(2022-06-27) Marketingbs A Review Of Talent

MarketingBS: A Review of Talent. Today’s essay takes a look at Tyler Cowen's latest book, Talent: How to Identify Energizers, Creatives, and Winners Around the World (co-written with Daniel Gross).

building a successful career is primarily, NOT about yourself — the real leverage you get in your career is by surrounding yourself with smart and talented people

For executives, recruiting and retaining a strong team is the best way to have real impact.

Both authors have a track record of identifying early-career innovators with the potential to change the world

in practice the book explores a subset of talent. As they describe it: “We focus on a very specific kind of talent in this book—namely, talent with a creative spark.” They describe these people as “project drivers.” (cf linchpin)

I’ve found they can be broken down into two sub-types of talent:

• Individuals who can run an organization. "run... a piece of an organzation"
• Individuals who can figure out how to build something new.

Both types of individuals are hard to find, but the second type are even rarer than the first.

As I read Talent, it seems like the project-driving talent Cowen and Gross were looking for fit almost entirely into the second category.

Among Talent’s most striking ideas, the authors recommend that interviewers should try and get candidates out of their comfort zone and away from prepared remarks.

I do not believe it is quite as important as the authors make it seem, which brings me to three places where I disagree with the book:

• The book’s central thesis is that the talent market is efficient
• Related to point 1, the authors believe that “intelligence” is “priced in” and “over-rated,”
• The authors believe that job candidates are prepared for most interview questions, so getting them “off script” is the best way

I think all three points are wrong.

The efficiency of the talent market

Are any business processes — at any modern company — at the frontier of efficiency?

The argument is straightforward: if AI is widely available, then everyone will use it; as such, your benefits of using AI will disappear, leaving you to find the candidates being overlooked by AI. This is ‘Recruitment as Moneyball.’

But I question whether most talent markets operate anything like baseball (or the stock market, Google paid search, or Facebook ads, etc.). At many companies, recruiting processes are terrible and poor decisions are made all the time.

Most of the time you can win candidates by getting the basics right:

• Reach out to people, don’t wait for them to come to you.
• Build relationships before you need them.
• Develop followership (so people that work with you once will want to work with you again).
• Get candidates excited for the job before you start screening them.
• Make your workplace a good place to work for smart and talented people (which is NOT the same as making it a “good place to work” generally, or anything from the HR/PR lists.)
• Be the type of manager that top talent will want to work for.
• Ensure that you have someone selling the candidate once you know you want to make an offer and start the selling process before the offer is made.
• Be polite.
• Be fast.

If you take care of these type of basic things, you will out-compete almost every rival*

It also helps if you try to recruit really smart people — something that many organizations fail to do.

The (lack of?) importance of IQ

we’re also going to tell you about things you might think you know but that aren’t true. For instance, for a large swath of jobs, intelligence and IQ are far less important than many smart people believe.

But they also go on to admit, “...research also suggests some very important cases where intelligence really matters.” The chapter explains that IQ matters for careers like “inventor”

To support their thesis, the authors list various research findings: that parental education is better than intelligence at predicting which children will pursue law or medicine

In the end, the authors concede that IQ is a valuable trait for employees, but that it’s “priced into” the recruitment process

I do, however, believe they are correct that CEOs are not always the most intelligent people in an organization.

My mentor would not have been surprised by the fact that CEOs are “only” at the 85th percentile in IQ. But he would snicker at the idea that that proved IQ did not matter for consultants trying to achieve change in an organization

when hiring Type 2 talent — the type of people you need to build NEW organization or products or business processes — I have never felt that any of my directors were “too smart,” such that I would trade some of their raw intelligence for some other attribute.

success at the manager or director level requires well-roundedness — but the degree of success is often directly related to the person’s level of intelligence.

Everywhere I have worked, the organization’s hiring processes were tilted in favor of experience over intelligence.

A new way to interview

Asking unusual questions that learn what the person does in their downtime away from formal work settings

Asking meta-questions like “How do you think the interview is going?” or “What questions would you ask if you were interviewing candidates for this job?”

Asking for more and more examples

Plus, there’s a harder question for the interviewer: “what do you do with the answers?”

But when the entire point of the interview is taking the conversation in unpredictable directions, how will you know how to evaluate a “good answer?”

Most people cannot accurately assess whether a candidate’s gait or “microexpressions” would make them a good VP of Operations. And yet, these types of qualitative assessments are exactly what Cowen and Gross propose the reader do

The authors explain that academic literature indicates that qualitative techniques do NOT lead to better hires, BUT that might be attributed to the average interview’s lack of sophisticated skills and insights. In other words, the authors believe their own abilities are better than average

I agree! Cowen and Gross both have track records of finding early-career people who went on to achieve incredible success. But will average readers of the book enjoy the same type of success?

In practice, then, I think new interview techniques need to be incorporated gradually.

The process of careful iteration might be less important if you are looking for talent like Cowen and Gross. In both cases, the authors are evaluating candidates and thinking about the power law. They are not so much looking to avoid disaster as they are hoping not to miss grand slams (A-list). For both Cowen and Gross, the constraint is talent, not cash.

So, if you are going to use the techniques from this book, I would recommend caution.

Everyone I’ve ever worked with has grown tired of me telling them that for any given price point there is a trade-off between hiring experience or intelligence. The market is efficient enough that if you have two candidates in front of you at a given title and salary level — both recruited via the standard ways — then the one with more experience is almost always the one that is less intelligent.

for most roles in the business world, skills and experience are not nearly as important as IQ — especially for roles that require building new things

You can do very well in recruiting talent by following three principles:

• Get the basics right.
• Aim to recruit really smart people (even if they possess less experience).
• Don’t throw out all your current processes to chase the newest trend.

Footnote

In The Average is Over, Tyler Cowen describes the incremental development of chess AI

there was a period of time when chess AI programs could beat all humans, but they were still beatable by humans that worked in tandem with AI programs. (The competitions were called “Freestyle Chess” - centaur). That window was still open when the book was published (2013) but has since closed.

Most AI is not as advanced in its function as chess AI, so the idea is that there is an extended period of time in any particular field

GPT-3’s progeny may eventually eliminate the need for novelists, but well before it does so, humans will be working with deep learning language models to write books and screenplays far faster than any time in the past.