Distilled lessons, ideas and wisdom from the most interesting reading of the past month
Writing on Medium, sales consultant Andrew Raskin outlines the structure of what he considers to be an effective sales presentation:
1. Name an important and relevant change that is underway. Rather than starting by talking about something specific to your proposition, name a major trend that has significant and urgent implications for the audience. As opposed to starting by naming a problem, which can make people defensive or uncomfortable, this approach encourages people to open up about the implications, problems and opportunities associated with the change. It also grabs their attention as, in the words of Hollywood screenwriter Robert McKee, ‘what attracts human attention is change. …if the temperature around you changes, if the phone rings — that gets your attention. The way in which a story begins is a starting event that creates a moment of change.’
2. Demonstrate that there will be winners and losers. To combat loss aversion (the tendency to weigh losses more strongly than similar gains, thus creating a bias towards the status quo), show that, just as adapting to the trend could deliver major opportunities, failure to do so will likely result in significant loss.
3. Provide a glimpse of the desired outcome. Rather than jump into the details of your proposed solution, outline a brief image of the outcome that the audience desires (i.e. what it means to win in the new context) but which is difficult to achieve without your help. This should focus not on having what you are offering but rather on how things could look as a result, and is critical for the audience to pitch the idea to others within their organisation.
4: Introduce your solutions as the ‘magic’ solution to getting to the desired outcome. After outlining why it will be hard to achieve the ideal outcome with traditional methods, present your offering as a the ‘magic ingredient’ for helping the audience get there.
5. Present evidence that you can deliver. To overcome skepticism of the proposal, provide evidence of your ability to deliver it. Raskin suggests that ‘by far, the most effective type of evidence is a success story about how you’ve already helped someone else (who is similar to the prospect).’ If this is not possible, product demos are the best alternative, with features presented in terms of how they enable the desired outcome to be achieved.
Raskin also argues that this approach is most effective when the entire organisation aligns around it.
2 – How to Hire
Writing in the Harvard Business Review, advisor and former Netflix Chief Talent Officer Patty McCord provides advice on how to conduct a recruitment process. Her key tips and insights include:
- Good hires are often not what people expect. ‘Cultural fit’ normally translates to ‘someone I’d have a beer with’, but that typically applies to someone similar to the interviewer. This approach results in a lack of diversity and negative assessment of many people capable of doing a good job.
- The interviewing process provides an important first impression of an organisation, and so it is advisable to make sure that all candidates have a positive experience (even if they are not hired, they could influence someone that would be). Netflix operates a policy through which staff are encouraged to engage with people they see waiting for interviews.
- Salary benchmarking tends to provide only a basic understanding of market demand, which in itself is ‘based on the historical value of what employees have produced rather than on their potential to add value in the future.’
- Paying more for really good candidates is often worth it. Among other things, it prevents them from joining a competitor and often encourages others to stay or join.
- Similarly, the strict application of salary boundaries can be counterproductive, particularly in quickly evolving markets. McCord writes that ‘we realized that for some jobs we were creating expertise and scarcity, and rigidly adhering to internal salary ranges could harm our best contributors, who could make more elsewhere. We decided we didn’t want a system in which people had to leave to be paid what they were worth.‘
- The 80/20 rule (20% of inputs result in 80% of outputs) often applies to teams, so where budget is an issue, she recommends that organisations identify the most important positions and pay what is necessary to fill them with excellent people.
Writing in the Financial Times, Sarah O’Connor looks at the realities of group decision making, citing two recent studies that show that:
- The extent to which misconduct punishments vary by the sex and ethnicity of employees reflects the composition of management. For example, variance in punishments between male and female staff reduces with more senior female representation (source).
- Judges in Olympic dressage competitions are likely to favour people of their own nationality or a nationality shared by other panel members, possibly due to the formation of a temporary group identity (source).
O’Connor argues that rather than ensuring ‘diversity’ or ‘inclusion’ within decision-making groups, suitable representation should be prioritised within such processes. She writes that ‘Our identities and experiences — our gender, race, nationality, class, and any number of other factors — shape the way we see the world. And when the mix of people in a group changes, so do the decisions that group makes…So if we want groups to make fair decisions, our best shot is to make the groups representative of the people who are subject to those decisions.‘
Software developer and Stanford University academic John Ousterhout outlines his ‘favourite sayings’, conveying a number of principles that, while directly linked to software development, have much wider applicability.
- The greatest performance improvement of all is when a system goes from not-working to working. Many developers focus on building complex solutions designed to improve performance. However, in many such cases performance is already good enough and the real challenges relate to quick completion, ensuring quality and managing complexity.(In fact, attempts to improve performance can have the opposite impact. For instance, ‘faster’ algorithms often have larger constant factors so only become more efficient at large scale). Thus simplicity rather than performance should be the primary design criterion. In many cases the simplest code is also the fastest code.
- Use your intuition to ask questions, not to answer them. With experience and knowledge comes intuition, which can be hugely helpful in saving time and effort when dealing with problems. However, assuming that intuition is infallible can lead to mistakes (for instance making a system more complicated without addressing the actual problem) and so it should be treated as a hypothesis to be verified. This process of constantly challenging and verifying can help to further sharpen intuition.
- The most important component of evolution is death. Most organisms, social structures and organisations are highly resistant to change, hence the death and replacement of these is central to evolution. Software runs counter to this – it is often easier to update than replace, although making significant structural changes is usually difficult. As a result, it tends to persist (with a growing number of issues) for far too long.
- If you don’t know what the problem was, you haven’t fixed it. He writes ‘Don’t ever assume that a problem has been fixed until you can identify the exact lines of code that caused it and convince yourself that the particular code really explains the behaviour you have seen.‘
- If it hasn’t been used, it doesn’t work. Regardless of how much a piece of software has been tested, there will be problems as soon people start using it (e.g. bugs that have been missed, clumsy features or a requirement for new features). As a rule of thumb, when you first think a software project is nearing completion, it is only 50%-75% done. He writes, ‘no software is ever gotten right the first time. The only way to produce high-quality software is to keep improving and improving it. There are 2 kinds of software in the world: software that starts out crappy and eventually becomes great, and software that starts out crappy and stays that way.’
- The only thing worse than a problem that happens all the time is a problem that doesn’t happen all the time. ‘In my experience any problem that can be easily reproduced can also be tracked down pretty quickly.‘
- The three most powerful words for building credibility are “I don’t know”. Admitting when you don’t know something or made a mistake helps to build credibility, as it shows that you do not make things up in order to create or maintain a facade.
- Coherent systems are inherently unstable. Unlike nature, humans tend to construct coherent systems (i.e. where constituent elements share many characteristics) as a result of the efficiency these typically offer. For instance, having large numbers of computers running on a single operating system makes sense, as a single improvement can be used by all. However, coherent systems are inherently vulnerable, as a single issue can quickly affect all constituent parts.
On the Shortness of Life, written by Roman stoic philosopher Seneca (5BC-65AD), is a short treatise covering a range of subjects including morality, reason and the art of living. Key musings from the book include:
1: On living: ‘You must not think a man has lived long because he has white hair and wrinkles: he has not lived long, just existed long.’
2: On worry: ‘There will always be causes for anxiety, whether due to prosperity or to wretchedness. Life will be driven on through a succession of preoccupations: we shall always long for leisure, but never enjoy it.’
3: On dealing with problems and suffering: ‘In any situation in life you will find delights and relaxations and pleasures if you are prepared to make light of your troubles and not let them distress you. In no respect has nature put us more in her debt, since, knowing to what sorrows we were born, she contrived habit to soothe our disasters, and so quickly makes us grow used to the worst ills. No one could endure lasting adversity if it continued to have the same force as when it first hit us.’
4: On envy: ‘Let us not envy those who stand higher than we do: what look like towering heights are precipices.’
5: On judging others: ‘What can happen to one can happen to all.’
6: On sources of happiness: ‘We are born under circumstances that would be favourable if we did not abandon them. It was nature’s intention that there should be no need of great equipment for life: every individual can make himself happy. External goods are of trivial importance and without much influence in either direction: prosperity does not elevate the sage and adversity does not depress him…How then can you think that it is the amount of money that matters and not the attitude of mind?’
7: On greed: ‘Just as no amount of fluid will satisfy one whose craving arises not from lack of water but from burning internal fever…in every desire which arises not from a lack but from a vice…however much you heap up it will not mark the end of greed, only a stage in it. So the man who restrains himself within the bounds set by nature will not notice poverty; the man who exceeds these bounds will be pursued by poverty however rich he is.’
8: On grief: ‘It is better to conquer our grief than deceive it. For if it has withdrawn, being merely beguiled by pleasures and preoccupations, it starts up again and from its very respite gains force to savage us. But the grief that has been conquered by reason is calmed forever.’
9: On approach to life: ‘Unless you regard anything that can happen as bound to happen you give adversity a power over you which the man who sees it first can crush…that is why we say that nothing happens to the wise man against his expectations. No condition is so bitter that a stable mind cannot find some consolation in it.’
10: On work and rest: ‘Just as you must not force fertile farmland, as uninterrupted productivity will soon exhaust it, so constant effort will sap our mental vigour, while a short period of rest and relaxation will restore our powers.’
Writing in the New York Times, author Steven Johnson looks at a number of often under-appreciated recent developments in the science of decision making. Key tips and ideas include:
- The Importance of alternatives. Studies conducted by researchers including Professor Paul Nutt have found that decisions between two or more options are less likely to be judged as failures than those involving just one. One way of expanding the option pool is to diversify the people involved in the decision making process.
- Scenario planning. An effective way to assess options is to imagine three outcomes (one good, one bad and one strange) and develop a story to explain each. By forcing the consideration of alternative outcomes, this approach helps people to avoid being seduced by an outcome that is based on a number of distortions such as confirmation bias and overconfidence. This works best when it incorporates a number of different perspectives – in order to replicate those of a competitor or outsider, an internal person or team may be assigned the task of adopting an external mindset and conducting a systematic process of ‘devil’s advocacy’ (s0-called ‘red-teaming’). In his book ‘Farsighted: How We make Decisions that Matter the Most’, Johnson writes that:
‘Experimenting with different futures and identities is more than just a way of uncovering new opportunities (or pitfalls). Hard choices are often hard because they impact other people’s lives in meaningful ways, and so our ability to imagine that impact — to think through the emotional and material consequences from someone else’s perspective — turns out to be an essential talent.‘
- Conduct a ‘premortem’. This is a technique, developed by psychologist Gary Klein, that involves simply asking decision makers to imagine a future in which the decision has been made and resulted in failure (with no reasons for this given), and explain why this has happened. This can be an effective way of overcoming mental biases and identifying potential risks and flaws.In ‘Farsighted’, Johnson writes that:
‘As Klein explains in a 2007 Harvard Business Review article about premortems, if you simply ask people what might happen and why, their explanatory models are less nuanced and imaginative than if you tell people that a disaster did happen and ask them to explain why it did. The act of conjuring that bleak narrative helps people perceive flaws you and they may not have otherwise seen. It also has two more benefits, Klein notes: it “sensitizes the team to pick up early signs of trouble once the project gets under way,” and it creates a safe space for people with negative opinions to speak without fear of seeming … well, negative.‘
- Use a ‘value model’ rather than a simple pros and cons list. This involves listing the criteria that are both valued and likely to be impacted by the decision, and giving each a numerical weight (between 0 and 1) that reflects their relative importance. For each option, each criterion is given a grade between 1-100, which is then multiplied by its weighting. The optimal choice is then identified through the aggregation of its individual scores.
Writing for Wired in 2008, Gary Wolf looks at the use of technology to improve learning, highlighting a number of interesting insights from the science of information acquisition and retrieval:
- The process of forgetting follows a pattern.
- There is an optimal moment to revise what has been learned – just as it is about to be forgotten (any earlier and it adds nothing, any later and material has to be re-learned).
- Correct spacing of revision / practice therefore has the ability to improve learning significantly.
- However, without technology, it is essentially impossible to identify the optimal timing. Applications such as SuperMemo attempt to do this, but the approach requires a daunting level of commitment and self-control.
- Memories do not decay or disappear – instead, ‘forgetting’ occurs because without continued use people become unable to retrieve them.
- Long term memory has two key characteristics – retrieval strength (how easily it can be recalled at a given moment) and storage strength (the extent to which it is deeply rooted in the mind). These are not necessarily correlated, so a reminder of an old address could be sufficient to restore the memory for a long period, while the names of new acquaintances are often quickly forgotten.
- In fact, as Wolf writes, ‘One of the problems is that the amount of storage strength you gain from practice is inversely correlated with the current retrieval strength. In other words, the harder you have to work to get the right answer, the more the answer is sealed in memory. Precisely those things that seem to signal we’re learning well — easy performance on drills, fluency during a lesson, even the subjective feeling that we know something — are misleading when it comes to predicting whether we will remember it in the future.‘ Thus it may be that some approaches to learning provide a false sense of achievement.
- Geographic (and hence currency) concentration, given that European companies tend to implement the most developed ESG policies. Some evidence suggests that currency has been a significant contributor to the strong performance of such investments in recent years.
- A tendency to invest in large and low volatility companies, at the expense of small and fast-growing alternatives.
- A bias towards best-in-class companies, reducing the pool of available options and increasing the tracking error of a portfolio.
An article in the Economist looked at the ways in which Silicon Valley’s recent technology success stories may actually be nullifying many of the factors that made it a leading start-up hub in the first place. Key factors include:
- Today’s large technology companies are somewhat different to their predecessors – they are bigger but also more able to quickly move into new areas. This makes it difficult for start-ups to succeed (even while they derive some benefits, for instance as a result of the lobbying activities of the technology giants), as they are often either ‘imitated, stamped out or acquired while they are still young’.
- Large technology companies are now so profitable that they can afford to compensate staff to such an extent that the potential payoff for establishing a start-up represents a poor reward for the levels of risk involved.
- Launching new ventures from within established companies likely involves working with a smaller and less diverse group of people (relative to the external ‘ecosystem’) and so the degree of innovation pursued may be somewhat checked.
In order to reduce costs and attract (and keep) staff, many Silicon Valley start-ups now opt to either:
- Launch elsewhere (for instance, Vancouver is a popular options given its proximity and the more lenient immigration policies in place)
- Move once a certain size is attained
- Maintain headquarters in Silicon Valley while growing operations elsewhere
Such alternative locations may also offer expertise in traditional industries that start-ups are trying to address.
Writing in the FT, economist Tim Harford looks at alternative explanations for why successful companies often succumb to disruption, a process defined by economist and author Joshua Gans as ‘what happens when firms fail because they keep making the kinds of choices that made them successful‘.
While Clayton Christiansen’s theory of disruptive innovation (which posits that new technologies emerge in rough form and with little market appeal, find niche applications, improve over time to become attractive to the broader market and eventually usurp established firms) is the most well known theory, it fails to explain cases such as Blackberry (disrupted by the iPhone, a premium product with new capabilities) or Kodak (which invented the digital camera, only to be put of business by it).
An alternative theory, developed by economists Rebecca Henderson and Kim Clark during the 1990s, suggests that dominant organisations are prone to losing their leadership position not because a technology is disruptive, but because it requires a new organisational structure. For instance, IBM dominated the computer industry for three decades, during which a huge amount of technological change occurred, but lost its leadership position when industry focus moved from mainframes to personal devices. In such cases, which Henderson terms ‘architectural innovations’, existing structures no longer represent an advantage and thus need to be changed.
Henderson explains that ‘An architectural innovation is an innovation that changes the relationship between the pieces of the problem. It can be hard to perceive, because many of the pieces remain the same. But they fit together differently.‘ One reason why such change is difficult to achieve may be that the people that drive it are politically naive or socially awkward. This also helps to explain why successful innovations that are developed by established organisations are often nurtured within silos, separated from existing activities and structures.
Harford suggests that the greater recognition received by Chistensen’s idea may reflect that fact that it is ‘a single clear theory of how disruption happens — and a solution, too: disrupt yourself before you are disrupted by someone else. That elegance is something we tend to find appealing. The reality of disruption is less elegant — and harder to solve. Kodak’s position may well have been impossible, no matter what managers had done. If so, the most profitable response would have been to vanish gracefully.‘
Other interesting things
The History of Philosophy: Summarised & Visualised – an amazing resource for anyone remotely interested in philosophy.
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