Unintended Consequences: bag bans

Potential bias: if bring-your-bag was equivalent to free-throw rate I’d be an all star.

Update: since drafting this post there was a related interview on Data Skeptic with Becca Taylor about this. It was good

Our evolutionary advantage was to see cause and effect. This If this then that approach to life kept us alive. It was a simple rule that worked great in a simple system. Modern life is not so simple, but that doesn’t mean we need complicated rules (see Gall’s Systems Bible).

A modern simple rule with great effect is to ask and then what when faced with an intervention. There’s always cascading effects and asking and then what is a way to look for the larger effects.

Chicago, 2016-2017, offered a chance to see this question in terms of plastic bags at the grocery store. In sequential months, there was a ban on thin plastic bags, no ban or tax, and then a tax on disposable bags.

This legislative two-step occurred because the first bag ban was a debacle. Lawmakers gave the wrong answer to the and then what question. Instead of ‘people will use reusable bags’, it was ‘stores will get around this by using a slightly different bag.’ 

Asking and then what helps us find that when schools ban soda sales households buy more, when communities ban payday lenders pawn shop foot traffic booms, when governments limit cars one day a week the total number of cars rise. 

From, Skipping the Bag: The Intended and Unintended Consequences of Disposable Bag Regulations:

We 􏰂find that plastic bag bans lead retailers to circumvent the regulation by providing free thicker plastic bags which are not covered by the ban. A regulation change that replaced the ban with a tax on all disposable bags generated large decreases in disposable bag use. Our results suggest that plastic bag bans—stricter, but more narrowly defi􏰂ned regulations—􏰁are less effective than market-based incentives on a more comprehensive set of products

There are a cornucopia of incentives to use to change behavior. Sometimes money works well (bag tax). Sometimes social norms work (the authors note that this may be present in their study). The best thing to try might be small bets


Ticketing Analytics in 2020

At SSAC20, Rob Sine, Adam Grove, Kristin Bernert, Patrick Ryan and Shira Springer spoke about ticketing in professional sports, among other areas. A few highlights.

Do we measure what matters? When asked what the opportunities are in the industry, Sine said, “going from season ticket units to revenue which keeps the lights on.” We can imagine a time when season ticket sales were a good proxy for revenue but with the secondary markets, public spaces, and better televisions at home people go to games less. Plus, people are busy. The successful teams will head back to ‘first principles’ and re-focus on revenue.

Who is your customer? “When you look at the data, an account holder for a full season goes to thirty percent of the games, the half season buyer goes to about sixty percent, and the quarter buyer goes about eighty percent. So you’re kinda servicing the same person,” explained Bernert. It’s a case of JTBD. It’s a question of, what are they hiring me to do?

Are there latent needs? When asked if the season ticket is dead, one panelists wonders if they were ever alive. “Teams and venues have always had to recreate what the fans are looking for,” said Sine. Patrick Ryan suggested teams talk to the ushers to hear what the fans are saying—not necessarily what they are asking for.

What are the intangibles? “There’s a lot of pride in being a season ticket holder.” “There’s a great benefit to saying, ‘I was there.'” “A lot of the L.A. Dodgers season ticket holders said the biggest benefit was the person checking them in at the premium station knowing their name, and how that impressed the clients they were with.” The best returns on an investment are the ones with the smallest cost, intangibles are often just that.

Are there latent needs, part 2. One growing request from customers is something Rory Sutherland calls this the airport lounge problem. What some customers want is not one visit on each trip to the airport, but one visit on some trips and a family pass twice a year. Teams like the Orlando Magic are offering this, buying back unused tickets for full face value and allowing that money to be used in the gift shop, concessions, upgrading future tickets, or special events.

One thing that SSAC offers is the chance to hear from people on the ground who may not often speak about their experiences. This was certainly one of those panels. Thanks again to Jessica and Daryl.

Your random fact of the day: Only two college bowl games sold out last year (2019/2020) (45:45).


The Bird: Margin of Safety




Thaler, Massey, and Losers

Well before he won The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel, Richard Thaler wrote The Loser’s Curse. Along with co-author Cade Massey (well before he hosted the Wharton Moneyball podcast), they found that NFL teams tend to trade too many assets to choose higher in the draft.

With the idea that it’s not what you buy, it’s what you pay we’ll revisit the paper. (Here’s a related 2018 work, also a gated 2020 analysis)

Also, Thaler spoke at SSAC20 about the paper in a panel with Bill James.

Thaler and Massey noticed that in-practice, NFL draft picks declined steeply in value. Top picks were worth a lot. Low picks were worth much less. The chart looked like a roller coaster’s first hill.

What they found was what’s known in the league as ‘The Chart’. The rule-of-thumb systems born in Dallas in 1991, and spread through the league. Thaler and Massey wrote that the chart standardized trades and created the norm to ‘gain a round waiting a year.'” It was the way things had always been done and few teams at the time considered why we’ve always done it that way. 

“What our analysis shows is that while this chart is widely used, it has the ‘wrong’ prices.”

The chart suggested that the first pick of the first round in the draft delivered less value than the last pick of the first round.

Thaler and Massey found the ‘right’ prices by comparing draft slot against games started and pro bowls awarded. Lower drafted players scored higher.

Thaler and Massey wondered if there was a ‘star premium’. “Over their first five years, first-round draft picks have more seasons with zero starts than with selections to the Pro Bowl.” Busting was as likely as breaking out.

Thaler and Massey wondered how often one pick was ‘better than the next guy’ at the same position. “Across all rounds, all positions, all years, the chance that a player proves to be better than the next best alternative is only slightly better than a coin-flip.”

In the paper Thaler and Massey lay out a variety of reasons why ‘The Chart’ was so different from the results. Let’s add four more.

Possible explanation 1: Measurement error. Quarterbacks are tremendously important and the stats underrate their impact. On the Wharton Moneyball podcast Massey brings this up and hints at it on Twitter. In the paper Thaler and Massey do boost performance scores by 50% without seeing value returns shift.

However maybe there was a trend they didn’t or couldn’t quite measure. More and more quarterbacks throw for more than 4,000 yards.

Possible explanation 2: Ownership incentives. The NFL—or any sport—isn’t just about winning. Though Massey and Thaler write that people don’t tune in to see their team lose, they don’t address whether people view interesting as different from winning. We think there’s only one honest sport.

If owners see values rise, share revenues, watch mediocre play, and they themselves face little (social) cost, how strong is the incentive to ‘just win baby’?

Possible explanation 3: Luck matters a lot . Michael Mauboussin writes about guidelines for situations that are more dependent on skill and ones more dependent on luck. For situations with more randomness (and luck) people should trust the base rates more and give more weight to environmental rather than personal factors. By thinking they can find a diamond in the rough, teams are operating like drafting players is more skill than luck based.

However, there’s always a chance to develop better talent evaluation, incorporate new technologies, or coach players better. Those are all skills that could improve the 52% ‘better than the next guy’ success rate.

Possible explanation 4: Culture is king. The effect that Thaler and Massey find could be partially driven by bad organizations picking at the top of the draft. Imagine these were not football franchises but restaurant franchises.

The best chefs keep their jobs and the talent pool for the open positions is a mix of unproven leaders, bad situations, or people who have already failed ‘but learned the right lessons’. The ownership of these franchises are people who have already proved they themselves are bad talent evaluators, or else they wouldn’t be looking for a new coach/chef.

What’s great is that while the data is old the ideas from Thaler and Massey are still present. They’ve taken new forms and changed in many ways but good decision making is still something worth thinking about.


Thank you for reading and supporting.


Sarah Tavel

Sarah Tavel spoke with Patrick O’Shaughnessy and in their discussion included five good questions. Perspectives from differing industries make these questions especially helpful, a change in point-of-view is worth forty IQ.

What weaknesses accompany competitor’s strengths? Ebay is a behemoth. They sell everything. So Tavel points to Goat, “and one of the founders had ordered a pair of sneakers off of eBay, opened the box up, and they were counterfeit.” That was their founding insight, eBay has all the supply, which includes fake products.

What business serves too many people? New companies arise to serve new needs. One helpful framing is to read is books from the late-90s an early 00s about technology and the remarkable respect for Microsoft. Everyone worried about them but large size brings weaknesses too. Why does TikTok work in a YouTube world? Why does Snapchat when there’s Facebook? Why Zoom with Skype?

Does this exist elsewhere? Tavel said, “It doesn’t really make much sense if you’re a real estate broker to be on LinkedIn. It’s not your network.” What if there were a network where brokers could share leads then share commissions? Poker does this when one player stakes another. “Real estate brokers do share leads with each other and if one of them converts they get a share of the commission, but there is no formal system.” There’s no such thing as new problems.

What job—and this may be different from what customers say they want—do customers really want? At Pinterest the power users wanted to rearrange pins on their board. This was a difficult engineering challenge and only requested by .1% of users—but that was still a lot of people so the Pinterest team built the feature. “It was a symptom of something else not working in the product, which was an inability to search your boards,” Tavel explained. They didn’t know the JTBD.

What choices reinforce our advantages? “Anytime a user clicks or taps they are using energy and you want to direct that energy in a way that creates the most value for the system that you have. Usually there’s a core action in your system that is most correlated with a user retaining, and creates accruing benefit for your product.” Richard Rumelt’s Good Strategy Bad Strategy is summed up by a different phrasing of the same question; what collection of choices is the most synergistic?


Thanks for reading and supporting.


The Bird: Fighting Entropy



Parlay Maths

A gambling parlay is a bet where two or more things have to happen. Will you have coffee and eggs for breakfast is less likely—thus longer odds and higher payout–than just betting on one or the other.

And people love betting parlays. The most popular Super Bowl bet is the coin toss, and Americans bet seven billion dollars (legally) on the game. 

And casinos love people betting parlays. According to UNLV, sports books earn five percent on bets, except for parlays. On those bets casinos take 30%.

Why do bettors do so poorly? It’s a little too much psychology and a little too little numeracy. Bettors, said Rufus Peabody, love to bet for things to happen. It’s easier to imagine one outcome than all outcomes. It’s why the ‘no safety’ bet almost always has positive EV. 

Bettors also don’t consider the numbers in the right light. Two independent seventy percent events only both occur half the time. Let’s run with that.

According to smart air filters, a t-shirt-mask will stop 70% of an airborne bacteria which is smaller than the coronavirus. That’s good. But what if we parlay masks?

If I wear a mask a t-shirt-mask and you wear a t-shirt mask we’ve reduced the viral load ten-fold. Thirty-percent of thirty-percent is .09. 

The same math that makes parlays good for Vegas and bad for gamblers is what makes masks good for all of us.

I wore mine to the store for the first time. It felt kinda foolish. But then I did the math.

UNLV explains the casino win percentage as “Win percentage, or win as a percentage of drop, AKA hold percentage, the percentage of money wagered that the casino kept.”

Peabody also tweeted about this: 


Framing Employment

Framing is so important because it’s a way to get ‘free value’. Things well framed are perceived as well done—and perceived value is all there is.

I ran this one question poll on Mechanical Turk, Amazon’s data collection service, and Twitter to see how people perceive the same news. Each option describes the US labor market from mid-March to mid-April.

The question was, which one of these is the best (or least bad) way to describe what’s happened.

Over the last month..

The most important data isn’t that one section of the pie is larger than another but that there are sections of the pie. If  “135 million people remained employed” took the king’s share there would be nothing to figure out. In the many slices though we get many ideas.

Jason Zweig demonstrated this magnificently in a recent WSJ column. Imagine you’re of a certain age with a certain income and a certain promise of social security. It’s likely more than you realize. Zweig wrote:

The $2,000 a month that you and your spouse will each receive in the future has a present value of $772,235, according to

That’s roughly what it would cost an insurance company to provide each of you with a guaranteed, inflation-adjusted $2,000 monthly payment for the rest of your lives (assuming you file for retirement benefits at age 70 and your spouse at 62).

So your expected Social Security payments are like a giant phantom annuity—a bundle of inflation-adjusted bonds you don’t own but whose income you have the right to receive. The same is true—usually without the ability to keep pace with inflation—if you are fortunate enough to have a defined-benefit pension plan.

Much of poker is played by the number. Professionals fold many more hands than they play because the numbers tell them that. But people don’t like to feel like automatons. They want action. When Annie Duke started teaching clients how to play poker she had to reframe how they saw the game.

Duke’s insight was to get her clients to choose to play by the numbers. She appealed to their meta side. They had to see the analytical next to the emotional and make a choice from those two options.

People are relative thinkers and many many decisions come down to framing one thing against another. It works for news, marketing, home purchases, dinner options, and dates. It works for everything.



Colossal Comprehension


This is the earth.

Part of our quarantine education was to get outside and make some scale drawings of our solar system.

We made our earth one roadway wide, about twenty feet in diameter and paced off two hundred yards and drew the moon. It was five feet wide. The ISS was seven inches from the earth’s surface.

It’s always challenging to consider the scale of the universe. It’s huge. It’s so huge that Mars was sixty miles away in our little universe.

Part-of-the-reason Einstein marveled about compound interest is because scale is really hard to understand. Once things scale up or down past the human perspective we just don’t quite get it. This came up on two recent podcasts.

First, Peter Attia spoke with his daughter about the coronavirus. It was an excellent, simple, good-for-kids episode. So how big (or little) is the virus?

“If were to cut one of your hairs, and you can barely see the edge when it’s cut, how many coronaviruses do you think we could line up on the tip of your hair when it’s cut?” Attia asked

A thousand viruses. That’s beyond the human scale of understanding.

One the other end of the spectrum, and closer to the solar system situation was Cade Massey’s longhorn lament.

“One of the things that frustrated me most when I to talk with people was them saying ‘Well, you’re not going to get this if you’re young.’ We knew the probabilities are steeply related to age but there’s still a probability for every age group. Throw millions of people at a small probability and you’ve got some sick people. We just aren’t good psychologically with these kinds of probabilities.” Cade Massey

The percentage for infection, hospitalization, and ventilation are remarkably small.

New York City houses eight million people and the metro area is home to twenty-one million. Projections note that only .27% will need beds, and only .063% will need ventilators.

Right now my sixth grade daughter is learning percentages as parts of the whole. She answers questions like; “If sixty percent of a class of twenty-four are boys, how many children are in the class?”

That’s good sixth grade math but it gets hard with large numbers. One-fourth of a percent is really small but eight million is really large. How does someone make sense of that? We probably just need to think slow, not fast.



Precise Emergency Funds or Accurate Emergency Funds

The rule of thumb for an emergency fund is three to six months of expenses. The specifics depend on a host of  factors like fixed costs, number of incomes, and type of job. In the Need for Speed post we suggested how Variance Response Time might affect someone’s budget. The theory was that an excellent salesperson would have a faster and higher quality response (i.e. new job like the old job) faster than a teacher.

What was implicit in that post was the idea of being precise or being accurate.

At the end of March 2020 during the coronavirus pandemic I compared our family’s emergency fund to our previous month of expenses. Aside from travel for work and weekend activities, our monthly spending was flat.

Dollars devoted to dining out were diverted to stocking up. Weekend activities become home activities.

How long would this ‘as-is’ lifestyle last using our emergency fund?  The good news was that it would last five months.

But that begat more questions. If this were a true emergency how long could we last? Cutting out the extra expenses like Netflix, home repairs and maintenance, and Target and our runway ran up to eight months.

Okay, but how long could we really go? What if we tapped our home equity, liquidated a 401k (and paid the 35% penalty), and sold one car? That would mean things were really bad but we could still survive for a long, long time. A room, a roof, and rack in oven goes a long way in those conditions.

These calculations were all in a spreadsheet and so the numbers were nice and precise. And probably wrong. Here’s how James Allworth put this idea on Exponent 184: 

“Something I learned early on in consulting was when clients came to you with problems you needed to model them in some way or another and I remember, early on in my career, being really proud about building very sophisticated models with different variables. It could handle all kinds of things.

“One of the partners came along and started to use it, and he laughed. He’s said, ‘James, one thing that you really need to understand if you want to be effective in situations, especially ambiguous situations, is understanding the difference in precision and accuracy.”

That wasn’t in my spreadsheet. Our ‘needed’ 401k was unlikely to be worth as much as it is today, reduced as it is. That car I might sell couldn’t be given away. If things were that bad there were would be so many more sellers than buyers.

At the 2009 annual meeting, Warren Buffett was asked how he calculates value if he doesn’t use a discounted cash flow.

Warren whimsically recalls Aesop’s fable about a bird in the hand being worth two in the bush. Investing, Buffett said, is all about the exchange of the bird in the hand, “But the real question is, how many birds are in the bush? You know you’re laying out a bird today, the dollar. And then how many birds are in the bush? How sure are you they’re in the bush? How many birds are in other bushes? What’s the discount rate?”

He goes on to say, “we do not sit down with spreadsheets and do all that sort of thing. We just see something that obviously is better than anything else around, that we understand. And then we act.”

Charlie anything to add? Yes, Munger says, “I’d say some of the worst business decisions I’ve ever seen are those that are done with a lot of formal projections and discounts back.”

For an emergency fund then, more is better but anything is good. With so much uncertainty there are good ways to gamble. Ian Cassel told Patrick O’Shaughnessy that he tries to keep his fixed costs low and his variable costs variable. If someone has saved and can scale their expenses, then they have an emergency fund. Too much spreadsheeting leads to numbing numbers.

We’ve gotten quite creative with making breakfast.