Waste & True-Up

Problem
How can the user capture all unknown discrepancies from day to day?

Role
Product designer & user researcher + 3 eng, pm, qa
Background: A discrepancy suddenly arose and we might start to lose cafes' trust. We need to huddle and make an emergency effort to save and keep customers happy. A four person Tiger Squad forms for a 2-day hack-a-thon to solve the high priority problem of capturing and decreasing the unknown discrepancies day to day. We brainstormed, discussed, and chose three pain points to rapid prototype. We discovered these pains during past user research sessions: a running low on inventory button, way to waste out an item, and a sold out button. Cafes were happy to hear that we were working on solutions to improve their work flow. and actually launching product. With additional user feedback and testing, we made a plan for Odeko 1.0. Three OKRs were targeted: to increase accuracy of orders, increase cafe usage of app, and increase data accuracy.
The 2-day hack-a-thon prototype screens above were used for user research, answering these scenario questions:
1. The last Chocolate Croissant just sold, report this sell out.
2. While in the app, you remembered you spilled 1 San Pelligrino item, report this as waste.
3. Check that your next delivery will include a San Pelligrino and a Chocolate Croissant.
4. Correct your current delivery of Matcha Banana Bread to 2 received.
Whiteboard sessions with the squad, and diagram drawn in my notes.
We were able to identify that errors in data were taking place around tasks they performed throughout the day. The features we produced above were working, but were clunky, incomplete, separate prototypes, and needed to further ensure all data points were addressed. We decided to introduce data entry into three parts of their day to ensure accuracy: 
  1. The Morning shift accepts deliveries. (in development, soon to launch) 
  2. The Afternoon shift counts inventory. (already exists in app) This downtime can be used to correct inventory levels that don’t go on the POS system, for us to make better orders.
  3. End of day shift confirms Waste & True-Up. Step by step flow to confirm waste and inventory after a day of transactions, delivery of the wrong items, accidents of dropping pan of muffins on floor, and waste outs, internal consumption.​​
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The three verbs above, reflect the three actions the user can take from our nav bar. 
Two early concepts presented to squad. We selected option 2 to move forward with.
Wireframe options of tool tab usage.
Cafe manager conducting user research by testing an early prototype version.
Prototype screen by screen set up with hotspot links.
We iterated on this new idea, made multiple prototypes, tested with numerous users, presented to retail managers and ceos of the cafes, and soon came to a validated prototype to start developing the flow in the image below. Also prepared handoff to cafes about Odeko 1.0: we made training decks, user manuals, handbooks, demos, collateral, and email announcements.
Prototype screens of the winner version used for deployment.
MVP screens split up into sprint work.
Weekly raw data we emailed the cafe district manager.
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Odeko 1.0 released and we saw changes in data instantly. More and more cafes were completing the flow, increasing data accuracy as a whole, and loving our company again. We even got ceo's across to change current waste processes to our new system and replace the POS. Above is raw data sent to the cafe district manager to review.

We changed the way our customers operated day to day, increasing our market value, and our need for each other.