Technology-enabled Blitzscaling

Stanford University continues it’s now long-standing tradition of inviting prominent tech leaders to teach an elective at the school.

The most recent example is a class with the odd name “Technology-enabled Blitzscaling” taught by Reid Hoffman (LinkedIn, Greylock Venturers), John Lilly (Mozilla, Greylock Ventures), Chris Yeh (PBworks, Wasabi Ventures) and Allen Blue.

The class focuses on the unique challenges and dynamics of the “hyper growth” stage of start-ups conveyed primarily through 1:1 interviews with other leading tech execs such as Jeff Weiner (LinkedIn), Marissa Mayer (Yahoo), Elizabeth Holmes (Theranos) Eric Schmidt (Google), Brian Cheskey (AirBnB) and many others.

Chris McCann, playing a key role in facilitating the class, took scrupulous notes of each session and posted them on Medium, creating a unique and high quality repository of some of the latest thinking by some of the smartest leaders in the industry, on the topic of hyper-growth:

Notes Essays —CS183C: Technology-enabled Blitzscaling — Stanford University, Fall 2015

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Technology-enabled Blitzscaling

Buffer’s Salary Formula

Introducing the New Buffer Salary Formula, Calculate-Your-Salary App and The Whole Team’s New Salaries

Let’s address the elephant in the room first: the most notable aspect of Buffer’s salary policy is that it’s 100% transparent. Anybody can go into the spreadsheet linked from the post and see what each Buffer employee is making.

This post is not about salary transparency.

It’s a contentious topic that will earn its own separate post in due time, when I can better formulate my thinking on this particular aspect.

But whether you agree or disagree with their full-transparency policy has little to do with the real learning opportunity here: looking at a very bold attempt to formulaically model “soft” aspects of the Buffer culture into the way Buffer employees are compensated. That is worth studying and celebrating. Let’s begin.

The current version of Buffer’s salary formula consists of 5 core components:

  • Role – talent markets matter. Software developers have a higher (talent) market valuation than accountants, for example. This component accounts for that. (more below)
  • Experience – how good you are at what you do matters. Note that this is not “tenure” (x years of experience doing y), but an assessment of the level of skills based on discussions. Buffer currently uses 4 ties with a multiplier varying between 1x and 1.3x 
  • Dependents – the social dynamic that you live in matters. For every family member that depends on your income you get an extra $3K/year
  • Loyalty – loyalty matters. You get a 5% increase for every year with the company
  • Choice – your risk tolerance matters. Employees have a choice between an extra $10K or 30% more equity

Here’s a representative example:

buffer-salary-formula

The role component is worth further exploration as it’s the most complex one. It’s impacted by the following elements:

  • Overall base (35%) – standard US data for a particular role
  • Location base (65%) – accounting for variations in cost of living across multiple locations
  • Role value – Buffer may disagree with the way the market values a certain role (for example, if they think that customer support reps are undervalued by the market). This multiplier allows it to adjust for that.
  • “The Good Life Curve” – (cost of living correction) a $0-$8K adjustment that takes into account the market rate for a certain role in a certain location. This is perhaps the most thoughtful and interesting piece of the equation. The folks at Buffer argue that taking the market rate at face value is unfair. For example, while there may be a 4x cost-of-living difference between SF and Capetown (CPI of 113 vs. 30) there may be a 5x salary difference ($124K vs $25K) leaving the person working out of Capetown worse-off compared to his peer in SF. This component introduces a multiplier that’s meant to address that.

In future iterations the Buffer team plans to take a deeper look at two existing components that have become stale/outdated: the way experience and risk tolerance (“choice”) factors in, as well as two add’l external/environmental factors: taxes and exchange rates.

I’m excited to see where the Buffer team takes this experiment and particularly looking forward to see the next rev of the experience component, being the most “qualitative” component in the equation. Personally, I think their approach already leads to a better outcome than the standard “choose the percentile of market rate you want to be in”.  The biggest challenge the team will have to tackle has to do with complexity. Figuring out a way to keep the formula simple enough to understand while factoring additional drivers and addressing the interplay between them. Otherwise, “actual fairness” and “perceived fairness” will start to diverge.

Buffer’s Salary Formula

SCARF

SCARF: a brain-based model for collaborating with and influencing others

I remember hearing/reading about SCARF a few years back, but a recent conversation with a colleague made it top of mind for me again, so I decided to give it a deeper look.

In a nutshell, SCARF is a framework for understanding human social behavior through a neuroscience lens. It has broad applicability, prior to an interaction (predicting how people would react to certain conversation), during an interaction (helping to regulate responses to more tactical reactions) and after an interaction (explaining the root causes behind the outcome).

At its core, SCARF argues that human social behavior is dictated primarily by the human survival instinct, also known as approach-avoid, reward-threat, or fight-flight. SCARF then posits that human behavior can be analyzed and evaluated through the threats/rewards that a certain action triggers in each one of  5 domains: Status, Certainty, Autonomy, Relatedness, Fairness.

Below is a very crude summary, meant to give you a tase of framework and how it can be applied:

 

Definition Examples of reducing threats and increasing rewards
Status One’s sense of importance relative to others Perf Reviews/Feedback  – Allowing people to give themselves feedback on their own performance

Paying attention / acknowledging learning and improvement

Certainty One’s need for clarity and the ability to make accurate predictions about the future Encourage planing, decompose large projects to small tasks, set clear expectations on what’s likely to happen and what are the desired outcomes

Make implicit concepts more explicit

Overcommunicate

Autonomy The sense of control over events in one’s life and the sense that one’s behavior has an effect on the outcome of the situation Provide choices/options rather than dictate a certain course of action

Give control over L&D, workflow mgmt, working hours, etc.

Relatedness One’s sense of connection to and security with another person (in-group vs. out-of-group) Informal meetings, share personal stories,

Clearly defined “buddy systems”, mentoring, or coaching programs. Small groups are safer than large groups

Fairness Just and non-biased exchange between peoples Increasing transparency, increasing level of communication and involvement about business issues.

Set clear ground rules, expectations and objectives. Or even better, let set their owns.

 

It’s worth noting that some situations / actions force an unaviodable threat in one domain. But thoughtful design can often times help mitigate its impact by offerring rewards in other domains.

A later paper, published 4 years after the original one, covers more recent developments in the study of each domain and the framework in general. Perhaps the most interesting findings have to do with the individual variation in SCARF profiles (different people may be more/less sensitive to threat/reward in a certain domain) and the interconnections between SCARF domains, namely: status and relatedness, and certainty and relatedness.

The authors identify several areas where SCARF can be applied: managing oneself, educating and training, coaching, leadership development and organizational systems.  After spending a week looking at coaching and organizational systems tasks through a SCARF lens, I’m positively surprised by its ability to guide towards better outcomes. It’s a tool that I plan to keep at the top of my toolbox more than I did in the past.

SCARF

A New Year, A New Beginning

In a couple of weeks, I’ll be bidding Opower and Washington, DC farewell and move to San Francisco to join AltSchool as their new Head of People Operations.

Transitions are always bittersweet for me and this one is no different.

I’ll forever be grateful to Opower for giving me the opportunity to join a mission-driven company in a role that enabled me to apply my strengths and make a significant impact on the organization and its mission. My peers, managers and reports have been amazing catalysts of my professional growth. And if they can say the same about my contribution to them – then that would be my proudest achievement at Opower.

I’m extremely excited about this new opportunity for so many reasons. Let me call out a couple of them:

First, the organization that I’m joining. I learned early on in my career that a strong mission orientation is a necessary condition for me to fully engage in my work. Opower was a particularly strong validation of that. My bar for what qualifies as a mission-driven company is rather high (some may say “unrealistic”), and AltSchool was one of a handful of companies that actually passed that bar. There is so much to fix in education systems worldwide, and there is no silver bullet in fighting such massive scale societal problem (another lesson from fighting climate change with Opower). But AltSchool is definitely moving the needle in the right direction and with the right vision in mind, at least in my opinion.

Second, the role. If you look deep into the heart of modern collaborative software development methodologies (agile, kanban, etc.) you’ll find a humanistic approach to system and process design. An attempt to incorporate modern, progressive insights on what motivates people to apply themselves fully and the environment that fosters the most effective collaboration. But often times, this approach grinds to a halt at the walled fence of the R&D garden. More fundamental processes and systems that define the organization at its core, are based on anachronistic, industrial-era, mechanistic principles. Be it a performance management system that outweighs extrinsic motivation over intrinsic one, or an expense policy that outweighs abuse-prevention over the exercise of good judgement. This role puts me in a high-leverage position to continue pushing for a more humanistic organizational core, in an organization that’s already ahead of the curve in many aspects of this transformation.

I look forward to this new challenge a sharing many of the new lessons-learned and experiences with the readers of this blog.

A New Year, A New Beginning