What to Why


“Keen insight into how leaders can build high-performing teams the right way, without wasting time or resources fitting square pegs into round holes.”

Brian Cotton, Global Vice President, Frost & Sullivan WWHHAT YTO

The Fundamental Shift in the Way Leaders Build High-Performing Teams

ClearFit Founder and CEO



Praise for What to Why

What to Why will change how you think about creating a world-class team.”

—Anna Carney

Partner, Innovative HR

“ I would strongly recommend this book for any leader who wants to learn how to create a world-class team. I will be taking it back to my organization immediately.”

—Shirley Porjes, MBA

CFO, Finance and Administration, Western Plastics

“ In 20 minutes What to Why will guide you on trans forming the way you approach your most strategic hires.”

—Allan Kates

COO, BA’s Real Estate Management

What to Why is an insightful read and provides leaders with a complementary solution for finding the right people for their teams in today’s talent marketplace.”

—Peter Gilfillan

Senior Vice President and General Manager, Canada at Monster Worldwide


The Fundamental Shift in the Way Leaders Build High-Performing Teams

ClearFit Founder and CEO





Copyright © 2015 ClearFit Inc.


The Authors

Jamie Schneiderman

Jamie believes job performance depends on people working in roles in which they are built to succeed. He has long been an advocate of creating a world where the right people are in the right jobs, resulting in happier employees and more productive organizations.

He is the Founder and CEO of ClearFit, the leader in people performance insights that allows organizations to easily and consistently select, develop, and promote top talent.

Jamie has spent over 20 years building companies like Procter & Gamble, Coca-Cola, and Rogers, along with several technology start-ups.


Jamie has a Commerce Degree from the University of British Columbia and an MBA from Harvard University.

He currently lives in Toronto, Canada, with his wife and two children.


Donald Cowper

Donald is a best-selling author of several business books who has spent his career using a storytelling approach to help grow organizations. He has written several business advice columns on popular sites such as Inc.com. He currently heads up content at ClearFit.



Why I’m Writing About Why

Page 8

*The Leader Who Went from *

What to Why

Page 12

The Three Steps to Why

Page 49

Key Takeaways

Page 50

Want to Learn More About Why

Page 53


Why I’m Writing

About Why

I (Jamie) am writing this book because I’m hoping my personal experience, and the experiences I’ve had with leaders in a wide variety of industries, can help you build a high-performing team.

Let me tell you how I got here.

Saying No to the Dream

In 2006, I received an offer for the dream job that I had spent the previous dozen years working toward.

I turned it down.

The path to that decision began six months earlier when my daughter was born. Time spent with her was special and 8

made me reflect on my life in a way I hadn’t before. The one area that consumed my thoughts was work.

Since graduating with a degree in business, I had gone on to work in senior roles at major brands. I was following the path that made logical sense. Although I had moments when I was passionate about what I was doing, I often found work frustrating and unfulfilling.

I wondered if there was a better path for me. And so I set off on a journey to discover work that I would both love and excel at.

The “Aha” Moment

I got lots of advice. Most of the people who gave me guidance pointed me in the direction of my past experiences—more of the same.

But somewhere along the way, I met some experts who were discovering new insights around work, happiness, people, and performance. After spending just a short amount of time with them, they were able to show me why I was unhappy with my career. There was a big disconnect between the work I preferred and the work I was actual y 9

doing. These were insights about myself I wished I had known years earlier. This was powerful stuff. It was a light-bulb moment when I realized how many other people must be in the same situation.

I knew that insights like this could radical y improve the way organizations and people came together.

“ I knew that insights like this could radically improve the [*way organizations and people came together.” *]

And so, by the time the offer for my dream job came in, I decided to not go down a path I knew wasn’t a fit for me. Instead, I founded ClearFit to take these new insights to businesses everywhere—and help create a world with happy employees and more productive organizations.

Nine Years Later

It’s been nine years since that decision. While building a business has certainly had its moments, I am definitely in the right job and have been able to be true to myself. In these same nine years, thousands of organizations have begun to use these new insights to improve the happiness 10

of their employees as well as increase the performance of their teams. It has created a shift that I call “WHAT TO


So what exactly do I mean by WHAT TO WHY? This book is a twenty-minute story based on a leader I know that wil answer that question. Although the leader is the head of a sales team, the insights are applicable to any team in any industry.

So, if you are a leader who wants to learn about a new approach to increasing the performance of your team, this book is for you. If you are an individual who is struggling to find your path, as I was nine years ago, I have no doubt you’ll find the insights helpful too.

In the meantime, let’s meet Mario, the leader who went from WHAT TO WHY.


Jamie Schneiderman

Founder & CEO



The Leader

Who Went From

What to Why

“It’s tough to build a high-performing team.”

Mario, the VP of sales at a software company, said those words to me (Jamie) three years ago.

Like so many leaders across the world, Mario believed this was a true statement. And why not? The evidence to support it seems to be all around us. Leaders everywhere struggle to build high-performing teams. Some never manage to create teams that perform at world-class levels. If they do, it has frequently come from a great deal of effort, expense, and time. But for Mario, the most compelling evidence was his own personal story as a leader up till that time—a story similar to ones I’ve heard from countless leaders.


A year earlier, Mario had been a successful director of sales at an international tech company, where he had led several years of 25 percent annual sales growth for his team. That success had caught the attention of the CEO of TLZ, a large software company, where sales in one of their key divisions had been flat for a couple years. The CEO of TLZ

was looking for someone to lead dramatic sales growth in that division and offered Mario the VP Sales position.

The Big Opportunity

Mario saw the move as a career-making opportunity.

He believed in TLZ’s product line and thought that as a senior leader in one of their key divisions with control over building and developing the sales team of 25 reps, he could play a big part in establishing TLZ as a global leader. He also believed that as someone who had studied best practices for building a high-performance team—

particularly a sales team—and who’d implemented many 13

of them, he could deploy the right plan for turning things around at TLZ.

So Mario accepted, and after moving his young family across the country to TLZ’s head office, he quickly got to work rolling out the various strategies of his plan.

Hitting a Pothole

But Mario found it harder than he had expected to turn around TLZ’s sales team. After a year, sales growth was nowhere near his target of 25 percent. The poor results were a blow to Mario’s confidence, and to his job security.

The CEO was obviously disappointed, but was willing to give Mario more time. However, if Mario couldn’t start to improve sales in the next couple quarters, enough to demonstrate that he could hit 25 percent annual growth, he knew he would be looking elsewhere for work. Mario also knew that opportunities would be harder to find with the failure to deliver at TLZ on his record.


A Chance Encounter

Around this time, a mutual friend who had heard me speak on the latest in people performance insights suggested Mario call me for advice.

When Mario and I got together, one of the first things I asked was why he had original y thought he could turn the sales team around. What made him think there was any potential for growth?

A Lopsided Team

As Mario explained, he

thought there was a

huge opportunity at TLZ

because of how lopsided the team was. Five out of the 25

sales reps were responsible for 65 percent of the revenue.

Some sales reps were barely making sales, and the vast majority showed inconsistent or underwhelming results.

Mario knew that this was actual y typical of many sales teams, but it also pointed to the potential for growth: get more sales reps performing like the top five and results would improve.


Mario had just laid out a very simple and effective strategy for dramatical y improving performance and growth in any team. All teams, sales or otherwise, have a range of performance levels—usual y a small number of top performers, followed by a long tail of mid-range performers, and some low performers. Clearly, getting more top performers and more people performing closer to the top level will lift up any team. It’s the right strategy to turning around a team in a relatively short time period.

However, executing it successful y requires that the leader base their plan on a full understanding about what underlies performance at work.

In order to help Mario, I needed to get a clearer picture of what his beliefs on high performance were and where he might have gone wrong. To flush these out, I asked him to tell me about his plan and what his experience had been so far.


The Best Laid Plan

Mario had two essential parts to his plan. One was simply to let some low performers go and replace them by hiring high performers. The other part of his plan was to raise the performance of everyone on the team with a number of initiatives. These ranged from improving processes, like how marketing supported sales, to upgrading or adding things like onboarding and training programs, sales support systems, mentoring, and coaching. Another key initiative was restructuring the team into differentiated sales roles—having some reps specializing in new business and others in account management.

Mario’s plan made perfect sense—bring in high performers, while also creating the structure and systems to develop high potentials into high performers.


Unfortunately, problems began to emerge early on. Some of the new hires that Mario had expected to perform at a high level turned out to be low performers. And while some of the people on his team had shown improved performance from all the training, systems, and process improvements, others hadn’t.

To deal with the hiring challenge, Mario had started to work with various vendors to help attract and recruit more top talent, including passive candidates (top performers who were open to new opportunities but not actively looking), but the problem persisted—some hires didn’t work out, and every new hire that failed was an expensive mistake. As for the strategies to improve the performance of the high potentials, he’d explored dozens of solutions—

new training programs, new systems, and so on. Some seemed to move the needle a little, but he still wasn’t seeing the results he needed.

A Time Problem

Mario was in the process of speaking

with other consultants and services,

but he worried he wouldn’t find the

help he needed, because he had come


to realize that his essential problem was the time it took to find and develop the right people—and nobody could give him more time. Except his CEO, and he was already running short on patience.

As Mario explained to me, one of the mistakes he had made moving to TLZ was taking for granted how many years it took to create the high-performing team he’d had at his past company. Back then, just like every other leader building a team, he had made hiring mistakes, but he had been able to weed them out over time. It had also taken time to find out which high potentials would turn into high performers, because of course, not everyone with potential realizes it. Reflecting back on things, he realized he’d spent years creating what eventual y had become a solid, high-performing team.

Now, Mario was confident in his strategy and all the systems he was implementing, but he knew that to realistical y build a great team at TLZ, he’d need a couple more years—time he didn’t have.


An Information Problem

“You could frame it as a time problem,”

I said, “but you could also see it as an

information problem. And by that I mean

maybe you don’t have all the information

you need about the people you are hiring and training to know whether they are actual y similar to your top performers. You’re waiting to find out how they turn out, but maybe there’s information up front that could tel you which candidates, or which high potentials, real y are like your top performers.”

“We have as thorough a

[*“ Sometimes a time problem *]

hiring process as anyone

*is really an information *

else,” Mario explained,

[*problem.” *]

outlining a process that


included multiple interviews, a well-developed scoring system, reference checking, assessments, and so on. “In fact, compared to some of my peers at other companies, I think we get it right more than they do. The reality is, it can take months and months to discover if somebody is able to deliver like your top reps.”


Sasha: Great on Paper

As an example, Mario told me about

how he had hired three reps at the

same time. One was somebody named

Sasha. Sasha was a high performer if

he’d ever seen one. He had been one

of the top salespeople at a leading

organization. He looked great on paper, interviewed wel , and by the end of the hiring process, everyone on the hiring committee—a lot of smart, experienced people—

agreed he was the strongest by far of the three candidates.

But after a few months on the job, Sasha’s performance was well below the other two. Hiring mistakes like Sasha were frustrating for Mario, but he knew every leader made them.

“Those mistakes are indeed common,” I said, “and for many leaders, it unfortunately takes time to gain critical information about their people. But seeing that your goal is to find more people like your top performers, obviously the information you are able to gain on these people is vital to finding more like them. So, let me ask—what information and data do you collect about your high performers? What tel s you they are your high performers?”

“I look at their results, of course. Their sales numbers.”


“Is that how you identify your top performers—whoever delivers the best results?”

“Actual y, no.” Mario explained that he had learned long ago that revenue alone isn’t a reliable indicator of performance.

The rep who is slacking on the job could be the lucky one who answers a call from a client with a massive order.

Another rep who is always making her cal s and developing great relationships could have a client base in a sector that is struggling. The difference in revenue between two reps can often be a reflection of external factors and luck, and not on performance.

“ The difference in revenue between two salespeople can often be a reflection of external factors and luck, and [*not on performance.” *]

To see who was real y performing wel , Mario tracked as many performance metrics as he could—some related to quantity, like number of cal s and demos; and some related to quality, like how well the sales rep built rapport with their prospects. By analyzing these metrics, Mario could clearly see who on his team was performing at a high level and who was not.


A More Honest Picture

I was impressed that Mario had identified and collected data on the metrics that actual y track performance, rather than just ranking his people according to results. If you want a more honest picture of who your top performers are, it’s important to look past results into key performance metrics. Mario had done a good job here, but it raised a critical question: “How do you use this information to find others who can achieve the same performance numbers as your top people?”

“ If you want a more honest picture of who your top performers are, it’s important to look past results into [*key performance metrics.” *]


Mario thought about that and said, “Wel , I suppose I look for people who have performed well elsewhere.”

Mario explained that when he’s screening resumes or interviewing someone, he’s digging for evidence of high performance or impressive achievements in their past.

“But when you hire people who’ve been top performers elsewhere, they still frequently turn out to be low performers for you—Sasha, for example.”

Mario nodded, saying that’s what makes it so hard to build a high-performing team.

“Your experience is typical, as I’m sure you know,” I said.

“Just because someone performed well somewhere else doesn’t mean they will perform well on your team. In a poll we ran, we discovered that less than half of people who were high performers at their previous jobs turned out to be high performers in their new jobs. And these were 24

people who had the same skil s and experience as the top performers in their new company.”

“ Less than half of people who were high performers at their previous jobs turned out to be high performers [*in their new jobs.” *]

“Those aren’t good odds,” Mario said, adding that they were probably his odds too.

A Critical Truth

“Mario,” I said, “when you told me the story of that rep, Sasha, who eventual y disappointed you, you first referred to him as a ‘high performer.’ You used that label in a sense to define him.”


“That’s what I thought when I was hiring him. But it’s not how I would define him now.”

“Would you describe him as a low performer?” I asked.

“I would have when he was on my team, but I hear he’s joined his wife’s business and is doing a great job there. So obviously, labeling Sasha one way or the other isn’t right.”

“That’s a great insight, Mario. In fact, what you’ve described actual y reveals a critical truth about high performance, which is, high performance is not a permanent quality about a person. Performance depends on the context—to a much greater degree than we would expect. In the workplace, the context is the particular job someone is doing and the company they are doing it for.

Put Sasha in a certain job

and he soars; in another,

[*“ High performance is not *]

even one that appears to

*a permanent quality *

be very similar, he sinks.”

[*about a person.” *]


When we look at people like Sasha and label them as “high performers,” we run the serious risk of not seeing the truth, which is how much the context—the particular job and the company—mattered for Sasha to perform at a high level.


I explained to Mario that

[*“ Performance depends on *]

there’s a psychological

[*the context—to a much *]

term for the mistake we

*greater degree than we *

make, in defining people

[*would expect.” *]

as being high or low


performers, called the “Fundamental Attribution Error.”

We tend to want to explain people by what we see them do, rather than understand how their situation factors in.

Imagine seeing a penguin

for the first time—on

land. You would think

you’re looking at a poorly

designed, awkward “low-

performing” bird. But if you

saw a penguin in water—

zigzagging at high-speed

through a school of fish—you’d think you were watching a creature perfectly designed for excelling underwater.

So, here you have the same creature in two

different contexts, and it’s the context that makes all the difference to its performance.

We’re the same. In some jobs we’re like

penguins on land; in others, we’re

like penguins in water.


“These mistakes about

[*“ In some jobs we’re like *]

how we define people,”

[*penguins on land; in *]

I said to Mario, “can be

[*others, we’re like penguins *]

extremely costly when

[*in water.” *]

it comes to hiring and


training. Essential y what you’ve discovered, by expensive trial and error, is that the information you have about someone’s past performance isn’t enough to tell you whether they’re likely to become a top salesperson for you.

It’s good to know that somebody has proven performance in the past, but on its own, it doesn’t reliably predict performance on your particular team.”

“ Information you have about someone’s past performance isn’t enough to tell you whether they’re [*likely to become a high performer for you.” *]

“So, what other information do I need to know?”


What the Science Says

“Historical data on high performance tel s us that there’s a specific cluster of core attributes that make a person who they are—attributes such as how well they recover from setbacks and their openness to change, to name a couple. Unlike performing wel , these are things about a person that don’t change when they move from one context to another, or one job to another. Studies have shown that without this information, we can’t make reliable predictions about how someone will perform in a new job.”

“ Historical data on high performance tells us that there’s a specific cluster of core attributes that make a person [*who they are.” *]

As I explained to Mario, when we move from one job to another we leave our past performance behind, but we 29

take our core attributes with us.

We take our skil s as wel , but

nowadays for many jobs, skil s

become obsolete very quickly and

we have to constantly learn new

ones. What doesn’t change

is who someone is.

“I actual y pay a lot of

[*“ When we move from one *]

attention to who someone

*job to another we leave *

is,” Mario said, adding that

*our past performance *

he looks for people who are

*behind, but we take our *

driven, likeable, good under

[*core attributes with us.” *]

pressure, strong problem

solvers, and so on.

“I gather you first thought Sasha had all the qualities you look for.”

“When I interviewed him, yes. But obviously not when I got to know him better.”


Psychological Traps

“Your experience with Sasha,” I said, “is a great example of a trap we’re all susceptible to called the halo effect—

our tendency to think someone is good in lots of areas if they’ve impressed us in one area. For example, you might have first noticed how well-spoken Sasha was, and then begun to think he’d be good under the kind of pressure your sales reps are exposed to.”

Mario agreed and said he’d watch out for that trap.

Unfortunately, we can’t real y prevent ourselves from misreading people. It’s how our brains work.

“Many critical attributes are also hidden and not observable during an interview,” I said. “You might have the impression somebody is reliable because they showed up on time and answered questions wel , but what happens 31

when they’re on the job

[*“ Many critical attributes *]

and you need them to

*are also hidden and not *

consistently push day-in

*observable during an *

and day-out to deliver on

[*interview.” *]

your next quarter’s goals?


Maybe this is somebody who is dependable in only certain areas some of the time, and not someone you can count on whenever you need them.”

So one challenge is to somehow get past the limitations of human perception and ensure we get accurate, objective data on who someone is and their core attributes, prior to putting them to work. But perhaps the bigger problem is that we often don’t know what attributes actual y impact performance for the job we’re hiring for. The truth is, most of us guess. And the reality is often surprising, and sometimes counterintuitive. In our research, we have found companies where the top customer service agents have a low interest

[*“ Objective data takes us *]

in helping people, or

*past the limits of human *

organizations that believe

[*perception.” *]

they are all about team


play but their top people are actual y highly independent.


Because Mario had some

assumptions about what attributes

mattered for performance on

his team—like drive and problem

solving—I suggested we collect objective

data about his team by profiling all his reps.

This would allow us to see which attributes were actual y behind the performance of his top people.

Surprising Results

When I got together with Mario, I went through the results.

The data revealed several significant findings. Drive was indeed a critical attribute, with Mario’s top reps showing scores for drive well above the rest of Mario’s reps, and well above the average person. But Mario’s top performers scored quite a bit lower for problem solving than his lower performing reps—indicating that, contrary to what Mario 33

believed, sales performance in his organization did not depend on people who were open and willing to learn and solve challenging problems.

There are certainly some sales roles where problem solving would be critical, but not on Mario’s team. In fact, problem solving might have been vital for the sales roles at Mario’s previous company, which relied on a more consultative approach, where the reps had to have a deep understanding of the customer and their problems before showing how the product could help. The top reps at TLZ

didn’t have to know as much about their prospects, or solve complex customer problems. Instead, the attributes that drove their success were ones that helped them quickly build rapport and demonstrate the benefits of TLZ’s product line.

Another major insight was that every high performer on Mario’s team who was in a new-business sales role scored well above the normal range on their ability to recover from setbacks. And virtual y everyone that wasn’t a top performer had a normal or below normal score for this attribute.


“I’m guessing,” Mario said, “that it’s not realistic of me to expect someone who doesn’t score high for their ability to recover from setbacks to become one of my top new-business reps.”

“The data is telling you that it’s at least very unlikely.”

Mario took a long look at the profile data of his reps and pointed out that nearly all his top reps scored well below normal for their preference for structure while his low performers had normal or even high scores. “I’ve been trying to impose more structure on the team. Maybe I shouldn’t, or at least not for my top people.”

The Power of Why

“What you are looking at,” I said, “is the data on why your reps perform the way they do. So I’ve called it WHY data.

The data you have been collecting on your performance metrics to date is what I term WHAT data. In other words, you’ve been looking at what your reps have been doing—

how many cal s they are making, how many demos, and so on. That’s what they do. Most organizations look at this type of data; and many, like you, Mario, do a great job in this area.”


WHAT data provides only half the picture, because it can’t tell you WHY your top performers are your [*top performers.” *]

WHAT data is extremely valuable, because it can help tell you who your top performers are. But WHAT data provides only half the picture, because it can’t tell you why your top performers are your top performers. And it can’t tell you what to realistical y expect from the people on your team who you might consider high potentials. It’s like using only half our brain.

The Other 50 Percent

In the same way that we need to use both sides of the brain—the rational left hemisphere as well as the intuitive 36

right hemisphere—to perform well in the world, we need the data on _what _ our people do as well as _why _ they do it to know how to create high-performing teams. In a sense, WHAT data provides 50 percent of the information we need to make good decisions about people, and WHY

data provides the other 50 percent.

[* “ WHAT data provides 50% of the information we need to ] [*make good decisions about people; WHY data provides] [*the other 50%.” *]

The Three Steps to Why

Leaders who are using WHY data to build high-performing teams follow three basic steps.

Step One: Understand the Individual

The first step is to look at every individual on your team and understand their core attributes—what makes them tick.

Mario said, “I’d like to know this information, not just for my current team members, but for everyone who wants to join my team.”

“I think that’s a good idea,” I said. “You can certainly start to profile anyone applying to your team.”


Step Two: Understand the Role

The second step is to profile the high performers for each different role on your team to figure out their common core attributes. This will reveal what is actual y driving performance on the job and provide a success profile for each role.

“I have two different sales roles—a new-business role and an account-management role,” Mario said. “I can see by looking at the top performers for each role that there are some critical differences between the attributes driving success for these two roles.”

“Yes,” I said. “Just like no two individuals have the same profile, no two roles are the same.”

Step Three: Compare Individuals to Roles The third step is to compare every individual to the roles on your team to figure out who belongs where, who is likely to succeed, and who to invest in.

“I’d like to move to this third step,” Mario said, “by taking a closer look at some of my reps.”


Aiden: Low Scorer

Mario pointed to the profile of Aiden, a new rep he had hired. Aiden had attractive skil s and experience, but scored well below normal for recovery from setbacks. He currently had a low number of cal s, and Mario was hoping that by training Aiden and providing other support, he would eventual y perform at a much higher level.

“Aiden’s low score,” I said, “tel s us he doesn’t cope well with rejection. Every rejection affects him, so he needs time to recover and likely puts off making the next cal . You could try everything to motivate Aiden—you could train him, give him scripts to follow, and support him with software and systems—but none of those interventions will change who Aiden is.

“The relatively low score for this attribute reveals that Aiden is going to struggle in any role that demands quick recovery from setbacks, such as a role for which he has to call on people who are likely to reject him.” I looked at Mario and 39

added, “I would also guess that Aiden isn’t very happy in his role.”

Mario nodded and told me that he’d been concerned about this, but had hoped he could turn things around for Aiden through training and motivating him.

Charlotte: High Scorer

For comparison, I pointed to Charlotte, one of Mario’s top reps, who scored well above the normal range for recovery from setbacks; in fact, it was the highest score on Mario’s team. Here’s a person who gets rejected and it doesn’t faze her. Charlotte doesn’t care about the nine out of ten people that reject her—she wants to get through those rejections as quickly as possible because she knows she’s getting closer to the one who will say yes.

“Yeah, and Charlotte loves her job. I definitely want more people like her,” Mario said. “But I like Aiden. I want him to succeed, but I can see that he has low scores for almost every single critical attribute.”


“Mario,” I said, “you can’t change who Aiden is. When people have their core attributes profiled ten years apart, their scores are almost identical. But what you can change for Aiden is the context. You might be able to move Aiden into a different type of role on your team, or perhaps on another team at your company where he is more likely to succeed. Or maybe the right job for Aiden is at another organization.”

Because Aiden was currently a new-business rep, I suggested to Mario that we compare the profile of Aiden’s core attributes to the success profile of the account-management role. When we did that, we discovered that Aiden’s profile matched Mario’s high-performing account managers.

Mario said, “I probably would have tried to move Aiden into account management in a few months, which is what I’ve been doing for most reps who don’t succeed in the new-business role. But I can see that I should probably do this now.”


Instant Access

“Mario,” I said, “you’ve been using time as your filter to discover who will succeed. But the WHY data isn’t dependent on time. Because it’s part of who we are, you can access that data anytime. It can reveal information about someone that would otherwise take you months to discover, or that you might never actual y discover because it’s not real y perceptible. By profiling everyone on your team, you can instantly see what roles they are built for. You can also profile every applicant to discover whether or not they possess the same attributes as your top performers.”

“One thing I’ve noticed,” Mario said, “is that whenever I adjust or change our sales strategy, sometimes different people on my team emerge as new top performers. When that happens, I could look at their WHY data and see what’s driving their performance, and then start looking for people who possess these same attributes.”

“ Whenever I adjust or change our strategy, sometimes different people on my team emerge as new top [*performers.” *]


I nodded. “The wonderful [*“ Top performers possess *]

thing about having

*the very information *

top performers is that

*you need to find more of *

they possess the very

[*them.” *]

information you need to


find more of them—you just have to uncover it.”

Critical Decisions

Over the next few weeks, Mario used the WHY data on his reps to make some key decisions. In some cases, he helped low performers whose profiles revealed they weren’t built for any roles on his team find opportunities elsewhere in the organization, where they eventual y thrived. In other cases, he moved low performing reps, like Aiden, into different sales roles for which they had the success attributes.


Mario also began to profile every applicant to get their WHY data, which allowed him to see whether or not they possessed the attributes of his current top performers.

He ended up hiring candidates he never would have considered before, including two people who had almost no prior sales experience. These were people he would have passed over before based on their resumes and their lack of history as high-performing sales reps. Within the next few months, however, these two hires would prove themselves to be among Mario’s top performers.

A Team Transformed

The decisions Mario made for his people—where to put them, who to let go, and who to hire—had a dramatic impact on the performance metrics of his team, and overal results. Within a couple quarters sales improved enough that the CEO let Mario continue rolling out his strategies.


By the end of the year, nine out of twenty-five people were performing at or above the level of his previous top five performers. And the average performance of the rest of the team was close to 20 percent higher than the average prior to incorporating the WHY data. Perhaps most importantly, Mario’s team exceeded the revenue target, delivering an increase of 48 percent over the previous year.

A lot of that growth was driven simply by Mario’s ability to quickly identify and bring on four reps who matched the profiles of his top five reps, and who were able to deliver at the same level. Of course, raising the overall average contributed as wel .

In the following two years, Mario’s team would continue to exceed the 25 percent revenue growth objective.


By the way, Aiden, the salesperson who had struggled as a new-business rep, became one of Mario’s top account managers. A proof point that Aiden is not a “high performer”

or a “low performer”—we can’t define Aiden this way, but we can say Aiden is someone who performs well in the roles for which he is built. Mario was also thrilled to inform me that Aiden was happy in this new role—not surprising, considering that high performance and happiness have a tendency to go together.

Happiness at work also goes [*“ High performance and *]

together with longevity

*happiness have a tendency *

in the role. And on top of

[*to go together.” *]

improved performance,


Mario can also point to

[*“ Happiness at work goes *]

significantly reduced

*together with longevity in *

turnover for his team.

[*the role.” *]



Completing the Picture

When all we have is WHAT data, we tend to make the mistake of defining people by what they’ve done or what we see them do; we’ll label them “high performer” or “low performer.” And when we do that, we miss the truth about who they are. The WHY data completes the picture of somebody. It reveals the conditions they need to perform at their highest level, providing us with the information on how to best set them up for success.

[*“ The WHY data completes the picture of somebody. *]

It reveals the conditions they need to perform at their [*highest level.” *]

Like many leaders who have now begun to look at the WHY data of their people and job applicants, not just their WHAT data, Mario has discovered

that high performers are actual y more

abundant than he previously believed,

and easier to develop. The hurdle

many of us have to overcome is

our tendency to believe

that high performance

is transferable. What is

transferable is the person


“ The hurdle many of us have to overcome is our tendency [*to believe that high performance is transferable.” *]

and how they are built. Even when people have the right skil s and experience, when they work in roles where the success profile isn’t a fit for who they are, they often perform at subpar levels. When they work in roles that suit their core attributes, they frequently perform at the highest levels.

Embrace the Power of WHY

I hope that after reading Mario’s story, I have inspired you to explore the power of WHY data. I have seen the number of leaders embracing WHY data grow from almost nothing to thousands. I believe that in the coming decades those thousands will turn into millions, and the world will be a better place for it—with happier employees and more productive organizations.



The Three

Steps to Why

To use WHY data to build your own high-performing organization, follow these three steps:

Step One: Understand the Individual

Take a look at every person in your organization and everyone who wants to join your organization and understand their core attributes—what makes them tick.

Step Two: Understand the Role

For every role in your organization, look at the top performers and figure out the common core attributes—

what is actual y driving their success.

Step Three: Compare Individuals to Roles Compare every individual to the roles in your organization to figure out who belongs where, who is likely to succeed, and who to invest in.


Key Takeaways

uuPast performance is not a permanent quality about a person, which is why it’s not a reliable indicator of future performance.

Òu General y, only half of people who were high performers at their previous job will turn out to be high performers in their new job.

uuPerformance depends on the context—to a much greater degree than we would expect.

uuWe each possess core attributes that make us who we are, and that don’t change when we move from one job to another.

uuObjective data on who someone is takes us past the limits of human perception.

uuWHAT data is the visible data about someone, such as: ÒuResults

Òu Skills

ÒuPerformance Metrics



Òu360 Feedback


uuWHY data is objective data on someone’s core attributes that reveals why they perform at the level they do on the job.

uuThe challenge of building a high-performing team is often framed as a time problem, because it can take months, sometimes years, to discover which new hires and which trainees will perform like your top people.

But another way to frame the problem is to see it as an information challenge, and to solve it by uncovering information up front that tel s you which candidates and which high potentials possess the attributes of your top performers.

uuWHAT data provides 50 percent of the information we need to make good decisions about people; WHY data provides the other 50 percent.

uuBy profiling the WHY data of all your candidates and team members, you can instantly see which roles they are built for.

uuTop performers possess the very information you need to find more of them.


uuWHY data completes the picture of somebody. It reveals the conditions they need to perform at their highest level.

  • *



Want to Learn

More About Why?

uuDiscover your own personal WHY insights

uuLearn how to discover the WHY insights for your team

uuShare your thoughts on the book


About ClearFit

ClearFit, the leader in people performance insights, makes it easier for leaders to consistently hire and develop top people.

ClearFit helps leaders go beyond the data they collect on the performance and activity of their top people, by providing a new form of data—insights into _why _ your top-performing employees are succeeding, and your underperforming employees are struggling.

ClearFit shows you how to apply these crucial insights so you can drive results to new levels. This is the data the top leaders in the country are now using to gain an edge.


Document Outline

  • The Authors
  • Contents
  • Why I’m Writing About Why
  • The Leader Who Went From What to Why
  • The Three Steps to Why
  • Key Takeaways
  • Want to Learn More About Why?
  • About ClearFit

What to Why

The 20-minute book for leaders who want to discover the new insights driving today’s top performing teams. “What to Why” shows you WHY your best people outperform. WHY data is a new type of data and thousands of business leaders have begun to use it to build world-class teams—teams with little turnover, markedly happier employees and more members performing at the top level. If you are a leader who wants to learn about this new approach, this book is for you. "Keen insight into how leaders can build high-performing teams the right way, without wasting time or resources fitting square pegs into round holes." —Brian Cotton, Global Vice President, Frost & Sullivan

  • Author: Sydney Finn
  • Published: 2015-10-14 20:35:10
  • Words: 7275
What to Why What to Why