133 - 2024 - a year in preview



Writing like cooking, learning like playing, and being helpful

These are three ideas I’m carrying over to next year.

Being helpful

I recently had a breakthrough thought. I was thinking about how I could be better at football.

Earlier this year, I made a return to football after a hiatus of 15 months. Before that, all through my adult life until 2021, I had been physically active. I did long-distance running (full and half marathons), played 50 weeks a year, used to be a gym rat for several years.

So when I found myself short of breath during a football tournament in October 2021, I put it down to an earlier bout of COVID. Then it happened again, and again. A visit to the cardiologist followed by a stress test on the treadmill and some bloodwork in the lab revealed I was genetically predisposed to high cholesterol and to problems that came with it. My diet and lifestyle had to change.

I won’t say that I took the opportunity to redesign my life because I did not. I languished. Being physically active had been part of my identity and here I had been asked to stay away from doing the things that gave me joy, that I had taken for granted. I went through an ego death. It was not until the second half of 2022 that I mustered the discipline to mount a get-back-to-the-field project.

Back to my light-bulb moment. I thought if I could be available to my teammates when they had the ball on the field, they would appreciate it. I would present an extra option for them to consider. And if I could be free—that is, shake players off me—I might just raise myself to the top of their charts. I could make myself the best available option for my teammates. Always finding someone to pass to, they would make fewer mistakes. They would have an easier, better game.

To be able to always be available for my teammates, I had to be fit. I needed to have the legs to cover all that ground. So, now my fitness had a clear goal: get fit enough to be helpful. It was/is instantly energizing.

I have now started looking at other fields of play through the same lens. I want to take this attitude of being helpful to my roles as a parent, as a husband, and as a colleague. Maybe helpful is vague for you—I get it. The idea came to me, as I’ve recounted here, from the football field. I don’t assume the same field of play to matter to you. So, how about becoming easy to live with or easy to work with? What can you do to make the lives of those around you at work or at home better?

People don’t just believe in reciprocity. They practice it. Being helpful to someone at a time of their need induces them to be there for you when you need them. So, if I’m there for my friends and family and colleagues, my own life may transform because of my attitude.

Writing like cooking

Cooking is a funny business. You take a bunch of raw ingredients and put them through a sequence of steps that transforms not just them but the ensemble that you make of them. And then you feed others what you’ve made and the slate is wiped clean at once. There’s no proof or record of what you just did. To achieve the same effect, you have to do it all over again.

Such alchemy, yet so momentary.

Still yet – food touches hearts like few other things in life. Our fondest memories, our widest smiles, our deepest gratitude are sometimes tethered to what was once on the plate.

I started writing in 2021 when I was going through a tough time at work. I felt out of my depth and that forced me to pick up new skills and that got me writing as I thought the best way to pin down what I learn was by trying to put it down in words. I also told myself that I was writing and publishing the same to get feedback and get better. I said the same to a mentor. When I whinged to him that I wasn’t getting the volume or depth of feedback that I wanted, he challenged my story. He said I didn’t want feedback.

It took me a long time to realize he was right. It took me a while to grasp that my writing was the opposite of cooking. I was producing something for posterity and because it would be there for good I wanted it to not be tarnished in any way. So, I sought the gentlest of receptions. Social media (LinkedIn) became a self-image haven for me.

My mentor suggested that I wrote for validation. Optimizing for validation means sacrificing a look in the mirror.

When you write for the attention of those who pick up raffle tickets at a supermarket, you fight for validation from the many and concern from a few. Those people don’t expect their lives to be changed because of this raffle ticket they (barely consciously) bought and you don’t care about changing their lives either. You just want them to snatch that ticket you’re waving in their faces so that you can say you’ve sold these many tickets. You can see your name up on the numbers board, get a kick out of it.

You see? The opposite of cooking.

Writing as cooking, on the other hand, is about intent. That intent lends meaning. I write – I’ll remind myself in the coming year and more – to express myself. Self-expression leads to self-discovery. You cannot find what you haven’t manifested. Lately, I’ve been enjoying the process of learning and writing. More on that below.

Learning like playing

Some big ideas I have dipped my toes into this year: regression to the mean, tackling the hardest part first (or the more colorful, monkeys and pedestals), meta-learning (learning how to learn), framing, design of business, exploring versus exploiting, thinking about money (mental accounting), quitting (or thinking in opportunity costs).

A pattern I noticed earlier this year is that I stopped being curious about a topic once I had written about it and published it. The act of putting my thoughts out put a tourniquet on my thinking. Hitting publish became the finish line in the race to learn. And I’ve had many finish lines to aim at—this newsletter has popped in your inbox more than 55 times this year.

An accompanying symptom to this goal-oriented process was stress. I found myself worrying about the next issue. Now, it is completely reasonable to be under-confident at the beginning of the process – for the kind of writing I do. But to tether my ambition to putting this newsletter out every week or showing up regularly on social media made learning feel like a job.

Luckily, sometime mid-year, I discovered the autobiographical writings of Josh Waitzkin, polymath and lifelong learner, and I found the curation of Michael Simmons (here and here for starters).

Michael Simmon traced these two paths.

Like most, I found myself on a path like this:

Goal ➡️ Strategy ➡️ Discipline (push) ➡️ Success ➡️ Do what you actually love

Like only a few, I want to stay close to this path:

Do what you love ➡️ Devotion (pull) across time ➡️ Skill + Body of work ➡️ Success

If you notice, our first and most energizing loves in life, whatever that may be, follow the second path. They have us in their palms like little children. I won’t belabor the point here. Instead, I’ll let you in on something I look at on my wall every day.

>>>>> gd2md-html alert: inline image link here (to images/image23.jpg). Store image on your image server and adjust path/filename/extension if necessary.
(Back to top)(Next alert)


These are three ideas I’m taking with me to the new year (and beyond). What are yours? Wish you happiness in the coming year. See you in 2024.

_Why hiring a star may not bring you what you want _

If you’ve ever hired someone with a stellar CV and recent impressive projects behind them only to find them floundering, you may have been fooled by randomness.

Market tailwinds, level of skill complementarity with team/business unit, life stage with lower opportunity costs, hot hand stints that are shorter than the time required for regression to the mean – there are so many factors at a systemic level that can affect outcomes that are not down to the competence of the knowledge worker.

OPTION 1: #132 - A general truth about mid-career knowledge workers

A general truth about mid-level managers I learned from doing user research interviews across organizations and industries over the last several months:

1️⃣They don’t feel the need for decision-making training. Why?

2️⃣They rarely get to make consequential decisions in their organization. Why?

3️⃣They are generally not privy to strategic org direction and future plans needed to make such decisions. Why?

4️⃣Companies practice information asymmetry borne out of a need-to-know philosophy. Why?

5️⃣Those above mid-level managers (executives, managers of managers, CEOs, founders) believe that transparency is a net negative strategy.

It is not hard to see that, following the trail of whys, we started with a symptom and ended deep into patterns of organizational behavior.

The issue is systemic.

Sometimes mid-managers do have the information/context. In such cases, they often have to follow decision-making approval loops up the chain of command. So, the decisions don’t go into their books. Their bosses stand beside them, holding an umbrella over their heads.

Mid-managers could still learn from the decisions of their bosses if the bosses open-sourced their thinking/reasons for key decisions. This tends to happen less often than is healthy because 𝘴𝘦𝘯𝘪𝘰𝘳 𝘮𝘢𝘯𝘢𝘨𝘦𝘳𝘴 𝘵𝘰𝘥𝘢𝘺 were mind-blown 𝘮𝘪𝘥-𝘮𝘢𝘯𝘢𝘨𝘦𝘳𝘴 𝘺𝘦𝘴𝘵𝘦𝘳𝘥𝘢𝘺.

When these mid-level managers make the jump to senior management, they become cats on a hot tin roof. They are paid big bucks to deliver on this product called decisions but they have not learned and fine-tuned a product development process (= a decision-making process).

All this access to information and org context, thanks to their higher position on the corporate ladder, has the opposite effect of hijacking their thinking. As a clueless boss, they go on to share less. The problem propagates.

I’ve a few Kahneman stories filed away in my head. My second favorite (after the one in which he responds to a reporter’s call asking for a byte on his friend and new Nobel laureate Richard Thaler by saying, ‘Thaler’s most special quality is that he’s lazy.’) is one where, as his contribution to an online magazine’s collection of scientists’ famous equations, he offers:

success = talent + luck

great success = a little more talent + a lot of luck

Oh, how I love this self-deprecating chap!

This equation, in my humble opinion, is an onion. And in today’s issue, I will try and peel it for you.

Regression to the mean sounds jargony. What it means is simple. Most outcomes in life are a combination of skill and chance. The more the element of chance, the more random the outcome is. The more the influence of random factors, the greater the swing from extreme outcomes to moderate ones.

You know that a coin toss is random. But imagine it took a certain amount of skill to get heads on a coin toss. The game is to get as many heads as possible in ten coin tosses. A beginner coin tosser will maybe score two heads out of a set of ten. An expert will get eight or more. Now, say, you get three heads from your first set. It would be reasonable to conclude that your chances of getting to eight in your next set are very slim. Because the gap in skill needed for a three and an eight is too big for anyone to bridge in one try. You’ll probably need to train several months at the National Coin Toss Academy and practice under regular supervision before you can make a go at eight.

Now hit pause on your fanciful thoughts. Slowly return to reality.

Now play the same game with the same rules, with just one change. The coin toss requires no skill. It is entirely random. So you go. In your first set of ten, you toss two heads. In your next set, you get to — voila! – an eight. You’re happy but you somehow are not entirely gobsmacked. Assuming you find this outcome believable, allow me to ask you why you find it so.

For a simple reason — the outcome is pure chance. Over a small enough sample, which is what ten coin tosses is, it is very much possible for you (or anyone) to score eight heads. You get giddy at this early success. You wonder if you can be a professional coin-tosser. You go all in, trying to make it big in this exotic profession. You practice tossing sets of ten over and over again, every day. A few months pass. The results should be there for you to see. Going over your scores, you find sequences of eleven heads and thirteen tails, but your overall average is split 50-50 between heads and tails.

The only thing it means is this:

If you try to measure some attribute on N occasions (where N is a large number), and that attribute is governed by random forces, then the overall measurement will tend to stay close to an average value.

I asked ChatGPT to come up with headlines from different walks that laugh at the idea of regression to the mean. These are what it gave me:

Politics: New Mayor’s First Month Sees Record Low Crime Rates: Promises to Eliminate Crime Entirely by Year's End

Sports: Rookie Hits 5 Home Runs in Debut Game: Fans Expect Season Total to Surpass 800

I prefer a cricket version: Rookie Hits Fastest Century in IPL History; Experts Hail the New AB de Villiers

Cinema: Director's Multi-Starrer Film Is a Dud at the Box Office; Studio Backs Out of Next Venture

Now you see it. But let’s face it — you’re not in the movies or in politics and coin tosses are not a big deal. What are some situations when the hand of lady luck is not acknowledged in your line of work — that is, in knowledge work?

What do you not see when starting a company or launching a product or hiring a candidate?

What makes such decisions especially tricky is not just the role of luck is under-emphasized in general but also that you almost never have access to a big enough sample size, so you end up judging on a small and unrepresentative data set. You judge a second-time founder over their last venture, a product manager over their last couple of products, and so on.

What to base my judgment on, you ask.

On the strength of the correlation between skill and the outcome. How closely related are skill and the desired outcome.

All outcomes are random in different proportions. You’ve got to form an idea about the degree of randomness. That’s the work. If the correlation is perfect, it means they move together. If it is imperfect, they travel apart depending on the degree of imperfection.

This approach moderates your prediction by taking the evidence and regressing it to the mean based on the strength of the correlation. If there’s a strong correlation between the outcome and skill, the adjustment is small. In other words, the outcome was skill-dominated. If the correlation is weak, the adjustment will be big. You will not read too much into the fact that the social media manager CV on your table has three successful campaigns, all centered around the same influencer who went viral just before the campaigns and had a follower base that very closely matched her previous employer’s target audience. Look beyond any of those contributing factors and the outcome is hard to replicate.

Let’s go back to Kahneman’s favorite equation:

success = talent + luck

great success = a little more talent + a lot of luck

What Kahneman seems to be saying is that, by and large, luck has a big hand to play in unprecedented success. But the reason he seems to suggest it as an non-obvious insight (and not an obvious truth) is because people love attributing success to something within their control. Imagine a parent or teacher tasked with explaining this equation to a teen who prefers smoking pot to anything remotely constructive.

Just as parents choose to believe it was their tough love that helped pull their teen from the doldrums, marketing managers do not want to change a thing from the last campaign if it was successful and founders are worried about their second line getting complacent after a blockbuster year.

All are explained by regression to the mean. Few are acknowledged. Next week, I’ll use Kahneman’s equation — remember the thing about it being an onion — to show you how the very best trounce regression to the mean.




Acknowledging randomness underestimates the role of skill in success and suggests a ‘what’s the point of life’ kind of fatalism. There’s an argument against my last piece. That argument has heft.

Riffing off Kahneman’s _success = talent + luck, _I can say that talent contributes to success _because of _it while luck leads us to success _regardless of _your talent. So,

Success = success _because of _your skill + success _regardless of _your skill

👉Success in sales = success because of your selling skills + success because you happen to be selling a great product (something that is completely unrelated to your skill)

👉Success in management = success because of your ability to lead + success because you’ve a great team (unrelated to you)

In What Got You Here Won’t Get you There, executive coach Marshall Goldsmith writes:

Successful people tend to have a high “internal locus of control.” In other words, they do not feel victims of fate. They see success for themselves and others as largely a function of people’s motivation and ability—not luck, random chance, or external factors.

Achievers tend to believe that their success is earned through their ability and motivation (and others’ failures are similarly earned through their lack of ability and motivation). It is plain to see how such a belief empowers. It also hoodwinks.

I think the narrative of skill only travels one way. This piece will mount a challenge against the notion that all successes are purely a result of skill.

When it comes to any meaningful outcome, as humans, we hate to let randomness have a seat at the table. We like cause and effect so much better, and skill makes for a great cause in the stories we tell each other. So we attribute to skill (and design and intent and other controllable attributes) what happens due to chance (uncontrollable). We do this over and over again, and we assign credit and blame when neither is deserved because — it is random.

All things are random in different quantities. A coin toss is pure chance; a Wimbledon victory is some chance and some skill; eight Wimbledon championships is some chance and buckets of skill.

Here’s the big question:

What can be attributed to chance that we attribute to skill, and how does this misattribution shape the world we live in?

You may have heard of the Sports Illustrated Cover Jinx.

It’s a popular belief that individuals or teams who appear on the cover of _Sports Illustrated _magazine will see a decline in performance subsequently.

From Wikipedia:

May 26, 1958: Race car driver Pat O'Connor appears on the cover of the magazine. He dies four days later on the first lap of the Indianapolis 500. August 7, 1978: Pete Rose appears on the cover the same week that his 44-game hitting streak ended.

Exceptional, right? But what explains it better than a wretched curse?

When a professional produces an extreme performance in their chosen field of play (business, sports, wherever), the next performance is likely to be less extreme and closer to the average. What explains this phenomenon is not a sudden change in skill level but randomness inherent in any outcome. This is regression to the mean.

The sources of randomness are many and varied. If we’re talking business it could be market conditions, timing of an innovation, or a geopolitical event. If we’re talking sports, it could be weather, quality of opposition, team composition.

Run this experiment. Take a sample of the bottom 10% performers in your organization and put them on some sort of a Performance Improvement Program. It doesn’t matter how rigorous the program is. Wait out three months, measure the performance of the participants, and you will arrive at the inevitable conclusion that the program helped improve performance. If you happen to be the CEO or unit head or someone with clout, you may even bankroll this program across the org.

Continue to run this program for the next several quarters and you will find – barring major changes in your hiring policy — that the average employee performance across the org hasn’t budged.

What! How?

Here’s an explanation that – I warn you now — you will not want on your CV. Perhaps the marked increase in performance of all the PIP folks was a case of regression to the mean after all. It was not the intervention (the diligently designed PIP) but a simple case of returning closer to the median performance after a poor spell.

I said perhaps, so even I’m not sure. Well, then, how do you know whether the PIP worked or not?

That’s simple. Run the experiment again but with one difference. Randomly divide the pool of bottom performers into two groups. Make the second group a control group that you do not touch with a barge pole. Let their lives go on exactly the same. Wait out three months and measure. Then compare the measurements for the two groups.

(By the way, what I just explained is the best way scientists have today to test out their hypotheses.)

If you find the experimental group has done fabulously better than the control group, there you have it! Proof about the impact of your masterful PIP. If both groups show a similar uptick in performance, damn you, regression to the mean! (Though you should be happy for saving your firm a pot of money on useless PIPs)

There’s no employer I know who has run this experiment. At the very least, it is not a corporate thing. And I presume the reason for that is not that running such experiments is expensive (not any more expensive than PIPs are), or that it requires a certain scale, but that the concept of regression to the mean is much misunderstood and ignored.

If success is the result of a mix of skill and chance and we can’t separate the two with certainty, how should we evaluate performance?

To answer this question, here are some stats on Michael Jordan I pulled out from a Columbia University blog. From a comment to the blog post [bless you, Jordan fans]:

Take Michael Jordan as both an example, perhaps an exception that both proves and disproves the rule, of the rookie phenom regressing to the mean. In his highest PPG seasons (1986-87 & 1987-88) he scored 37.1 and 35.0 points per game respectively. The Bulls ended in 8th and 3rd. During each of the 3-peat runs Jordan averaged 31.4 and 29.6 respectively. Was this regression to the mean only to be expected or was it that Scottie Pippen averaged 19.1 & 20.3 points per game during each of those runs? Or was it that he faced better defense?

Any of you who have seen _The Last Dance _would remember that Jordan had a phenomenal rookie season and followed it up — after a much-truncated second season because of a broken foot — with two outstanding seasons. If that was rare, what made his feats stratospheric was that his points per game for the next five years did not drop below 30.

What does Jordan’s career say about how you should evaluate performance?

1️⃣Don’t make hiring decisions by the extreme-ness of the career highlight. Look for consistency and longevity instead.

2️⃣Know that the candidates who appear extreme in either direction are most probably less extreme if measured again. Temper your expectations.

3️⃣Beware of finding cause-and-effect relationships for things that are simply symptoms of a reversal to the average. Think of alternatives to the stories that immediately jump out.

A good barometer for the proportion of skill needed in the recipe for success in a profession or activity is the longevity of its top performers. If an outcome was entirely a matter of luck, it would be hard to beat the odds again and again. Do you know any repeat lottery winners?

On the other hand, the best in a profession dominated by skill show slow regression. Jordan was right there at the top.

If any sporting outcome was decided entirely by skill, there would be no regression. But that doesn’t happen. There’s always some element of chance. The stiff neck you woke up with the morning of an important presentation that made it hard for you to maintain eye contact with your investors is chance.

_When _chance plays a hand in your career makes a difference too. A _child prodigy _is called that and not just a prodigy thanks to regression to the mean. Albert Einstein was an early-career prodigy. He saw a period of extraordinary scientific contribution very early in his career. The weight of his later work dropped. Hilary Mantel went through a career of relative obscurity before winning two Booker prizes from the last three books she wrote.

Yet, it is possible to up your skill level to an extent that it drowns out random fluctuations. That’s what is meant by being so good that you’re better than the rest even on your bad days. Tennis star Rafael Nadal has a 112-3 win-loss record at the Roland Garros, popularly known as The French Open. Again, if:

Success = Talent + Luck

Success in a particular competition = Above-average skill displayed at the competition + Lucky in the competition

Now it is possible that luck may have gone Nadal’s way in a particular year’s French Open tournament. The championship winner has to win only seven matches in a row. But to win sequences of seven matches not once, not twice, but fourteen times means having the skill to counterbalance a stretch of poor luck.

It is entirely possible that some years Rafael Nadal would have won The French Open despite being unlucky.

Success = Way-above-average skill + unlucky in the competition

Nadal’s stellar record at The French Open points to two things:

1️⃣he has earned his success _because of _his high skill level AND

2️⃣he is so far superior to his contemporaries that he has been successful in spite of the vagaries of nature (being in a more difficult half of the draw, injuries, weather, et cetera)

Acknowledging randomness underestimates the role of skill in success and suggests a ‘what’s the point of life’ kind of fatalism. There’s an argument against my last piece. That argument has heft.

If _success = talent + luck, _I can say that talent contributes to success _because of _it while luck leads us to success _regardless of _your talent. So,

Success = success _because of _your skill + success _regardless of _your skill

👉Success in sales = success because of your selling skills + success because you happen to be selling a great product (something that is completely unrelated to your skill)

👉Success in management = success because of your ability to lead + success because you’ve a great team (unrelated to you)

In What Got You Here Won’t Get you There, executive coach Marshall Goldsmith writes:

Successful people tend to have a high “internal locus of control.” In other words, they do not feel victims of fate. They see success for themselves and others as largely a function of people’s motivation and ability—not luck, random chance, or external factors.

Achievers tend to believe that their success is earned through their ability and motivation (and others’ failures are similarly earned through their lack of ability and motivation). It is plain to see how such a belief empowers. It also hoodwinks. We come up with causes for randomness. We pretend we have more control over things than we actually do.

#Midweek 130 - How to ask for feedback

My relationship with feedback

With a brusque wave of my hand off screen, I quieted my senior colleague, as I answered the client with a smile. If that was the definition of career suicide, no one had told me as marched cooly to the cliff edge.

I said last week that you’ve to be creative to get reliable and frequent feedback as a knowledge worker given that the odds are stacked against you. What I’m going to share here is more art than science. How you do it should mirror you. The challenges you will face will be yours.

All that points to this piece probably — most definitely — being my most personal piece yet for this newsletter.

Last week I met an ex-colleague and friend over coffee. The last several times we have met we have ended up having freewheeling conversations, and I had made a mental note of asking him for feedback.

So I asked: ‘This year, across all the times we have met, what has surprised you about me the most?’

But such a conversation was unimaginable four and a half years ago.

June 2019. Experimentarium, the biggest science museum in Denmark, a few minutes outside of Copenhagen. A balmy summer evening. It was my third conference on the road, on either side of the Atlantic, leading a science communication studio whose clients included the top academic publishers of the world and the top universities in the Far East. With another two weeks and three countries to go before my travels would be over, I was already tired. Tired of the smiling, the networking, the pitching.

Perhaps that explained my offhand wave for our global Sales head who had not let a word in through the length of the call. But unknown to me, my behavior had made my colleague and arguably my most important stakeholder feel sidelined for months. Months, and I had no idea.

The detonation that followed the call and the shock of it continues to have a life of its own in my memory. It carries a lesson I’ll never forget.

For the two years leading up to that moment, I was nose to the ground starting up a services business unit that repurposed published scientific research into more accessible formats such as videos, infographics, and lay summaries. The market for this was new and so as to not be hamstrung by sales bandwidth, I did as much selling as I could. I pitched to customers, I finalized contracts, I managed accounts, and I basked in the responsibility.

My evening that fateful day in Copenhagen ended with me being at the receiving end of ‘How dare you…’ I walked away from the exchange and went back to my hotel.

But no flash of insight jumped out at me. The problem, whatever it was, stayed hidden. I thought I had done everything right. I had tried my best and yet my colleague had behaved unprofessionally.

In hindsight, I should say, my colleague had behaved like a human being. I was alarmed by what he was thinking, yet unconcerned by what he was feeling. Emotion, at our most vulnerable, comes before cognition. I was ignorant.

As we took a stroll, I clarified to my friend and ex-colleague that he could point out both pleasant and not-so-pleasant surprises, but that I was particularly interested in the latter.

A couple of months ago, I switched roles at work. I sent out a Google form to four colleagues — those with whom I had worked the closest in the previous quarter. Two of them responded (= felt comfortable enough to share their thoughts about a senior) and we ended up having meaningful follow-up conversations.

About two years back, I finished up a rather challenging stint during which I led a multinational team that was building a smart writing assistant. It was a group of people who were way smarter than me and highly skilled in their respective disciplines. The stint tested me for another reason. I was answerable to some key figures in the company leadership who had chosen me to lead the project. All of this as COVID was playing out and we had gone (and stayed) fully remote. It remains the hardest position I have ever held.

At the end of that professional chapter, I sought out the Chairman, the CEO, and the CMO to help shed light on my performance.

By now, if it wasn’t clear, let me tell you that I have no formula for soliciting feedback. But I’m happy with going with my gut because the benefits are obvious.

Each time I put word out to the world about what I was interested in, three things happened.

1️⃣I learned something new about myself. Stuff I could not have found out in any other way, or stuff I could not have discovered at such a bargain price.

2️⃣It became easier to ask for feedback with each subsequent effort. With each try, it was more of ‘I have been here, done this.’

3️⃣My colleagues opened up when they saw what it meant to me to know what they thought of me. It signaled that I respected them.

When your colleagues think you have a chip on your shoulder or you don’t give two hoots about what they think, you’re unlikely to know that in time. That’s what happened to me. I paid a steep price to learn what a colleague thought of me.

Soliciting feedback need not be contingent on an occasion–role change, end of project, etc. It need not be about Google forms or what questions to ask in such forms. You can ask to be evaluated any time, any way.

👉Call your review meetings Idea Improvement Catch-ups. Consider the meeting successful if it helps improve the quality of the ideas or decisions that emerge from the conversation, instead of being wrapped up in the idea you came up with.

👉Send work-in-progress versions of your thinking to stakeholders and ask them what they see differently.

👉Give your colleagues incentive to invest in you by acting on their feedback you find constructive and sharing the results with them as a way of showing your gratitude. I got this idea from Marshall Goldsmith and though I don’t do it as often as I should, the few times I have I have earned myself a cheerleader for nothing.

Feedback has a useful byproduct. It reveals what matters to the feedback giver. When you’re asking for feedback with the intention of acting on it to become a better version of yourself, you’re asking those around you, ‘What can I do for you?’ That’s a specific and a powerful question that most aren’t used to being asked. It makes them feel like a millionaire.

I’ve a much better mental model of what matters to those I work closely with. I may not agree with them but I’m less likely to be surprised by what drives them.

What has been your experience with feedback? Has it surprised you? Has it guided you? I would love to know.

Enjoying the article?

Check out our free ebooks and companion resources to aid your learning and development!

Explore Ebooks

Articles Categorised with the same tags