Every system using data separates humanity into winners and losers.
The creative folks intuitively design what's best for the user, while data folks provide great insights. The true unicorns are those who can go end-to-end designing, building, measuring, analyzing, and iterating with a combination of user intuition and deep analytics.
Data about an innovative idea is rarely crystal clear.
. . . a person and an organization must have goals, take actions to achieve those goals, gather evidence of achievement, study and reflect on the data and from that take actions again. Thus, they are in a continuous feedback spiral toward continuous improvement. This is what 'Kaizan' means.
. . . negative feelings are not true feelings at all; rather, they are your thoughts about something, based always on the previous experience of yourself and others. You will not find Truth in your past data, only past data that is based on other past data that is based on other past data, and so forth. Forget your "past experience" and look directly at the experience you are having. Right Here, Right Now. There is your Truth.
Students using astrophysical textbooks remain essentially ignorant of even the existence of plasma concepts, despite the fact that some of them have been known for half a century. The conclusion is that astrophysics is too important to be left in the hands of astrophysicists who have gotten their main knowledge from these textbooks. Earthbound and space telescope data must be treated by scientists who are familiar with laboratory and magnetospheric physics and circuit theory, and of course with modern plasma theory.
The four most dangerous words in finance are 'this time is different. ' Thanks to this masterpiece by Carmen Reinhart at the University of Maryland and Kenneth Rogoff of Harvard, no one can doubt this again. . . . The authors have put an immense amount of work into collecting the data financial institutions needed if they were to have any chance of making quantitative risk management work.
Nothing is more detestable to the physical anthropologist than. . . the wretched habit of cremating the dead. It involves not only a prodigal waste of costly fuel and excellent fertilizer, but also the complete destruction of physical historical data. On the other hand, the custom of embalming and mummification is most praiseworthy and highly to be recommended.
Although the prime numbers are rigidly determined, they somehow feel like experimental data.
That was one of my most surprising discoveries when I dug into the history of average-ism: When you actually get the data, it rarely captures anyone. Which then begs the question, why are we using this as a reference standard for human beings?
I have never left the company. I keep a tiny residual salary to this day because that's where my loyalty should be forever. I want to be an "employee" on the company data base. I won't engineer, I'd rather be basically retired, due to my family. (talking about his relationship with Apple Inc)
Management must provide employees with tools that will enable them to do their jobs better, and with encouragement to use these tools. In particular, they must collect data.
We have 25 or so years invested in the work. Why should I make the data available to you, when your aim is to try to find something wrong with it.
It amazes me how people are often more willing to act based on little or no data than to use data that is a challenge to assemble.
Get the weirdnesses into the data where you can manipulate them easily, and the regularity into the code because regular code is a lot easier to work with
Theory without data is myth: data without theory is madness.
A hacker doesnt deliberately destroy data or profit from his activities.
There is no experimental data that exists that supports the view that the Earth's climate is changing in any dangerous way.
The TV scientist who mutters sadly, "The experiment is a failure; we have failed to achieve what we had hoped for," is suffering mainly from a bad script writer. An experiment is never a failure solely because it fails to achieve predicted results. An experiment is a failure only when it also fails adequately to test the hypothesis in question, when the data it produces don't prove anything one way or another.
On the question of whether a behavioral science can in principle be constructed, we shall take no sides. That some kinds of human behavior can be described and even predicted in terms of objectively verifiable and quantifiable data seems to us to have been established.
