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$1 Toronto real estate

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Average is like my reciprocating saw: never as useful as I expect. Part of the reason average sticks around is economics, It’s cheap to produce.. Average is a crude tool, like with student loan debt, and often hides the heterogeneity of a situation.

We’re entering an era of precision. One covid lesson has been the effect size of heterogeneity. At the macro level, the impact of covid depends on time and place. At the micro level, the impact depends on age, immunity, and social network. Covid was (is?) difficult to judge because there are a lot of factors that need fitted together.

If we need precision we should probably think about distributions at least as often as we think about averages. An example is the periodic one dollar real estate listing. Yes, this generates attention, spins up the market mechanism, and might be the marketing magic an owner needs. But it also changes the distribution of offers without changing the average offer.

“When you give people a listing price they ask if it’s worth more or less and by how much, so they anchor at the listing. If you don’t have an anchor people build a valuation from first principles. The average (offer) doesn’t change but the distribution does. For a one dollar listing you get some really high rates and some really low ones. In the listing price you get distributions around what the asking price was. This is a world where the seller doesn’t care about the average, they only care about the top end of the distribution.” – Dilip Soman, The Decision Corner, October 2021

Maybe this is being too hard. Average, like the saw, has its uses. The aim here is to combine numeracy with psychology to get by in the world. That means presenting the ‘best’ wait times or predicting rain more often. Being numerate is understanding that the average age is 78, but if you make it to 65 you’ll probably live well past eighty.

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“The average looks like 10-12 years lost due to Covid – but that’s an average of a distribution with a very odd shape, a highly skewed distribution, some people have lost forty years of life. The peak of the distribution is people who lost less than a year of life.” – David Spiegelhalter, Risky Talk October 2021

Interval training

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One of the perks of this blog is repetition. There are areas afield of the core focus (which itself moves) but there’s a lot of repetition. This is good. Jason Zweig once said that his Wall Street Journal articles were just the same principles in different forms.

There are other intervals. Sleep and exercise seem to be daily intervals. Eating might be longer or shorter. A business’s innovation interval depends on the industry. What’s the interval might be an interesting question.

There are vaccine intervals. Pfizer and Moderna tested three and four weeks and were (largely) administered in that time space too. But not always.

“In Quebec, in early 2021, the world was short on vaccines. To spread the doses in Quebec they decided to spread the interval to sixteen weeks. The researchers looked at the immune responses after the second doses and found a lot of similarities to people with hybrid immunity: high levels of antibodies, and neutralizing diverse coronavirus variants.” – Ewen Callaway, Nature podcast, October 2021

In Quebec at least the longer interval worked better.

Part of what makes cac such an interesting business angle is that there are a lot of ways to reduce the number and a low cac changes a lot of the economics. Intervals are like that too. The cost to experiment in intervals is low but the effect might be large.

DuoLingo experimented a lot with their reminders and what ultimately worked was one of their early interval tests, remind people about a day later. That will happen with experiments, but knowing about intervals as an option expands our field of experiments.

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Excellent endocrinologists

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In Average is Over Tyler Cowen predicts that future jobs will reward people who work well with machines and humans. There will be good careers for people who understand people and data.

For instance, a doctor spends years of her life in medical school and residency and attends continuing medical education courses to ‘know a thing’. But she also must convince her patients. The way we do each of these will change with time but these are the two parts any job. Put another way, it doesn’t matter how good the model is if people don’t follow it.

“The (diabetes treatment) model we created beats 95% of primary care physicians, not because they aren’t smart, but they don’t go through the six million (treatment) combinations in their head. For endocrinologists there’s a top quintile who get results as good as the best output of our algorithm. They don’t do it by choosing the best algorithm, they use their humanity to talk to their patients about adhering to the drug regime. They are getting results a different way.” – Len Testa, Causal Inference, October 2021

Good convincing outperforms better medicine! This is why financial education does not work. Action does not follow information like a tail follows a dog.

Testa doesn’t elaborate how the doctors describe the diabetes deterrents, but it’s probably in the listener’s language. “Excise the statistical jargon,” said David Spiegelhalter and communicate better.

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Sounds like a JTBD post no?

JTBD is iteration

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The 2012 job-to-be-done at Calm was meditation. But when engineers looked at the usage data they noticed something interesting, there was a lot of Calm usage at night. “When they started productizing around sleep,” explained Vinny Pujji, “that’s when it opened up from being just a meditation focus thing to what they are today, which is mental fitness.”

We’ve looked at a few JTBD ideas: does the bundle of good explain the transaction, as it does with free breakfast? Is there zombie revenue? Even Jazzercise was job-ercised.

With hindsight ‘jobs’ sound easy, but they are iterated solutions. David Packles of Peloton shared (October 2020) two instances where Peloton had to iterate on their first JTBD solution.

First, Packles and his team looked at the largest Peloton Facebook groups. Rather than build for the power users, a no-no, they looked for wider use cases, and thought peole wanted to see when their friends were working out.

“People hated it,” said Packles. While the camaraderie between instructors and peers was important to users, the now-ness was not. So they tinkered. There was almost always at least two people in the same workout at the same time. ‘Friends working out now’ became ‘here now’. This worked, forty percent of daily active users now use this feature.

A second instance was the location field. Rather than where, people used it for what. Packles himself is a ‘Peloton dad’. So Peloton added tags which per Packles, “exploded in popularity” and “became a means of expressing yourself rather than connecting with club.” Half of DAUs have some kind of tag. Rather than people near me, the Peloton users wanted people like me.

That’s interesting moments help us understand how other people see the world. Instagram once had a tool that fought spam by looking for accounts that posted a lot and deleted a lot. During one glance through the data, Mike System noticed that in Indonesia a person was doing that – but in an interesting way. Way back in 2013 she was uploading photos of her store’s products and when they sold she would remove the post. Interesting right?

JTBD feels like a spirit of philosophy as much as it feels like a technique or tactic. It’s a way of regularly reflecting on the world. JTBD isn’t an equation, it’s a long process with a lot of inquiry. But it’s worth the work.

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Two cool Peloton stats: they film thirty hours of content a day and their 18 month churn is 14%.

Two health designs

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We highlight design because humans are conditional creatures. Certain circumstances make certain actions more or less likely. Living near a huge retirement community in Florida shows this contrast clearly. The involvement in new sports like pickleball, water volleyball, and sand tennis exemplify the design principle: If you build it, they will come.

In talking about his book,Drink?, David Nutt notes how much alcohol is a cultural act. Per Nutt, alcohol’s health impacts are terrible, the societal costs are large, and meaningful outcome changes wouldn’t require that much tweaking to the current system. But we don’t change.

Culture is design too. So to not drink a person needs to counter culture.

“In my book I suggest if people say to you, ‘Why aren’t you drinking?’ quite a good repost is to say, ‘Because I’ve got quite a busy day tomorrow.'” – David Nutt, London Real, February 2020

That’s good communication, it’s in the listener’s language.

The second design is around fasting, an area design helps.

“Right around the five hour mark of a fast you’ll probably get hungry (this being our ‘normal’ time between meals), and that’s the most difficult time. Sleeping through that is the best idea then. If you can start a fast at three p.m., then in the evening you have to stay away from the snacks, but when you wake up you’re in that cruise state of twelve plus hours.” – Matt Tullman, No Meat Athlete Radio, October 2021

In my experience this is true. Fasting pangs are non-linear. Depending on the time, circumstances, and maybe even hydration, a fast can be more or less difficult. Sleeping through those time-based hunger troughs can help.

You are a designer. I’m a designer. We are all designers.

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Nutt sounded quite certain in the podcast about the health effects, but a query for “cancer alcohol meta analysis” showed less convincing results. In an attempt to be more Bayesian I’ll update from ‘quite bad for you’ to ‘pretty bad for you’.

Sports bras and pickup trucks

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One of the hallmarks of a Job-To-Be-Done approach (our series) is not to ask the people what they want. A better approach is to understand what job people want to do. That means looking at how people hack your product or when there is zombie revenue. It means what people do, not what people say. Here are two additions to our collection.

Of the thousands of first Title Nine catalogs only a handful of orders came in. But…

“Many of the people put a sports bra on their order. So while I may not have been the quickest study, you don’t have to tell me twice, wow, sports bras are the most essential piece of sports equipment for the average American woman.” – Missy Park, How I Built This, October 2021

Park built her first catalog by choosing the clothes she wanted. Park grew her business by solving the JTBD.

Our second comes from another CEO:

“Being with F-150 customers is like having a barbecue with the next door neighbors, we know them that well. The Homer had a doughnut maker and beer dispenser. If you ask people what they want, you get a Homer, but if you know the customers really well you can surprise them with twelve kilowatts of power to power their home. They won’t tell you that. They won’t tell a focus group that. But if you know them well enough you know they’ll like it.” – Jim Farley, Decoder with Nilay Patel, April 2021

Whether the Ford Lightning succeeds remains to be seen, but the fact that they promote the frunk’s ability to hold two carry-ons and one full-size suitcase shows a JTBD focus.

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My first collection is 26 Jobs to be done, it’s $3 on Amazon.

TTID Restaurant

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Restaurants are an interesting case study. In part because of the accessibility, everyone has can cook something. So much like making movies or winning wines there’s a fair bit of “I’ve seen that done so I could do that”.

But restaurants are difficult businesses. The pricing power belongs to the landlord not the chef. Staffing is brutal. Inventory expired expediently. Examples like Chez Panisse, Five Guys, McDonald’s, and In-N-Out provide great history through industry, but are outliers in business.

I’m reminded of Sir David Spiegelhalter’s (OBE FRS) comments about health news. Basically the Brit wants us budding Bayesians to not update. Health news, David said, is only news because it is novel.

But.

Maybe.

This time is different.

One template for TTID is to ask if the technology has changed the system in an important way. For hobbies it was the internet. For air travel it was deregulation. For tickets it might be NFTs. For high jump it was the landing materials.

Another way to think of technology is: rules of the system.

For restaurants it might be robot. A restaurant rule of thumb is that food, labor, and real estate each tend to eat up 30% of the costs. Yet just with location is the issue of “wholesale transfer pricing“. It’s the same idea behind Netflix’s original content: Can my suppliers raise prices faster for me than I can for my customers? If the answer is yes then we don’t need Admiral Ackbar to note it’s a trap.

But the pasta robot changes that:

“The robot means Cala saves 60% on real estate costs, which it says it puts into spending more on the cost of food ingredients, allowing it, Richard says, to deliver higher quality meals at a better price. The company’s labour costs are similar to other restaurants — they still have staff serving the meals to customers.” – Freya Pratty, Sifted, October 2021

Cala, like ghost kitchens, has shifted the 30/30/30 economic equation. If the JTBD of food has changed then maybe the economics have changed too. Maybe future restauranteurs will feel a little more full.

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Even TTID is subject to Spiegelhalters’s scorn. It’s attention grabbing to say that things really are different this time. Hopefully our series helps us figure out when it truly is.

Always buy two new cars

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I’ve been driving my wife’s car a lot lately. Her car is nice. It’s smooth, it’s got more room, and it has bells and whistles. It’s always had these things but I’d never noticed.

It’s refreshing to notice instances of relative rather than absolute value. Her car is nice relative to mine but not so nice relative to the newest thing for sale. After driving her car I kinda wanted a new car.

Like made up start ups, the advice to ‘always buy two new cars’ is half a joke. Much of the personal finance advice around here is to choose from pretty good options. Emergency funds should be generally right, both 15 and 30 year mortgages are good choices, and personal finance expertise is from experience not eduction.

To buy two new cars then means that the relative value of the next new car will be largely hidden from me. Sure there will be neighbors and Ubers and advertisements but I make – we make – easy decisions. If it’s not easy to compare then it’s a comparison that won’t occur.

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Ironically I noticed this idea with iPhones a couple of years ago. It only mattered that the phone was newer, not that it was newest. All value is perceived value.

Favorites or the field? (part two)

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In the first post we jumped off with the idea that the S&P500 is an unbalanced collection of stocks. The top five companies, noted Carl Kawaja, generate 22% of the earnings, so why not only ‘bet on’ the best?

This led to thinking about predictability. Chess is easier to predict than my morning pickleball game. Michael Mauboussin wrote a wonderful book about predicability as framed by skill and luck.

Think about events, Mauboussin explained, as a continuum: from the least skill activities (roulette) to the more skill components (stock markets, hockey, football) to the mostly skill components (basketball, chess). An event’s predictability slides as the skill portion of an outcome increases.

Here is how sport predictions look.
Update two

On the Wharton Moneyball podcast the hosts often talk about betting the favorites or the field. Bettors in events toward the left of the graph are better off betting favorites and events toward the right taking the field.(1)

With two years of data (sorta) it seems that some sports are more predictable (more skill, less luck) than others. Here’s how Mauboussin ranked sports, starting with most skill based: NBA, EPL, MLB, NFL, NHL.

Contrast that with our (sorta) model: EPL, NBA, MLB, NHL, NFL. That’s a pretty good match!

How to use this: to consider if our predictions are more like the NBA or more like the NFL and it’s “any given Sunday” ethos. In NBA-like situations there are a few big issues (players) that drive the results. In NFL-like situations there are more chances for odd bounces (fumbles), subjective decisions (pass interference), or fortuitous circumstances (turnover-worthy pass attempts).

Nothing in real life will be like these sports, but to have a good analogy is a good decision making tool.

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(1) “Buying good things can’t be the secret to success in investing,” wrote Howard Marks), “It has to be the price you pay. It’s not what you buy, it’s what you pay. There’s no asset so good it can’t become overpriced.”

The capacity-efficiency tradeoff components

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One of the things brought to light by Covid has been the balance between capacity and efficiency. In general, things with high excess capacity aren’t efficient and things with high efficiency lack excess capacity. Another way to think about capacity is as a margin of safety.

Each link in the medical supply chain, wrote Scott Gottlieb, balances capacity and efficiency. Swabs, like those for Covid, are produced efficiently.

“One of the things I learned at the FDA, watching other critical medical products go into shortage, is that it’s often the lowest-margin constituent in a complex supply chain that’s most vulnerable to shortages. Often the only way to produce such a part profitably is to manufacture it at a very large scale, which means it’s likely to be made by a small number of big, consolidated suppliers.” – Scott Gottlieb, Uncontrolled Spread, published 2021

Sixty percent of the swab market was from an Italian supplied, an Italian supplier in the Lombardy region. Eventually the United States scaled up swab productions only to be limited by the machines that ran the tests, another part of the system where the incentives pointed more towards efficiency than capacity. A system is only as strong as the weakest-link-in-the-supply chain.

There is a tradeoff between efficiency and capacity and that tradeoff depends on time and consequences.

“Flatten the curve” demonstrates this. Our highly efficient (low capacity) healthcare system could have been overrun. The consequences of that were huge. One physician friend thought she might have to work in a field hospital – and she’s a dermatologist.

A smaller example is a student taking Algebra. If an Algebra exam is during a sport season, the student will have less time to study being highly efficient with their use of time. The lack of capacity might lead to a lower grade.

However, in the case of Algebra, the time and consequences are more muddled. Is the goal to ‘learn Algebra’ or ‘score 93% on the Algebra Chapter Two Test’? In the case of the former, the time pressure changes.

Personal finance encompasses this idea too. A large capacity is an emergency fund. Those dollars could be invested to earn the historic seven percent. Time here matters too. Typically a person has one source of income (their job) and these vary in pace of payment. A salesperson can work more – and get paid more faster – than a bookkeeper. Their time aspect is different and the consequences for each depends on the difference between income and expenses.

Like the tuning of stereo, these three aspects can be balanced to fit the conditions. There is a trade off between efficiency and capacity. There are consequences in that exchange. And there is cadence for reaction.

Big shocks, like Covid, are out of our control. But though exogenous to our life, there’s still at least three dials to get things that sound right.

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