Book Review: Nine Lies About Work

Have organizations gotten it all wrong all these years?  As a career HR practitioner many would call me an “expert” in many HR practices and programs.  For some parts of human resources, I might agree, for others, perhaps less so.  But I do have enough knowledge to be dangerous in most HR areas.

Suffice it to say, then, that I was floored when I recently read the book Nine Lies About Work by Marcus Buckingham and Ashley Goodall.  This book challenges many of the underlying assumptions that HR practitioners, HR functions and indeed companies of all sizes and types have had since the emergence of management science in the 1960’s.

One might be tempted to write-off their conclusions as ill-informed, but they have the benefit of decades of data and insights on topics like trust, team effectiveness and employee engagement behind them.  Buckingham worked for the Gallup organization doing research on employee engagement for a decade and is now the head of all people and performance research at the ADP Research Institute.  Goodall is the Senior Vice President of Leadership and Team Intelligence at Cisco.  Between them they know a thing or two about both the theoretical and real-life application of these concepts.

So, what did they have to say?

Their book focuses on “nine lies” – things that we take as gospel but that are in fact (according to them) based on flawed logic, and not backed-up by the research.  The nine lies are:

1.     People care which company they work for

2.     The best plan wins

3.     The best companies cascade goals

4.     The best people are well-rounded

5.     People need feedback

6.     People can reliably rate other people

7.     People have potential

8.     Work-life balance matters most

9.     Leadership is a thing

I know – these statements are shocking to me too!  But let’s unpack what the authors have to say about each.

Lie #1 - people care about which company they work for

The authors of Nine Lies About Work have found through their analysis that answers to engagement survey questions about feelings about their company are virtually consistent across all companies. No companies really stand out from the others.  The data also show that variability within companies is virtually identical across all companies, and it is huge.  What leads to the variability of responses being greater within companies than between companies?  The authors have found that it is not macro issues that drive divergent worker experiences.  Instead, it is the local experience that drives worker feelings about working for their company.  Factors like interactions with colleagues have an outsize influence on overall sentiment toward the company.  And this translates directly to “intent to stay” scores.   People with positive local experiences are more likely to stay.  Further, their research found that “team members who said they trusted their team leaders were twelve times more likely to be fully engaged at work.”  Their major conclusion is that it is the immediate team, the team leader, and experiences with immediate team members that have the largest impact on engagement.  They suggest that the following eight questions from the Great Place to Work Trust Index have the largest predictive influence on trust and engagement:

1.     I am really enthusiastic about the mission of my company

2.     In my team, I am surrounded by people who share my values

3.     My teammates have my back

4.     I have great confidence in my company’s future

5.     At work, I clearly understand what is expected of me

6.     I have the chance to use my strengths every day at work

7.     I know I will be recognized for excellent work

8.     In my work, I am always challenged to grow

The first four deal with the “communal experience of work”, or the “best of we” questions.  The next four deal with the “individual experience of work”, or the “best of me” questions.  Together they represent what we need at work to thrive.

Lie #2 – the best plan wins

Companies love to plan.  Especially bigger companies.  There are strategic plans.  Long-range plans (LRP), business plans, functional plans, marketing plans, customer service plans, and every other type of plan imaginable.  Firms spend huge time and resources building plans.  Unfortunately, the moment the ink is dry on their plans, the context within which the plan was drawn-up has changed and the plan is no longer valid.  Think about the plans used by energy companies in arriving at their 2020 budgets.  With COVID-19 and crude oil dumping practices by Saudi Arabia and Russia, we are in an entirely different world than only a few short months ago.  Plans drawn-up in late 2019 are completely useless in the second quarter of 2020.

Instead of the best plans, the authors suggest that the best intelligence wins.  Good information leads to good decision-making.  Good decision-making leads to great results.  So how do we ensure we are leveraging the best intelligence to make decisions?  The authors suggest there are a few strategies to do this.  First, liberate as much information as possible.  Don’t limit key information to the most senior leaders.  Instead make it available to all employees on-demand, in real time.  People are smart and want to do good work.  Give them the information to do so.  Second, watch for the data your people find most useful, and give them more of that.  Reduce the noise by removing data they don’t need or use.  Third, trust your people to make sense of the data.  Liberate them from relying on custom reports, data translators and complex processes.  Give them simple dashboards instead.  The authors also suggest we stop using huge alignment meetings and complex planning processes and instead rely on a delightfully simple humanistic process – the one-on-one meeting. Data suggests these 1:1 meetings don’t even need to be terribly “effective” to have the desired impact; they just need to happen.  Frequency trumps effectiveness.  In the opinion of the authors, these check-ins are the most important part of leading.

Lie #3 – the best companies cascade goals

Most organizations use some kind of goal-cascading process.  The annual plan mentioned above establishes the priorities for the coming year, and these priorities are translated into a set of goals.  Sometimes they are organized into categories like financial, sales, operational, innovation, customer-service or people.  These goals then get cascaded from the executives down to each level of the organization.  Employees and their leaders struggle to shoehorn their own work priorities into these goal categories, but it often doesn’t really align well.  Unfortunately, the research suggests that cascaded goals actually limit performance.

Goals are primarily used for three management functions: to stimulate activity, to track progress, and to evaluate performance.  They are about control.  As a tool to evaluate they are particularly dangerous as to be reliable the goals must be calibrated to ensure standardized difficulty.  But this is not possible without even more top-down process.

The more effective approach according to the authors, is to cascade meaning.  People don’t need to be told what to do; they need to be told why.  They suggest cascading meaning through our expressed purpose, values, rituals and stories.  Talk about the purpose of the company and how our work links to enabling it.  Talk about the priorities in front of us and how each member of the team can support these broad priorities. Liberate people to find meaning in their work rather than prescribing, top-down, their specific goals and tasks.

Lie #4 – the best people are well-rounded

Suffice it to say that the authors are not big fans of competency models.  They go into great detail about how flawed these models are, starting right from their highest-level intent.  Competency models tell us that for a given role, there is an ideal mix of proficiency levels of a certain prescriptive mix of competencies.  You are not ideal unless you check the box at the right proficiency level of each of the competencies assigned to your role.  Besides the fact that humans are not effective raters of one another (more on that later), the data suggests that the most effective humans have very distinct strengths in only a few key areas.  Their research has found, study after study, that one single engagement question has the most predictive power into effective teams: “I have the chance to use my strengths every day at work”.  Teams of individuals that rate this question high are disproportionately more effective.  Less effective teams have individuals that rate this question lower.  The authors say: “The well-rounded high performer is a creature of theory world.  In the real world each high performer is unique and distinct, and excels precisely because that person has understood his or her uniqueness and cultivated it intelligently.”  Think of professional sports.  The best athletes are very good at specific things.  The renowned footballer Lionel Messi can only really kick with his left foot, but he is lethal with it.  Alex Ovechkin has a killer one-timer and scores most of his goals from a single spot on the ice.  Babe Ruth could hit a homerun like nobody else.  But each of these athletes had a long list of weaker skills.  They are not well-rounded.  They have distinct strengths that make them great.

With this understanding of strengths, how do team leaders go about building great teams?  They start with focusing on business outcomes rather than tightly controlling everything from cascaded goals to day-to-day process.  They use the example of a young engineer that had difficulty following process, getting along with others and challenging authority.  In his first few jobs he was over-looked for leadership positions because he didn’t fit the mold of what others felt was expected of a “leader”.  He finally got his shot and now leads some of the most innovative and successful organizations on the planet.  His name is Elon Musk.  Anyone that suggests Elon Musk is not a “high potential” is crazy.  But this is exactly what talent processes at his early companies found.  And they were terribly wrong.  Referring to the history of jet fighter design the authors suggest that organizations should “fit the machine to the pilot, not the other way around”.  Recognize the strengths of each team member and let them flourish.

Lie #5 - people need feedback

We have been conditioned to think that people need feedback, and lots of it, in order to self-actualize.  Millennials, we are told, need more than previous generations.  We’ve heard of things like the feedback sandwich, which refers to sandwiching a piece of negative feedback between two pieces of positive feedback.  We’ve heard other models including “5 to 1”, which refers to the suggestion that every piece of negative feedback should be accompanied with five pieces of positive feedback in order maintain employee engagement.  An entire cottage industry has developed around feedback models, how-to guides and books on effective delivery of various types of feedback.  But what does the research say about the impact of feedback in general?  First, feedback is plagued with bias of many types.  The authors explain that humans have a tendency of skewing their explanations of others’ behaviour (particularly negative behaviour) toward stories about who they are.  This is referred to as Fundamental Attribution Error.  There must be something wrong with that person!  Why else would they do what they did?  We have no idea what is going on in others’ minds, what is happening in their homes or with their families.  Concluding for ourselves what must be wrong and basing our feedback to them on our own conclusions is perhaps the most un-human thing we could do as leaders.

What can we learn about feedback from social media platforms?  The authors compare Facebook and Snapchat and suggest that Snapchat users prefer that platform precisely because of the absence of feedback.  There are no likes, angry faces or even comments.  There is only a brief message that then disappears.  Research on millennial use of Snapchat suggests they prefer Snapchat specifically because they can participate in the community without the pressure of feedback. The absence of feedback allowed users to be more at ease and more real.  It was a safer place.

The authors next turn to the famous Hawthorne experiments of the 1920’s.  The Hawthorne effect was named for the increase in productivity of workers when they were being monitored by observers.  At first it was thought that the changes in working conditions were the cause of the increase in productivity (improved lighting, etc.) but when the experiments ended the productivity returned to pre-study levels.  It was not sustained.  Why?  It turns out that it was the fact that leaders were paying attention to their workers that led to the increase in productivity.  So, the key lesson, then, is this: when leaders show interest in their employees they tend to perform better.  The authors cite research that suggests that positive attention is thirty times more powerful than negative attention in creating high performance on a team (and twelve-hundred times more powerful than ignoring people).

For me the take-away is simple: give your team members positive attention.  Don’t focus on feedback per se.  Show a genuine interest in their work.  The research shows this will result in the best possible performance.

Lie #6 - people can reliably rate other people

This is a doozie.  Every organization I have ever worked for has had a broad set of processes that require ratings of people.  Mid-year and year-end performance reviews.  Goal assessment.  360 reviews. Competency assessment.  Skills assessment.  Assessment of potential.  Talent and 9-box reviews.  At the core of all of these processes is an implicit assumption that humans can accurately rate other humans.  But it turns out they can’t!  In the result, the conclusions of every one of these assessments is invalid.  This means that all of the decisions that get made from them are also invalid.  The authors show that performance ratings assessed by team leaders are more reflective of the personality of the rater than the person they have rated.  In one study they demonstrated that “54% of the variation in ratings could be explained by a single factor: the unique personality of the rater”.  This trend was consistent across all types of raters – the boss, peers, subordinates, and others.  They name this effect the idiosyncratic rater effect.  This is essentially another in a long line of human biases.  It has the effect of applying the same pattern of ratings regardless of the individual being rated.  This pattern is unique to each rater.  Ratings reflect what is unique about the rater more than what is unique about the individual being rated.  Further, when we enhance ratings definitions and leverage tools like behaviourally anchored rating scales to attempt to enhance the accuracy of ratings, we actually do the opposite – we magnify the effect of the idiosyncratic rater effect.

The authors delve into what makes for good data.  Reliability.  Variability.  Validity.  Data is valid when it can be used to accurately predict something else.  Think about Amazon’s algorithm and how the clicks from one page can accurately predict clicks on another.  Variability refers to the natural variation or range in the data.  Forced distributions are used to force a non-variable set of data into a target model to achieve a target rate of variation.  By definition this means the data is not variable and therefore not good data.  The authors suggest that for most work, particularly knowledge work, we have no way of knowing what drives performance because we have no reliable way of measuring performance.

So, what does this means for every organization on the planet that has processes where humans are expected to rate other humans?  The authors point out that while humans are not accurate raters of other humans, humans are themselves very accurate raters of their own experience.  Asking someone how they feel right now will be quite accurate.  Asking that same person to rate how another person feels won’t be accurate.  It can’t be accurate because we are not inside the other person’s brain.  The general rule for accurate and reliable data is to ask questions only about an individual’s own experiences.  The authors then propose a method of rating that will provide reliable and accurate data from which to understand performance:

Stop asking about others and start asking about ourselves.

·      Do you always go to this team member when you need extraordinary results?

·      Do you choose to work with this team member as much as you possibly can?

·      Would you promote this person today if you could?

·      Do you think this person has a performance problem that you need to address immediately?

A conclusion the authors draw is that “the key to understanding performance is to stop thinking of it as a broad abstraction, and instead start finding elements of it that we can measure reliably and act on usefully.”

Lie #7 – people have potential

This doesn’t literally mean people don’t have potential.  The point is that everyone has potential, but that their potential is unique.  Linking back to Lie #6, humans cannot accurately rate the potential of others so processes like the famous 9-box talent assessment are flawed because they assume people can accurately rate the potential of others.  It is not true that only people in the upper-right hand box have potential.  Everyone does.  It is the role of the team leader to identify how to best utilize the unique strengths and talents of every member of the team.

So how would a team leader do this?  The authors propose a model of momentum, which consists of massand velocity.  Mass refers to how an employee feels about themselves.  Questions like “what do you love most about your job right now”, “what job do you want next”, “what about that next job do you think you might enjoy”, “what is your perfect job”, and other questions specific to the employee and how they feel.  Velocity refers to how the employee has moved through the world so far, how fast they have progressed, how quickly they learn, etc.  Questions that focus on current performance, past performance, skills, certifications and qualifications, etc.  From these mass and velocity questions we can decipher insights about the employee at work.  Answers to the mass questions refer to the employee’s traits.  “Things that are inherent and enduring in her – not entirely unchanging, but nonetheless resistant to change.”  We can also decipher insights about velocity including things “she has acquired as she’s applied herself in the world to move in a particular direction: her current and past record of performance, and her tested certifications.”  Together these two things combine to form a person’s momentum.  Everyone has momentum, but everyone’s momentum is unique to them – a combination of their own mass and velocity.

Let’s use one of the key engagement questions to compare potential and momentum.  “In my work, I am always challenged to grow”.  “Potential doesn’t do that, it doesn’t challenge you to grow.  It tells you that you either will, or won’t.  Addressing potential makes people feel like they’ve been dealt with.  Addressing their momentum makes them feel understood.”

Lie #8 – work-life balance matters most

This has been a huge topic in management science for a very long time.  Organizations have rolled-out countless programs to try to address the concern that people don’t have an appropriate balance between work and life.  But the authors suggest this is the wrong question to focus on.  Instead, the focus should be on the degree to which the employee loves their work.  If they love their work, the concept of balance fades out of the equation.  As the authors state: “when you are in love, you are simply magnificent.  Look at those adjectives again: productive, creative, generous, resilient, innovative, collaborative, open, powerful.”  These are the qualities we are looking for in our employees.  “That’s the power of love.  With it, you blossom.  You flourish. You look forward to what you’re about to do.”  The data suggests that those who report spending at least 20% of their time on something they love had dramatically lower risk of burnout.  Why don’t we all have a big part of our jobs that we love?  A bit part of the answer to this question, according to the authors, is that our jobs are too constricted, too controlled.  In a large study conducted by the ADP Research Institute researchers found only 16-17% of workers globally said they had a chance to play to their strengths every day.  This is obviously a huge problem.  But how do we address it?

The authors suggest a simple exercise.  Pick a random week in your schedule.  Take a notebook and divide a piece of paper into two columns.  As you progress through your random week, write down the things that bring you joy on one side, and the things that you loath on the other.  Don’t bother with the meh things in the middle that neither bring you joy nor cause you to loath.

·      Things you love: you look forward to them; time speeds up; you’re in a state of flow; afterword you look forward to doing them again

·      Things you loath: you procrastinate; you delegate them to someone else or avoid them altogether; time drags on; you consciously hope to avoid having to ever do them again

Once you have a clear picture of what you love and loath, find ways to do more of what you love and less of what you loath.  Talk to your boss about these lists and find ways to modify your job to focus more of your time and effort on the things you love.  This is the art of focusing on strengths and a key strategy for leaders to bring out the very best in each person.

Lie #9- leadership is a thing

All of the lies to-date have turned sixty-plus years of management science on its head, but this one perhaps takes the cake.  The leadership industry draws billions of dollars of “investment” every year in the form of books, conferences, courses, programs, podcasts, models, self-assessment tools, action planning frameworks and much, much more.  Organizations routinely drop $10,000 or more on week-long programs at places like Harvard, Stanford and Queen’s to try to teach the art of leadership.  But what is leadership?  The models and books would suggest there are dozens or even hundreds of types of leadership, and certain types demand high scores on certain competencies.  But with the knowledge we now have about the difficulty with ratings and the flaws with competency models, what is the point?

The authors distill leadership to its most fundamental construct: “The only determinant of whether anyone is leading is whether anyone else is following.”  So, what makes someone follow someone else?

The authors suggest it is not the well-rounded leader that scores a level three on ten of their twelve leadership competencies that makes others follow.  Instead it is the “spikes” or unique strengths of a particular leader that people follow.  It is Warren Buffet’s genius at finding and buying companies, Churchill’s ability to inspire uncompromising resistance, Steve Jobs’ ability to design beautiful products that people love to use, George Patton’s ability to fight, and JFK’s ability to inspire a bright and morally uplifting future.  Each of these great leaders had a long list of weaknesses and character flaws.  But it is not these things that made them great leaders. It is their few unique strengths and how they leveraged them in the context of the situation they were in that made them great.  And every leader has the ability to bring out the best qualities in each of their team members, helping them to be great in their own right.

The final paragraph in the book is worth quoting in full:

Leading and following are not abstractions.  They are human interactions; human relationships – the currency of emotional bonds, of trust, and of love.  If you, as a leader, forget these things, and yet master everything that theory world tells you matters, you will find yourself alone.  But if you understand who you are, at your core, and hone that understanding into a few special abilities, each of which refracts and magnifies your intent, your essence, and your humanity, then, in the real world, we will see you.

And we will follow.

Appendix

The appendix includes a thorough analysis of a global engagement study conducted by the ADP Research Institute and an in-house study undertaken at Cisco.  I thought I would include a few of the more impactful statements from each as they really bring the points from the book home.

ADPRI Study

Engagement has remained stubbornly constant over time, shifting only 0.3% over three years of the period of the study (16.2% were fully engaged in 2015 vs. 15.9% in 2018)

Workers who say they are on a team are 2.3 times more likely to be fully engaged than those who say they are not

Across the world, the data reveals that it is extremely difficult to engage workers who do not feel part of a team

Of those that strongly agreed that they trusted their team leader 45% were fully engaged.  Of those that didn’t strongly agree only 6% were fully engaged.  A worker is twelve times more likely to be fully engaged if she trusts her team leader

Two questions in the survey showed the strongest relationship to a worker’s feeling of trust in his team leader.  These two conditions are the foundation of trust:

1. Do I know clearly what is expected of me?
2. Do I have the chance to use my strengths every day?

In all countries and industries, virtual workers – so long as these workers are also team workers – are more likely to be fully engaged than those who do their work in an office

Workers with more education and at higher levels of the organization are generally more engaged

Millennials have approximately the same degree of engagement as non-millennials

Cisco Study

More frequent check-ins are associated with increased use of strengths

As workers moved from team to team, company engagement varied the least, whereas the items “In my team, I am surrounded by people that share my values” and “My teammates have my back” varied most

“Me” items (addressing expectations, use of strengths, recognition, and growth challenge) are most sensitive to an individual’s relationship with his or her team leader

Decreasing engagement leads to voluntary attrition

Some forms of attention are better than others in creating engagement

1. Any attention is better than no attention
2. Frequent attention is better than infrequent attention
3. The type of attention a leader gives matters (live discussion has greatest impact regardless of the conversational skill of the leader)

Conclusions

As I said at the outset, this book floored me.  The nine lies and their underlying analysis challenges everything I took as truth with respect to management science and the design of HR programs honed over the last 60+ years.  But upon reflection the conclusions make intuitive sense.  So, what do we do about it?  I intend to take this new knowledge into my own leadership, and also to use this insight to help shape future iterations of HR programs and processes.  Posting this on LinkedIn and sharing it with 2500+ professional acquaintances will help spread the word and maybe inspire others to pick up a copy and read it for themselves.  Maybe a few people will even re-share this and further spread the word.

We won’t turn 60 years of management science on its head with a book or a LinkedIn post.  But we can at least start the conversation.

Jim Finnigan

Calgary, Alberta, Canada