… Innovating

One of the most important takeaways from school is learning how to think. We go in thinking that we will be taught knowledge, but really what we need to be able to do is take in knowledge and do things with it. We need to analyze if we believe it is true and properly contextualized. Can we convince with it, create new ideas with it, or critically evaluate how truthy it is, in the famous word of Steven Colbert.

One of my favorite classes in business school was Technology Strategy. At its core it taught us how to think. We were taught critical tools that can be used to evaluate and come to conclusions and develop new ideas and concepts. One of the tools we wee taught is a type of trend analysis. Applying it to topics broad and narrow, it can quickly succinctly coalesce many different elements of a topic into a few manageable categories and then allow the user to make trend predictions based on what they observe in the field.

Defining the Topic

The topic can be broad or narrow. I’ve seen trend analysis applied to concepts as broad as work or food service and as narrow as Star Wars. Whatever you want to analyze, go for it. I recommend thinking bigger rather than smaller. That allows you to capture more and not miss something that falls outside the scope of your topic but is related either directly or indirectly.

Step 1: Manifestations

Once you have your topic, start jotting down a list of everything and anything going on in the field. If your list gets long try categorizing these “manifestations.”

Here’s a quick example:

That took me about sixty second. With some more concerted thought and organization it is possible to have an extensive list of what’s going on in the world of beverages, under some broad categories like Products, Availability, and Consumer Preference. Also notice how I defined the category as Beverages, not alcoholic beverages or non-alcoholic beverages. This allows me to explore the interplay between these two types of beverages, and also go deeper into social and cultural trends.

Step 2: Establish Axes

I believe this step is the most important, and can require some refinement after you initially define your axes. Establish two axes that broadly cover the topic at hand. They should be vague and broad and allow for a wide variety of trends to populate a spectrum.

Topic: Beverages

Axis 1: Consumption

Axis 2: Preference

The axes are continuums, but they need poles. The poles are the logical extremes of each axis and they help to constrain the eventual trends that emerge.

For Consumption: Non-Descript, Public

For Preference: No Choice, Endless Choice

Again, this is my cursory attempt at creating an example, but jotting down ideas early in the trend analysis process is important. You do not want pre-conceived notions or the opinions of others to taint your analysis too early. These axes and their associated poles can be refined later, but it’s important to quickly establish some boundaries for the analysis.

Step 3: Quadrants

With two axes, four quadrants naturally emerge. Give these quadrants descriptions based on their relation to the poles. The descriptions do not need to be technical, although they can be. They can be very matter of fact (as I do below) or more succinct.

 

Step 4: Relate the Quadrants

It will help you and your audience if your quadrants are easily relatable. You’ll need to get creative here, but it’s fun. Choose something from pop-culture or history and assign each quadrant a category from what you choose.

Relation: Car

Quadrant 1: Beverage choice as a fashion statement <> Unique Cars

Quadrant 2: Beverage consumption as status <> Sports Cars

Quadrant 3: From the water cooler right back to your desk <> Mass Market Imports

Quadrant 4: Customized Thirst <> Classic American Brands

 

Step 5: Name the Quadrants

Based on the categories assigned to each quadrant, give it a name corresponding to something from the real world in that category.

Unique Cars: Tesla

Classic American Brands: Chevrolet

Mass Market Imports: Honda

Sports Cars: Lamborghini

Feel free to also assign funny taglines or phrases associated to each quadrant and category. For instance, “Honda: The Civic – Everyone seems to have one, but you drive right on by them.”

Step 6: Sort the Manifestations

You now have a well-defined framework to begin to truly analyze the topic and determine what is to come. Take your list of manifestations and roughly sort them into the quadrants.

Tesla

Kombucha – “Questionably good for me, but I love it when people ask me what it is”

In-a-Can – “It tastes just as good in a can and I want you to know that I know that”

Flavored Sparkling Water – “Don’t you dare take the last pamplemousses!”

Lamborghini

Sessionable – “I’m here to be seen and need to be able to keep up all day”

Spiked Sparkling Water – “I could just make a vodka soda, but I prefer to pay more so I can hold a skinny can in my hand”

Honda

Seltzer – “Low calorie bubbly goodness is enough for me”

Free at Work – “I’m glad that they want me to be happy and hydrated beyond coffee and the water cooler”

Rosé – “I like it, ok. I don’t care if the wine snobs think it’s crap.”

Chevy

Fermented beverages growing in popularity (functional beverage)

Craft/Micro – “I just need better, plain as that”

Naturally Low Calorie – “I get what I need with no unnecessary frills”

With your trend landscape clearly defined and all of your manifestations organized, all that is left is to decide what trend (or quadrant) will prevail. Determine this based on the emerging manifestations and what you believe will prevail.

For beverages, are you going to go with the Honda? Probably not! The Chevy, Tesla, and Lambo all offer appealing attributes, so you can choose one of those quadrants and run with it or pick and choose from all three of them.

Final Step: Hope Your Right

If you want to put a confidence interval around your predictions, it’s infinite. You may be right, and you may be wrong. Experience certainly helps. This technique really just serves to organize thoughts and hopefully clear away some of the clouds surrounding what might be going on within a certain field or topic.

For me, I’d put my money on the Tesla-beverages. People are always on the hunt for new flavors. Coca Cola is launching new flavors of Diet Coke. Trends come and go, but consumers’ appetite for new flavors seems to persist. However, they want choice, and they want people to know that they are making bold choices. I’d put my money on customization and the ability of people to publicize their choice. Imagine a vending machine or kiosk where you could select what exotic flavorings you want in your bottle of Coke or your six pack of seltzer, it mixes it automatically for you and then puts a vibrant label on the containers. Maybe you could even make your selections via an app and it automatically posts to your Instagram or you Snapchat with your personalized flavor mix.

… Manhattan

I recently noticed on Facebook that a New York Times article in a column called “The Hunt” has gained some traction, mainly in a negative light. The article is titled, “How to Get to Manhanttan? Save, Save, Save,” and it tells the story of a very young woman who was able to afford a nice apartment on the Upper East Side. The problem with the story is that the math just doesn’t add up.

Annie, a financial services adviser and the subject of the piece, put down 35% on a $426,000 apartment. That’s $149,100. Plus, she spent $30,000 on renovations and remodeling. In total, she used $179,100 of her savings. From the article, it sounds like she worked for about two years and a quarter before making the bid on the apartment. That means she was putting away $6,633.33 a month, at bare minimum. Assuming she was putting away 100% of her take-home pay into savings, her average annual salary was a whopping $79,600. I personally worked in banking consulting until the beginning of this year, starting right out of college just like Annie, and I never made that much even before taxes.

But further questions remain. She certainly couldn’t have saved 100% of her salary. Even though she lived at home she must have used some of her income on transportation (particularly to get to work, even if it is deductible), food, entertainment, clothing, other personal items, and leisure and entertainment. Did she pay for any benefits through her employer, such as health insurance, life insurance, long-term disability insurance, eye care, or dental care? Most likely. What about her 401(k)? Certainly someone as financial savvy as Annie  would be putting away money for retirement at her young age and taking advantage of what we can assume was a match from her employer. And then of course there are taxes. Working in New York and living in New Jersey, Annie must have been hemorrhaging paychecks to the Man on those long nights stuck in the Lincoln tunnel. All in all, this article would lead you to believe that Annie was making six digits out of college.

The last question that needs to be raised really doesn’t need to be asked at all. By now, it should be apparent that Annie received considerable financial help, most likely from her parents, in the purchase of this apartment. So one could assume that she doesn’t have any student debt because her wealthy benefactors most likely supported her through Binghamton University as well. And herein lays my major complaint with this story. The article lauds the virtues of saving and what it can get you in the (relatively) long run. However, the subject of the article is a daughter of wealthy circumstance. I concede that she likely saved a large ton of money, especially for someone of her age. But the fact remains that for the 99% a free education is not possible, and even someone with the discipline of Mother Theresa could never afford that apartment after working for less than three years without someone pitching in with a fat check.

My true complaint is not with Annie though. She legally bought this apartment and she has every legal right to live in it and pursue satisfaction and happiness in her life however she pleases. The problem in this case is the NY Times. By failing to run the numbers and fact check this article they failed their readership. But through this failure they have reinforced the false ideal that hard work and discipline alone can help you achieve your materialistic goals. Rather, the NY Times should be espousing alternatives means by which young people and the middle-class can find safe, comfortable housing in New York City and other places around the world. What we need is innovation. Innovation in how we finance shelter. And innovation in how we actually shelter ourselves and how we conceive of adequate and satisfying shelter. This article reinforces materialistic societal norms and makes people believe that they are doing something wrong if they are not walking a taught tight rope towards their “American dream.” Didn’t we learn with the Triple-F Fiasco (Fannie-Freddie-Foreclosure!) that the American dream can easily turn into a nationwide nightmare? Renters can be happy people too. The NY Times doesn’t seem to realize this. With income inequality large and growing the NY Times and its readership need to realize that wealth and assets are not the only way to lead the good life. People can choose their own path.

I suppose since this blog is called “The Economics Of …” and I titled this post The Economics of Manhattan I should talk about economics a bit. I hope that my readers do not think that economics is about making everyone rich or maximizing wealth for everyone. I am an economist because I want to maximize opportunity for everyone – their opportunity to be happy, whether it is through wealth and asset accumulation, or whether it being through less materialistic means. My hope is that societies will put policies in place so that the opportunity is available to everyone, not that society will define what happiness is and have everyone marching towards that goal through the engines of the economy.

… Uber

To me, Uber is the pinnacle of economic innovation. It harnessed technology, the app revolution, and used it to improve efficiency and provide a new service. The service is designed to deliberately overcome a classic economic problem, asymmetric information. And the pricing model is based on sound economic principles. It is at the forefront of a technology driven revolution that economists are calling “the sharing economy.” Similar services include Lyft, AirBnB, and Craigslist.

Uber, at its core, is simply an app. You download it to your smartphone from an app store, and then you give it some basic information, including a credit card number. Then, whenever you need a ride you use a map to tell the app where you want to be picked up and you specify the level of service you want – a private car, a taxi, a black car, or an SUV. The app takes care of the rest. It dispatches a driver and gives you his or her name, user rating, contact information, and estimated time of arrival.

When the driver arrives the app alerts you and you can head outside and hop in. All you need to do is tell the driver where you are headed and he or she will take you. Then when you arrive at your destination you just get out. No fumbling for change in your pocket or listening to the taxi driver grumble about you wanting to use a credit card. The app, which already has your credit card information, automatically bills you based on level of service, distance traveled, and time elapsed. All of this information, including a map, is e-mailed to you. I’ve used these e-mails in the past to compile invoices for my business trip expenses at my old job. Gratuity and any taxes are automatically subsumed into the rate. The app simply asks you to rate the driver, out of five stars, and provide any comments or feedback.

Asymmetric information is a classic economic challenge. It is when the two sides of a transaction – the buyers and sellers, demanders and suppliers, consumers and providers, whatever you want to call them – do not have the same information about the product or service. For example, the used car market suffers considerably from asymmetric information. The dealers know a car’s history and if it’s a lemon, but the buyers don’t have this information, which saps demand and can lead to less than optimal prices on vehicle sales.

Uber has solved this problem for the chauffeured rides-on-demand market. Not only does the rider have to rate the driver, but the driver has to rate the rider. Riders and drivers both have average ratings out of five stars, which are revealed to both parties when the service is called for. Riders can decline a driver with a poor rating, and drivers can decline service to rude riders with a poor rating. This symmetrical access to information improves the efficiency of the market and helps secure the fairest price for service possible. It also ensures quality. I’ve taken many uber-clean Ubers in which I’ve been offered a small bottle of water or a nice sucking candy, at no additional cost.

Pricing is another strong feature of Uber. Accurate prices take into account both real-time supply and demand for a service. But sometimes prices are fixed and only take into account one side of the curve. For example, one problem with certain popular “hot lanes” on interstates is that they only take into account demand. The price goes up when the normal lanes are congested, but it doesn’t take into account how congested the express lanes are. When the express lanes are also jammed this has the effect of unnecessarily attracting more vehicles, worsening the congestion. And when the fast lanes are empty the prices are not optimized to attract more vehicles, improving traffic flow for the normal lanes.

Uber, on the other hand, has base rates for distance and time traveled. However, when demand is high or there are not a lot of cars available, they implement a surge pricing scheme which multiplies the price of the ride based on the real-time state of the market. At first this pricing scheme got Uber some bad press due to lack of transparency, but now that they have improved the app to make the user aware of the price it is a great system. The people who are most willing to pay for the service, as expressed by price, are most efficiently matched with the drivers most willing to provide the ride.

I’ve never seen surge pricing this high, but it only reflects real-time market conditions. It could have been during a bad storm when no one wanted to be out driving, or during a high-demand period, like New Year’s Eve

The app is sleek. The pricing system is fair, and the its rating system overcomes classic economic challenges to ensure as free of a market as possible. So what’s the problem? What’s all the fuss with Uber about? The problem with Uber and the sharing economy is that everyone who has their hands in the traditional economic structure is throwing a fit. Uber’s success is partially at the expense of traditional taxi drivers. And taxi services are heavily regulated in most cities around the world. This is leading to taxi commissions throwing up roadblocks (some literal, most legal) all across the world. However, regulated taxi markets are a relic of an over-regulated past. Like most markets, regulation and government intervention benefits few and passes on unnecessary costs and under-service to most. I can certainly understand why taxi commissions are protesting. The livelihood of their beneficiaries is being completely upended. However, innovation, invention, and new technology, are the engine of economic growth. When government policies suppress the urge for unnecessary regulation and allow innovation to flourish economic prosperity reaches the most people – even the disrupted taxi drivers, once they adjust their service or find another job.