Washington, DC is a city of great institutions — the foundations of our republic, historical landmarks, monuments to great men and women, and so many exciting events that you can spend years living here and never make it to all of them. But, throughout my six years in DC, there is one institution, above all, that has soaked up a disproportionate amount of my time and attention: Chef Geoff’s, a classic American establishment not far from the alma mater of myself and my fellow The Postrider co-founders, American University. Just off of New Mexico Avenue, it’s a beacon of great happy hour deals and good times, camaraderie and friendship, with burgers to die for and their infamous “supermugs” to wash it all down in a statement of thrilling excess.
In fact, I go to Chef Geoff’s almost every. single. week. Weekly happy hour became a tradition amongst The Postrider gang back when Michael and I first began working together. It’s now a lynchpin in our lives, as we’ve grown personally and professionally in this great city, and brings us all together each week to have a good time and talk about work, life, love, politics, drama, and everything else over some good food.
In honor of Chef Geoff’s, to live out my dream of being a food critic, and, in part, to finally get noticed for my unusual adoration of this dining establishment, I’ve decided to start what I’m calling the Chef Geoff’s Bulletin (CGB) here at The Postrider: a periodical chronicling every visit, using data and metrics (I am the lowly State & Science editor, after all), and providing a critical assessment of the restaurant. The CGB will be a near-weekly blurb on our visits that can be expanded into a larger analysis over time. In each addition, I’ll list what I ordered, and provide the R-Score for the experience.
I covered the R-Score metric last month as a comprehensive measure for evaluating a dining experience in a fairly objective and standardized way. For more information on the methodology, you can read all about it here, but here’s a fairly quick analysis of how it will be used for the CGB:
- Fare (value over price): This is the quality of the food and drink relative to the price. If the price for the meal was perfectly worthwhile, the score will come out to a 1. If the meal wasn’t worth the price, it’ll come out to less. And, if it’s the greatest meal I’ve ever had relative to the price, it’ll be higher than a 1. This is also how we track price over time. Chef Geoff’s recently raised many of its prices,1Much to my dismay as a consumer, but to my delight as an economist wanting to occupy more of a scarce resource (seats at Chef Geoff’s). so this should make for an interesting starting point. The methodology on evaluating my perceived value is a bit long-winded, so I do recommend reading the R-Score article if you’re more interested in the details, but, in Chef Geoff’s case it revolves around a classic question I face every week: order the burger or order the pizza?
- Service (1-5): This is fairly straightforward. It’s the quality of the service. Waiting a long time for food, drink, the receipt, etc. would bring this score down, while attentiveness and surprise bread for the table bringing it up. Service is weighted the same as fare.
- Atmosphere (1-3): This is the general vibe and pleasantness of the space. Clean bathrooms, good music, and a good crowd are better to have than not to have, after all. Atmosphere is weighted half as much as food and service.
- Time-to-Seat (TTS) (in minutes): This is a frequent struggle at Chef Geoff’s. Happy hour there can be popular, and there are a limited number of seats. TTS factors into the equations as a subtraction from the total score over a standard time of 10 minutes. This means that 10 minutes is roughly equal to losing out on one point of quality in another area or 0.10 overall.
- Above and Beyond (AAB) (binary): This is a potential way to reconcile something else going awry. AAB accounts for anything the restaurants does that’s not usually expected of it (like comping a meal or giving you a free drink). This is a simple binary yes or no indicator accordingly, and it can only increase the score.
These components contribute to a metric that generally fits squarely between 0 (very bad) to 10 (very good) for any given time at the restaurant. And that metric will give numerical data to plot countless visits from here onward. It should make for a unique data story once we’re in the thick of it, and serve as useful testing-grounds for the R-Score methodology. We’ve already got three visits and their data up, and you can track the CGB overall right here.