A MaxDiff comparison helps reveal the ranking of pairs of features without directly asking users to stack rank them. People have an easier time saying the best or worst item in a set than to rank them so this technique is a way of getting a more accurate idea of the relative priority of a feature. See also:
Próspera is a charter city run by the Honduras Próspera Inc (HPI) in conjuction with the Honduras government ZEDE laws which enable setting up economic zones (i.e. charter cities) governed by a non-Honduran entity (like a corporation). The group established the first zone in Roatan in an area of unused land the size of Central park. Their planned government is libertarian, emphasizing property rights, low taxes, and small government. The ruling council is composed of 5 elected members and 4 appointed by HPI which keeps it small (although the 4 appointed members would likely vote as a group and elected member would likely not i.e. political parties). 3D property rights would solve air rights issues (e.g. building a tall building) and a property token will be used to finance the development of the land. A 10% tax rate would attract people and busineses and they would cut 1% to the Honduran government. Read Prospectus On Próspera. See also:
Versioning is a pricing strategy for information products where you create different versions of the product for different users. The version the users pick reveals the value they place on the information and what they are willing to pay for it—without alienating users by charging different prices. This is especially important for digital information products that can drive prices and margins down due to competition. Types of versioning include: The number of versions depends on the number of distinct user segments. Even with a small number of segments, businesses can benefit from having three tiers for the same product to move users from the lowest price into the middle price tier (Goldilocks bias). Read ‘Versioning is the smart way to sell information’ See also:
A ‘back of the napkin’ estimate that can be quite accurate. By estimating multiple variables somewhat accurately and both underestimating and overestimating, the variables tend to balance out and result in accuracy within an order of magnitude. This is usually enough to get a general idea of the problem and solution which is useful, similar to dimensional analysis like Big O Notation. See also:
Since PEOs are the employer of record, they shoulder the insurance risk for health care, workers compensation, and unemployment. They must be mindful of this exposure as they grow and control for it with risk management. For example, if a PEO takes on a client with a higher likelihood of physical injury (like a construction company) they risk more workers compensation claims and thus a higher workers compensation insurance premium. This will cause them to either lose margin or pass it on to their customers raising the price and potentially causing churn. That’s why it’s useful to think of a PEO as an underwriting business where they must carefully manage their exposure and unexpectedly lower or higher revenue as a result. See also:
Paul Graham argues in How people get rich now that we are returning to a period where wealth is mostly generated from starting companies (as opposed to inherited wealth from oil and natural resources) and that’s a good thing even though wealth inequality is growing. He argues that it’s that rich people coming from tech get rich faster and much more wealthy and not something more sinister that technology companies growth correlates with rising income inequality. Of course, it’s not that simple and Just be rich, a reaction to the essay mentioned above, points out that Paul Graham’s essay is meant to make rich people feel better for being rich and that the answer is to start a company and be rich. That’s a bit of a straw man which makes it easy to poke at PG, but it seems they are both right. Declining middle income is bad and causes struggle and lack of access to opportunity. Also, tech is better than what we had 40 years ago when most wealth was generated by exploitation of natural resources or inheritance. While the reaction blog post got a lot of airtime on HN, it’s a bit sensational. The reaction offers no alternatives and draws no new conclusions about what to do about the problem. See also:
An off speed high arching pitch in baseball that is meant to catch batters offguard. Sometimes called a blooper pitch, or as it’s name derives from Yiddish, a nothing pitch.
The percentage of employees working for enterprise companies (500+ employees) has increased as a percentage of the workforce compared to SMBs. From 2007 to 2017, the percentage of the workforce employed by enterprises increased 1.9%. See also:
One of the benefits of a PEO for small businesses in the U.S. is access to better healthcare plans. Since the PEO is an employer of record, they have many employees which improves their buying power when negotiating plans. A small business on their own does not have many employees to negotiate better rates. See also:
The overall opportunity for PEOs is $56B (source: JP Morgan) which represents 21.5 million SMBs with 10-99 employees. However, in the US, workers are increasingly working for larger enterprise companies and those enterprises have the resources for in-house employment. See also:
Curtis Yarvin wrote in a blog post announcing his departure from Urbit, that building a product is like an annealing process. It starts as gas (an idea, amorphous and unconstrained) and ends in metal (a product in the hands of users). In the process, it can cool too fast causing structural weakness requiring heat to temper it (iteration and refinement). See also:
NASA uses a Human-Rating Certification for vehicles transporting a human crew into space. The vehicle must have a 1 in 500 probability of a loss on ascent and a 1 in 500 probability on descent.
In a tweetstorm from Andrew Wilkinson about how their task list app Flow was out competed by Asana. To summarize, his team built an early SaaS task list web app that was growing fast until Asana arrived and quickly outpaced them. Their growth slowed and eventually decided to shut down after many years. He frames the underlying causes as bootsrapped vs venture backed and how, “Good product with great marketing beats amazing product with no marketing.” He offers a word of caution about bootstrapped businesses that are in a highly competitive space with low barriers to entry (like a todo list app) and how a well capitalized competitor can win. See also:
There are two approaches for creating something of significance, the cathedral and the bazaar. The cathedral is best for creation and the bazaar is best for growth. The cathedral is unified coordination mechanism that is well suited for reaching a singular vision. It is hierarchical which provides a clear line of decision making. This consolidation of decision making makes it efficient for coordination. The bazaar is a distributed and loosely coordinated mechanism best suited for growing something that is well defined. By agreeing on a few rules (like commerce, or open source code) it can grow autonomosly—far exceeding what a single person or group (cathedral) could do on their own. However, the bizaar fails to create something new that’s also great (like designing by committee). Read Curtis Yarvin’s blog post A Founder’s Farewell. See also:
The core thesis of Monetizing Innovation is that product failure is rooted in the failure to put the customer’s willingness to pay at the core of product design. Designing around the price—which measures value and priority—helps guide product design based on the customer. Companies often build the product and then do marketing and pricing, but that amounts to a leap of faith at best and a painful disconnect that leads to failure at worst. See also:
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Inspiration quickly fades and is not enough to sustain a prolonged effort. That’s why you should act immediately when inspiration strikes. For example, when you have the idea for a blog post, jump straight into writing it—waiting causes the inspiration to pass and the likelihood of writing it goes down. See also:
Public data from San Francisco revealed disturbing statistics about buildings and homes that show how difficult it is to create new housing. 54% of homes inn SF are in buildings that would be illegal to build today and 34% of buildings would be illegal. See also:
A product design partner is an early user and potential customer that provides regular organized feedback about your product. In return, they get a hand in designing the product to fit the needs of their organization, early access to the product, and discounted pricing once it launches. These partners should match the target market closely otherwise you will end up getting misleading guidance (or guidance on a different problem). A good sign of validation is when several design partners convert into paying customers after launch. See also:
In the early years of his career, Robert Moses—with all of his idealism and arrogance—failed to reform the New York City government and improve efficiency as he proposed. None of his reforms were ultimately taken up and Tammany Hall retook the mayorship from the ‘Boy Mayor’, John Purroy Mitchel the reformist, after three short years. After his brief stint in local government he was out of a job and bounced between jobs or was fired. It wasn’t until Belle Moskowitz chose Robert Moses to be her Chief of Staff did his career take off. See also:
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PEO’s often position themselves in the market as a service where you can entrust them to do everything for you. However, that is not the case. For example, while using a PEO you still need to handle leave of absences (e.g. customizing a leave letter), prepare for involuntary separations, develop a parental leave policy, set up harrassment prevention training, and even set up certain employer tax accounts (i.e. Client-reporting states). See also:
The probability that belief A is true, given new evidence B is equal to the probability of B given A times the probability of A (regardless of B) divided by the probability of B (regardless of A). For example, suppose you are getting a medical test to find out if you have a disease. The disease only appears in 1 out of 100 people and the test is 99% accurate. What is the likelihood you have the disease if you receive a positive test result? Plugging it into the equation: P(A|B)
The probability of having the disease given a positive test result (what we want to find out). P(B|A) = 99%
Probability that the test is accurate if you actually have the disease. P(A) = 1%
Probability of having the disease regardless of the test. P(B) = (1% x 99%) + (1% x 99%)
The probability the test is accurate means summing a positive test result and the probability of a false negative test result. To get the false negatives if you have a population where 100 people have the disease and take the test which is 99% accurate, you get 1 false negative. Result
There’s a 50% probability you have the disease given a positive test result (99% x 1%) / ((1% x 99%) + (1% x 99%)) = 50%
Conventional ways people (and law enforcement) use to spot a liar is pseudoscience. Research studies have found that markers like fidgeting, looking away, and emotional response are not science-based and no better than guessing. This is problematic in the justice system and other law enforcement like the TSA because they are convicting people based on appearance of guilt that is baseless. Alternatives that are found to be effective and science-based include withholding evidence to catch contradictions and sketching interviews which aids in recall (liars are less detailed). See also: