Should You Hire for Fit or for Potential?

Hunter Walk published a short post titled:

Hiring for Fit Gets You to IPO, but Over Time, Hiring for Potential Wins

It’s based on a 2002 research paper by Baron and Hannan exploring the impact of “employment blueprints” on companies success.

I was excited to read the 25-page paper as it covers one of the topics that I’m most passionate about: the impact of organizational choices and decisions on company performance. And on a more meta level, it also seems to corroborate a broader pattern that I’ve observed: we seem to have a serious knowledge management problem when it come to organizational design. This paper was published in 2002. 13 years later it is rediscovered, but during that time, the debate about some of the insights (for example: hiring for fit vs. potential) raged on, uninformed by data as always…

Reading the paper left me with mixed feelings. On the one hand, the “blueprint” approach seems to resonate and yield some pretty interesting insights. On the other hand, the opacity around the analysis done by the authors, casts a serious doubt on the validity of the insights, at least in my opinion.

The Good

The team looked at a 200-company data set from the “Stanford Project on Emerging Companies” . They’ve classified the employment decisions that they’ve made on three dimensions: basis of attachment and retention, criterion for selection and means of control & coordination:

arch1

They then clustered the 36 possible permutations into  five common blueprints (archetypes):

arch2

After looking at the impact blueprint selection has on softer aspects, such as other choices in organization-building (timing of bringing in specialized HR capacity, sequence of hiring compared to other business milestones, level of early attention to organizational concerns), and exploring some initial attributes of blueprint switching (who switches, why, and to what), the authors turn their attention to the main research question:

Once a certain blueprint was chosen, do the benefits of switching outweigh its costs?

To answer that question, the authors first explore the intrinsic costs and benefits of each blueprint. The costs are measured in the level of administrative overhead over time, and the benefits are measured through the impact on three performance indicators:

  • Likelihood of Failure
  • Likelihood of IPO
  • Annual growth rate in market capitalization (post IPO)

The “commitment” blueprint seems to be the clear winner of the first two, while the “star” blueprint is the winner of the last one.

fig6 fig7 fig8

Then they turn to explore the impact of changing the blueprint, and find that while it slightly increases the chance of IPO, it has more profound effects in increasing the likelihood of failure, increasing employee turnover and reducing yearly growth in market cap. Perhaps the most interesting finding w/r/t employee turnover was the following:

“It turns out that CEO succession does have a strong effect on
turnover. However, this effect appears to be due entirely to the tendency for
CEO succession to be accompanied by changes in HR blueprints”

fig9

The Bad

As I’ve eluded to in the intro, the opacity around the statistical analysis done by the authors is an issue that kept bothering me throughout the paper. The authors mention several times that they’ve taken other factors into account while performing the analysis but don’t reveal any of the data. A subsequent working paper sheds some additional light, but not enough alleviate my concerns. This is particularly troubling for several reasons:

  1. Small data set – only 156 companies
  2. Selection bias – only 42 of the companies went public, so any analysis of post-IPO performance is particularly selection-prone
  3. Unclear statistical significance of the results – for example, w/r/t the information shown in figures 6 & 7, the authors acknowledge in the working paper that: “The differences among models (aside from the contrast vis-à-vis Commitment) are not jointly significant”
  4. Unclear explanatory power – I’m probably not using the right statistical term here, but here’s the issue: almost all the information is presented in relative terms looking at the impact of one blueprint compared to another, typically using the “engineering” blueprint as the default. However, what portion of the overall variability in the performance indicators is explained by blueprint selection (and whether that insight is statistically significant) is never discussed. Put differently: it seems unlikely in the heavily-scrutinized post-IPO environment that if switching  from the “engineering” blueprint to the “star” blueprint would have yielded an 80% improvement in the annual growth in market cap, only 11% of companies would switch blueprints…
  5. Unique time bias– the boom-and-bust period of the late 90s and early 00s

Bottom Line

The subsequent working paper exposes another facet of this paper, which may help explain some of the analytical challenges with it. In it, the authors state that:

“The main focus of this research was to learn whether changing initial blueprints destabilized the SPEC companies”

And that is indeed, the less controversial part of the research. I really like the idea of organizational blueprints/archetypes and think it merits further exploration. Beyond that, personally I find it hard to overcome the analytical challenges in making a call on whether one blueprint is better than the others.

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Should You Hire for Fit or for Potential?

The Cultural Manifesto

A recent piece by First Round Review recaps a talk Kevin Scott, LinkedIn’s SVP of Engineering and Operations gave at their recent CTO Summit:

How I Structured Engineering Teams at AdMob and LinkedIn for Success

There are many good nuggets of content in the piece, but at its core is an artifact referred to as the Cultural Manifesto: “a document or a set of materials to help your entire engineering team get on the same page about how you make and operate things, and how you function as a team”.

Not surprisingly, it has three main sections covering the organization concrete, documented opinions in three main areas:

  1. How we make things – code reviews, branching, deploying code, enabling features, etc.
  2. How we operate things – monitoring & alerting, production access, data integrity, etc.
  3. How we function as a team – role of engineering, culture and values, conflict resolution, etc.

cultural manifesto

 

It’s a phenomenal starting-point checklist to go through. If you don’t have a concrete, documented opinion on one of these line items – you probably should.

“Don’t let your CFO start capitalizing R&D labor” is my own personal favorite 🙂

The Cultural Manifesto

Rubber Bands, Efficiency-Responsiveness and Coordination-Motivation

Adam Pisoni penned a thoughtful post on First Round Review titled:

Letting Go of Efficiency Can Accelerate Your Company – Here’s How

Adam argues that the age old business strategy focused on efficiency at scale can become your biggest enemy, the moment the future becomes unpredictable (as it more and more does nowadays). Since efficiency, by design, lock in roles, processes and practices and therefore makes it much harder to change.

An alternative paradigm, more suited to an unpredictable future, is one of responsiveness – being nimble and agile in responding to the changing reality. The challenge of switching from efficiency to responsiveness is a cultural one. Switching from a model based on secrecy, planning and control, to one based on transparency, experimentation and empowerment. The problem gets conflated because those cultural attributes are interrelated:  they can be described as “sliders” on these three spectrum, bound together by a rubber band. In order to move one of them in a certain direction, you have to move the others.

efficiency-responsiveness

He then goes on to illustrate the tension with a few real world examples. And outlines the path for transformation.

But instead of going down tat path, let’s zoom-in on one of these tensions, with the help of Alfred Wagner and another short post:

Networks, Firms and Markets

Alfred takes us 80 years into the past, to Ronald Coase‘s “The Nature of The Firm” and the two fundamental problems that it outlines in organizing economic activity: motivation (getting people to expend effort, companies to allocate resources to an activity) and coordination (arranging activities so that they fit together, such as making sure a part needed for production arrives on time). There is an inherent trade-off  between the two, also reflected Pisoni’s piece (control vs. empowerment is the most notable one). Alfred’s key point that this trade-off can be reduced (but not eliminate) through technology. For example, the evolution from a hub-and-spoke communication structure to a fully-mesh one enabled end-points to make informed decision without having to rely on a central decision-maker – better coordination without forcing a hit to motivation.

Now according to Pisoni’s all of that doesn’t matter, since responsiveness trumps efficiency. I (and others) however, are in a camp that believes that successful companies need to have both. More on that in the next post.

Rubber Bands, Efficiency-Responsiveness and Coordination-Motivation

Vindictive Protectiveness

Let’s balance last week’s quant-heavy post with a post about a much softer topic: words.

Though I sometimes disagree with his views, Jonathan Haidt is one of my favorite academics. If you haven’t read The Happiness Hypothesis and The Righteous Mind, you should definitely add them to your reading queue. And if that’s too much of a time commitment, spend 20 mins watching his TED talk.

I just finished reading the Atlantic’s September cover story, that he co-authored with Greg Lukianof:

The Coddling of the American Mind

In it, they describe a cultural shift in American campuses – an attempt to shield young adults from words and ideas that make some uncomfortable, which they’ve labeled “protective vindictiveness”. It manifests itself in the form of growing accusations of “microaggressions” and requirements to issue “trigger warnings” (more on those in the article). Given that the aim of the movement is centered around emotional well-being, they use Cognitive Behavioral Therapy as a framework, to argue that it may be doing more harm than good on that front. Encouraging students to develop extra-thin skin, just before they go out into the “real world”, where they’ll encounter a plethora and words and ideas that they cannot control. It is worth reading their piece in full as I won’t be able to do it justice in summarizing it. In this short paragraph, I’ve probably already made some word choices that cased someone, somewhere to take offense…

But why am I covering a piece about campus culture in a blog about business organizational effectiveness? I’m glad you asked:

  • Today’s college culture problems are tomorrow’s business culture problems, as current students leave college and join the workforce, with this cultural indoctrination in mind.
  • Looking at the direction that typical “office sensitivity training programs” are headed, and the way that some related incidents are handled, some may argue that this culture has already started trickling into the work place.
  • Tech companies will be affected first as their demographic tends to skew young.
  • No matter on which side of the academic debate on “whether it’s the colleges’ job to prepare students for post-college life” you fall, this piece suggests that the skills/culture gap is widening. If colleges are not stepping up to address it (and some may argue, are making it worse), workplaces will have to.

With that last point in mind, Haidt and Lukianof suggest steps that can be taken to remediate the situation. Perhaps the most relevant one to the business world is teaching students (employees) how to practice Cognitive Behavioral Therapy, avoiding unhealthy emotional biases and applying more objective, critical thinking not only to the business problems they are tasked with solving, but more broadly to the way they chose to experience life.

Patty McCord, creator of the famous Netflix culture deck offers this relevant piece of advice: “97% of your employees will do the right thing. Most companies spend endless amount s of time and money writing and enforcing HR policies to deal with problems the other 3% might cause”.

Vindictive Protectiveness

2 Minutes on Focus

Many have made the case for the importance of focus in driving a top performing business.

But what does that actually means? What does focus actually looks like?

This 2-min bit from Keith Rabois’ talk at Sam Altman’s Startup Class answers that question beautifully:

How to Operate

This bit is short enough to transcribe it here fully:

“So I am going to argue that you need to spend a lot of time focusing on people. This is something I learned from Peter Thiel actually. He used to insist at PayPal that every single person could only do exactly one thing. And we all rebelled, every single person in the company rebelled to this idea. Because it’s so unnatural, it’s so different than other companies where people wanted to do multiple things, especially as you get more senior, you definitely want to do more things and you feel insulted to be asked to do just one thing.

Peter would enforce this pretty strictly. He would say, I will not talk to you about anything else besides this one thing I assigned you. I don’t want to hear about how great you are doing over here, just shut up, and Peter would run away. And then focus until you conquer this one problem. And the insight behind this is that most people will solve problems that they understand how to solve. Roughly speaking, they will solve B+ problems instead of A+ problems. A+ problems are high impact problems for your company but they are difficult. You don’t wake up in the morning with a solution, so you tend to procrastinate them. So imagine you wake up in the morning and create a list of things to do today, there’s usually the A+ one on the top of the list, but you never get around to it. And so you solve the second and third. Then you have a company of over a hundred people so it cascades. You have a company that is always solving B+ things which does mean you grow, which does mean you add value, but you never really create that breakthrough idea. No one is spending 100% of their time banging their head against the wall every day until they solve it. So I highly recommend some version of that. You can be less stringent, you can give people three things to work on, but I would still track the concept of what would happen if you only gave everybody one thing to prioritize.

2 Minutes on Focus

Spotify

Henrik Kinberg‘s seminal work at Spotify has made real waves in the community when Scaling Agile at Spotify started making the rounds. More recently, Henrik put out these two videos outlining the key components of Spotify’s engineering culture:

Spotify Engineering Culture – Part 1

Spotify Engineering culture – Part 2

The thing I found most impressing about these videos is the connection between the high level, abstract culture, and the more pragmatic set of business practices that it was broken down to.

As Henrik mentions in a different post, there is no right or wrong answer here. Every cultural decision has a trade-off built into it:

rightwrong

What’s really unique about the Spotify case, is the way they acknowledge and own up to the trade-offs that their culture embodies, and fully align their business processes with it. This tight alignment between culture and process/structure is rare, and in my opinion, one of the key ingredients in what makes Spotify so successful.

Spotify

Engineering Serendipity

“If so many discoveries – from penicillin to plastics – are the product of serendipity, why do we insist breakthroughs can somehow be planned?”

The short answer to this question, according to Greg Lindsay, is “because it can be planned”. To a degree of course.

In his essay, Greg covers the aspects of physical structures, organizational structures and networks that can foster or hinder reaching a serendipitous mindset.

More here:

Engineering Serendipity

 

Engineering Serendipity