Beer Tracking: The Trilogy

September 24, 2011 by Gabe | [mmd] |

The Trilogy

This is the opening crawl to a trilogy. Like any good trilogy, it will begin with episode 4 and never, ever speak of episodes 1–3.

The trilogy will describe a quest to find the ideal solution for curating my collection of micro-brewery beers. The quest spans several suites of applications: Bento, OmniOutliner and iWork Numbers. I’ve learned a lot about how I can use these tools and I hope someone else gets something out of this series.

 

The Introduction

I really enjoy high quality beer. I am a home brewer and I cellar a great deal of micro-brewery beers. My stock is approaching 200 bottles of all styles.[1] I decided that it would be a good idea to keep an inventory of everything that I have in my collection.

If you think of good beer like a fine bottle of wine, you want to know what’s in your collection for a couple reasons: 1. Ideal pairing with meals 2. Drink it at its prime 3. Compare and contrast vintages 4. Avoid buying duplicates of bad beers 5. Encouraging buying duplicates of good beers

There are a number of programs for wine cellaring but beer cellaring is different enough, I could not just translate my collection to a wine centric system.

 

Ground Rules

Now, most people probably have no need to inventory a beer collection.[2] However, I think my list of requirements is rather generic and could be applied to many other use cases.

 

Ubiquitous Capture

The inventory should be available on my iPad, iPhone and Mac. When I’m at the beer shop, I’ll have my iPhone with me. If I’m at my bar, I’ll have quick access to my iPad. I want to be able to also sit down with a big screen and comfortable keyboard to annotate the collection.

 

Average Intelligence

I wanted an easy way to add new acquisitions and a simple way to search the inventory. The inventory doesn’t need a lot of intelligence, but I should be able to easily determine the total number of items in the inventory and sort by relevant meta data (see below).

 

Social Drinking

Finally, I want to be able to share the list with friends. That’s one of the best parts about collecting and trying beer. It’s nice to quickly send a couple of recommendations to a friend. In return, I often get good recommendations back. An invetory system should make that process easier.

 

Requirements

For this specific use case, I have a few fields that I wanted to capture for each bottle in the inventory. The majority of the information is less than 128 characters. Some are dates, some are numbers and at least one is an image.

  • Name
  • Brewery
  • Quantity
  • Vintage
  • Purchase Date
  • ABV
  • Style
  • Link (to Beeradvocate.com page)
  • Expiration Date
  • Rating
  • Notes
  • An identifying image of the bottle

To Be Continued

In Episode 4 I will highlight Bento from the former Claris group and now an Apple subsidiary. They are more famously known for FileMaker Pro and making Macs awesome in the early 90's.


  1. I do not collect beers from the large breweries such as Anheiser-Busch. My collection only contains beers that age well and change in complexity and flavor profiles over time. There is no benefit to cellaring a big-brewery beer made to last decades without changing its flavor profile.

  2. I have previously applied a similar model to my software licenses. I think an ideal solution could be used for any relatively flat collection with little hierachical or relational data.

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