Smarter Faster Better uncover how high achievers get so much done and accomplished while having the same time like everyone else does. In the author’s own words:
Productivity, put simply, is the name we give our attempts to figure out the best uses of our energy, intellect, and time as we try to seize the most meaningful rewards with the least wasted effort.
The author has broken down productivity, the hairy topic, into eight parts that include motivation, teams, focus, goal setting, managing others, decision making, innovation, and absorbing data.
People who know how to self-motivate, according to studies, earn more money than their peers, report higher levels of happiness, and say they are more satisfied with their families, jobs, and lives.
A prerequisite to motivation is believing we have authority over our actions and surroundings. To motivate ourselves, we must feel like we are in control.
People with an internal locus of control tend to praise or blame themselves for success or failure, rather than assigning responsibility to things outside their influence.
If you can link something hard to a choice you care about, it makes the task easier.
We should reward initiative, congratulate people for self-motivation, celebrate when an infant wants to feed herself. We should applaud a child who shows defiant, self-righteous stubbornness and reward a student who finds a way to get things done by working around the rules.
A good manager:
On the best teams, for instance, leaders encouraged people to speak up; teammates felt like they could expose their vulnerabilities to one another; people said they could suggest ideas without fear of retribution; the culture discouraged people from making harsh judgments.
For psychological safety to emerge among a group, teammates don’t have to be friends. They do, however, need to be socially sensitive and ensure everyone feels heard.
Once in a cognitive tunnel, we lose our ability to direct our focus. Instead, we latch on to the easiest and most obvious stimulus, often at the cost of common sense.
Reactive thinking is at the core of how we allocate our attention, and in many settings, it’s a tremendous asset.
Reactive thinking is how we build habits, and it’s why to-do lists and calendar alerts are so helpful: Rather than needing to decide what to do next, we can take advantage of our reactive instincts and automatically proceed. Reactive thinking, in a sense, outsources the choices and control that, in other settings, create motivation.
The downside of reactive thinking is that habits and reactions can become so automatic they overpower our judgment. Once our motivation is outsourced, we simply react.
The superstars weren’t choosing tasks that leveraged existing skills. Instead, they were signing up for projects that required them to seek out new colleagues and demanded new abilities.
The superstars also shared a particular behavior, almost an intellectual and conversation tic: They loved to generate theories—lots and lots of theories.
Mental models help us by providing a scaffold for the torrent of information that constantly surround us. Models help us choose where to direct our attention, so we can make decisions, rather than just react.
You can’t delegate thinking. Computers fail, everything can fail. But people can’t. We have to make decisions, and that includes deciding what deserves our attention.
No one goes to work wanting to suck. If you put people in a position to succeed, they will.
Most commitment companies avoided layoffs unless there was no other alternative. They invested heavily in training. There were higher levels of teamwork and psychological safety.
Employees work smarter and better when they believe they have more decision-making authority and when they believe their colleagues are committed to their success.
The paradox of learning how to make better decisions is that it requires developing a comfort with doubt.
We only live on one reality, and so when we force ourselves to think about the future as numerous possibilities, it can be unsettling for some people because it forces us to think about things we hope won’t come true. — Barbara Mellers
Learning to think probabilistically requires us to question our assumptions and live with uncertainty. To become better at predicting the future—at making good decisions—we need to know the difference between what we hope will happen and what is more and less likely to occur.
How do we learn to make better decisions? In part, by training ourselves to think probabilistically. To do that, we must force ourselves to envision various futures—to hold contradictory scenarios in our minds simultaneously—and then expose ourselves to a wide spectrum of successes and failures to develop an intuition about which forecasts are more or less likely to come true.
Almost all of the creative papers had at least one thing in common: They were usually combinations of previously known ideas mixed together in new ways.
“Creativity is just connecting things,” Apple cofounder Steve Jobs said in 1996. “When you ask creative people how they did something, they feel a little guilty because they didn’t really do it, they just saw something. It seemed obvious to them after a while. That’s because they were able to connect experiences they’ve had and synthesize new things. And the reason they were able to do that was they’ve had more experiences or they have thought more about their experiences than other people.”
When strong ideas take root, they can sometimes crowd out competitors so thoroughly that alternatives can’t prosper. So sometimes the best way to spark creativity is by disturbing things just enough to let some light through.
Humans are exceptionally good at absorbing information—as long as we can break data into a series of smaller and smaller pieces. This process is known as “winnowing” or “scaffolding.”
One way to overcome information blindness is to force ourselves to grapple with the data in front of us, to manipulate information by transforming it into a sequence of questions to be answered or choices to be made. This is sometimes referred to as “creating disfluency” because it relies on doing a little bit of work.
The engineering design process was built around the idea that many problems that seem overwhelming at first can be broken into smaller pieces, and then solutions tested, again and again, until an insight emerges.
Psychologists say learning how to make decisions this way is important, particularly for young people, because it makes it easier for them to learn from their experiences and to see choices from different perspectives.
Our brain wants to find a simple frame and stick with it, the same way it wants to make a binary decision.
One of the best ways to help people cast experiences in a new light is to provide a formal decision-making system—such as a flowchart, a prescribed series of questions, or the engineering design process—that denies our brains the easy options we crave. Systems teach us how to force ourselves to make questions look unfamiliar. It’s a way to see alternatives.
When we encounter new information and want to learn from it, we should force ourselves to do something with the data.
Productive people and companies force themselves to make choices most other people are content to ignore. Productivity emerges when people push themselves to think differently.