How Would You Like Your Coffee?

I found the following quote: “Do I like my coffee black?  There are other colors?”  (And there are other colors depending upon how much milk/crème/water one adds.)  Most of the world, there are different varieties not listed here, such as Greek Coffee, but the world drinks coffee

Here in the United States, the UrbanCoffee.com lists that 64% of American adults daily consume coffee.  That’s a lot of people, but where do people get their coffee?  Most brew their coffee at home, as this graph from Coffee Brew, but there are numerous places to get a cup of java!

But the real question is not much coffee we drink, but how dependent we are on coffee imports. Hawaii is the only state that grows coffee, with over 6,900 acres producing over almost 12,500 metric tons of coffee beans in 2020-2021.  In 2020, the United States imported almost 1.5 million metric tons of coffee.

So, where did all this coffee come from?  The top import sources are Brazil, Colombia, Vietnam, Nicaragua, Guatemala, but all coffee producing area ship coffee to the United States.  And as this is mostly shipped through the nation’s ports (except for Mexican beans that move through various land crossings), the largest import gateways are New York, New Orleans, San Francisco, Charleston, Baltimore.  I am doing my best to help New Orleans be number one, but no one really knows where a roaster sourced their coffee!  

So, when you have your next cup of coffee, and enjoy that first ship of goodness, remember that your coffee is the end of a global supply chain.   I’m off to get my favorite cup of coffee, one that is “As Black as Night, As Strong as Death, as Hot as Hell, and As Sweet As Love.”

 

 

Stirring in Training With Some Coffee

Last week, I went to a coffee shop early in the morning to get some work done. The morning staff, a barista and a chef, were working hard. The barista was overwhelmed with drive-in orders. She asked the chef to assist, which he did, and here is where the morning got interesting.  

The cook became frustrated. Obviously, he did not want to help but felt compelled to do so, as he was prepping the day. And once he started with my order, his inability to work the cash register was noticeable. He could not figure out how to put in a black coffee, and when I presented him cash, the drawer was not prepped. He was managing his rising anger, but it was noticeable which I expect for the following reasons:

  • He did not want to handle orders (he’s a cook and was prepping his day),
  • He was not trained in how to work the system (or he never assumed he would do this),
  • Maybe he felt that the job could not be that hard, or that he should be able to figure this out,
  • The person before him did not prepare him for success, as there was no change in the drawer. (The problem of everyone paying with a credit card?).

But the barista could have done some things differently:

  • The cook had to ask the barista for assistance several times, making her less effective in serving her customers. 
  • Maybe the barista could have rung up the order and he could have prepared the beverages. I suspect the barista’s focus on the next immediate task and not the total work at that moment seemed confusing to the chef.  

So, the takeaways?

  • Know all the tasks you may need to engage in during your day. Although you may not be the expert, at least training and understanding of distinct roles could be beneficial.
  • Understand what your teammates are doing and what they can bring to address a solution.
  • Say “no” if you know you cannot do something or at least offer an alternative to the original suggestion.
  • The manager who encourages teamwork should also encourage understanding boundaries and training. No one wants an overly willing teammate who is unable to contribute.

The manager did not know how to plan for the workload – within 20 minutes, two more baristas showed up! We have to remember we do not control external inputs.

How much will you pay for a bottomless cup of coffee

close up of coffee cup on table

Often we don’t think about coffee refills, as most diners will try to keep your cup full. For most restaurants, refills are free. As such, it is not uncommon for people to have a few cups of coffee. If someone is bringing you coffee, it is easier to keep the cup full than if one has to get up and walk to a coffee station. (And for most people, no one wants to refill the almost empty pot!) So, you make a decision concerning how much effort do you want to spend to get that next cup of coffee? But some people will go to the extreme! Especially if one tries to drink 60 Cups of Coffee!

https://youtu.be/e0SdBEKbZ7E

This raised the question, economics utilizes the concept of utility. One of the concepts is that there is a decline regarding new happiness for each unit consumed. For example, drinking one cup of coffee may be existing, but when you get to the fifth cup, the perception of the utility (enjoyment) of drinking the coffee may decline, even if the quality of the coffee remained unchanged. So, really, did the person really feel better after drinking the 60th cup of coffee? I don’t know, but I think Frank and Earnest would agree.

Buying a Cup of Coffee – Data Becomes Wisdom

The Ancient Mariner could have as easily said “Data, Data, everywhere”,  as discussions regarding big data and other analytical approaches seem to be the order of the day Wall Street Journal.  We often make data out to be this mysterious element, but data requires context to be useful to anyone if they intend to make a decision, as I hope to show below.  For example, data becomes information when it is categorized, which then becomes intelligence when a decision can be made, and ultimately wisdom when an action occurs based on intelligence.

One of my favorite quotes about Coffee comes from Charles Maurice de Talleyrand-Périgor, who said that the perfect cup of coffee should be: “Black as the devil, hot as hell, pure as an angel, sweet as love.”  I would agree that a good cup of coffee is a bargain at any price, so let’s think about how the decision to buy a cup of coffee can explain transforming data into wisdom.

The objective:  I would like to purchase a cup of coffee at Giddyup Coffee in Folsom, LA.  So, I asked the two baristas if I could do take a few pictures for this blog post.  They thought it funny that someone would actually do this, but they agreed.  So, the research question is: do I have enough loose change to purchase a cup of coffee.

 

Data:

Loose Coins – represent Data

There will be a cost of purchasing a cup of coffee, so I look into my coin purse.  These loose coins are simply data points, each representing a certain value.  (Coins contain other information, such as their size, year and place it was minted, as well as the coins condition based on circulation.  These data points are not relevant for this purpose are ignored.) However, beyond knowing that I have coins, I do not know if these coins are enough to purchase a cup of coffee.

 

 

 

 

 

Information:  The loose coins now need to be organized before I can actually make a decision, so the coins were put into different categories.  This act of putting the coins into categories, based on the relative value of the coins, resulted in the data about the coins becoming information.

Data becomes Information

Intelligence:  Now that I know the relative value of the coins, I next have to make a comparison.  Do I have enough to actually purchase the coffee with the coins that I have?  So, I add a new data element, namely the posted value of a cup of coffee.  So, the addition of the information posted on the menu allowed me to determine if I could make a purchase with my loose change.

Wisdom:  I bought the cup of coffee, once I had enough intelligence to make a decision based on the cost of the cup of coffee and my loose change.  (Wisdom is the only attribute with a future component, namely, data, information, intelligence are all static elements at the moment a decision is made, but Wisdom will influence my future actions.)

 

I learned this paradigm as the more formal DIKW: Data, Information, Knowledge, Wisdom.  While one could argue that the DIKW is based upon filtering data to make a decision, I changed Knowledge into Intelligence.  I see Knowledge represents a broad body of information, based on many factors, including not only the data itself but the cultural, contextual relationship of the researcher to the topic being researched.  For example, I could have taken the coins to a Coinstar or a bank, or made a different decision concerning these coins.  For my father who abhors coffee (his loss), the research question (can I purchase a cup of coffee) would mean nothing to him,  (much like saying “what does that have to do with the price of tea in China?”!)  For me, knowledge serves not as a filter of the data/information as normally discussed in the DIKW paradigm, but rather a filter through the act of transforming data to wisdom can even occur.

Finally, we can not remove the researcher from the research, but a good researcher should understand what data elements are useful to become transformed into intelligence based on understanding what answer is required.

Here is a toast to your health!