Inspiration
Our inspiration to create this product was after some research on some major companies. They spend millions of dollars each year to transport their employees to a city for a meeting along with the time that goes into figuring out the logistics. Our product would optimize this process and help plan conferences easily at the least possible cost.
What it does
Our product is a tool that determines the top three places to conduct the conference by considering expenses such as travel costs, catering fees, and opportunity costs. Our tool targets companies, big or small, to help them save time researching the best location and money for the conference.
How we built it
We used Alteryx to build our project and Microsoft Power BI to generate the maps.
Challenges we ran into
We were unable to train a model within the time frame and the visual(maps on Power BI) would not connect to the code(Alteryx) to have on-time results.
Accomplishments that we're proud of
We are proud of having a running model that cost optimizes to a high accuracy.
What can we do to improve this program in the future?
APIs and Databases: Ideally, our program would be connected to APIs such as Google Maps to get the longitude and latitude of employee locations. We would also connect to a database of available conference venues and flight details.
Generalization: Right now, Co-Op Buddy is designed to work specifically for conferences. However, it could easily be generalized to work with events, presentations, and other meetings. We can do this by asking for another piece of data: What do you want to plan?
Accuracy: All of our outputs are approximations because we utilize zip codes for flight and distance approximations. With time and more development, our algorithm and data collection will be refined.
Dynamic output: Right now, our code is working off of one data set. Ideally, our code would work with any data set. However, it would take weeks to train the model which we did not have time for.
What we learned
We learned to use Alteryx, generate maps using Power BI, and research how to train the model.
What's next for Co-op Buddy
We would generalize our code and train a model to be used for all data sets.
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