How Mindfulness Improves Decision-Making

[This piece was first published in Fast Company on October 23rd, 2019]

Everywhere you look, mindfulness meditation is touted as a wonder drug. Meditation can supposedly support weight loss, lower stress levels, increase attention, and reduce anxiety. But there’s one benefit that I think many people overlook—being mindful makes you a much better decision-maker.

Two years ago, I went to a 10-day silent retreat in Ladakh, India. The retreat center was akin to a monastery, located in a scenic panorama of the Himalayas, at an altitude of 12,000 feet. Insects enjoyed undisturbed existence in our dormitories, protected by our oath not to harm any living being. The schedule was also ruthless: First meditation sessions began at 4.30 a.m., and the days lasted until 10.30 p.m.

What I learned about my internal dialogue

What must sound as the most grueling of days from the outside ended up being some of the most meaningful days on the inside. I learned that my mind is hardly ever still. Instead, thoughts just come up. Ruminations, emotions, memories seem to pop up out of nowhere, mostly unsolicited and untriggered. When you’re meditating, you can’t decide what to think next, and you can’t choose not to think at all.

What’s more, these subconscious thoughts often trigger an automatic “chain reaction.” They evoke feelings, which materialize in bodily sensations, and they, in turn, elicit counter-feelings and reactions. Most of the time, the temptations of the modern world distract us from processing these feelings. But the complete silence and alpine tranquility of the retreat environment allowed me to do just that (and gain a lot of clarity in the process.)

The magnitude of our distraction in daily life should come as no surprise: The addictive use of media and the omnipresence of screens make deep focus a challenging endeavor.

But interestingly, even going entirely off the grid for 10 days didn’t prevent my mind from distracting itself. If I’m that inattentive when I sit in complete silence, I realized that the level of distraction in my “normal life” is orders of magnitude bigger.

These distractions have a significant impact on my decision-making capacity. The noise produced by my mind and my environment distorts my clear thinking, which interferes with my judgment.

How to use mindfulness in decision-making

Mindfulness meditation can both help with diagnosing and treating the problem. And while I highly recommend everyone to try out actual meditation retreats, you don’t need to travel to the Himalayas to learn how to be mindful.

Being mindful means turning the camera back on yourself. It means learning to observe your inclinations, preoccupations, and distractions.
You can’t take a shortcut to mindfulness. It takes time to practice and nurture the habit of reflecting. The more you practice, the more insights you gain about the way your mind works and how you can factor that in your decision-making process.

To stay on course, it helps to ask yourself the following questions:

1. What brought me here? Think about what prompted you to the decision in the first place. Let’s say you want to buy a couch, and you’ve narrowed down your options. What made you “want” a new couch? An advertisement? An offhand comment from your partner? The interior of your best friend’s apartment?

2. What thoughts, emotions, or biases may be clouding my judgments? You might have recently read an article about the economic promises of biotechnology, but that doesn’t mean now is necessarily the right time to invest in biotech stocks. Think about whether cognitive bias clouds your ability to see things clearly and make a decision that is best for you.

3. If contexts were to change, would I make the same choice? Most of our decisions are context-dependent. For example, an earlier emotional experience might cast a shadow over every choice we make later that day. In a series of studies, researchers “primed” test subjects subconsciously, who went on to make very different decisions compared to the control group. Pause and ask yourself, would you make the same decision tomorrow (or if your context were to change)?

Answering the questions above can help you make better choices. Being a good decision-maker starts with re-centering yourself, being aware of your own emotions, thoughts, and sensations, all while cutting through the noise. When you learn to do this, making the right choice becomes much easier.

Tackling tough problems? Think first, solve second.

Karl Popper, the Austrian philosopher of science and a personal hero of mine, famously posited that “All life is problem solving”. Popper’s experimental approach to generating knowledge lays the groundwork of what we know today as the scientific method:  Beliefs about the state of the world should only be valid until proven otherwise. Statements should be expressed in a way that makes them falsifiable, you must be able to test them against reality.

For Popper, problems were statements in search of falsification, but for most of us – employees, entrepreneurs, policy-makers – problems are questions in search of solutions. And while many are excellent problem-solvers, few are excellent problem-framers.
In fact, there’s a lot of value hidden upstream of problem-solving. In our upcoming book, co-author Julia Dhar and I offer five important – yet somewhat counter-intuitive – observations.

1. Problems come with ‘meta data’

From early on, we are expected to answer questions, to find solutions to textbook problems, to complete tests.
By automatically jumping into answer-mode, we miss out on important information: Think of it as ‘meta data’ – information about a problem’s framing and origin – that each problem comes equipped with. Decoding and critically reflecting on the problem at hand before jumping into solving mode can be surprisingly insightful. Reflect on these questions:

  • Who framed the problem? And what are their underlying interests?
  • Cui bono? (Who benefits from it being solved?)
  • Who loses out?
  • Why this problem (vs. others?)
  • Why now?

2. Problems don’t just exist, we actively choose them.

It is widely assumed that problems simply ‘exist’. They don’t need to be identified; they simply impose themselves on us. This is a mistaken belief. Picking a problem to solve is almost always an active process. This is true for any problem – regardless of whether it emerges in your private or professional life. It is worth the effort to try and elevate the selection process from the subconscious to the conscious level.

Are you facing many problems and not sure where to start? A pragmatic tool that I use all the time is the impact/feasibility matrix: Plot the expected impact of the problem being solved on the y-axis, and the cost or effort of doing so on the x-axis. Invert the x-scale (low cost/effort on the right; high cost/effort on the left) – and you’ll create a useful prioritization matrix. Start with the problems in the top-right corner and work your way down from there.

Next time, before you jump into problem-solving mode right away, take a step back to reflect on who decided that the issue you are facing is a problem worth solving, and think about why they did so, and what their perspective might be.

3. Not every problem needs to be solved

Problems seem apparent when you first encounter them. Even if the path to implementing the solution appears straightforward, it might cause subsequent effects that are hard to factor in.
Policy-makers know these effects as unintended consequences.
If unintended consequences (higher-order effects) outweigh the benefits of your intended solution (first-order effects), you may consider other options – or leave the problem unsolved.

Examples are plentiful:
For some medical conditions, “the cure is worse than the disease”.
Or consider the example of cane toads, originally brought to Australia to kill bugs that lived on sugar cane, but started to disrupt the whole ecosystem.
Or your supplier is charging you more than the market rate, but demanding a lower price might threaten its liquidity, in turn leading to supply uncertainty for your business.

4.    Not every problem needs to be solved immediately.

Many problems seem to demand immediate attention, but oftentimes we confuse importance with urgency. In fact, a consumer research team led by Zhu, Yang and Hsee found a significant ‘urgency effect’ – a mindset of focusing on urgent rather than important tasks.
Their experiments showed that test subjects tend to prioritize tasks with a lower expected reward over tasks with a higher reward, when the former were merely classified as urgent.[1]

A prioritization model, such as the well-known ‘Eisenhower matrix’ can help when deciding which problems to tackle in which order. It may not surprise you to learn that Dwight D. Eisenhower, a five-star general, supreme commander of the Allied Expeditionary Forces during the Second World War and US President, was a master organizer and productivity guru in his time. He saw past the blinders of urgency, coining the phrase, “What is important is seldom urgent, and what is urgent is seldom important.”[2]

In addition, a surprisingly large number of problems, if left to their own devices, appear to magically take care of themselves. Have you ever found an abandoned, months-old to-do list with a few items checked off and the rest still unchecked? In all likelihood, most of the ‘unchecked’ tasks have either become obsolete or already been taken care of.

5.    Not every problem needs to be solved by you.

 “What would happen if I didn’t tackle this problem?” The what-would-happen-otherwise is known as the ‘counterfactual’ approach. Let’s apply counterfactual thinking to career decisions:
I mentor a number of graduates and young professionals early in their career. In typical millennial fashion (disclosure: I’m a millennial myself), they rank ‘making the world a better place’ high on their lists of job characteristics. Leaving an impact can be achieved in two ways: either by improving the lives of other people or the environment directly (for example as a physician, political campaigner or aid worker), or indirectly by enabling others to do better or more work (for example, by donating to a charitable NGO). The impact of someone working directly on important causes can often be lower than the impact of someone accepting a high-paying job and giving a substantial amount to effective charities.[3] Because many of the directly impactful ‘doing-good’ positions are in high demand, there’s a lot of competition for them. If one doesn’t take that job as an aid worker, someone else (who is probably similarly skilled) will. So the real impact from that career choice is most likely smaller than its perceived impact – an important distinction.

Although decision making can be daunting and overwhelming, learning how to think first will keep you afloat and thriving instead of drowning in a sea of choices. The introspection required of these strategies can help you create a methodology to approach the unforeseen, to see all of the possibilities of a decision with its gains and/or losses.
No matter what the problem is or where you come at it from, it’s essential to hold up the facts for examination and to test them for falsification, as Popper reiterated throughout his whole academic career. If all life really is problem solving, then framing problems correctly will get you halfway to the answer.


This piece is an edited extract from The Decision Maker’s Playbook (Financial Times Press, London: Sep 2019). You can pre-order it here: US, UK, EU.

[1] Meng Zhu, Yang Yang, Christopher K Hsee; ‘The Mere Urgency Effect’, Journal of Consumer Research, https://doi.org/10.1093/jcr/ucy008

[2] Dwight Eisenhower presented a version of the adage in a 1954 speech at Northwestern University in Evanston, Illinois to the Second Assembly of the World Council of Churches, in which he credited an unnamed “former college president” for it

[3] This idea is known as ‘earning to give’, and part of a wider philanthropic movement called “Effective Altruism”

Us vs. them? Decision making in an algorithmic age

We started working on The Decision Maker’s Playbook in 2014. It was in that year that Google acquired DeepMind, a leading Artificial Intelligence company. Two years later, algorithms dethroned the incumbent Go champion, a testimony to how mature they have become.

Algorithms and decision support systems increasingly influence our choices. They do this in a number of ways, but they primarily use our past behavior and the revealed preferences of people similar to us to help filter our options. Take review platforms such as Yelp or Foursquare, for example. It’s nothing new that we follow the advice of our friends and visit the restaurant that most of them recommend. But the internet has made it orders of magnitudes easier to share and aggregate data such as reviews or recommendations. So even though we theoretically have many options, we end up mostly booking the restaurant on top of the list (and those with the largest number of reviews, a new study found).

Soon the world will be dominated by algorithms which predict fairly accurately what we want, prefer and do next. The more data these algorithms gather, the better their predictions will become. It’s not science-fiction to suggest that in the near future, algorithms will know which of our mental (and emotional) buttons to press in order to make us believe, want, or do things. In itself, this is not necessarily bad – after all, we use these algorithms voluntarily because they offer us some kind of benefit. They take some load off our shoulders to sift through options and present us with the most suitable ones – or they present the pieces of information that we are most likely to latch on to.
And they don’t have to do that perfectly: it’s enough for them to simply be better than what we can come up with ourselves. Google Maps’ routing feature occasionally leads us to blocked streets and we need to take a detour. But in the overwhelming majority of cases, Google Maps leads us the along the most time-efficient paths, saving us hours, days or even weeks of lifetime.

It’s not hard to see that incentives may not be fully aligned: From the perspective of their owners, algorithms are tools to accomplish a goal – such as selling services or keeping us on a website so we can be exposed to ads. In solving these goals, such as profit maximization, algorithms serve us suggestions (such as nuggets of ‘news’ that are designed to stir outrage and polarization) that may not be in line with the goals we set for ourselves (being open-minded and weighing evidence of either side to form a balanced opinion). Our dependency on algorithms can make us subject to manipulation.

The more we use digital systems, the more data that is collected. The more data collected, the better algorithmic models can be trained, and the more powerful the algorithms get. The more powerful these algorithms become, the more we delegate our decision-making authority to them. And this is where the problem lies: in doing so, we give up part of our autonomy, and we become dependent on algorithms. We become vulnerable against big tech, which is – thanks to large scale effects of data – is increasing the concentration of information and making it harder for us to ‘opt-out’ or switch. Just as Google Maps is better than a taxi driver at selecting the fastest route, we surrender to algorithms for much more important decisions: what we read, who we date, or who we vote for.

I’m highlighting the potentially dangerous aspects of technology here, and the problems related to it: technological dependence, safety, biases, intransparency or ‘black boxes.’ I don’t talk about the tremendous welfare gains that algorithms such as search engines have generated such as in the fields of logistics or healthcare. These achievements are clearly laudable, but they don’t take away from the risks.

There’s need for self-regulation and government intervention to shield against fraud, manipulation and addiction. But there’s also the need for algorithmic literacy — to enable children, teenagers, and adults to understand, reflect on and wisely interact with algorithms.
Critical thinking – and decision-making – has got some serious competition: machine algorithms. The smarter we are in reflecting on the models driving machines and critically compare those to the models in our head, the better we can preserve our autonomy.

This text a further refined version of an excerpt of The Decision Maker’s Playbook (to be published in the summer of 2019 with Financial Times Press).

Maps and Territories

A map is not the territory it represents, but, if correct, it has a similar structure to the territory, which accounts for its usefulness.

Alfred Korzybski, Science and Sanity, p. 58.

Over the last decade or so, I’ve made a habit out of systematically collecting mental shortcuts: Models, tools, ‘hacks’, rules-of-thumb, heuristics and patterns that people around me use to get stuff done.

Curiously, I found that many of the tools employed in one domain — say, how game theory informs a military strategist, or fail-fast experimentation a tech entrepreneur — can be employed in other contexts just as effectively. While these tools don’t necessarily explain the fabric of reality, they provide a pragmatic foundation for making sense and navigating it effectively. Over the last four years, my co-author (the brilliant behavioral economist Julia Dhar) and I have been writing, re-writing and editing the manuscript countless times — breaking several deadlines, much to the frustration of our editor.

Finally, after years of work, I’m glad to announce that Financial Times Press will publish “The Decision Maker’s Playbook” this September.
Pre-ordering via Amazon is available: US, UK, EU.

I very much hope that the ideas in the book resonate, and of course it would highly appreciated if you could leave a review.