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After reading some of the posts on this blog, it would be reasonable to conclude that I am presenting a sort of naïve idealism regarding the nature of people.
I am not an idealist. Instead, I am a realist. The response when initiating a cultural transformation can be broken into three parts.
The first are those who enthusiastically embrace the change you wish to see, adopting whatever individual changes are necessary for making that transformation a reality. Although they are the true believers, they are also few in number, and are never enough to initiate any lasting change.
The majority will not embrace your vision, at least not initially. They won’t tell you this. Publically, they’ll support your new initiative, often maintaining the façade through a few tasks and exercises. Privately, they’ll express their skepticism (or cynicism) through a few eye-rolls, all while demurring to their coworkers. For these, “cultural change” is just the most recent fad.
And then there are the remaining few who will seek to destroy your efforts from the beginning. These are your opponents for winning the hearts and minds of the skeptical majority.
How do you win the skeptical majority? By expanding the few in your corner until they are the majority, thus isolating the few that are not in your corner.
To put it another way, by understanding the normal curve in your organizational culture, and working towards skewing it.
A multitude of data points
People fascinate me.
I observe, study, compare, contrast, group, and categorize them, all before de-categorizing them and starting over (because I prefer to see people for who they are, and not what I think they are). I do this while conversing with them – it’s a background process, always running in my brain.
My primary reason? Qualitative data, for the purpose of helping those I serve. I collect a mountain of data from many single-subject observations (whether individuals or single groups). Some of this data proves quite useful, and if there is one thing I have learned from this background process, it is that we often don’t see the full range of themes and tendencies (the variables) driving both individuals and groups.
This also means we don’t see the distribution.
A normal curve (also called normal distribution, or bell curve) is nothing more than the most likely distribution of a single variable across a given group. The easiest example is I.Q. Within a group of people, there are a few who are brilliant, a few who are challenged, and a majority best described as “meh” (the hump in the curve). Normal curves are found across many characteristics: height, weight, operational ability, and so on. They are also found in group characteristics, such as technical expertise and turnover rates.
Some of these variables are interdependent, contributing to the distribution of each other. For example, if the people in your organization rate low in the personality trait of agreeableness (a Big 5 personality trait), then the curve representing employee turnover is likely going to skew towards a high rate of turnover. This skewing highlights an important point: if you are not seeing a normal distribution in your organization for any given variable, then this likely means there is an outside pressure skewing that curve. We’ll come back to this point in a moment.
A normal curve is not an objective fact in itself. Let’s say I’m selecting employees to form a recreational softball team, and I know everyone’s batting average. It would make sense to select those with the highest batting averages for my team. Yet, if I think this is a good indication of talent, I would be mistaken: the mean batting average for my team may not be as good as opposing teams.
Alternatively, if the mean batting averages between both teams are the same, but I discover that the opposing team obtained their averages playing fast-pitch softball (versus my slow-pitch softball team), I’ll quickly discover we can’t compete, even though the team batting averages are the same.
Unlike sports, organizations often don’t have clearly defined comparisons. This means we often accept the batting averages of our employees as normal, all while believing that our competitors are experiencing the same (everyone plays slow-pitch softball). This failure leads to mediocrity, until either a new-hire demonstrates a new “normal” (they played fast-pitch), or a competitor resets the bar for “normal” (a team of fast-pitch players), often followed a loss before you hit the showers.
How do we mitigate this? By looking at the outliers, those few at the tail ends of your curve who buck the averages. Truth and enlightenment are often found in the outliers.
Let’s continue with the softball analogy. While my team is getting its butt kicked, I notice one member of my team getting hits. If I dismiss this outlier as someone who possesses natural talent (which may be true), I miss the possibility of discovering that my hitter took some lessons on fast-pitch softball before we began the season (which requires knowing your players). Discovering this allows for the possibility of asking my player to provide tips to the rest of my team so we can avoid the next shellacking.
Applying this concept to your organization yields a multitude of questions:
- Which leaders garner more loyalty and productivity than the mean?
- Which leaders do others turn to when faced with a difficult situation?
- Which employees consistently turn in a higher level of performance over a consistently longer period of time (while still maintaining their health)?
- Who is currently bucking the trend in our organization, demonstrating a higher level of proficiency than the mean within your organization?
Who are your outliers and what makes them different?
These outliers are often motivated by something more than the usual concerns of others. They rise above the fray of the moment, providing a calm voice in any conflict. They demonstrate a sanguinity in the heat of daily tasks. They are the glue that holds your organization together, the go-to people when times are tough, and the problem-solvers when faced with difficulty.
And they exist within every organization, including yours. They are easy to identify if you are utilizing the ethnographers in your organization. Identifying these outliers is your first step.
But it’s not the only step. The next step is to understand the exceptional people at the other tail of your organizational curve. Failure to do so will result in the death of your organization, no matter how many all-stars you have.
The tale of two tails
Just as everyone knows the all-stars are in your organization, everyone knows who can’t be trusted, not just in performance, but as a person. These people are the other tail in your curve.
They are the kind of people every HR staff is terrified to hire. They are a small minority, a standard deviation away from the mean in the opposite direction of those you want. Synonymous with a normal curve, these people number somewhere between 10-15 percent of the total population (meaning you have a good chance of hiring at least one at some point). Just as I have yet to discover an organization without at least one all-star, I also have yet to discover an organization without at least one of these malevolent individuals.
There are a multitude of reasons for their behavior, along with a multitude of characteristics and identifying traits, ranging anywhere from personality disorders, to an obtuse lack of self-awareness, to hidden agendas, to something else entirely. The reasons are not relevant: what is relevant is that this group of people will never align themselves with any proposed change (an unwillingness extending to many aspects of their lives).
The only constant is their sabotage: they don’t play well with others because they don’t play well with anyone.
Many organizations make the mistake of hunting and shooting these individuals. The problem with this approach is the death of innocents caught in the crossfire: you can’t shoot the fox in the henhouse without hitting a few chickens. The remaining witnesses (of whom many can’t tell the difference between a fox and a hen) become afraid, wondering if they will be shot next. Many organizations develop a culture of fear and paranoia specifically through fox hunting.
So, if you can’t shoot them, how do you get rid of these malevolent individuals?
Simple: by improving the quality of the
How do you improve the quality of the organization? Through the help of the exceptional people you previously identified in the first step. The exceptional become the focus of your time and talents, enlisted to share their talents and traits with the majority of your group. By adding their unique voices and behaviors, you make multiple appeals to the larger group (especially when that group sees who gets rewarded for what).
Together, you prove your sincerity in transforming the culture to the benefit of everyone. You don’t need to coerce anyone: each will begin to see the tangible benefits for themselves, voluntarily joining in those efforts. Those tangible benefits are unavoidable: a “we” is always more productive and healthier than a “me”.
In time, all that will be left are the ten percent, a group which will stand out like an eye sore to everyone. You won’t have to identify them, as they will identify themselves through further ostracization from the whole. Don’t be surprised when many of the foxes leave on their own accord. The rest will eventually self-destruct, doing something that makes their removal relatively easy.
How do you get rid of the cancer in your organization? How do you prevent the cancer from returning? Both answers are the same: through better organizational health.
That’s not idealism. It’s realism.