issue of lengthy ready instances on the baggage carousel?
  4. What did the airport finally notice was key to lowering wait instances at baggage declare?
  5. What method have the theme parks talked about within the textual content taken to enhance the ready expertise for guests?
  6. How did the designers of the “Race Through New York Starring Jimmy Fallon” trip at Universal Studios tackle the difficulty of wait instances?
  7. What has the airport finished to revamp the airport and cut back ready instances at baggage declare?
  8. How did the query of “How can we shorten the waiting time?” to “How can we improve the waiting experience?” affect the vary of options thought-about by the airport?
  9. How has the airport’s resolution to the issue of lengthy ready instances on the baggage carousel additionally benefited the airport financially?
  10. Can you give an instance of an business apart from the aviation and amusement park business the place minimizing ready instances or bettering the ready expertise is essential?

Most of them will not be that attention-grabbing at first look, however in case you use your creativeness, new concepts can emerge.

For instance, #1 might result in, “How can we allow more carry-on luggage on the plane?” Or perhaps even “How can we allow EVERYONE to take all their luggage?” Perhaps a bit excessive (with the STRETCH lens from Invisible options), however nonetheless thought-provoking.

Is It Higher To Reframe After Studying?

Now that it is had time to course of the content material and have a look at it from completely different angles, I’ve requested it one final query:

Q: Given what you understand now, please rephrase the unique drawback “How can we speed up the bags?” 7 other ways.

A: Sure! Here are 7 other ways to resolve the unique drawback of “How can we speed up the bags?” to reformulate:

  1. How can we shorten ready instances on the baggage carousel?
  2. How can we enhance the general expertise of ready for luggage on the airport?
  3. How can we be sure that baggage and passengers arrive on the baggage carousel on the identical time?
  4. How can we decrease the time it takes to switch baggage from the airplane to the bags carousel?
  5. How can we streamline the method of bags dealing with and transportation throughout the airport?
  6. How can we optimize the velocity and effectivity of the bags dealing with system?
  7. How can we cut back the time it takes for vacationers to obtain their baggage after arriving at their vacation spot?

#1 and #2 are straight out of the bags declare story. It nonetheless did not decide up on slowing down the passengers, though quantity 3 does trace at it. #4 – $7 is actually simply the unique “speed up the bags” drawback.

Overall I’m impressed. While it could possibly’t actually suppose by itself, it is nonetheless a useful gizmo for brainstorming concepts. You could need to dig to seek out the nuggets. But it is fairly good and could be a helpful sounding board. If you mix this with my 25 lenses it could possibly definitely enable you to. In truth, one in all my subsequent experiments will probably be to show ChatGPT my 25 lenses and see if it could possibly study them after which use them successfully to reframe. Stay tuned!

So guess what?

h/t to Adam Leffert for suggesting utilizing the “learn:” operate in ChatGPT.


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