Distilled lessons, ideas and wisdom from the most interesting reading of the past month
‘If a brain anticipates that it will be rewarded for adopting a particular belief, it’s perfectly happy to do so, and doesn’t much care where the reward comes from — whether it’s pragmatic (better outcomes resulting from better decisions), social (better treatment from one’s peers), or some mix of the two’
– Kevin Simler.
Writing in the New Yorker, Elizabeth Kolbert looks at an interesting theory explaining the many irrational cognitive biases that impact human reasoning and decision making. These are well documented (see Daniel Kahneman’s excellent ‘Thinking, Fast and Slow‘) and include difficulties with changing beliefs, even when the information they are based on is shown to be wholly inaccurate or false, and a propensity to overvalue information that is consistent with existing beliefs (confirmation bias).
In ‘The Enigma of Reason’ cognitive scientists Hugo Mercier and Dan Sperber point out that reason is an evolved trait and, while it may fail in many contexts within the modern world, at some point such quirks must have proved advantageous. Summarising the main argument, Kolbert writes that ‘Humans’ biggest advantage over other species is our ability to cooperate. Cooperation is difficult to establish and almost as difficult to sustain. For any individual, freeloading is always the best course of action. Reason developed not to enable us to solve abstract, logical problems or even to help us draw conclusions from unfamiliar data; rather, it developed to resolve the problems posed by living in collaborative groups.’ In particular, the ability to spot flaws in the ideas of others and win arguments was central to social status, and arguably far more important than the ability to reason clearly.
Thus, while irrational thinking patterns may not make sense from an ‘intellectualist’ perspective, they may very well have been sensible from a social ‘interactionist’ point-of-view. As Mercier and Sperber write, ‘This is one of many cases in which the environment changed too quickly for natural selection to catch up.’
In a similar article with the same title, author James Clear notes that, in many cases (particularly in a hunter-gatherer context, where separation from the tribe would likely spell death), social connection offers greater rewards than clear reasoning or establishing the truth. As Harvard psychologist Steven Pinker argues, ‘people are embraced or condemned according to their beliefs, so one function of the mind may be to hold beliefs that bring the belief-holder the greatest number of allies, protectors, or disciples, rather than beliefs that are most likely to be true.’
Alongside helping to explain certain behaviours, such as the tendency to avoid argument in social gatherings, Clear suggest that this explanation reveals a better way to change the minds of others, writing that:
‘convincing someone to change their mind is really the process of convincing them to change their tribe. If they abandon their beliefs, they run the risk of losing social ties. You can’t expect someone to change their mind if you take away their community too. You have to give them somewhere to go. Nobody wants their worldview torn apart if loneliness is the outcome. The way to change people’s minds is to become friends with them, to integrate them into your tribe, to bring them into your circle. Now, they can change their beliefs without the risk of being abandoned socially.’
He suggests that writing may be more effective than conversation or debate in changing opinions, given that it allows people to consider the arguments in isolation and outside of the influence of concerns relating to status and appearance. ‘Any idea that is sufficiently different from your current worldview will feel threatening’ observes Clear, noting that ‘it’s easier to be open-minded when you aren’t feeling defensive.’
Speaking on TED, cognitive scientist Tom Griffiths explores how some principles from computer science can be applied to decision making more broadly, particularly when dealing with problems that are too hard to solve through sheer effort alone. Examples include:
1: The explore / exploit trade-off : In many situations, such as choosing where to eat, people find themselves in a quandary about whether to try something new (explore) or stick with something that they already know to be good (exploit). As Griffiths notes, one principle from computer science is that ‘the value of a piece of information increases the more opportunities you are going to have to use it’. Therefore, if in a place for a short time, the rational decision is to ‘exploit’ (i.e. stick with what you know), as there is no point in gathering additional information. If in a place for a longer period, it may be more rational to explore (i.e. try something different), as the information gathered can improve future choices.
2: Deciding what to keep and remove: wardrobe space and physical filing systems are like the memory of a computer – they have limited capacity but should provide quick access to the items most likely to be needed, which means that some items must periodically be removed. The approach to removing items could follow a random or ‘first-in first-out’ strategy, but it turns out that the optimal approach is to discard items that have been least recently used (i.e. last accessed furthest in the past). The same principle could perhaps be adopted in a much wider range of applications, such as maintaining professional networks or updating skills.
3: Good-enough decision making: Ultimately, our ability to make good decisions is constrained, and even following an optimal decision-making strategy does not guarantee a perfect outcome. For instance, it is often impossible to evaluate all available options. In such cases, computer science adopts the approach of deconstructing issues into simpler problems, for instance by allowing approximations, removing constraints, not considering all options or settling for ‘pretty good’ rather than ‘perfect’. Solving such simpler problems can provide good good insight into the more difficult issues, or result in good outcomes in their own right.
As Griffiths notes, ‘You can’t control outcomes, just processes, and as long as you’ve used the best process, you’ve done the best that you can…sometimes those processes involve taking a chance, not considering all of your options or being willing to settle for a pretty good solution. These aren’t the concessions we make when we can’t be rational, they are what being rational means.’
Author Greg Satell outlines four important but seldom recognised attributes of innovation:
1. Your Success Often Works Against You
Managers often focus on optimising operations and reducing mistakes, standardising where possible to achieve predictable outcomes. However, this is fundamentally at odds with the experimentation (and inevitable failures) required to generate new innovations. Hence success in one realm acts as a hindrance when conditions change.
2. Rapid scale-up can be dangerous
New innovations tend to be imperfectly understood, so quick growth can be problematic as unanticipated problems will need to be addressed at scale. A better approach is to identify a use case that needs the innovation to such an extent that any glitches will be overlooked, and use the learning from such interactions to identify and address problems before rolling-out.
3. It is important to tackle the biggest challenges first
He writes, ‘at Google X, the tech giant’s “moonshot factory,” the mantra is #MonkeyFirst. The idea is that if you want to get a monkey to recite Shakespeare on a pedestal, you start by training the monkey, not building the pedestal. Because training the monkey is the hard part. Anyone can build a pedestal.
The problem is that most people start with the pedestal, because it’s what they know. And by building it, they can show early progress against a timeline. Unfortunately, building a pedestal gets you nowhere. Unless you can actually train the monkey, working on the pedestal is wasted effort.’
4. New innovations take time to achieve success
Successful innovations never emerge through a single event, tend to be misunderstood and overlooked at first, and must go through a lengthy process (often taking decades) to gain traction. As computing pioneer Howard Aiken said, ‘Don’t worry about people stealing your ideas. If your ideas are any good, you’ll have to ram them down people’s throats.‘ Successfully developing an innovation requires a good idea but also the resilience to stick with it through this process.
Writing in bi-monthly publication Queue, Kate Matsudaira outlines five approaches to unlock productivity when feeling unmotivated:
- 1: Reduce the inertia to starting by breaking a task down into many small chunks (each requiring less than 15 minutes to complete), and use a few small wins to build momentum.
- 2: Avoid being distracted by setting aside specific blocks of time to dedicate to the task. These must be sufficiently long to (realistically) be able to make meaningful progress.
- 3: Establish accountability by involving other people, for instance through scheduling regular catch-ups or asking for help on certain aspects of the project. Studies have shown that making a commitment to do something with someone else significantly increases the likelihood of doing it.
- 4: Talk about the task with other people in order to diminish any stress or anxiety associated with it and generate suggestions for how best to approach it.
- 5: Take breaks and engage in short bursts of unrelated but satisfying activity. These result in the release of creativity-inducing dopamine, which can generate new approaches to the task.
Writing in the Guardian, Harriet Griffey looks at the impact of the contemporary phenomenon of the ‘always-on’ mentality, precipitated by smart phones, email and social media, in which we ‘exist in a constant state of alertness that scans the world but never really gives our full attention to anything’.
As she explains, constant interruptions diminish our ability to concentrate and reduces productivity. While we can adapt to such demands in the short term, the stress hormones adrenaline and cortisol, which result from constant switching between tasks, can create an addiction to (digital) stimuli and, in the long term, nullify serotonin and dopamine to disrupt sleep and cause anxiety and depression.
It may therefore be necessary to relearn the ability to pay attention, and Griffey offers a number of strategies for doing so:
- Deliberately reduce exposure to social media and communications. Start by switching off alerts or removing apps, then switching off devices for increasingly long periods.
- Do things that engage you exclusively for a period of time. For instance, extended periods of exercise help to develop concentration. Similarly, reading a book (not on a screen, which encourages skim reading) for at least 30 minutes, which is long enough to engage interest, can boost concentration.
- Follow the ‘five more rule’, which instructs that when you feel like stopping, commit to completing five more minutes, pages, exercises etc. This encourages us to push beyond the point of frustration and builds concentration, with a useful productivity-enhancing side effect.
- Spending a few minutes counting backwards (e.g. in sevens from 1000), spelling words backwards or sitting in a comfortable position and focusing on something nondescript, such as a spot on the wall, can be useful shortcuts to clearing the mind. Another approach is to focus on the second hand of a clock, starting at the 12, for one whole revolution. If concentration is broken with distracting thoughts during this minute, start again.
- Get more sleep.
Writing in the Guardian, Maia Szalavitz notes that growing levels of inequality are ‘perversely altering how we see ourselves and what we value.’
She argues that, in today’s ‘hyper-capitalist’ world, advertising and financial pressures place achievement and status at the heart of the identity and pursuits of many. This is further exacerbated by inequality, which promotes ‘materialistic values’ such as money and image over things such as family or having fun.
A 2014 meta-analysis of hundreds of studies of materialistic values, conducted by Tim Kasser, professor of psychology at Knox College, found no link between materialistic values and well-being. On the contrary, materialism has been found to be linked to lower levels of life satisfaction and happiness, as well as higher levels of anxiety and depression.
Alongside advertising and media, which promote the trappings of wealth, ‘a sense of economic uncertainty, instability, precariousness or actual experience of low economic status’ tends to shift focus to money and increase materialism.
Hooked: How to Build Habit-Forming Products, is a book first published in 2013 and written by Nir Eyal, a US-based consultant, angel-investor and blogger. The book builds on a number of examples, taken predominantly from social networking pioneers, that have been successfully employed to compel adoption and continued engagement of new products.
Eyal defines a habit as a situation ‘when not doing an action causes a bit of pain’. Habit forming products can start as ‘nice to haves’ but become ‘must haves’ with increasing use. The central thesis of the book is that habitual use of products and services arises through the combination of four key characteristics:
1 – Trigger: An engagement-stimulating event, which may be external (i.e. occur within the user’s environment) or internal (an association within the user’s memory).
2 – Action: An action is made in anticipation of instant gratification and driven by either a desire to avoid pain / gain pleasure, avoid fear / seek hope or avoid social rejection / gain social acceptance. For an action to occur, a user must have the required ability (in terms of time, money etc) to complete it when the trigger occurs.
3 – Variable Reward: The reward for completing an action should be variable and non-finite (i.e. not simply one of a limited set of known possibilities). Rewards can be of three types: Tribe (connection with other), Hunt (delivery of material resources or information) or Self (intrinsic rewards of mastery, competence or completion).
4 – Investment: A requirement for some degree of user investment (e.g. time invested to master use, networks built with other connections), which relies on anticipation of future reward.
Investor Charlie Huggins looks at the pros and cons of pursuing a growth-based investment approach (investing in companies with strong growth prospects) and a value-based strategy (investing in companies that are undervalued).
While a mix of pricing changes and growth will determine investment returns (they will have different impacts over different time frames) in all cases, the following considerations should be taken into account when picking a strategy:
- Timing of entry and exit is generally more important in value investing, as undervaluations tend to be short lived in (relatively) efficient markets while growing companies allow for a greater margin of error. As Warren Buffett notes, ‘time is the friend of the wonderful business and the enemy of the mediocre.’
- Value investing may involve shorter hold periods , as investors tend to sell when their estimation of fair value is reached, whereas growth investors may hold investments for a long time. The former approach is thus often more challenging as it involves sourcing and executing a greater number of transactions, which in turn incurs higher transaction costs.
- Value investors are vulnerable to value traps, through which a perceived undervaluation actually reflects fundamental issues with the business (e.g. a vulnerability to being disrupted by new technologies). Many investors underestimate the difficulty of turning such situations around.
- While investors often pursue fast-growing companies in ‘hot’ sectors, companies with a sustainable competitive advantage that are experiencing lower but consistent growth are often overlooked for a number of reasons:
- Some investors tend to be reluctant to project performance more than a few years ahead and have an expectation that growth spurts are inherently short-lived.
- It is human nature to look for bargains, so many investors are dissuaded from buying into companies that have recently seen an uplift in valuation. Even if such an uplift is justified by underlying business performance, it is often assumed that the ‘good run’ will soon come to an end or that a better entry point will soon present itself.
- The short investment horizons of many investors (the average hold period for shares traded on the New York Stock Exchange is eight months) mean that they are more interested in changes in valuation than long term growth prospects.
In a related article on Nautilus, Investing is More Luck Than Talent, professor Moshe Levy of the Hebrew University Business School looks at the reasons underpinning growing inequality. Despite common narratives pointing to the talent, effort and social connections of high earners, he writes that ‘they cannot possibly be the whole story at the high end, where people’s wealth is primarily determined by capital gains or losses on investments’. For instance, if the ‘average’ person has an IQ of around 100 and earns approximately $40,000, a constant relationship between IQ and earning would imply that the highest earners have an IQ of around five million! Levy’s analysis suggests that wealth distribution, at least at the highest end of the scale, is consistent with that which would be expected through pure chance. If indeed luck is a greater influence than talent in success, he suggests that this should be reflected in the pay of ‘star’ CEOs and fund managers, while taxes could be reframed as redistributing luck rather than penalising talent.
Jeff Ferguson of PipelineDB outlines three mistakes that founders of software companies often make in their approach to sales:
1 – Building a product before starting the sales process: Many companies wrongly assume that they are building something that people want or are willing to pay a certain amount to use. This can be addressed by talking to potential customers as an initial step, which has the added benefit of generating a customer pipeline for when the product is ready, and providing evidence of demand for fundraising.
2 – Talking instead of listening: interactions with sales targets provide an opportunity to gain deep insights into their requirements, approach and objectives by asking strategic, open-ended questions. However, many people that are trying to sell simply launch into monologues about product features and how they can address (assumed) problems.
Ferguson writes, ‘When it comes to sales, it does not matter what you think about your product. It only matters what customers think about your product. In order to win customers you must set aside your own thinking and get into the mind of your customer. The best way to do this is by asking good questions, and then listening carefully and taking notes.
Without this information you are essentially flying blind in the sales process and likely inundating sales prospects with information that may or may not be relevant. With this information you can deliver a concise, tactical proposal about how your product would add value for them, or determine that your solution actually isn’t a good fit for them and save both you and the prospect time by disqualifying them and moving on to another sales conversation that is likely a better fit.’
Such an approach involves resisting the common urge to talk unnecessarily when feeling uncomfortable about asking difficult questions relating to intentions to buy, or waiting for an answer to these.
3 – Mistaking Interest for Demand: A product that delivers incremental value will usually generate interest, but this is often mistakenly interpreted as a willingness to pay for it (demand). For this reason IBM developed a checklist, summarised in the acronym BANT, to validate demand by verifying the following four conditions:
Budget: the organisation has sufficient budget to purchase at an acceptable price.
Authority: the person being engaged with has the authority to make a buying decision.
Need: the organisation truly needs the product.
Timeline: the purchase can be made within an acceptable timeline.
Gathering as many signed purchase agreements, or even non-binding letters of intent, as possible is a good way to prove demand.
A Google blog post outlines eight generally applicable principles that have been employed to create a culture of innovation at the company:
1 – Think 10x: look for ideas that can deliver significant rather than incremental improvements. Doing so often forces adoption of a fundamentally different approach to solving a problem.
2 – Launch, then keep listening: release products in ‘beta’ and iterate quickly based on user feedback.
3 – Share everything you can: encouraging transparency and information sharing among employees facilitates collaboration. Google hosts a weekly meeting, which all staff can attend or stream online, to enable company leaders to share news, updates and information.
4 – Hire the right people: use a structured hiring process, tapping into the ‘wisdom of the crowd’, to find talented staff. Examples include encouraging existing staff to refer good candidates and using a team of four people, each focused on assessing a distinct skillset, during interviewing processes.
5 – Use the 70 / 20 / 10 model: allocate 70% of resources to initiatives dedicated to the core business, 20% to those that are related to it, and 10% to unrelated projects. This approach helps to look after existing business lines while allowing for exploration of ‘moonshots’.
6 – Look for ideas everywhere: including internally, among customers and in different sectors or countries.
7 – Use data, not opinions: test and measure everything so that decisions can be based on data.
8 – Focus on users, not the competition: any product can be improved by focusing on how to make it better for its users. Doing so will create a loyal base of users, from which everything else follows.
Other interesting things
I wish there was an app for…
Crowdsourced suggestions for useful apps.
An interesting solution for email overload
Daniel Egan of online financial management firm Betterment suggests imposing a ‘sender-pays’ model for email, in which people must agree to pay a (relatively small) fee or donation in order to be able to send an email to someone that they do not know. This is a model, employed by venture capital investor Marc Andreessen among others, that is designed to reduce the clutter that generic requests create (after all, ‘an inbox is the to do list that anyone can add to’), freeing time to focus on and commit to dealing with the truly relevant. More.
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