Committing to rewriting

When we write, the first draft is simply a crystallization of our thinking. The first draft, in essence, is for us. The challenge with writing well is rewriting that first draft with our audience in mind. Doing so helps us separate the process of thinking from the process of writing.

While this sounds simple in practice, this turns out to be very hard. As Barbara Minto articulately describes – “Once you put ideas in writing, they take on an incredible beauty in the author’s eyes. They seem to glow with a fine patina that you will be quite reluctant to disturb.” 

This is true – at least in my experience.

One approach to solving this problem is to lay out your thought process on a piece of paper before writing. That, however, may not work for everyone. While I’m keen to test it, I’m not optimistic about my attempts to do this well.

The alternative solution I’m more hopeful about is to start writing by making a strong commitment to rewrite as soon as I complete the first draft. Setting this expectation will hopefully make it easier for me to not get lost in the “glow” of my first draft.

Here’s to experimenting with both.

PS: Thankfully, the tools we use today are perfect editing and rewriting. It is a pity if we use our current suite of editing tools like typewriters.

Don’t rush to be embarrassed by the first version of your product

The intent of good quotes is lost over time. So, they are often misunderstood and misused because they are applied out of context. Reid Hoffman’s quote – “If you are not embarrassed by the first version of your product, you’ve launched too late.” – is a great example of loss of intent.

I’ve seen this quote used as an excuse to justify a crappy v1/first version product. I haven’t heard Reid talk about this in person – but, I’m fairly certain that that wasn’t the intent.

There are two good reasons to be embarrassed about v1 (in hindsight). The first is the most common – you didn’t know better and/or couldn’t do better with the tools available. The first website I put together looked horrendous. I didn’t understand the basics of web design and it was also built on an early version of Adobe Dreamweaver. Now, however, I have slightly better design skills and, more importantly, have access to amazing tools. Thanks to the likes of Bootstrap and services like WordPress, it is very easy to build a good website.

The second is the result of prioritizing one killer use case/risky assumption for your product and ignoring everything else. You may still be embarrassed by the first version – but, you’ll still have served that basic user/customer need.

Source: Unknown – thank you to whoever made this.

The truth is that you’ll be embarrassed by nearly everything you ship. Over time, your skills will improve, the tools will get more sophisticated, and your understanding of the user/customer need will get better. So, you don’t have to work too hard to cut a few corners now to ship something you’ll be embarrassed by. Time will take care of that. The key, instead, is not to knowingly do something you will regret.

So, the two questions I’d suggest asking are –

  • Is what we are shipping helping us learn what we want to learn while providing value to the user?
  • Is this our best effort based on what we know/have access to now?

If the answers to both are yes, ship away. Even if you are eventually embarrassed about what you ship, this approach will make sure you will not have any regrets.

Directional answers and precise answers

I use simple a rule of thumb for the difference between attempting to convert a directional answer into a precise answer – 10x+ time investment.

Attempting to find a reasonably good pair of headphones might just take you 10 minutes on Amazon. However, if you’re looking for the best headphones you can find for your budget, you could easily spend 100+ minutes searching.

Similarly, if you want to predict the effect of your strategy on key metrics, you might be able to get to a directional range in 2 hours. But, if you want to isolate and understand every variable and its interactions, you’ll want to budget at least 20+ hours of work.

This is analogous to being a satisficer versus a maximizer. Attempting to maximize everything you do by getting precise answers is very expensive. Thus, the implication in conducting analysis as in living life is similar – assume you need directional answers unless it is clear that precise answers are the way to go.

Every once a while, you’ll realize that you’d have been better off finding that precise answer. But, thanks to this strategy, you’ll have enough buffer time to course correct. :-)

Managing perception and leading with it

“Perception becomes reality” – is one of the marketing’s cardinal principles. Taken to its extreme, it could mean working away at improving our perception, i.e. “our brand,” at the expense of everything else. In this race to improve perception, it is easy to forget that…

… companies renowned for good customer service start by providing great customer service.
… we get better at leadership by caring more about people, processes, and results than the next person.
… a person’s network is directly proportional to a person’s net worth – valued either by money or by character – sometimes both.
… and so on.

Perception undoubtedly matters. But, building a brand on perception is akin to vaporware. A select few manage to use the fuel from vaporware to build great products. Most don’t.

The most reliable way to build brands – organizational and personal – is by actually doing/building good things that create value and/or impact people in positive ways. Once you work on improving reality, it is critical to manage perception.

But, beware leading with it.

Abraham Wald

As Allied Planes in World War II were being shot down at a devastating rate,  the US Air Force wanted to reinforce the planes with armor. However, every pound of extra armor took away the attack capacity of the planes. The person tasked with solving the problem was Abraham Wald, a Romanian Jew who’d fled the Nazis to become a Professor at Columbia University. He was recruited in the US Army efforts in World War II as part of the Statistical Research Group.

The Air Force supplied Wald with the data available – number of bullet holes grouped by their location on all the planes that returned to base. Most bullets were around the tail gunner and the wings. So, the army suggested reinforcing these regions with armor.

In what has become a legendary piece of analysis, Wald disagreed. He noted that the fact that the planes had survived despite these injuries suggested these areas needed no reinforcement. All the other planes had likely been struck elsewhere – the engine and the cockpit for example. Those were the areas that needed to be armored.

Wald gave us survivorship bias. In simpler words, he reminded us to look for insight by being very mindful of the data that isn’t in the room. And, as I think of a recent error that rose from jumping to a conclusion with available data, I realize I must spend more time channeling Abraham Wald.

3 steps to making that big career transition

When we make career transitions, we typically change one or more of the following – (1) Company, (2) Role, (3) Industry, and (4) Location. These are ordered in ascending order of difficulty with changes in location – for the majority of the folks on the planet who do not possess rich country passports – being the hardest by a distance. Most importantly, combining these factors does not simply mean adding up the difficulty – the change gets exponentially harder.

Thus, career transitions can be very hard to make. While there is something be said about experimenting in the early stages of our careers, there are benefits to being in the right (for you) location, industry, and role early. Career transitions are also hard because they require dealing with all the feelings of insecurity and inadequacy that accompanies job hunting. This is heightened if you are an immigrant as you are doing it with the weight of uncertainty about how your change will work given your immigration status.

The result, for many folks, is multiple cold inMails and connection requests to folks they find on LinkedIn searches to ask for referrals or mentorship. This is understandable. Attempting to make a career transition is stressful and any help is appreciated. Sadly, cold inMails to strangers turns out to be the least effective approach.

Over the past five years, I’ve been fortunate to make a transition that involved changing all 4 factors. As with most things, it took a combination of intention, work, dumb luck, and accumulated privilege. We’re still working through visa challenges – so the location change is far from final. Nevertheless, I thought I’d share a 3 step approach toward making big career transitions. To ensure broad relevance, I’ve focused on the key principles while also adding color based on my experiences.

(1) Construct plans A-F: The first and most important assumption I’ll make is that you know exactly what you want to do (if you don’t, please see the resources section below). Once you do so, construct plans A-F. This means having at least 6 routes to the destination. I think the word “destination” is particularly applicable if you are trying to make a cross-country switch as it is worth tackling that head on.

I say plans A-F because it is highly unlikely your plan A will work. And, as you cycle through them, it’ll become easier to move past F to other alphabets. :-) For example, I learnt about the Bay Area and tech while working on a student job portal start-up (that eventually failed) through university. That’s when the idea of working in tech in the Bay Area took hold. But, as I mentioned above, location switches are the hardest kind to make if you don’t have the right passport. In the next 4 years, I cycled through plans A-F before finally finding a graduate school in the US that took a chance on me. (Graduate school is a staple in the immigrant playbook to switch locations)

The next step was to make an company + industry switch – i.e. find a tech company that would take a chance on me – and then a role switch – I’d learned about product management and believed I’d found my functional home. But, how do you get a start when everyone wanted folks with relevant experience?

Below is an image with the 6 questions I’d suggest asking.

Next, my suggestion would be to build your plans by attacking as many of these options. For example, here’s how I approached it  –
A: Was connected to a role thanks to a past colleague.

B: Was connected to a few folks by the same past colleague (he’s a good samaritan) – one of these folks worked at LinkedIn. Also got a referral into someone from my graduate school alumni network. She helped with an interview call.

C: Didn’t attempt connections with strangers on LinkedIn as I wasn’t sure how I’d do so in a thoughtful manner.

D: I signed up for interviews with most companies that took a shot on MBA students without visa sponsorship for Product Management positions.

E – I thought highly of LinkedIn’s product and the vision and felt I’d fit in well. But, LinkedIn was also very mainstream. So, I was also focused on a company like VMWare that was focused on solving solutions with a high level of technical complexity. I figured thorough prep on server virtualization would be a competitive advantage – since few folks would actually do it.

F – I ended up betting on an internal transfer to move into Product Management at LinkedIn. These sorts of transfers are painful in most places. So, this wouldn’t have been my dominant strategy had it not been for an intersection with an opportunity to work with someone I liked and respected, a company whose mission resonated deeply and because of immigration considerations.

All in all, once I’d managed the location move, I attempted all options except emailing a random stranger because the chances of that working are minimal at best. If you are keeping count, I was well into plans M and N by this point.

(2) Understand base rates, preferred demographics and stereotypes: This step is designed to accomplish two objectives – i) Add a dose of realism to your search, and ii) Aide your preparation for an interview which you hopefully will land.

Step (1) was all about mapping your path to what you believe is a dream role. However, it helps to get a sense of the odds. Here, there are 3 questions that might help –
A. Base rates: Are there folks “like you” (similar education, work experiences) who are in those roles in companies you want to be?
B. Preferred demographics: Are you in the demographic that companies are hiring for right now?
C. Stereotype: Do you fit the stereotype that recruiters/hiring managers love?

I understand these may sound like controversial sounding questions. But, just because no one likes talking about them doesn’t mean they aren’t a key part of the hiring process.

In my case, the base rates were encouraging. There were folks with similar education, experiences in roles in tech. However, I wasn’t doing good on B. No one was jumping out of bed excited to add another Indian guy who needed visa sponsorship – which was getting more and more problematic – to their team. And, my stereotype was a mixed bag. The consultant + MBA combination was appreciated by some and despised by some. Now, you might say – “Hey, but what I did in the past doesn’t/shouldn’t define me.” Yes, it shouldn’t. But, given our human need to make quick decisions and label people, it does. So, we might as well learn to overcome it.

While you can’t do much about base rates and preferred demographics, it is important to note that you can do something about stereotypes – especially if you don’t believe you are the typical specimen. – by working on your story in your interviews. I didn’t think I was. I also had spent 3 years in a start-up and worked on plenty of side projects. I hoped to weave that into my story.

I had 2 key takeaways from my own inventory check –
1) This change was possible but was not going to be easy as the field was very competitive.
2) I’d have to find a way to make any interview calls I receive really count. I didn’t have experiences at a big name brand pre-graduate school. This generally means fewer interview shots since fewer folks are willing to take a chance on you. That, in turn, meant I needed to over index on interview readiness as I’d need to have a higher conversion rate.

(3) Take a really long term view. Do you care enough about your career switch to work on it for 5 years? If you do, that is good news. Here are 3 reasons why a long time horizon helps –

1) You will learn and grow through the process of attempting to make a switch. All these experiences will make you a better candidate – if you are willing to persist.

2) It is easier to change fewer variables at a time. For example, a change of location and role or location and industry are easier switches than attempting to change company, industry, role and location. This is particularly the case if you are immigrant – getting your location via visa sponsorship will likely be your dominant strategy.

3) You will have the time to convert random strangers and acquaintances to friends and well wishers. This is really really important. A big part of making transitions is building a network of relationships who will support you through it. And, it is very hard to build this network if you want immediate results. You can’t plant trees the day you want fruits.

I have a couple of stories to make my point. In my case, one of my failed early plans to move involved a final round interview that didn’t go well. However, I stayed in touch with the friend of a friend I’d mentioned above. We ended up meeting in person a couple of times and, thanks in no small part to the help I received, I ended up working on their team a full two years after we connected. Second time lucky.

Another related story – I was connected to someone by an acquaintance. This person stayed in touch via my blog with email exchanges over three years. That led to an in person meeting, then another one, and then a few calls. A full four years later, I was thrilled to help this person find a role where I work.

I could share a few more such stories to continue hammering this point home. But, I’ll stop. The key takeaway – our career journeys are long and full of surprising and random twists and turns. You never really know who will open a door for you some day in the future and you definitely don’t know if a good/bad day is so. It is futile to connect dots forward. So, a better approach is to make commitments on directional plans in the long term, be kind and thoughtful, and keep plugging away.

If this post is reaching you in the midst of a tough time, I’m sorry to hear that. It is surprisingly common on such journeys as the odds are always stacked against you. But, I’ve come to believe that the arc of success and opportunity bends toward merit in the long run. It helps to approach the whole journey as a mixture of scientist and student. Start with hypotheses, run experiments, test, learn, and iterate.

As the wonderful saying goes – “Things work out fine in the end. If it’s not fine, it is not the end.”

I hope this is helpful. Wishing you all the best on your journey.


Additional resources: Here are 5 resources that might help.

(1) The 3 phases of a job search process: This is a companion long read that dives into the details of the job search – figuring out where to apply, getting interviews, and doing well:

(2) 3 principles of asking for favors

(3) How to ask for help from people you don’t know and related – Ask advice better by replacing the generic question with a hypothesis

(4) How to ask for a cold call

(5) The 3 laws of privilege: Slightly off topic – but important. :-)

In data we (don’t) trust

There’s a growing legion of companies and product teams that aspire to call themselves “data driven.” When they make decisions, they tell tales of how Google tested 40 shades of blue and eliminated the need for intuition and gut-based decision making.

But, as data might suggest, extreme beliefs in any approach are problematic and a belief in data driven decisions is no exception.

For the data to point the way, we need suitable problems, the right inputs and tracking based on good questions and thoughtful hypotheses, reliable data pipelines, good analytical judgment in overlooking outliers and picking a robust methodology, and versatility in the tools to analyze and interpret the outputs. Every once a while, all of these align and it all just works.

But, for the most part, we’re better off marrying a desire for data with a healthy skepticism for what it is telling us. It is that skepticism that will ensure we keep pushing for the right questions and iterate our way into insights that get us closer to the truth.

Better to be data informed than data driven.