“I could really go for a Hamburger right about now”
It started on an evening in January. Strolling out of the office, Wilson and I look to each other and decide in the moment to trod not in the direction of the Union Square subway stop but down 5th avenue toward a restaurant we’ve heard serves the best burger we’ll ever try.
The Art of the Hamburger
Truthfully, that’s how all hamburgers start. The hamburger isn’t an “I’m gonna plan my night around this” type of food group. It’s something you get while sitting at a bar. Despite the trend of some restaurants toward offering a gourmand burger, the vast majority of hamburgers are consumed by people who look at each other and say “yeah, why not grab a burger?” I don’t need data to support that statement. I just know.
I can also tell you as a long time purveyor of hamburgers that there are a disproportionate number of bars where, hanging in the corner, you’ll find a chalkboard where written in thick washable Crayola you’ll find the claim “Best Burger in Town.”
And the great thing about these hamburgers is that they’re all, with small exception, the best burger in town in that moment. Washed down by a cold beer or an iced tea, a hearty burger satiates like very few things can. It makes you want to lean back in your chair, smack your lips, inhale deeply, and bellow as if you’re at the summit of a mountain. It takes you somewhere.
The burger is an American tradition that greatly interests me, in particular because it is such a curated experience. There are best practices for serving the hamburger that vary but not too far from a predefined set of standards – you must always use a bun, for example; a burger on sliced bread would seem garish and manipulative. And there are a set of toppings – lettuce, tomato, pickle, onion, some combination of which tend to be used while deviations from this norm qualify a burger to be a “specialty of the house.”
One of the things I’ve learned about design through working with Tableau and through other education (I was, briefly, an architecture major in college, an endeavor where I discovered that I was fascinated by the design principles that made up the architectural canon and also that I couldn’t draw worth a damn) is that true beauty in design comes from manipulating a set of restrictions. In data visualization, this comes from pre-attentive visual attributes, generally accepted visualization best practices, and the canvas in which these are presented to the viewer. In architecture, design comes from combining materials in a way that builds upon humanity’s requisites for living.
I love how Alberto Cairo defines disciplines like these as a Functional Art. And in a slightly less socially important way, but one that matters deeply to our culture, hamburgers are a functional art as well. The standards mentioned above govern the creation of an artifact whose beauty can be interpreted not just visually but through other senses like taste, texture, and smell. And because of the fleeting nature of food the art exists more purely in the experience of consuming it rather than through the artifact itself.
Hamburger enthusiasts both, Wilson and I found ourselves on that January after work discussing the merits of the Minetta Tavern burger, often written up was the best in New York, through the language of style – the quality of the beef, the balance of the toppings, the presentation. Can qualitative evaluations like these be analyzed? Can the experience of eating a hamburger be recommended by ratings? How can these experiences be communicated?
And, as many things do for Tableau employees, this led back to an analytical problem.
Ranking and rating are important functions in analytics that are more complex than most people realize. Because ratings usually exist as discrete numbers, consumers often don’t evaluate what went into arriving at the rating – was the system used to determine the rating fair? Are there biases that the evaluators didn’t consider?
In addition to the challenges presented by performing the rating, communicating results in a meaningful way can be quite difficult. Are the top-rated items the most important, or do all members matter? For rankings that represent how an item performs in comparison to others, charts often do a terrible job because they fail to show how much farther apart 1 is from 2 than 2 is from 3. There are entirely different schools of ranking that are appropriate in different situations – friendly or competitive ties, dense or unique numbering.
At Tableau, the topic that Wilson and I find ourselves debating most often is Presidents Club. As a form of employee recognition, sales organizations often recognize their top performers by inviting them to a “quota trip” at the beginning of a year to reward quota attainment in the prior year. It’s relatively easy to rank sales people by how much money the company booked based on transactions they sold. But what about sales representatives that have different quotas? What about presales people who support multiple sales reps? What about managers? How should those people be ranked? And how can the rankings be communicated in a way that is clear and agreeable to the people affected?
Another source of some ratings consternation among people in my job is the Gartner Magic Quadrant. We recently did a podcast about this document, an annual and independent rating of technical platforms with the intention of advising purchasers on products that get the best customer reviews. However, the ratings process is incredibly opaque – Gartner refuses to share their ratings methodology other than two generic measurements of “Completeness of Vision” and “Ability to Execute,” neither of which have a clear numeric connection. The results are published in a scatter plot but it’s impossible to know how the ratings correspond to the X and Y axes, if they do at all.
It’s impossible to discuss either of the above two topics, or many others for which ratings are relevant, without feeling personally invested, probably due to the nature of ratings systems as methods for evaluating items in relationship to each other. Wilson and I wouldn’t be good people to present a new and improved version of the Gartner Quadrant from Business Intelligence, because we’d likely suggest, consciously or subconsciously, changes that would favor Tableau rather than evaluate based on criteria that most benefits business intelligence customers. The Presidents Club discussion is even more fraught with opportunity for our bias to get in the way.
But we have no bias when it comes to hamburgers.
Ability to Hamburger, and Completeness of Hamburger
As a way to explore rating systems, share our analysis with others, and eat more hamburgers, Wilson and I have devised the New York Hamburger Magic Quadrant,the intention of which is to build a document that evaluates and communicates the ratings for hamburgers from New York restaurants.
To start, we’re basing our rating system on Gartner’s, and while the name of each axis in our rating system is somewhat tongue-in-cheek, the process that results in those metrics has been taken seriously.
Our presentation will look like Gartner’s, but we will not hide the factors that contribute to our ratings process from our audience. In addition, the ratings will be adjusted upon revisiting some of the restaurants included therein, and to account for new information that might affect our evaluation. Here’s the process:
- Wilson and I have devised a list of restaurants that we have heard serve excellent hamburgers. We expect this list to grow over time.
- We’ll attend these restaurants at a rate frequently enough to populate our ratings list but infrequently enough to not overload our arteries.
- We’ll eat a burger, and rate it under each of our two metrics.
Ability to Hamburger is made up of: Quality of Meat, Bun, and Topping Balance
Completeness of Hamburger is made up of: Preparation, Presentation, and Mouth Feel
Each of the six key factors is rated on a scale of 1-10 by Wilson and by me. We then average our ratings to come up with a final rating. As part of our process, we’ll be exploring different options for coming up with a final metric. Is a pure mean the best way of averaging? Or should we weight some of the factors more heavily than others? Does it matter how far apart Wilson and I were on our ratings?
Presented herein is the first iteration of the Magic Quadrant, but we will be publishing updates as more hamburgers are tried.
We also set up some ground rules for consuming hamburgers in order to appropriately frame our ratings and get a consistent sample of comparative data.
Rule 1: Always get the house burger – If you go to a restaurant and there is an option on the menu for The [Restaurant Name] Burger, you must get that burger. It has been curated by the restaurant as iconic of their cooking.
Rule 2: Stick close to the standard toppings – too much topping variance makes the rating system more about what toppings add to hamburgers than about hamburgers themselves. That said, if adding a particular topping would make the experience sufficiently rad, it is allowed. Rad is a scientific term.
Rule 3: Try for the counter/bar service when possible – Not every restaurant offers this, but due to the some what improvisational nature of going to get a hamburger, the counter service seems to be the purest form of burger consumption. In addition, this removes factors like dining room decor and relative quality of service from the hamburger experience.
Rule 4: Beef-based burger – This system exists primarily to compare hamburgers at their essence. That said, there are excellent burgers that use other types of meat, and in some cases no meat at all. We plan on including notes and evaluations of alternative burgers in our document, but mostly as a reference and comparison to the primary form of hamburger. As the quadrant expands, we may find room for more non-beef options.
We’ll be eating more burgers, updating our list of places to try, and evaluating our ratings system as we go. If you’re interested, please provide feedback here or suggestions for places you think we have to try.
Coming soon: a write up of the first few burgers to make the list.
Based on popular demand, we’ve included a map to help share where these burgers are -WP