DINNER IS SERVED:
To some restauranteurs, running dinner service every night can be like watching a slow-motion train wreck. If front/back-of-the house operations aren’t precisely coordinated, the whole system falls apart. That’s why more owners are turning to data-driven solutions, like VengaDine, to help them anticipate and proactively address issues before they occur. It can be difficult, however, to translate messy data into something actionable. That’s where I come in!
Problem: Users have trouble drawing actionable conclusions from Venga’s data tables on their own, without the help of Venga’s Support Team
Task: Redesign a feature that would increase the usability of Venga’s data and could be implemented immediately
My Role: Product Designer
Time Required: 4 hours
Select a Feature
Dine vs. Move
I know both industries well, but I have applied experience in hospitality (wineries)
Missing feature documentation for Move (support page down)
Welcome to Venga Webinar (Mike)
Pre-shift report seems like a high-priority feature for the user
Doing some QA testing of the printing feature in the pre-shift report, I noticed the graph that’s present in the web app is excluded from the PDF
Data visualization is the goal here, so when a feature removes visual information, that’s something I want to take a closer look at
Granted, a PDF printout isn’t the sexiest thing to redesign, but it is an often overlooked feature that will go unnoticed until a user really needs it. I think that if you can’t get the small details right, like a PDF, how can you hope to execute on the big ones?
Feature Selected: VengaDine’s Pre-Shift Report Printout
Personas and use cases
Persona: General Manager
Focused on efficiency, customer service and turning tables
Place high value on products that are fast, reliable and easy to reference at a glance
Working in restaurant conditions, which can be loud, crowded, chaotic, dimly lit, and high stress
GM of Fennel & Fog, a hip new 6-table restaurant, needs to impress first-time clientele and reviewers. Intimate (cramped) and cozy (dimly lit) atmosphere and 2 seatings/night. Still ironing out back-of-house kinks. The GM is also colorblind.
GM of JUMBO, the largest restaurant in the city. Several hundred covers/shift. Speed of service and reliability of guest management system critical. Nearby thunderstorms have knocked out internet service. Phones unaffected.
Some restaurants don’t have color printers, so all printouts need to be readable in greyscale
The restaurant atmosphere may be ‘romantic’ and candlelit, so considerations like readability in low-light environments need to be considered
Internet connectivity can’t be taken for granted. Outages are common
When it’s busy, managers need information available at a glance and easily referenced
The service industry lives and dies by Yelp reviews. A positive customer review is critical to the bottom line
UNMET USER NEEDS
Printable PDF export with graphs and tables for reliable, off-line reference
Easily readable in dimly lit environments
Preferably one-page for ease of use
Accessible for visually impaired, including colorblind and farsightedness
Simply adding the missing graph back into the document increases usability tremendously. The GM can easily see when the restaurant will be busy.
But what happens if the GM is colorblind…and in a dim restaurant? Is the document still usable?
Graph starts to lose fidelity, but data labels still visible
Simulated Colorblindness & Dimly Lit Restaurant
Graph is largely useless and data labels can’t be read
Sadly, the document ceases to be useful under these use cases. Could changing the graph type improve usability?
The circular arrangement of bars is suggestive of a clock. Even in dim conditions, it might be possible to read the relative position and length of the bars on the clock face without needing to see it clearly.
Same as the previous chart, but with an added data series that could be adapted to show different classes of party sizes.
With simulated darkness applied on our new version, the user is able to see the positioning of each bar around the clock. They don’t have to be able to read the data label to get the information they need.
User testing and iterations
Refine data series for the graphs and color choices (optimize for use cases)
Experiment with data table formatting to fit more on a single page
Collaborate with Development to gauge level of effort for implementation