Love this quote from The Design of Everyday Things by Don Norman
“Eliminate the term human error. Instead, talk about communication and interaction: what we call an error is usually bad communication or interaction. When people collaborate with one another, the word error is never used to characterize another person’s utterance. That’s because each person is trying to understand and respond to the other, and when something is not understood or seems inappropriate, it is questioned, clarified, and the collaboration continues. Why can’t the interaction between a person and a machine be thought of as collaboration?
Machines are not people. They can’t communicate and understand the same way we do. This means that their designers have a special obligation to ensure that the behavior of machines is understandable to the people who interact with them. True collaboration requires each party to make some effort to accommodate and understand the other. When we collaborate with machines, it is people who must do all the accommodation. Why shouldn’t the machine be more friendly? The machine should accept normal human behavior, but just as people often subconsciously assess the accuracy of things being said, machines should judge the quality of information given it, in this case to help its operators avoid grievous errors because of simple slips. Today, we insist that people perform abnormally, to adapt themselves to the peculiar demands of machines, which includes always giving precise, accurate information. Humans are particularly bad at this, yet when they fail to meet the arbitrary, inhuman requirements of machines, we call it human error. No, it is design error.
Designers should strive to minimize the chance of inappropriate actions in the first place by using affordances, signifiers, good mapping, and constraints to guide the actions. If a person performs an inappropriate action, the design should maximize the chance that this can be discovered and then rectified. This requires good, intelligible feedback coupled with a simple, clear conceptual model. When people understand what has happened, what state the system is in, and what the most appropriate set of actions is, they can perform their activities more effectively.
People are not machines. Machines don’t have to deal with continual interruptions. People are subjected to continual interruptions. As a result, we are often bouncing back and forth between tasks, having to recover our place, what we were doing, and what we were thinking when we return to a previous task. No wonder we sometimes forget our place when we return to the original task, either skipping or repeating a step, or imprecisely retaining the information we were about to enter.
Our strengths are in our flexibility and creativity, in coming up with solutions to novel problems. We are creative and imaginative, not mechanical and precise. Machines require precision and accuracy; people don’t. And we are particularly bad at providing precise and accurate inputs. So why are we always required to do so? Why do we put the requirements of machines above those of people?
When people interact with machines, things will not always go smoothly. This is to be expected. So designers should anticipate this. It is easy to design devices that work well when everything goes as planned. The hard and necessary part of design is to make things work well even when things do not go as planned.”
“Spend each day trying to be a little wiser than you were when you woke up. Discharge your duties faithfully and well. Step by step you get ahead, but not necessarily in fast spurts. But you build discipline by preparing for fast spurts. Slug it out one inch at a time, day by day. At the end of the day-if you live long enough-most people get what they deserve” – Charlie Munger
I have quite a few ambitious friends who have graduated for a few years now and are in finance or consulting want to start getting into tech, specifically earlier stage companies. Being at a single startup for nearly 4 years now, I thought it would be helpful to share a few lessons learned as it pertains to thriving in an early-stage environment. The common problem that I’ve seen is that many of them don’t fully understand what it takes to (1) break into the industry and (2) to thrive in the role. I thought it’d be helpful to shed some light on the day-to-day of growing a startup as well as recommend a few books I like on the subject.
To join a tech startup, many people want to do the sexy stuff and be in a strategy role or management role right from day one. However, you’re going to find yourself hitting barriers during the interview process as your existing resume is full of internships at great companies that can be interpreted as risk averse decisions that translates into a lack of transferable skills for a startup.
My advice is to focus on the core skills that you want to develop and learn as opposed to being obsessed with chasing a specific industry or company.
In addition, you need to spend 20% of your time learning skills that will make you more deadly from an operational perspective. Common skills include learning sales + marketing, specific technical knowledge, SQL, hiring, and understanding the customer life cycle.
The best book I’ve read on this lately is by DuckDuckGo’s founder, Gabriel Weinberg entitled Traction.
Earn vs. Learn
Most people don’t make the right earn vs. learn calculation properly when they are looking to join a startup. The reason is because they are not prioritizing the learning potential of their first startup.
The common question I’ve found helpful to ask is: who are the smartest people that I have access to who are hungry and want to teach me the specific skill that I’m looking for?
Alignment of motives is very important and this is why having a mentor is not enough. A mentor is someone who you can touch base with once a month/quarter/biannually but not someone who really has skin in the game to see you succeed. They will offer you recommendations but at the end of the day, whether you are successful or not doesn’t really matter to them because your fates are not tied together. In addition, as Sam Altman once pointed out, a lot of advice that you’re getting is someone’s past experiences based on a completely different sort of circumstances and they are not really with you in the trenches trying to solve the problem.
Grit and Politics
The amount of grit it takes to go in day in and day out to not only start a company but to help scale it. This is another skill that I see people who come from less operational roles being less able to pick up from day one. You need to understand that in most cases, you’re making a sale internally to multiple people within your organization and there is a network of decision makers and end-users that will need signoff. Not to mention that you’re not looking just for signoff but whatever project you’re championing to thrive and be successful. I highly recommend picking up a book such as Influence by Richard Cialdini on how to become better with this skill as it is not something anybody is born with right off the bat.
On the subject of building great teams, this reminds me of an excerpt from one of my favorite basketball books, Bill Simmon’s The Book of Basketball in which he explains that the secret to basketball success isn’t just about talent but talent management. Are players willing to sacrifice for the good of the team? Specifically for a startup facing initial success, how well do you handle the “disease of more”?
When it comes to grit and persistence, the only real tip I have here is to set yourself up in the mindset where you are activity focused as opposed to just worrying about the results. Focus on your daily, weekly, monthly activities and the end results will follow. My favorite book on this subject is by Bill Walsh (legendary SF 49ers football coach) entitled “The Score Takes Care of Itself.”
Thanks to Yvette for the inspiration for the post!
“In truth, there is no such thing as a growth industry. There are only companies organized and operated to create and capitalize on growth opportunities. Industries that assume themselves to be riding some automatic growth escalator invariably descend into stagnation.”
“I observed something fairly early on at Apple, which I didn’t know how to explain then, but have thought a lot about it since. Most things in life have a dynamic range in which average to best is at most 2:1. For example if you go to New York City and get an average taxi cab driver versus the best taxi cab driver, you’ll probably get to your destination with the best taxi driver 30% faster. And an automobile; What’s the difference between the average car and the best? Maybe 20% ? The best CD player versus the average CD player? Maybe 20% ? So 2:1 is a big dynamic range for most things in life. Now, in software, and it used ot be the case in hardware, the difference between the average software developer and the best is 50:1; Maybe even 100:1. Very few things in life are like this, but what I was lucky enough to spend my life doing, which is software, is like this. So I’ve built a lot of my success on finding these truly gifted people, and not settling for ‘B’ and ‘C’ players, but really going for the ‘A’ players. And I found something… I found that when you get enough ‘A’ players together; when you go through the incredible work to find these ‘A’ players, they really like working with each other. Because most have never had the chance to do that before. And they don’t work with ‘B’ and ‘C’ players, so its self policing. They only want to hire ‘A’ players. So you build these pockets of ‘A’ players and it just propagates.” – Steve Jobs
I love building teams. Whether it’s helping friends at a startup find the key players that they need to grow or hiring people for my own team, one book I recently read entitled “The Rare Find” takes a contrarian approach to hiring that I wanted to share a few lessons learned. It was recommended by a long-time friend/VC, Nathan.
The book introduces the concept of “jagged resumes” as something hiring managers should focus on when looking for talent. Jagged resumes are people who may have taken a not so direct path to get to where they are today.
They do not tick off all of the traditional checkboxes such as brand-name school, prestigious internships and well-admired employers. It makes sense intuitively because if you’re looking for greatness, you have to look where other people aren’t looking.
As the book recommends, one way to find these people is to look at your own background and pattern matching from there. For example, it could be a shared university course that is known to be the most grueling, a love for tinkering with electronics/computers at a young age, or a hustle mentality (the proverbial kid who not only set up lemonade stands but was able to persuade his friends to come work for him), etc.
The reason you want to find people with jagged resumes is because when you’re hiring, you should be aiming not just for good and risk-mitigation (which is the default mode at many large companies), you’re looking for great.
Another point that resonated is to look for heuristics. The best basketball scouts can be watching thousands of young recruits a year and miss out on a few key players, but by and large, they have honed in on some ways to identify promising players that go beyond the stat line.
Having been a basketball lover since the age of 5, I can’t agree more with how one of the top scouts looks for winning players. The heuristic he employs when watching a game is to microscopically scrutinize a player’s attitude during a timeout or when a ref makes a call that a player doesn’t like, how does it affect the player? “Watch that player more closely on the next play, especially if he accidentally dribbles the ball off his shoe. The best players will regroup and shrug it off. Other players can’t do that. Their temper will get hold of them. You have to take them out of the game for a few minutes.”
The last thing that resonated with me is that the definition of work ethic differs across every industry and job function. It’s easy to forget this and to impart the virtues of one job and apply to a completely different job. I’ve found that this approach tends to be misguided – for example, applying an athlete’s type of work ethic to a job that doesn’t require the same level of competitiveness or manual training. Everyone wants a coworker that works hard. But ask yourself, “what does working hard really mean in the context of the role that I’m hiring for?”
Being an analyst at an investment bank, is actually about working long hours and having attention to detail. In complex sales, working hard doesn’t necessarily equate to that, it’s more about developing a work ethic towards studying everything about the product, your competitors’ product, and how your offering solves a customer need. In engineering, working hard means being efficient with your time and shipping code.
The reminder here is that when you’re hiring for your next role, keep in mind what work ethic means in the context of the job and look for candidates that signal positively towards this definition.
Whenever you have a process that takes your talented team members endless hours to complete, you should always think of ways to help them remove the bottleneck.
One example we recently faced at Skillz which took us longer than desired was Reporting and Revenue Statements. To solve the issue, our team mocked up a new tool to help us revamp the process and shorten the time needed to complete the task by 6x less. That’s hundreds of hours of time saved per year on the account management side when you add it across all team members.
The reminder that as a manager, these are the places you should actively look for to improve upon.
Look at the workflows of your team, what’s taking a freakish amount of time that can be solved by working with your engineering team and building a better tool?
A few places where new tools have been clutch:
– Email to Salesforce functionality
– Email lookup tools, finding lead emails
– Customer service tickets
– Developer troubleshooting tickets
– SCRUM notes
– Event registration software
Enjoyed this excerpt from Ross McCammon.
“Innovate. Please. The future depends on it. But also: Invent. Because the feature depends on results, too. Things we can touch and walk through. Things we can smell and experience. Services that will change our lives.
Innovation merely ensures that we are working on something. Invention ensures that we are creating what we said we were going to create. We need actuality. We need fulfillment. We need results. And our words need to connote obligation as much as promise.”
Having been in tech for half a decade, there’s more talk than ever before on creating innovative products, but so much of technology are mere solutions in search of problems. Instead, why not commit yourself to the problem and aim hell and high water to solve it?