Category Archives: Career

Jobs: Supply and Demand

Source: WSJ, Apr 2017

Startups that can’t be articulated in the right words.

Source: Business Insider, Nov 2016

How does Thiel seem to find fast-growing startups so easily?

One good rule of thumb: look for startups that can’t be articulated in the right words.

“I think in some ways the really good companies often couldn’t even be articulated…we didn’t quite have the right words. Or maybe they were articulated but were articulated in terms of categories that were actually misleading,” Thiel said.

That means the startup’s idea has to be so new that it’s not easily understood by everybody. For example, Thiel said most people called Google just another search engine, when in fact, it was the “first machine-powered” search engine. Even Facebook, he says, was called just another social network, when it was actually a company that “cracked real identity” online.

Thiel added the same thinking goes the other way: avoid startups that use too many buzzwords.

So if a startup describes itself with trendy words like big data, cloud computing, or software-as-a-service, it’s time to run away.

“I’d often said when you hear those words, you need to think fraud and run away as fast as you can,” Thiel said. “It’s like a tell that you’re bluffing, that there’s nothing unique about the business.”

Be More Convincing

Source: Business Insider, Dec 2016

if you want to convince someone that your explanation for something is the best way to explain it, you might want to tack on some useless (though accurate) information from a tangentially related scientific field.

It turns out that when you tack on additional information from a respected field of study, people think that makes an explanation more credible.

one of several cognitive biases we have in favor of certain types of explanations. We think longer explanations are better than short ones and we prefer explanations that point to a goal or a reason for things happening, even if these things don’t actually help us understand a phenomenon.

As the authors behind this most recent paper note, previous research has also shown that we prefer explanations of psychology when they contain “logically irrelevant neuroscience information,” something known as the “seductive lure effect.”

 

  • Good explanations matter, and were rated better than bad explanations (even if the bad explanations had reductive information).
  • Adding useless reductive information made the biggest difference when researchers added neuroscience to an explanation of psychological science.
  • Participants trusted psychology the least and — in the one exception to the general rule — didn’t think adding psychological explanations to social science made those explanations more credible (though these particular findings weren’t statistically significant).
  • Study participants actually considered neuroscience more rigorous and prestigious than the sciences considered more fundamental by researchers (biology, chemistry, and physics). This could explain the big effect that neuroscience explanation has when added to explanations of psychological science.
  • Mechanical Turk respondents thought the explanations with reductive information were better than undergraduates thought they were. That information made a big significant difference for them, but it was less of a big deal for undergraduates. Different groups of people are going to evaluate information in different ways, and neither of these groups of people can accurately represent the way the entire population evaluates information.
  • People who were better at logical reasoning were better at evaluating explanation accurately (they gave less credence to reductive information). The researchers think this could mean that philosophers who have studied logic are less susceptible to this cognitive bias.
  • People who knew more about science were also better at telling good explanations from bad explanations.

 

Automation Forces a Rethink of “Jobs”

Source: HBR, Feb 2017

More nuanced analysis points to a less dystopian future where a great number of activities within jobs will be undertaken by intelligent systems rather than humans. This view, in effect, calls for a re-examination of what a “job” actually is: how it is structured, and how it should be reconfigured, or perhaps redefined, in the age of intelligent automation. How should companies rethink the value of a job, in terms of increased performance through machine intelligence? What set of skills should companies invest in? Which jobs should remain within the company, and which should be accessed via talent platforms, or perhaps shared with peers, or even competitors?

… five steps we recommend companies take to rethink work in light of automation and AI:

  • Gain clarity on pivotal vs. proficiency roles in your organization
  • Understand the specific nature of the relationship between performance and value for your pivotal and proficiency roles
  • Disaggregate the different parts of the curve shown in the chart above and determine how AI can play a role
  • Determine the specific activities that these different forms of AI might transform, and the relevant cost, capability, and risk implications
  • Plan for how stakeholders can be engaged in understanding and embracing the potential changes to work, recognizing the aforementioned biases and resistance factors

Clustering Your Star Talent

Source: HBR, Jan 2017

What steps should organizations take to make the most of their star talent? Our research highlights five best practices:

Know who the stars are in your organization.

It is difficult to deploy scarce talent effectively without first identifying your company’s A players. Most companies employ some form of assessment based on performance and potential, typically as a vehicle for determining compensation and career progression. Following this approach, A players are employees who score highly on both dimensions.

Know where your A players are (and could be) deployed.

Knowing who your stars are is just the beginning. You also need to know how effectively they are being deployed. For each star in you company, ask two important and related questions:

Where are they currently deployed?

What role is each star currently playing in the organization? This information will help you assess how effectively you are deploying scarce star talent.How fungible are they? Could they perform some other role with the same (or similar) performance? Your most valuable people are both highly proficient in their current roles and highly versatile. If you find that you have underinvested scarce talent in a number of critical roles, versatile stars can help to fill these roles.

Identify the business-critical roles in your company.

Not all roles are created equal. Some are inherently more important than others in successfully executing a company’s strategy and delivering superior performance. The best companies identify these roles explicitly. They ask themselves: “Which roles benefit the most from star talent?” and, by implication, “Which roles can we afford to fill with ‘good enough’ talent?” Having the best software programmer in the world makes little difference if your business is consumer packaged goods. But having the very best brand managers and marketers may make a big difference. The best-performing companies put their talent where the money is.

Treat star talent as a company-wide resource.

Organizations commonly struggle with moving great talent from one part of the company to another. Your star talent can quickly become the property of a single business unit or function unless you have the processes and practices to ensure that these scarce resources are invested on behalf of your entire company, not just the division, business, geography, or function where they currently reside. Organizations that put these practices in place make better use of their existing talent and avoid the artificial shortages of talent that can be created by parochial hoarding of A players.

Ensure that business-critical roles get first dibs on star talent. Once your leadership has the information it needs to determine who and where the stars are in your organization, it must be ruthlessly nonegalitarian in the way it assigns talent. It must make sure that business-critical roles are filled with A players first, and then turn its attention to roles that are important but less business-critical. Only then can you be assured that your star talent is being deployed as well as possible.

Ever since the start of the “war for talent,” companies have invested billions to attract, develop, and retain the very best. Now that war looks like a stalemate: Most companies, on average, have the same amount of stars. The companies that perform the best are the ones that treat star talent as the scarce, hard-won resource that it is.

Machines (AI) Can Do 25% of CEO Tasks

Source: HBR, Feb 2017

half of the activities people are paid to do in the global economy have the potential to be automated using current technology. The most automatable activities involve data collection, data processing, and physical work in predictable environments like factories, which make up 51% of employment activities (not jobs) and $2.7 trillion of wages in the U.S. These activities are most prevalent in sectors such as manufacturing, food services, transportation and warehousing, and retail.

More occupations will change than will be automated in the short to medium term. Only a small proportion of all occupations (about 5%) can be entirely automated using these demonstrated technologies over the coming decade, though the proportion is likely to be higher in middle-skill job categories.

But we found that about 30% of the activities in 60% of all occupations could be automated — and that will affect everyone from welders to landscape gardeners to mortgage brokers to CEOs. We estimate that about 25% of CEOs’ time is currently spent on activities that machines could do, such as analyzing reports and data to inform decisions.

Like President Johnson in the 1960s, we see that automation could make a major contribution to productivity and prosperity. Our research suggests that future automation could raise productivity growth globally from 0.8%–1.4% annually, which can make a meaningful contribution to global economic growth and compensate for the demographic headwinds of aging populations. For companies around the world, automation will offer the potential to capture

Leading People Too Smart to Be Led

Source: HBR, Jan 2017

how Krakauer leads a wildly creative, highly effective organization. There were six things he told me that I think could be transferrable to leaders in any organization:

See yourself as “a colonel with an army of generals.” Humility is an essential prerequisite for a leader who’s in the middle of a maelstrom of talent. “Lead by example and set a tone,” encouraged Krakauer. “Great talent must be inspired to be part of your organization.” Amplifying Krakauer’s maxim, the way to get the best contributions from world-leading talent is to inspire them to be part of your organization — rather than making the hard sell or overmanaging them.

Don’t valorize failure. “Everyone says failure is a wonderful thing. I totally disagree,” Krakauer says. It might make a provocative slogan, but few brilliant people are really motivated by the prospect of failing. He laments the current fad of celebrating failure, a prescription I often hear in my role of working with executives eager to enhance corporate innovation capabilities. Instead of celebrating failure, we need to reframe the challenge. “Here we celebrate success. We also celebrate experiments,” Krakauer explains.

Encourage smart recklessness. Each of us has a crazy idea from time to time. We should probably share them more often than we do. People sometimes overprepare to avoid embarrassment, and most institutions are designed to eschew such concepts. But in these embryonic ideas might lie greatness. Krakauer advises leaders to create opportunities where people are expected to share these “reckless” ideas. With this expectation, many more novel ideas are likely to emerge. But setting up these kinds of conditions is different from valorizing failure. Quoting Murray Gell-Mann, the Nobel laureate physicist, Krakauer says, “Wrong ideas can be interesting, but correct ideas are great.”

The organization should be a crucible, not a crib. Encouraging rigorous, constructive debate is indispensable to navigating challenges of high uncertainty, from extending the bounds of knowledge to scaling a business. Argument is “how we come to understand things,” observes Krakauer, a tough and contentious critic who sees SFI’s role as a crucible, a place where ideas are put to the test. “I believe in freedom and I believe in community. I also believe in rigor and…challenging nonsense.” Many companies, however, develop cultural and procedural barriers to productive debate, valuing organizational harmony over innovation. The challenge is to find the balance: to foster an environment where people feel comfortable sharing — and arguing — the merits of different perspectives.

Search for “stupid” practices as much as you seek best practices. “We have hundreds of organizations researching intelligence. Why don’t we have at least a few researching stupidity?” asks Krakauer. “After all, stupidity is at the heart of why and how things go wrong.” Anyone operating in a large enterprise feels the truth of Krakauer’s quip. Overcoming collective stupidity on an ongoing basis is a role for leadership in any organization. Structure can help, and SFI’s flat, organic arrangement certainly does, but structure isn’t enough. Leaders who do well in large organizations get the right things done — sometimes by leveraging the bureaucracy, and sometimes in spite of it.

Persist. Near the end of our conversation, I asked Krakauer about his experiences as a scientist studying complexity theory. It’s a relatively young field, and early on in his career Krakauer had had serious reservations about how far it could advance. But he persisted even though he was faced with major doubts. He told me he kept going because of “curiosity, a desire to understand the universe…pushing the boundaries of what you can understand on a fundamental level. That overwhelmed the very real prospect of making little progress.” That’s good advice for leaders, too. On days when nothing is going right, and even Management 101 seems to be failing, focus on persistence. If the vision and purpose are sound, you may just get further than you thought you could.