A cohesive culture is not for everyone

Netflix’s “No Rules Rules” — Part 1

Source: No Rules Rules

I recently finished “No Rules Rules” by Reed Hastings, Netflix’s founder and CEO, and Erin Meyer, a business professor at INSEAD. 

There’s a lot to extract from this book and I’m going to split that into a few blog posts with this rough game plan: 

  • Part 1: (this post) high-level review of the book. 
  • Part 2: review of specific Netflix processes and practices discussed in the book (may be split into more than one post). 
  • Part 3: the culture map. 

The book aims to provide a pretty deep dive into Netflix’s company culture: how it came to be, how it’s reinforced and what business benefits it unlocks. 

Hastings and Meyer tag-team the writing, with Hastings typically providing the history of how a certain element of the culture came to be, how it evolved over time, and why it’s important, and Meyer providing both scientific backings to the merits of the element/practice and detailed on-the-ground depiction on how it manifests in the day-to-day life of Netflix’s employees. 

In a nutshell, Netflix’s culture is described as three key elements that are deeply intertwined: high talent density (quality of employees), high level of candor, and high level of freedom (low levels of control). The latter two are the source of Netflix’s famous “Freedom & Responsibility” (F&R) motto. 

After a brief introduction, the book goes through three iterations across these elements, each time offering a more evolved and sophisticated way to implement the element and take it to the next level. It concludes with a chapter on taking the Netflix culture global, which will be the sole focus of Part 3 of this series. 

Source: No Rules Rules

Three things made this book a very worthwhile read: 

  • First, it shows how the three cultural elements are intertwined, and how “leveling up” one element unlocks the next level of the other elements. 
  • Second, some of the practices, like “sunshining” and in-person 360 feedback are finally described in a level of detail that makes them “safe enough to try” and opens the door to experimenting with them, at least in some contexts. Though the first point is an important caveat here: optimizing the part doesn’t necessarily optimize the whole. 
  • Third, this is not a “Kool-Aid” book. As a reader, I didn’t get the impression that it was written by a Netflix culture zealot. There were no claims that these structures will work well outside of Netflix. I appreciated the authors’ efforts to share the challenges with the trade-offs the culture implies, alongside its strengths. Kyle and Donna’s struggles with the vague vacation policy, Jaime’s struggles with the vague expense policy, and Russel and Han’s struggles with paying top-of-market salaries are just a few of many examples that are covered in detail and demonstrate that the Netflix way is not necessarily the easy way. 

It is easy to come away from reading a book like this one with the wrong conclusion that the Netflix way is the best way and that every company should follow its lead. This is the lesson that many CEOs have (hopefully) learned, often times the hard way, trying to imitate Steve Jobs’ leadership style. 

The deeper and more useful insight from this book, in my mind at least, is the power of a cohesive culture, where elements reinforce rather than contradict one another, and the iterative process by which it evolves and strengthens. 

And even with that, a healthy amount of skepticism is still merited. As Steven Sinofsky once observed: 

Like so many company processes, when a company is doing “well” then the processes are exactly the right ones and magical. When a company is not doing so “well” then every process is either a symptom or the cause of the situation.

An often under-appreciated aspect of cohesive cultures is that inherently, they would never be a good fit for everyone. This is something that often gets missed by some of the big exposés about the Netflix (and to some degree, the ones concerning Amazon) and more recent critiques of the book. The personal stories of the individuals for which the culture didn’t work, or the edge cases where the culture broke can sometimes distract us from the bigger picture. 

And again, Sinofsky says it better than I can: 

Like so many things in business, there is no right answer or perfect approach. If there was, then there would be one [approach] that everyone would use and it would work all the time. There is not.

As much as any system is maligned, having a system that is visible, has some framework, and a level of cross-organization consistency provides many benefits to the organization as a whole. These benefits accrue even with all the challenges that also exist.

In the same essay, he also points out that “the absence of a system is itself a system”. And that approach too is not without its challenges. 

A cohesive culture is not for everyone

Mind the (survey) gap

Doing employee research right

A 2013 study by the Engagement Institute found that over 80% of global organizations survey their employees regularly, with an increasing number administering regular pulse surveys throughout the year. 

While employee survey research is one of the most common methods for conducting employee research, it is also the ONLY one widely used, leaving many organizations with significant blind spots and missed opportunities in improving their organizational health. Those challenges stem from both flawed execution and structural limitations of the employee survey methodology. 

A recent paper by Lewis Gerrard and Patrick Hyland offers a critical review of both theory and practice of employee survey research:

Employee Survey Research: A Critical Review of Theory and Practice

The origins of employee survey research can be traced all the way back to the 1920s. Today, well-designed organizational survey projects are characterized by three main activities: 

  • Careful measurement with the clear aim of measuring personal perceptions objectively. 
  • Robust data analysis, seeking to generate insight from survey responses. 
  • Collective feedback & action planning, recognizing the importance of involving employees, managers, and leaders in the process of interpreting results, recognizing areas for change, and developing plans for improvement. 

While this simple bar is not always met by many employee survey projects, the paper focuses on deeper issues. 

At the theoretical level, employee survey research is based on several incomplete or outdated philosophies about the nature of organizations. For example, the design and analysis of surveys assume a clear and consistent cause-and-effect relationship between various organizational phenomena. However, complex adaptive systems theory, suggests that this view is overly simplistic and does account for chaotic, disruptive and emergent organizational dynamics that make predictable causal links unlikely. 

The paper offers a few additional examples of organizational theories/philosophies that underlie employee survey research and recent developments and discoveries have proven to be either incorrect or incomplete. 

At the practical level, the paper highlights three methodological challenges and three analytical mistakes that often get in the way of drawing accurate insights out of employee survey research. 

Methodological challenges 

  • Overlooking the limitations of cross-sectional design: survey data is collected anonymously and analyzed at the aggregate level (department/organization) ignoring changes in employee population such as new hires, departures, and cross-departmental transfers between survey administrations. 
  • Ignoring common method bias & the necessary conditions for claiming causality: causality analysis is conducted within a single survey resulting first, in an inability to measure and control for systematic measurement error — variance introduced by the measurement method itself. And second, in limiting the credibility of any causal relationships uncovered between survey items/dimensions since they were only explored at a single point in time. 
  • Surveying only the evaluating and remembering self: since surveys often ask employees to make global evaluations about work based on retrospective reflections, they only capture people’s after-the-fact, reflected evaluations of events, which was shown to be different than their moment-to-moment assessment of the same events as they were happening. 

These methodological challenges are not without solutions: 

  • Longitudinal survey design, tracking attitudes at the individual level and making comparisons based only on employees who completed all surveys over a given time period can address cross-sectional design limitations. 
  • Creating temporal separation between measuring predictor variables and criterion variables — conducting statistical analysis across surveys rather than within surveys can address the “single point in time” challenges. 
  • Experience sampling techniques like The Day Reconstruction Method can complement the standard reflective method ensuring that data from both the “experiencing self” and the “remembering self” are captured. 

Analytical mistakes 

1. Assuming more is better: consistently positive survey results have three potential drawbacks: 

  • Strongly favorable attitudes may prevent organizational leaders from engaging in the critical process of reflection and change, increases the challenge of breaking out of the status quo. 
  • Employees in some roles may actually benefit from a sense of dissatisfaction at work, where a sense of frustration is an important driver of action.
  • In some cases, a stronger endorsement of an item is not predictive of increased outcomes. Some attitudes and employee states may be more beneficial if they fluctuate rather than maintained at a consistently high level. 

2. Overemphasizing contextual factors: the focus on measuring climate factors and shared employee experiences has led to a lack of practical integration between the psychology of individual differences and perceptions of workplace experience. A 2018 meta-analysis established that around 50% of the variance in an employee’s work engagement is predicted by personality and character variables. Therefore, variables like engagement are heavily influenced by the nature of the people selected into the organization. 

3. Assuming survey results will lead to change: while employee survey research has been a staple organizational practice for several decades, over a recent 18 year period (2000–2018), on average 30% of employees have been engaged at work, with a maximum variation of 4% in each direction. A principal assumption of the employee survey process is that leaders have the capacity and willingness to use employee feedback to create change. Yet this assumption has not always held true. Furthermore, studies demonstrated that factors like CEO personality play a key role in culture development, suggesting that a significant change in culture may only be possible with a significant change in leadership. A change that many organizations are often reluctant to make. 

Best-in-class employee research programs 

In addition to performing the activities required for well-designed organizational projects, addressing the methodological challenges and avoiding the analytical mistakes of employee survey research, the authors offer the following recommendations for creating best-in-class employee research programs: 

  • Learn to use multiple methodologies — complement employee survey research with additional methodologies that make up for its blind spots and shortcomings. 
  • Assess organizational phenomena at multiple levels — team effectiveness, for example, should be explored by assessing individual team member personalities, group-level behavior, and organizational-level culture. 
  • Integrate multiple datasets — rather than analyzing attitudinal data in isolation, link it with effectiveness, performance and productivity datasets to generate more valid organizational insights.
  • Engage multiple stakeholders — employee research programs aim to create insight, energy and direction for organization members, from front-line employees to c-suite members. Ongoing dialogue with that diverse group of stakeholders will help ensure that this objective is indeed achieved. 
Mind the (survey) gap

Achieving career growth: opportunities, skills & sponsors

Career ladders are not a prerequisite 

Photo by yang miao on Unsplash

For many of us, the opportunity to continue to grow our skills and impact is a significant decision-making factor in choosing career opportunities. Considering this through the lens of Self-Determination Theory, for example, makes it abundantly clear why: building our skills both improves our competence, and in an organizational setting, helps us build the credibility that enables us to operate more autonomously.

Career ladders are a common organizational construct that, among other important uses, can act as a useful roadmap for driving our growth, by outlining what the next level of performance looks like in the areas of competence that the organization deemed to be particularly important. 

However, career ladders highlight the destination (next level of competence) but not the path for getting there. And in some organizations, career ladders don’t exist or are not heavily utilized. Which begs the question: is growth still possible in situations? 

The answer is a resounding “yes”. 

Damian Schenkelman did a phenomenal job describing a system for growth that can be utilized without a dependency on ladders. 

He starts off by defining some key terms: 

  • Skills: what you can do, including knowledge required to do it.
  • Opportunity: a possibility for improving and/or displaying your skills. They might be accompanied by financial rewards, recognition, etc.
  • Growth: access to more challenging and/or new opportunities. Growth is multidimensional.
  • Sponsors: People that are aware of available opportunities and can grant them to you.

And putting them together in a system diagram: 

Source: https://yenkel.dev/

Your skills improve depending on how fast you learn from your opportunities and the rate by which opportunities are granted to you. That rate depends on your sponsors who are, in turn, impacted by the rate by which you display your skills. 

Skill alone doesn’t matter. If no one but yourself knows about your skills, you won’t get any opportunities.

That insight leads to a two-pronged growth strategy: maximizing available opportunities, and maximizing sponsors.

Maximizing available opportunities

Opportunities can be on-the-job/unstructured (working on a new problem set, leading a new initiative), semi-structured (being mentored by an expert craftsman, speaking at a conference), or structured (attending a workshop). 

Tactics to maximize available opportunities: 

  • Picking opportunities based on your growth goals 
  • Favoring opportunities that require less investment to get them — a conference that requires 2 hrs of prep vs. 14 hrs of prep, an organic opportunity within your existing team vs. one with a different team/org. 
  • Proactively create your own opportunities by proposing them to sponsors. 

Maximizing sponsors

Tactics to maximizing sponsors: 

  • Finding the right sponsors by understanding the informal organization and how it relates to the opportunities you are interested in. 
  • Making your skills visible to them through 1:1s, content generation, and sharing your accomplishments. 
  • Fine-tuning your self-awareness of your skills so you can focus your energy and attention on opportunities that are attainable. 

Lastly, Demian reminds us that we can always “sponsor ourselves” — decide to invest our time (and sometimes our $$$s) in building a skill even when either a sponsor or an opportunity is available. 

If you’re dissatisfied with your current growth rate, or just think that you’re not growing as quickly as you could — Damian’s post is a must-read. 

Achieving career growth: opportunities, skills & sponsors

Ego-centric vs. eco-centric networks

Less about your personal influence, more about our collective impact

I stumbled upon this wonderful gem by Christine Capra:

Network-ing Does Not Equal Network WEAVING

Christine makes a powerful distinction between two types of human networks: ego-centric networks and eco-centric networks. The key differences between the two are captured in the comparison table above, though the whole post is well worth the read. 

Similar to other distinctions, reality is a bit messier. Most of the networks that I’ve seen or been part of don’t squarely fit into the clear definition of either being an ego-centric network or an eco-centric network, but share some attributes of each. Though I can definitely tell whether they’re skewing more in one direction or the other. 

And here lies the true power of the distinction: as two paths, or directions if you will, that a human network can take. So it’s not about being one or the other but rather moving towards or away from one or the other. 

If I aspire to be part of the eco-centric network, the following question packs a lot of insight: 

In what ways can I/we move us to be more eco-centric and less ego-centric?

The table at the top of this post, offers some compelling areas to look at and focus on first. 

Ego-centric vs. eco-centric networks

What do we mean when we say “feedback”?

A short feedback taxonomy

I’m expecting a few shorter than usual posts in the coming weeks as I’m adjusting to my new work circumstances, but will stay committed to quality > quantity. 

Feedback is a word we love to use in professional settings, yet I’ve had a recent realization that we tend to use it to mean different things. 

Oxford Languages (Google’s English dictionary provider) defines feedback as: 

Information about reactions to a product, a person’s performance of a task, etc. which is used as a basis for improvement.

While this definition seems somewhat lacking or incomplete, it’s a good starting point. Feedback is information about a reaction to <something> used as a means with a particular <end> in mind. The different somethings that the feedback is a reaction to and the different ends that providing the feedback is meant to accomplish are two key differentiators that will allow us to distinguish between different types of feedback. To those two, we can add a third, which pertains to the period of time that the feedback is provided as a reaction two. 

Let’s get a bit less theoretical and a bit more practical. The following is a draft taxonomy that’s likely incomplete. Even in its nascent form, it provides some useful distinctions and insight. 

In a professional setting I find it useful to discern between: 

A. Feedback about the work

The work refers to a work product (deliverable), a project, a plan, a decision that needs to be made, etc. 

The trigger for further distinction between types of feedback about the work is the lifecycle stage of the work: 

  1. Problem validation — am I trying to solve a problem that’s worth solving?
  2. Solution exploration — what are all the potential ways so solve this problem? 
  3. Problem-solution fit — which solution (out of the now known set) will likely best solve the problem? 
  4. Continuous improvement — how well is the implemented solution solving the problem? 

B. Feedback about how we work 

This can potentially be further decomposed to “feedback about us” and “feedback about you” but I’m keeping those grouped together for the time being. 

The first trigger for further distinction between types of feedback about how we work discerns between different ends, and the second discerns between different time periods: 

1. Evaluatory / performance feedback — usually the responsibility of the manager).

2. Developmental feedback — how can we work better together? Can come from all collaborators and customers of the individual. Decomposed further by the period of time covered: 

  • Situational feedback — delivered in the moment or right after the moment. 
  • Episodic feedback — looks at broader behavioral and relational patterns and, usually facilitated by a formal quarterly/semi-annual/annual process. 

These different use cases of feedback often require a different process or structure to support them. A catch-all structure that does not account for the different types usually leads to a “jack of all trades, master of none” outcome. 

What do we mean when we say “feedback”?

Finding a job in unusual times

5 reflections on a months-long journey

Photo by Caleb Jones on Unsplash

I left Grammarly at the end of 2018 and after taking 2019 as a Sabbatical year with a pretty lightweight consulting load, I started my job search in earnest in Feb-March 2020. Consulting was never a thing I aspired to do, but certainly an experience that I was eager to explore. When it was time to ramp up my professional intensity (and income) I chose to focus on another tour-of-duty in an in-house role rather than on building my consulting practice up to a full-time-equivalent volume. 

There was only one wrinkle. COVID-19 hit the US at full speed, and my target sector, private tech companies, was holding its breath: freezing hiring, furloughing staff, and in some cases, conducting painful layoffs in an effort to extend cash runway faced with a future that just gotten way more unpredictable. I could not have picked a worse timing to look for a job. 

In late August, my job search concluded successfully, accepting an offer from a wonderful company for a dream role. This is a great time to reflect on my journey and share some lessons, for my own future reference, and hopefully for the benefit of others as well. 

1. Establish a rhythm

At the beginning of the search, I was following a very loose plan. I’ve been spending a lot of time in the previous year thinking about goals and how to pursue them wisely. Knowing that I’m not fully in control of the outcome, and without an external feedback mechanism: am I doing too much, overestimating my ability to influence the outcome and exhausting myself unnecessarily? or doing too little, resting on my laurels, underestimating my ability to influence the outcome, and unnecessarily prolonging an extremely uncomfortable situation when I could have done more? 

The insight came from looking within, reflecting on past challenges and situations and realizing that in this particular case, I’m likely doing too little than too much. That gave me the conviction I needed to push myself harder and put together a more disciplined plan. I certainly consider myself a creature of habit, so designing and scheduling a recurring set of activities was the best way for me to ensure that my actions reflect my intention. 

My job search rhythm consisted of the following: 

  • Daily — Review LinkedIn jobs emails that were pushed to my inbox based on 3 keywords I set up in advance, and take action on any relevant opportunities. 
  • Weekly — Go through the VentureLoop job board. Given my target sector, this was the job board most likely to yield relevant opportunities. 
  • Weekly —Continue to publish content on OrgHacking. The content I published on OrgHacking over the past 6 years has become a powerful tool to demonstrate what I’m bringing to the table in a way that a resume never could. I created a sample portfolio with some of my best posts and referenced it in my outreach emails. 
  • Bi-weekly — Go through a set of GlassDoor job searches. Lower ROI but still a very popular option with my target sector. 
  • Monthly — Exec search outreach — I built a list of the 15 top exec search partners in my domain and checked in with them on a monthly basis to see whether they’re running any relevant searches. 
  • Monthly — VC talent partner outreach (at a 2-week offset from exec search outreach) — I built a list of the 15 top VC talent partners and checked in with them monthly to see whether they know of any relevant openings in their portfolio companies. 

2. Manage the pipeline

As my rhythm was picking up steam and starting to bear fruit, I needed a system to keep track of the opportunities and ensure that I’m not dropping any balls. 

It was helpful to distinguish between a “lead” — a job opening that I saw/applied to, or a person that I was introduced to. And a “viable opportunity” — a job opening where I had at least one real-time conversation (phone or video) with the hiring manager or recruiter. 

Once a lead graduated to a viable opportunity, I added it to a simple Google Sheets tracker that I updated daily with the following info: 

  • Status: Open, Closed, On-hold
  • Company
  • Role
  • Hiring Manager
  • Hiring Manager role
  • Source
  • Stage: Recruiter screen, HM screen, assignment, on-site, final round
  • Last contact 
  • Notes

3. Introductions, introductions, introductions

In my almost-20-yr career, I have never gotten a job by blindly submitting a job application. And not for lack of trying. With the hyper-competitive market dynamic that COVID-19 created (scarcity of jobs and abundance of candidates), I figured that’s not going to change and focused on finding someone that can introduce me to the hiring manager (preferably) or the recruiter, regardless of how I first learned about the opportunity. 

4. Ask for help

This is a personal growth area for me that I’ve intentionally focused on in this search. My independence has been a deep source of strength in my life, but it’s not without its shadow side. While asking for help showed up in many ways in this journey, these were the key ones: 

  • Leaning on friends, family, and especially my partner, Kimberly, for moral support and sage advice. 
  • Adding the “open to work” frame to my LinkedIn profile. Publicly admitting that I’m looking for work. My inner daemons told me that there’s still a stigma around it and that it can come across as desperate. I decided not to listen to them and do it anyway. 
  • Working with a career coach. A good colleague and strong executive recruiter happened to complete a coaching training and was looking for his first coaching clients. I took him up on his offer and found the added accountability and advice to be extremely helpful. I tend to think of myself mostly as a “think first, talk second” kind of person, but more and more I’m learning that talking about unbaked thoughts out-loud is a powerful way to advance and distill my thinking. 
  • Making semi-open requests to my immediate network. This was the hardest and most valuable for me to overcome. I had no issues asking a specific person for a specific introduction, but felt extremely uncomfortable with a generic network-wide blast of “hey I’m looking for work, send relevant opportunities my way”. Partly because I think it’s ineffective, but partly because of my inner daemons. I landed on a middle-ground solution where I reached out to a dozen people in my network who I trusted the most, asking them to introduce me to three connectors or relevant hiring managers who are hiring or may be hiring in the near future. The combination of a more targeted outreach with a more targeted “ask” got me over the hurdle. The job offer I accepted can be traced back to one of those emails. 

5. The 5 Fs

At the end of my search, I needed to choose between two very compelling but very different opportunities. It was a tormentous decision, but one I was lucky to have to make, and at the end of the day, a clear winner emerged. 

In hindsight, had I used the “The A Method for Hiring” 5Fs framework, making the decision would have been a bit easier: 

  • Fit ties together the company’s vision, needs and culture with the candidate’s goals, strengths and values.
  • Family takes into account the broader implications of the job to the candidate’s family. 
  • Freedom is the autonomy the candidate will have to make his or her own decisions. 
  • Fortune reflects the stability of the company and the overall financial upside.
  • Fun describes the work environment and personal relationships the candidate will make. [personally, I have a more profound definition for fun]

While the differences were far more nuanced than this, one opportunity was stronger on “fit” and “fun” while the other was stronger on “fortune” and “freedom”. “Family” ended up being the area that tipped the scales quite heavily towards the winning opportunity. 

Finding a job in unusual times

The one formula every leader should know

It’s been a best-kept secret for more than 80 years

No. Not this one. 

I love it when seemingly disparate posts come together in a surprising way and culminate in an “a-ha” moment. 

What do posts about a behavior change model, DEI program, self-engagement, and change management have in common? The answer: 

Lewin’s Equation

Kurt Lewin, a Jewish psychologist who immigrated from Germany to the US in 1933 as antisemitism was rising in Europe, first presented his formula in his 1936 book Principles of Topological Psychology: 

Lewin suggested that behavior (B) is determined by two key elements: the person (P) and the environment (E). 

The variables in the equation (P,E), can be replaced with the specific, unique situations and personal characteristic. 

The equation is even more powerful when written in a dynamic form: 

A change in behavior is a result of a change in the person and/or a change in the environment. Or put more prescriptively: to change behavior, we need to change the person and/or change the environment. This is where nuance comes in: some behaviors will be more sensitive to changes in the person, while others will be more sensitive to changes in the environment. And, of course, both person and environment can change and be changed in multiple ways. 

To see the powerful explanatory power of Lewin’s equation, here are the key insights from each post, articulated using it: 

  • Getting personal about change — offers an expansion, or decomposition of Lewin’s equation. It breaks down P into “confidence and skill building” and “understanding and conviction”. And it breaks down E into “role modeling” and “reinforcement mechanisms”. 
  • D.R.I.V.E and prism — offers a slightly different decomposition. It breaks down P into “individual capabilities” and “(de)motivators”. And it breaks down E into “feedback” and “contextual triggers”.
  • Self-engagement — argues that traditional employee engagement efforts are not as effective as they could be, because they focus solely on changing the environment (ΔE), completely ignoring the opportunity to help people change (ΔP). 
  • Bias Interrupters —argues that many DEI efforts are not as effective as they could be, because they focus solely on helping people change (ΔP), completely ignoring the opportunity to change the environment (ΔE).

While I noted some of the similarities between the first two posts in D.R.I.V.E, the equation helps organize the patterns a lot more clearly. 

The focus reversal (from ΔE to ΔP) in engagement efforts vs. DEI efforts was a big “a-ha” insight to me and enabled me to capture the approach to improve both under a single thesis. 

There’s no leadership role in which behavior change is not a large and critical part of the role. Lewin’s equation should be part of any Leadership 101 textbook or training. 

The one formula every leader should know

Driving effective behavior change with Prism

A neat set of frameworks for creating the organizational behavior change you seek

source: affective-advisory.com

So much of the organizational work we do aims to change (or “sustain” as a special use case) certain behaviors in our teams. What’s the point of articulating a strategy if it doesn’t cause our teams to change their default behaviors and take a different set of actions to pursue it? What’s the point of a training or a workshop if the behavior before and after it is exactly the same. 

The team at Affective Advisory developed a pretty neat framework for driving strategic behavior change: 

The D.R.I.V.E Prism for identifying and evaluating effective nudges in practice

The framework builds on the core premise that human behavior is context-dependent and therefore, behavioral interventions have to be tailored to an individual context. Therefore, there are no universal interventions that are effective independent of context. Theoretical concepts need to be adapted into practice using a model-based, evidence-led approach and then tested and validated. 

The overarching framework for applying behavior interventions is outlined under the acronym D.R.I.V.E: 

  • D.efine strategy as a set of preferred target behaviors. 
  • R.esearch actual (current) behaviors and review related contexts relevant to the strategic challenge. 
  • I.dentify, evaluate, and adjust suitable science-based solutions. 
  • V.alidate the selected and tailored interventions across a representative sample. 
  • E.xecute behavioral interventions realizing behavior change at scale. 

Other than the neat acronym, there’s nothing earth-shattering here: define the change you need to make → understand the current situation → select an intervention → do a small pilot to ensure it drives the desired outcome → scale. 

The non-trivial piece comes in the middle of the process. Given the premise, how do we identify and adapt the right interventions that are most likely to drive the desired outcome in this particular context

This is where the prism comes in: 

source: affective-advisory.com

The prism is a three-dimensional taxonomy for categorizing different interventions and selecting the ones most likely to be effective in the specific context. 

Dimension I: Intervention levers

The underlying thesis here is that behavior can be changed by a combination of four different levers: 

  • Contextual triggers
  • (De)Motivators (automatic <-> reflective)
  • Individual capabilities (psychological & physical)
  • Feedback

Different interventions use a different mix of these levers. 

This construct can also be mapped to a similar behavior change model that I covered here providing further support to the taxonomy: contextual triggers → reinforcements mechanisms, motivators → understanding and conviction, individual capabilities → confidence and skill-building, feedback → role-modeling. 

Dimension II: The cognitive level

The levers outlined in dimension I can be designed to influence behavior through two cognitive levels: 

  • System 1 — unconscious, automatic, affective, effortless.
  • System 2 — conscious, deliberate, controlled, effortfull.

Interventions working through system 1 aim to either leverage or mitigate some of its unique attributes, for example: auto-saving documents based on a time trigger. 

Interventions working through system 2 aim to intentionally activate it to correct a system 1 driven behavior, for example: opening a dialogue box reminding users to save their file when they try to close it. 

Dimension III: The intervention level

Here, the taxonomy distinguishes between: 

  • Adding new enablers.
  • Removing existing blockers.

For example, a sign showing your current driving speed adds an enabler to drive the desired behavior. While default options and opt-out remove blockers by eliminating the need for a decision to reach the desired behavior. 

In Sum 

As it stands today D.R.I.V.E and specifically, prism, are useful tools for honing in on potentially effective interventions in a particular context. Especially if a specific intervention has been tried and didn’t work — exploring a different assumption around one of the prism dimensions may help identify a strong candidate intervention quicker. While contexts are inherently different from one another, I wonder if there are contextual patterns that make a certain type of intervention more likely to succeed than others. If that’s the case, a similar contextual taxonomy can be developed and more resilient mapping between contextual patterns and effective interventions can be drawn. 

Driving effective behavior change with Prism

Inclusive organizations change their systems, not just train their people

The Bias Interrupters Model

My ongoing quest to improve organizational equity and inclusion got me to the Center for WorkLife Law’s Bias Interrupters model.

The premise of the model is capture clearly by the team who developed it: 

Bias interrupters are tweaks to basic business systems that interrupt implicit bias in the workplace, often without ever talking about bias.

In many ways, it’s an evidence-based response to the failure of more culture-centric/training-centric approaches to significantly move the needle on eliminating bias in the workplace. 

The Bias Interrupters Model focuses on five core business systems: 

  1. Hiring & Recruiting
  2. Performance Management 
  3. Compensation
  4. Meetings
  5. Assignment

While the first three are capturing most of the current limelight as areas that required heightened attention to bias, conversations around inclusive meetings are still at their infancy and assignments are at the “inclusion frontier” as far as the broader conversation goes. Therefore, I found Bias Interrupters to be one of the most holistic approaches for driving this much needed systemic change.

The Bias Interrupters approach advocates for an iterative process consisting of:

  1. Establishing relevant metrics.
  2. Implementing evidence-based bias-interruption interventions.
  3. Assessing the impact the interventions had on the metrics and using the insights to inform the next iteration of the cycle.

Change to each of the five business systems listed above is supported by a recommended set of metrics to track, and a list of evidence-based standalone interventions. The idea here is that not all interventions have to be implemented at the same time, and different organizations can choose different paths to getting to bias-resistant business systems. For example, one organization may start tackling performance management by explicitly separating evaluating performance from evaluating potential, another may start by offering alternatives to self-promotion, and a third may tackle both of them at the same iteration. 

Furthermore, Bias Interrupters supports the systemic change needed in those systems on three different levels: 

Each level is supported by a toolkit including guides, worksheets, checklists, talking points and other relevant training materials. 

Different organizations take different stances on social justice issues and that can sometimes muddy the water around core DEI initiatives. The beauty of the Bias Interrupters program is that it’s completely agnostic to that stance, as if focuses on systemic bias which has no upside. It offers a blueprint for a way to run these core business systems that is flat out better than the alternative. 

Inclusive organizations change their systems, not just train their people

Changing the world with Heat AND Light

A balanced approach to social change

source:themindgym.com

On a recent MindGym webinar on The Future of Inclusion, I had a big a-ha moment, when they introduced their model of persuasion for changing behavior based on the work of Prof. Dolly Chugh.

Chugh’s model defines two approaches for pursuing social change: light and heat.  

Pursuing change through light-based means, puts the comfort of the target audience as a high priority. It aims to meet people where they are, recognizing that making people too uncomfortable will cause them to resist your message. It takes the time to educate, using factual, descriptive language, and a framing that focuses on our shared humanity. 

Pursuing change through heat-based means is specifically designed to make the target audience uncomfortable and to force acknowledgment of the problems and the need for change. It confronts the issue straight on, recognizing the subtlety may lead to a complacent response. It uses more emotive, visceral language and doesn’t shy from actions like protest and civil disobedience. 

One of Chugh’s most important insights from her research was that:

When historians study social-justice movements, they find that movements that only have heat or only have light tend to not make as much progress. Successful movements have both a more moderate and a more radical flank, if you will.

When I reflected on my own change strategy through this lens I noticed that I’m leaning more heavily towards the light-based approach. This also explained why I viewed heat-based strategies as less effective and, in some cases, moving us backward, even when we were all striving for the same social outcome. 

Shifting my perspective from looking at those strategies as an either-or choice to a both-and polarity, allowed me to recognize the importance of a combined strategy: too much light and not enough heat leads to complacency. Too much heat and not enough light leads to backlash and resistance. Effective social change requires a healthy mix of both. 

Changing the world with Heat AND Light