Ryan – The Bittesuite

4 of the Funniest Things People Think about Americans

Some call them stereotypical through disgusted grimaces. Some call them edgy through wry smiles. Still others call them signs of cultural harmony with glistening eyes.

Whatever you call them, and however you do it, there’s no denying the power of a cross-cultural joke to turn heads.

Among them all, there’s a certain flavor of cross-cultural joke that I find particularly funny. I’m not talking about “Why did the Italian cross the road?” or “What do you get when you cross an American with a Bolivian?” or “A German, a Russian and an Englishman walk into a bar…” Rather, I’m talking about a brand of joke you might encounter every day without even realizing it’s been made–a Seinfeldian brand of observational cross-cultural humor.

Wondering what I mean? Here are the funniest, most often repeated observations about American culture I’ve heard so far.

Let’s do this!

#1 Gun Ownership

I’m in a seminar called Behavioral Pricing. Our lecturer shows us a German advertisement for food that promises a donation of 1% of every sale to a small, local farm. The discount is an example of a psychological tactic that links the purchase of that food with “fairness,” which is evidently a very common and deeply-rooted German value.

A classmate raises his hand to ask a question. “But something like that wouldn’t work in all countries, or?” (he’s German) “In America, for instance, they don’t seem to care about ‘the little guy’ as much.”

“Yes, of course you have a point,” replies the lecturer. “The nature of the market will always determine whether or not a tactic is effective. Maybe if they promised to donate to small gun makers, or something…”

The lolz were real that day.

#2 Cavalier Capitalism

Gonna power that death lazer. Image Source: dailymail.co.uk — Gonna power that death laser.
Image Source: dailymail.co.uk

Especially among the people I’ve met on the entrepreneurship/management side of my master program, the U.S. is sometimes half-respected, half-mocked as a sort of test bed for commercial innovation. They cite the amount of money a startup can raise from a single venture capitalist in the States (millions, compared to hundreds of thousands at best in Germany). They also cite the number of banned substances in the cosmetics industry (1,371 in the EU, only 9 in the US).

Your chimp-powered death laser idea might hit all sorts of red tape here in Europe. Go the US, find the right investor, and you’ll have your monkey motor case studies in no time.

#3 American Friendship

Our friendship is not Western European friendship. We’re friends with our barbers and hair stylists. We’re friends with that coworker who got drunk and told us he hates his boss. We’re friends with the mailman (but not that other mailman). If we’re familiar with someone and we don’t hate them, what other option is there?

I’m exaggerating, but that’s what American friendship seems to look like to a lot of Europe. And, let’s be honest, it’s not very far from the truth.

Western European friendship is different. Classmates? No. Coworkers? No. That girl who’s always at the same parties as you? Not even her. “Friend” is a really special word. It might mean something close to what “best friend” means to many of us in the States. A friend is one of your go-to people, one of your secret-keepers, one of your crew. Not one of your acquaintances.

My favorite example of this joke in action happened two months ago. I’m in a seminar, listening to a small business owner talk about the business they own. His product is a social networking smartphone app that lets a group of friends go on multi-dates with other groups of friends they don’t yet know.

One of my classmates asks “How do you guys ensure that creeps don’t sign up with your group and ruin the evening for everyone?”

The business owner grinned and said “Well, you have to really know the people in your group before you sign up. We are promoting real friendship, here. Not American friendship.” The class just ate that up.

I guess a good way to sum this all up is that we from the US will get to know you by inviting you to our apartment for the pre-game with our best friends. Here (at least in Germany), you can just meet us all at the bar. What are we? Friends or something?

#4 Donald Trump

#makedonalddrumpfagain — Source: Reuters

At home, this guy is scaring the hell out of a lot of people (partially by making so many of those other people so happy). Here, at a safe distance, he’s just…well, okay he’s still scaring the hell out of a lot of people. Remember this? Now, imagine Donald Trump in old Georgy Boy’s place. I’m so sorry I just made you do that.

Trump comes up whenever politics comes up, recently. Every single time, the conversation starts in the same way these two did:

I’m sitting in a classroom, waiting for a seminar to start. A few minutes go by and my Irish friend Mark walks in the room. He puts down his things, walks across the room to where I’m sitting, rests on a nearby desk, and smiles. “So. Uh. Donald Trump?”
I’m sitting in a restaurant with some friends, waiting for the rest to arrive so we can set the food in motion. Swedish friend Erick arrives. After a brief moment, he walks over to my chair, places his hand on the back of it, leans in and smiles. “So. Uh. Donald Trump?”

Every single time.

What if We Stopped Learning to Speak Other Languages?

When’s the last time you learned a second language? What was learning it like?

I’ve been learning second languages for awhile, now. I made it through the German classroom circuit about a year ago, and now I’m in my streets phase with the language. In college, I studied Mandarin. As a child and then again in Junior High and High School, I learned Spanish. Sure, every language has its weird/unique mind games it can play with non-natives: German breaks more rules than it even has, learning to speak and write Mandarin basically means learning two languages at once, and Spanish has as many verb tenses as it has polite expressions that mean something dirty if you wink while you say them (lots and lots).

Despite the idiosyncrasies, learning a language is always the same in at least one respect: you can understand it before you can speak it.

And what was it like when you started using that shiny new second language you studied? Or, what’s it like using it now that it’s worn, flexible and maybe a little dirty? Have you ever wished you could simply communicate in your native tongue for just one second because you knew you’d be funnier, smarter, friendlier, more eloquent if doing so were appropriate?

Those two ideas have been stuck in my head for a good while, and they’re really making me wonder if life would improve if we all stopped learning to speak second languages. I know, I know, there’s at least one huge problem with that. I’ll get to it in a bit.

For now, imagine what it would be like if you only had to learn to understand other languages. For one, it would be much easier to integrate one’s self into a foreign society. When it comes to understanding, you’re usually ready to go after a few months in a local language class. If teachers could remove all of the speaking exercises from class, fluency in understanding would come even quicker. Perhaps this would make learning more than one second language more common (among those who aren’t officially language students or don’t speak a Latinate language natively).

An implication of this is that learning a language could be an exercise in adaptation rather than preparation. We could wait until it looks like needing the language is likely before we commit to learning it. Contrast that with the current approach: we spend years before and during college learning a language that might never be relevant during our particular lives. I, for example, studied Spanish as a child, because Mexico and Texas are sharing each other’s cultures more and more every year. As it turns out, Spanish has become very useful to me during my particular life. My girlfriend is Mexican, after all.

And now we live in Germany. Predictable needs for language skills, right?

Another aspect of life made better is maintaining proficiency in a language when you’re not using it. Lack of practice has to be the most common reason people are weak in a second language, even though they’ve studied it. My Mandarin was great when I was in college. Now, I sound like I’m trying to teach myself quantum physics, and that’s because I’ve been in precisely 0 situations that demanded my control of Mandarin since then.

To practice speaking, you need a speaking partner. Until you move to the country that speaks your second language natively, finding a speaking partner is tough. Practicing listening, though? Honing your ability to understand the language? That’s a piece of cake, no matter where you are. Subscribe to a podcast, tell YouTube you live in the language’s home country, watch movies in that language, find music on Spotify, Google online news media in the language, download a language pack for that video game you play once a day, change the OS language on your PC. Options for improving understanding are all over the place.

So, what would a bilingual conversation feel like? I think it feels really cool. Roxana and I have them every now and then. The results are maximum clarity and almost maximum comfort for both parties–Rox freaks out a little bit after a few minutes of conversation 🙂 Incidentally, this is also how almost the entire television show “Lillyhammer” works–the main character speaks English, while every other character speaks Norwegian. Bilingual conversations look cool, as well.

I’ve tried the approach with some German friends (without them knowing this is what I was doing). For about a minute, we’re having an especially cool conversation. They’re speaking German, while I’m speaking English. My mind feels fresh and energetic. I’m relaxed, as I assume are they. After the minute, though, my German friend will usually switch to English, presumably because they think I prefer English and they want to be nice. Then, I feel lazy and switch to German, and by the end of the conversation, I’m tired. It’s ultimately a really good mental exercise, but I’ve learned without a doubt that speaking is more mentally taxing than is understanding.

Despite its coolness, this supposed solution does not solve an existing problem. We could call it the Lingua Franca problem.

Today, the western world’s Lingua Franca is English–it’s the bridge language that most commonly connects people who don’t speak each other’s native language. If the bridge doesn’t connect both sides of the conversation, however, communication is not possible. That’s not necessarily praise or criticism. Just reality.

The “understanding only” system I describe in this post doesn’t fix this problem. At best, a conversation in the “understanding only” system would be one-sided if the language I speak doesn’t appear on the list of languages you understand. Communication between us would not be effective, unless you were my boss and our company ran on peon blood.

In fact, there could be no Lingua Franca in the “understanding only” system. We’d all be proficient speakers in only one language. If everyone on earth learned to understand English, that would mean nothing if the English-speaking world refused to learn to understand other languages. Or, what if English speakers tended to learn other languages, but not my language? That would suck–I would need to learn to speak English, even though speakers of other languages could get by with their comfortable native tongue.

And UN meetings would probably be complete messes.

But, every solution to international communication so far has its problems. It’s hard to motivate the world to learn and practice Esperanto. And, when an existing world language is the Lingua Franca (the current system), that arguably gives countries where the language is native an upper hand on the world stage.

Thought experiments are fun, aren’t they?

Professional Words and Phrases that Can Get You Into Trouble by Accident

If there’s something they don’t teach you in school, then it’s the “human” side of your future career. In marketing classes, you learn how to figure out how to reach people, what to say to them, how to figure out what they want, and whether or not a marketing program is worth it. In finance classes, you learn how to turn the next 10 years of a company’s or project’s “probable” performance into a single number that means either “invest” or “ignore.” In Engineering classes, you learn how to make kickass robots or something.

On the job, however, there’s routinely something in the way–something that redirects our marketing program at the “wrong” people, something that second guesses our valuation of a company, something that transforms our kickass robot into a somewhat interesting home appliance. They’re called people. And, truth is, their influence is largely positive, despite early-career feelings of the contrary. Assuming the human side of your job is constructive instead of corrosive (also possible), these people have caught our mistakes, mitigated our oversights, focused our ideas, and augmented our original contribution. Our original idea is now better than it was before.

That’s all peaches and rosewater–the power of teamwork, catalytic trust, construction through criticism and other what-have-yous.

Being human and being surrounded by them isn’t all productivity and optimization, however. There’s at least one aspect of the human side of The Career that is more often than not a shame and better off avoided entirely. It involves our words or, more specifically, that understanding them means interpreting them, and interpretation is by definition subjective and biased. People routinely receive messages others never sent, is what I’m trying to say. Here are 5 of the most hilarious words at the heart of this problem. Buckle up.

Recommendation

Many, when “recommendation” enters their ear holes, hear the word “mandate” or “directive,” instead. They perceive a loss of control over their own programs, and light their torches for the coming battle. I’d believe you if you told me that some people do use the word “recommendation” to soften a directive or a mandate. And, I’d agree if you said that never helps anyone. In most productive relationships, however, “recommendation” means “ideas that you may find helpful.” Take these relationships, for example:

– Consultant/Executive

– Agency/Client

– Analyst/Program Manager

– Adviser/Decision Maker

In these relationships, the consultant, agency, analyst or adviser has done some work for the executive, client, program manager or decision maker in order to help them solve a problem. After the work is done, the consultant/agency/analyst/adviser has perspective on the issue. They apply this new perspective to their expertise and come up with a list of recommendations meant to help the executive/client/program manager/decision maker solve the original problem. The expectation is that one of these things happen:

– Springboard: The decision maker doesn’t want to implement the recommendations as they are, but the recommendations do inspire new ideas that the decision maker thinks will work.

– Catalyst: The decision maker likes the recommendations and has some ideas of their own to make them even stronger.

– Solution: The decision maker likes the recommendations and wants to implement them as-is.

If the decision maker can’t do one of those three things, then the analyst can cry bitter nerd tears into their copy of Web Analytics 2.0. Seriously, I’m worried that one day I won’t even be able to read it, anymore.

Improvement

This one tends to hit a little harder than “recommendation.” When this word is misunderstood, it seems to mean something like “you suck” or “what you have here is garbage.” In my past, when I’ve played the analyst role and used this word, doing so has begged questions like “so, what exactly went wrong?” or “why don’t you think this was a good approach?”

In reality, an improvement is just a thing that makes another thing better. This means that the improved thing could have been “good” before the improvement, and the improvement is designed to make it “good + 1.”

The mindset that suggests the improvement believes that continual improvement is the mark of a successful or “good” program. It’s the reason why asking an analyst if a metric’s value is “good” or “bad” will turn the analyst’s face into a blank slate if your program doesn’t have its history documented. The “good” value of a key performance indicator is the one that’s better than it was last time.

Anyway, if the program’s outcome rate isn’t 100%, then outcome rate is a candidate for improvement–even if it’s 85%. If bounce rate isn’t 0%, then it’s a candidate as well. Any given program likely has a handful of improvement candidates at any given point in time. In fact, if an analyst ever reports back with “wow, this program is really great–keep it up!” without “and here’s how to make it better,” and the program didn’t just secure world domination for your company, then they’re either buttering you up, or their analysis was lazy. A particularly powerful approach I’ve found in my analyst roles is honing in on one single candidate for improvement and recommending the hell out of solutions for that candidate. Brand recall was 86%? How do we push it up to 90%? Typically, what makes an improvement candidate worth an obsession are that a) it makes the program significantly better and b) it’s easy to implement. Of course you’d make the easy improvements, first. Of course.

Next time the program is run, the program manager has made one significant improvement and is in a position to identify a new set of improvement candidates. This assumes that the program is more or less achieving the goal(s) the program manager set for it. Otherwise, you’re looking for fixes, not improvements.

The reason this tends to work is that improvements don’t occur in vacuums. When you improve one aspect of a program, it’s possible that…things…happen to the program’s other aspects. Implementing a batch of apparently separate improvements at one time may not have the effect the program manager expected.

Traditional

If you’re working at a company at which “traditional” is a bad word, then you’re celebrating far more than lamenting the misunderstandings. Sometimes, however, “traditional” is a word worth using, and that’s because its meaning is relative. Just like it is with every other adjective in every language. Compared with programmatic ad buying, negotiated/direct buying is traditional, even if the sellers are mobile apps and the format is rich media. Nothing wrong with that.

If you’re having a discussion about programmatic buying, and the program manager is unhappy that there won’t be an account manager on the seller side working with them, then what they prefer is a more traditional means of ad buying. Nothing wrong with that. Traditional is known, and known comes with its own set of benefits–security, feasibility and speed are usually 3 of them.

So, “traditional” can mean “the geriatric way” when it’s misunderstood. In the worst of cases, that’s exactly what the speaker means. In a productive relationship, it’s just a way to say “the usual way.” Nothing more.

This one really isn’t a very big deal, though. It’s just as easy to use other words that don’t describe an idea’s age (“He’d rather negotiate ad placements” may even be more communicative than “He’d rather buy ads the traditional way”) so it’s rare that “traditional” is a word that needs to be used.

Problem

Solving problems is arguably what anyone who’s good at their job does for a living. Gophers are problems for Groundskeepers. An imperfect record is a problem for a Football Coach. CO2 emissions, dependency on oil and a need for more speed are problems for Engineers (in a fantasy world without the auto industry, I mean). Their company not possessing all of the world’s disposable income is a problem for Marketers. That the entire company can’t immediately retire happily is a problem for Program Managers.

You get what I mean.

So, it’s a bit of a wonder to me when some colleagues flinch at the word “problem,” especially since so many people openly pride themselves on their “problem-solving skills” when they’re not in the middle of solving one. Without problems, there’s nothing to solve. Without something to solve, there’s no work to be done. Without work to be done, there’s no need for employment. Without employment…wait a minute…

Kidding aside, there’s nothing wrong with a program if it still presents problems to solve. That’s expected. At least that’s the case when you’re talking to an analyst. Only you can be sure what your boss means when they point out problems with your work.

Data (also: Insight)

At least as far as I’ve seen, doing business and doing science are two different things. When one sciences, they’re looking for knowledge–knowledge that gives reality just a little more definition. They (and especially their peers) hold their results to really high standards. There are 7 ways scientific results can be valid (correct) and 5 ways they can be reliable (reproducible). Even in social science, in which statistical analysis and interpretation tend to play stronger roles than experimentation, the researcher’s methods, strategy and analysis techniques will all be scrutinized before their results are allowed to leave the notebook. “Are you measuring what you think you’re measuring?” and “Are you measuring something general or esoteric?” are at the heart of much of the scrutiny. Data says something concrete to the researcher and their peer community, so there are such things as “good data” and “bad data.”

Business is different. Experimentation and data analysis do technically thrive in the most successful business programs. What doesn’t tend to matter nearly so much are the validity and reliability of those experiments and analyses. It doesn’t matter if we can’t be sure we’re measuring exactly what we think we’re measuring. It doesn’t matter if our program’s results can’t be generalized to describe the likely results of other programs. This is because, rather than seeking knowledge that helps us understand reality, we’re seeking insight that helps us make a decision. Data in this case are only as good as the decisions they inspire.

While a scientist cares about single measurements (10% of the population hate cookies really needs to mean that 10% of the population hate cookies), a business person cares only about trends and segments. It doesn’t matter that 0.75% of a website’s visitors clicked our banner ad this month. What matters is that 0.68% clicked last month and 0.50% the month before that. Or what matters is that our ad achieved 0.75% while another ad grabbed a full 1.0%. We don’t know how many of that 0.75% were bots, or page refreshes, or repeat visits, or visits from our coworkers because they were testing the ad at a coffee shop and our analytics software doesn’t filter the shop’s IP address. 0.75% is meaningless. When we say we’re measuring an audience’s response to our ad, we’re not sure that that’s actually what we’re measuring. And that’s not a big deal.

Three months of traffic increases summing to 50% does matter, though. This is especially true if we were split testing ad elements each month. The incremental increases suggest to us that the changes were improvements, and give us hints about what tends to inspire action among our audience. Here’s the catch, though–which hints the data are sending depends upon the person doing the analysis. One analyst sees a trend toward “friendlier” headlines each month, and then attributes the increasing effectiveness to friendly language. Another sees a pattern toward increased clarity–each headline was shorter than the last and spelled out benefits which were more concrete each time. Each will offer a different recommendation to their program manager at the end of an ad run–one will say “friendlier language” while the other will say “be more specific about benefits.” You won’t know which recommendation was more insightful unless you test them both.

And that’s when data are truly playing their role in business. Data isn’t the language of some behavioral code–it doesn’t tell you what to do. It whispers suggestions about what’s happening, and the human analyzing it has to turn those whispers into insight that fuels a recommendation. Data collection and analysis enables what people in suits call “data-driven decision making.” In terms of the benefit the approach affords a program manager, it enables “systematic decision making.” The program manager can make decisions with purpose–when one doesn’t work, they a) know it and b) can pretty easily figure out a way to make a different, educated one.

It’s a little bit of a shame, then, when people hear “data-driven decision making” and interpret “automated decision making.” Some such misunderstandings inspire strong resistance to analytics programs. Others inspire crippling dependence on them.

People Who Will Drive You Nuts: Munich Edition

Nothing on this planet is more selfish, careless or downright evil than a stranger. Am I right? Just think about one of those jerks right now. Who does he think he is? What’s her game, anyway? You’re getting angry now, right? Good.

As I was saying, strangers–the most selfish baskets of turd sandwiches in existence. What’s terrifying is that they live in every city on Earth. Even yours. In Dallas, for example, one such person wastes half of every green traffic light just sitting in front of it in their car. Maybe they’re putting on makeup. Maybe they’re texting. Maybe they’re shaving. Maybe they’re brainless.

In New York, I’ve heard that the most annoying of these jerks are the ones who will cut in front of one or more lanes of traffic just to make a left turn. Waiting a block to turn is for chumps.

This post is about Munich’s brand of jackassy stranger, complete with hilariously rage-inducing photos. The photos aren’t mine, but I’ll tell you where you can find the owner. I thought about photographing these people myself, but every time I try to imagine doing so, this happens in my head:

Selfish Douchebag: “Hey buddy, did you just take my picture?”

Me: (Laughing awkwardly) “Uh, yeah, sort of, I guess.”

Selfish Douchebag: “Why?

Me: “Because you’re being an ass, and I want people to see this on my blog.”

***

Anyway, let’s do this!

1. Person Who Leans on the Pole in the Subway Car

Either start dancing or give us some room. Source: towngrump.wordpress.com — Source: towngrump.wordpress.com

If you’ve ever seen one of the poles in a subway car before, then I don’t need to tell you how awe inspiring they are. For less raw material than it takes to make a car door, you can prevent 7-10 people from becoming human missiles during a train ride. Breathtaking.

Sometimes, though, you encounter a testament to human evolution like the person in the photo on the right. They see all of that tasty surface area and think to themselves “Finally! My entire back has been begging me all day for one of those!” And in their comfort, they never realize exactly how much chaos they’ve prepared to set in motion.

They will, though. All subway cars need to turn at some point, and when theirs finally does, 6-9 people won’t be holding onto anything.

2. Person Who Only Opens One Door of the Subway Car

For a calorie cost more or less equivalent to opening one’s eyes in the morning, you can double the size of the hole in that car, allowing untold numbers of people freedom from their BO prison on rails. If that realization just took your breath away, then you know how I feel. Exactly.

3. Person Who Stands on the Left Side of the Escalator

Very few places in your average developed city inspire hurrying more than underground metro stations. Even in a well-run city like Munich, they all fall on a continuum between two evils: Really, really boring (Feldmoching) and completely drenched in urine (Marienplatz). You want to spend the absolute minimum amount of time possible in those things, is what I’m saying.

Fortunately, you can look forward to the escalator–a time-saving marvel of the modern world. Imagine taking the stairs with the gift of super speed, and you’ve just had the same dream as the inventors of this godsend. Outstanding.

Then, you run into this turd basket. Everyone else is in the most politely organized single-file line you can imagine along the right side of the escalator. They’re making way for anyone who would rather walk their way to freedom from the metro’s bowels. This human blessing, however, is casually spaced out and standing right in the middle of the path they created.

I think the esoteric term for this kind of stranger is “tourist.”

4. Little Old Lady with Jacket and Bag

She’s older than the average fossil, smaller than the average toddler, and she’s somehow going to be in your way for the next 20 minutes of your walk.

She’s also completely immune to any attempt to get her out of your way. Because, you know. Old. If doing anything in this life causes dead kittens, then harassing little old ladies is one of them.

Being stuck behind one of these will very likely push your heart rate to the brink of time travel. But on the bright side, she’s adorable. So there’s that.

How Education is Different in a Master’s Program Taught by Scientists

My Bachelor was a dual-study in Business Administration and Advertising. Along with Engineering and Journalism, they’re probably two of the most practical academic programs on the planet. That is, they teach you things like these:

1. A fast 80% is often better than a slow 100%

2. Data analysis only needs to inform a decision, not yield The Truth

3. The best idea is the one you can get people behind

Arguably, those insights are really good fuel for success in business. Those programs were exactly what I’d hoped they would be.

After Bachelor, I went to work in Marketing for a large tech company. Those three insights above and a host of others resurfaced again and again on the job. My teachers seem to have known what they were talking about.

My Master’s program is more scientific (put your torches down, natural scientists–I just said “more scientific”). This time around, we’re learning how to beat a dead data horse into the ground in order to conclude exactly how right we can claim we are at the end of a sociological study. You’re only 80% sure that your study didn’t yield a false-positive result? Get back to your political polling, noob. It’s exactly what I’d hoped it would be.

I can stop there, for now. The point of this post is obvious–a Master’s program taught by scientists is a lot different than a Bachelor’s program taught by industry veterans. Here’s how:

1. “How right?” vs. “Not obviously wrong”

In the sciences, your audiences will usually be wondering how right you are–how comfortably they can consider your results an insightful description of something real. The quantitative side of this is obvious–which test did you run, and how significant are its results? There’s a number there. That’s pretty much the end of the story.

There’s a qualitative side, too. “Which model did you assume?” is one qualitative question. If you assume a linear relationship between a set of explanatory variables and an outcome variable, but the scientific community really thinks the relationship should be exponential, then your study’s a bust. It won’t get published, and your results will never enter conventional wisdom. Theoretically, the correct answer to “how right?” is “100%.” However, I don’t think any scientist will expect that any results are 100% correct, even if the data suggest that they are. Instead, you want to be 90-100% correct. Unless you’re into theory generation, in which case you’re a salesperson.

In school, this means that a successful project results in your thorough understanding of what’s already known. For instance, I’m taking a class called “Value Chain Economics.” It’s microeconomic theory applied to optimizing an industrial chain from start to finish–from raw materials gathering to finished good shipping. Our capstone project is exactly what you’d expect–analyze a value chain, identify its problems, and recommend a solution to one of them. In a business or ad program, we would be expected to gather as much insight as possible and then craft an original solution. Inductive logic usually feeds original solutions, so we’d be applauded for reasonable leaps in logic. In this program, however, one of the questions our graders are going to have is “how can you be sure this will work?” (contrast with a business professor’s “Why do you think this will work?”). This makes looking for case studies that document a solution to the problem a viable strategy.

“How right” rarely seems to matter in business, though. “Not obviously wrong” is what matters. You come up with a theory, get your colleagues behind it, run a program, and then determine and document how well the program performed. That’s where good business knowledge comes from. Plan, execute, evaluate, optimize–that’s the stuff, and it involves a lot of celebrated failure. It works, because it’s fast and, online at least, cheap. If your aim is making people aware that your product can fly, and your marketing plan involves a bunch of networking events and keynote presentations, then your plan might fail the “not obviously wrong” test.

2. A Master’s Student is Not a Student–They’re an Intern

I don’t know if it’s just because we’re not learning the basics anymore, or if it’s because scientist/professors are selfish, but I’m extremely suspicious that most of our projects are meant to help our professors do their jobs as researchers. If they teach us something as well, then hooray for two birds.

In “Conflict Resolution,” we’re supposed to identify a natural resource conflict, analyze it and propose a strategy for alleviating it. Sounds great, right? I still think it does. However, our professor is paying WAY more attention to those of us who chose mining-related conflicts than those who didn’t. And wouldn’t you know it, that’s the subject of her research. What a coincidence! Those poor “whaling conflict” groups.

This may be because the scientist/professor’s career is still active and tied to the university. In my business and ad programs, the professors had to be enticed away from industry jobs to finish out their working days teaching the next batch of young thems. In their case, teaching was their core function, and presumably that’s why our projects back then were extremely educational, but likely had very little use outside of our final classroom presentations (unless the subject companies were looking for ideas).

3. 80%? Are You Kidding Me?

Remember the “Fast 80” insight with which I opened this post? My worldview is informed by that insight to a large degree after Bachelor and those three years at the tech company. It makes an awful lot of sense–you’d be surprised how often you’ve done what you need to do by the time you hit the 80%-of-perfection point. In any case, I think its real value is in reminding us that it’s usually time to wrap up a project before we consider it truly perfect.

This difference is funny, because it affects the way we classmates interact with one another.

Our program probably contains equal numbers of what we’ll call “academics” and “industrials.” Industrials like me plan to continue in the business world after graduating. Academics want to keep doing research and get published. 80% is simply not enough for an academic, and trying to pitch them on the idea will drive them crazy.

An example of an industrial-academic conflict is this: some research says that plastic takes an average of 450 years to degrade naturally when thrown away. Other research says it takes 1,000 years. The industrial thinks “it takes a long time,” and just includes 450 years in their presentation to err on the conservative side. “It takes a long time” is really what the audience needs to know. The academic, on the other hand, needs to know which one is correct, or how it’s possible that both are correct. In a team’s context, as soon as the industrial settles on 450, the academic has a panic attack as visions of a declining final grade flash before their eyes, even if the decline envisioned is a 96% to a 93%.

I’m finding that this dynamic fosters extremely effective teamwork, however. In business school, everyone’s obviously an industrial. On the worst of teams, that leads to a lot of fudging–“eh, it’s close enough” adds up enough times to drive the final result so far away from insightful that the project ends up being a lazy, useless buzzword salad (startup company elevator pitches?).

Presumably, then, the worst of teams full of academics will have the opposite problem. They will have real, specific knowledge to share. They’ll have tons of it, in fact–so much that they have a hard time justifying cutting any of it out of their presentation. Collecting that knowledge took a lot of time and hard work, man! On presentation day, they give 250% of a presentation to a sleeping audience who already heard the industrials’ presentation a month ago.

You see where I’m going with this: the mixed industrial/academic team is really beneficial to both types.

So, there’s a taste of the differences I’ve experienced transitioning from a practical study program to a theoretical one, from business to science, from Bachelor to Master. Do you have similar or different experiences? Light up that comment section.