🤔 Where we come from
We previously did release waiting time and offices as open data and APIs:
... yet we were only able to give the current waiting time snapshot:
Last year, while projecting myself as a customer, I found that it would be useful to
- 💾 Keep the historical data of waiting time in an database : we chose Opensearch to be able to get nice looking dashboards as quick as possible
- **🎀 Serve the data **as a nice looking API
- 🛒 Share the API on our portal developer on APIGEE
- ➿ Quickly build a first prototype on top of the API with students to get feedbacks (and give some bug bounties) so we could build a develper friendly API
👉 This post is all about this last this adventure with students.
🎯 The pitch
Essentially as a PO, what I wanted was to be able, from a web interface to
- Pick any office
- Be able to browse the historical data of the current day
... and this is what we got:
🍿 For impatients
💰 Benefits of historical wait time data
There are a lot of benefits and potential that come with wait time, both :
- For the customer
- For enterprise
🤗 Customer : trends benefits
- While the current wait time gives you a snapshot, historical data gives you trends that make it possible for you to know if queuing is currently getting better or worst
- Makes it possible to the customer to choose the best time to come to the office (see "Crowdsourcing Feature Lets iPhone Users Determine Best Time to Cross U.S. Border")
🏢 Enterprise benefits and data-driven strategy
eg, from the service provider perspective, the main goal is to both:
- 📉 Minimize customers wait time to smoother Customer Experience (which also relies on digitalization and self service)
- 📈 Maximize service throughput : serve as much customers as possible with as less people a possible waiting in the office
So sharing live and historical wait time trends has a major impact and opens tremendous opportunities, see below some real life examples:
- Share historic data as ready to use open datasets to make Open Innovation possible
- Smart Wait Estimates: Increase customer satisfaction with accurate wait time quotes
- The Disney World case : Predicting Disney World Wait Times with Neural Networks : "In general, you can predict what sorts of wait times to expect based on the day of the week and the season-- September, for example, tends to have fairly low attendance due to kids going back to school"
- US Customs and Border Protection Airport Wait Times
- Government of Canada: Historical Border Wait Times – Land Mode
🔖 Resources
🧑🎓 More about University partnership
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