1. THOMAS RANDOLPH KYLE SMITH STUART FELDT NICK PARKER What: Restaurant Management System. Why: Improve customer experience. Makes us better: Ours is personal.

2. REQUIREMENTS Customer friendly Easy user interface Manager reports Suggestion algorithms Correct input/ output Correct cook views

3. DESIGN: Paper menu (lets go green!) Updated order status’ Wait time Order inaccuracies No data mining No food suggestions Flaws of current systems

4. IMPLEMENTATION - PAPER MENU Why is it a problem: Difficult to update Dirty Old fashioned Long-term costs How we fixed it: Digital menu Customizable Prices Names Prep time Tools we used: Web application PHP, HTML, Javascript, MySQL LAMP server

5. IMPLEMENTATION - ORDER STATUS Why is it a problem: No dynamic feedback People need updates Unsure of when order will arrive How we fixed it: Provide an order status page Allows you to repeat orders easily Tools we used: Item has prep time associated with it in the database 10 states the order can reside All orders saved in database

6. IMPLEMENTATION - WAITING Why is it a problem: Longer time for the waiter to take your order How we fixed it: Menu is at the table Order as soon as you are ready and submit Tools we used: Orders get sent to kitchen when you submit your order The cook has a screen that shows all current orders submitted

7. IMPLEMENTATION - ORDER INACCURACIES Why is it a problem: Orders can get written down incorrectly Cook has hard time reading handwriting on order ticket Lack of communication between waiter and cook How we fixed it: Easy to use touch screen ordering system Cook sees exactly what user ordered Tools we used: Web based application with a database backend Cook screen which shows all current orders

8. IMPLEMENTATION - DATA MINING Why is it a problem: No current way for managers to retrieve frequency data / customer feedback How we fixed it: Viewable reports for managers on various menu items that have been ordered to help them update their menu Tools we used : Saving the frequency of items that are ordered in the database Automated queries on tables to show data in a viewable form for managers to read

9. IMPLEMENTATION - ORDER SUGGESTIONS Why is it a problem: Customers find choosing an item difficult The menu is static and doesn’t assist the customer Customer’s default to what they know How we fixed it: On-the-fly suggestions based on customer actions Views and orders affect how the suggestion works Order up suggests items based on past preference Tools we used: Suggestions are based on characteristics Characteristics are weighted and averaged (frequency) Highest rated + Highest frequency is more highly suggested

10. IMPLEMENTATION- SUGGESTION ALGORITHM Does calculation based on item characteristics Gets list of all matching items Adds positive similarity for matches Ranks items from the highest to lowest similarity Pseudo-code: Loop (characteristics) { if (matching) similarity += 1; }

11. IMPLEMENTATION - DATA FLOW

12. DEVELOPMENT PROCESS Scrum Development *We are forced to test each piece before the component is considered DONE

13. COMPLETED ITEMS

14. ALTERNATE APPROACHES Developing for various phone and device apps (iPhone, Android, etc) We didn’t use this because web apps are cross compatible Order from home We didn’t do this because we wanted to dive into technology for inside the restaurant only Letting users assign tables to orders Users can say they are somewhere they aren’t

15. TESTING The scrum design forces testing as everything is being developed We also let three users test our device and order items and then give us feedback We all also tested the system and tweaked minor things

16. CLASSES THAT HELPED Networking – IT 2810 Cyber Security – IT 2910 Web Development - CS 2830 Database – CS 3380 Software Engineering – CS 4320 System Administration – IT 3850

17. FUTURE WORK Commenting / Rating System Add more of a social aspect for users to collaborate Mobile specific design Current design works well, but viewing would be difficult on a mobile device

18. QUESTIONS/ DEMO?