“You have an extremely productive employee who consistently fouls up the paperwork. How would you work with this person to help him/her be more productive?”
Great managers would find out why this employee is fouling up the paperwork. Perhaps she is new to the role; perhaps she could benefit from some training. But if they find out that the problem is lack of talent for paperwork, they will work to find a solution that enables the employee to manage around her weakness for administration and focus on her productivity instead.
“You have two managers. One has the best talent for management you have ever seen. The other is mediocre. There are two openings available: the first is a high-performing territory; the second is a territory that is struggling. Neither territory has yet reached its potential. Where would you recommend the excellent manager be placed? Why?”
Great managers would always place the most talented manager in the higher-performing territory. The key phrase in the question is “neither territory has yet reached its potential.” Great managers use excellence as their measure. They know that only the talented manager working in the higher-performing territory has a chance to help that territory reach its true potential. Taking that territory to excellence is just as much of a challenge for the talented manager as is moving the struggling territory up above average. Furthermore, the former is much more fun and much more productive. With the talented manager positioned in the higher-performing territory, great managers say they would then remove the poor manager and select a talented turnaround expert to fix the lower-performing territory.
To those who would do the opposite, great managers offer this cautionary word: Your less talented manager will never make the most of the higher-performing territory, and the lower-performing territory may well defeat your talented manager. In this case, with the best of intentions, you have set up two people to fail and halved your productivity.
Appendix C: A Selection of Talents
“Which talents are found most frequently across all roles?”
During our research Gallup has had the opportunity to study excellence in hundreds of distinct roles. The talents needed to excel in these roles vary greatly. But in response to requests from managers, we list here the most commonly found talents with a short definition of each. You can use these definitions to guide your thinking as you decide which talents you should be selecting for.
Striving Talents
Achiever: A drive that is internal, constant, and self-imposed
Kinesthetic: A need to expend physical energy
Stamina: Capacity for physical endurance
Competition: A need to gauge your success comparatively
Desire: A need to claim significance through independence, excellence, risk, and recognition
Competence: A need for expertise or mastery
Belief: A need to orient your life around certain prevailing values
Mission: A drive to put your beliefs into action
Service: A drive to be of service to others
Ethics: A clear understanding of right and wrong that guides your actions
Vision: A drive to paint value-based word pictures about the future
Thinking Talents
Focus: An ability to set goals and to use them every day to guide actions
Discipline: A need to impose structure onto life and work
Arranger: An ability to orchestrate
Work Orientation: A need to mentally rehearse and review
Gestalt: A need to see order and accuracy
Responsibility: A need to assume personal accountability for your work
Concept: An ability to develop a framework by which to make sense of things
Performance Orientation: A need to be objective and to measure performance
Strategic Thinking: An ability to play out alternative scenarios in the future
Business Thinking: The financial application of the strategic thinking talent
Problem Solving: An ability to think things through with incomplete data
Formulation: An ability to find coherent patterns within incoherent data sets
Numerical: An affinity for numbers
Creativity: An ability to break existing configurations in favor of more effective/appealing ones
Relating Talents
Woo: A need to gain the approval of others
Empathy: An ability to identify the feelings and perspectives of others
Relator: A need to build bonds that last
Multirelator: An ability to build an extensive network of acquaintances
Interpersonal: An ability to purposely capitalize upon relationships
Individualized Perception: An awareness of and attentiveness to individual differences
Developer: A need to invest in others and to derive satisfaction in so doing
Stimulator: An ability to create enthusiasm and drama
Team: A need to build feelings of mutual support
Positivity: A need to look on the bright side
Persuasion: An ability to persuade others logically
Command: An ability to take charge
Activator: An impatience to move others to action
Courage: An ability to use emotion to overcome resistance
Appendix D: Finding the Twelve Questions
“How did Gallup find the twelve questions?”
We began with focus groups. Each focus group included employees from each company’s most productive departments. An occupational psychologist from Gallup conducted the groups, asking open-ended questions about the workplace. Each focus group was tape-recorded. Over the last twenty-five years Gallup has conducted thousands of such focus groups.
From these focus groups we developed lengthy surveys, including questions on all aspects of the employees’ work experiences. These surveys were administered to over one million employees. After each study we performed analyses to identify the factors within the data.
Five factors consistently emerged:
Work Environment/Procedures. This factor addressed issues relating to the physical work environment — issues such as safety, cleanliness, pay, benefits, and policies.
Immediate Supervisor. This factor addressed issues relating to the behavior of the employees’ immediate supervisor — issues such as selection, recognition, development, trust, understanding, and discipline.
Team/Co-workers. This factor addressed issues relating to the employees’ perceptions of team members — issues such as cooperation, shared goals, communication, and trust.
Overall Company/Senior Management. This factor addressed issues relating to company initiatives and leaders — issues such as the employees’ faith in the company’s mission and strategy or in the competence of the leaders themselves.
Individual Commitment/Service Intention. This factor addressed issues relating to the employees’ sense of their own commitment to the company and to the customers — issues such as the employees’ pride in the company, likelihood to recommend the company to friends as a place to work, likelihood to stay with the company for their whole career, and desire to provide excellent service to customers.
Although other subfactors were found — subfactors like “communication” or “development” — these five major factors explain virtually all of the variance in the data. And of the five major factors, by far the most powerful is the immediate supervisor factor. It explains a disproportionately large percentage of the variance in the data.
Following this factor analysis, we performed various regression analyses on the data to identify some of the most powerful questions within the data set. During these analyses three dependent variables were used: rating of overall satisfaction; the five best questions from the individual commitment factor; and the performance outcomes of the business units.
Before
selecting the final list of twelve questions, we added a final criterion: The questions had to be simple and easy to affect. They had to be “actionable” questions, not emotional outcome questions like “Overall how satisfied are you with your work environment?” or “Are you proud to be working for your company?”
Having identified the twelve most powerful questions, we then subjected them to rigorous confirmatory analyses. The meta-analysis presented in the book was one such study. In the next section we will describe it in detail.
Appendix E: The Meta-Analysis
“What are the details of the meta-analysis?”
An excerpt from “A Meta-analysis and Utility Analysis of the Relationship between Core Employee Opinions and Business Outcomes”
Prepared by:
James K. Harter, Ph.D.
Ame Creglow, M.S.
Background to the Core Items
Over the course of the last 25 years, Gallup researchers have qualitatively and quantitatively assessed the most salient employee perceptions of management practices. In addition to designing customized surveys for nearly every organization with which Gallup works, Gallup researchers have sought to define a core set of statements that measure important perceptions across a wide spectrum of organizations. They have also tried to do so in a way that is not overly complicated or cumbersome for business professionals who are already deluged with other business-related responsibilities.
Researchers with the Gallup Organization have conducted thousands of qualitative focus groups across a wide variety of industries. The methodology underlying this research has been centered on the study of success. The Gallup Organization has studied productive work groups and productive individuals for more than 25 years. In developing measures of employee perceptions, researchers have focused on the consistently important human resource issues on which managers can develop specific action plans. The 13 Core statements evolved from a number of qualitative and quantitative studies. The quantitative data have been combined in the current meta-analysis. The 13 Core statements are as follows:
Overall Satisfaction — On a five-point scale, where “5” is extremely satisfied and “1” is extremely dissatisfied, how satisfied are you with (Name of Company) as a place to work?
I know what is expected of me at work.
I have the materials and equipment I need to do my work right.
At work, I have the opportunity to do what I do best every day.
In the last seven days, I have received recognition or praise for doing good work.
My supervisor, or someone at work, seems to care about me as a person.
There is someone at work who encourages my development.
At work, my opinions seem to count.
The mission/purpose of my company makes me feel my job is important.
My associates (fellow employees) are committed to doing quality work.
I have a best friend at work.
In the last six months, someone at work has talked to me about my progress.
This last year, I have had opportunities at work to learn and grow.
Meta-analysis
A meta-analysis is a statistical integration of data accumulated across many different studies. As such, it provides uniquely powerful information, because it controls for measurement and sampling errors and other idiosyncrasies that distort the results of individual studies. A meta-analysis eliminates biases and provides an estimate of true validity or true relationship between two or more variables. Statistics typically calculated during meta-analyses also allow the researcher to explore the presence, or lack thereof, of moderators of relationships. More than 1,000 meta-analyses have been conducted in the psychological, educational, behavioral, medical, and personnel selection fields. The research literature in the behavioral and social sciences includes a multitude of individual studies with apparently conflicting conclusions. Meta-analysis, however, allows the researcher to estimate the mean relationship between variables and make corrections for artifactual sources of variation in findings across studies. It provides a method by which researchers can ascertain whether validities and relationships generalize across various situations (e.g., across firms or geographical locations).
This paper will not provide a full review of meta-analysis. Rather, the authors encourage readers to consult the following sources for both background information and detailed descriptions of the more recent meta-analytic methods: Schmidt (1992); Hunter and Schmidt (1990); Lipsey and Wilson (1993); Bangert-Drowns (1986); and Schmidt, Hunter, Pearlman, and Rothstein-Hirsh (1985).
Hypothesis and Study Characteristics
The hypotheses examined for this meta-analysis were as follows:
Employee perceptions of quality of management practices measured by the 13 Core items are related to business unit outcomes (i.e., units with higher scores on these items have, in general, more favorable business outcomes).
The validity of employee perceptions of quality of management practices measured by the 13 Core items generalizes across the organizations studied.
A total of twenty-eight (28) studies are included in Gallup’s database — studies conducted as proprietary research for various organizations. In each study, one or more of the Core items were used, and data were aggregated at the business unit level and correlated with aggregate performance measures:
customer satisfaction/loyalty
profitability
productivity
turnover
That is, in these analyses the unit of analysis was the business unit, not the individual employee.
Pearson correlations were calculated, estimating the relationship of business unit average measures of employee perceptions to each of these four general business outcomes. Correlations were calculated across business units within each company, and these correlation coefficients were entered into a database for each of the 13 items. The researchers then calculated mean validities, standard deviations of validities, and validity generalization statistics for each item for each of the four business unit outcome measures.
Here is a summary of the studies composing this meta-analytic study.
There were eighteen (18) studies that examined the relationship between business unit employee perceptions and customer perceptions. Customer perceptions included customer satisfaction scores, patient satisfaction scores, student ratings of teachers, and quality ratings by those posing as customers (mystery shoppers). Customer instruments varied from study to study. The general index of customer satisfaction/loyalty was an average score of the items included in each measure.
Profitability measures were available for fourteen (14) studies. Definition of profitability typically was a percentage profit of revenue (sales). In several companies, the researchers used, as the best measure of profit, a difference score from the prior year or a difference from a budgeted amount, because it represented a more accurate measure of each unit’s relative performance. As such, a control for opportunity was used when profitability figures were deemed less comparable from one unit to the next. For example, a difference variable involved dividing profit by revenue for a business unit and then subtracting a budgeted percentage from this percentage. In every case, profitability variables were measures of margin, and productivity variables were measures of amount produced.
Fifteen (15) studies included measures of productivity. Measures of business unit productivity consisted of either revenue figures, revenue-per-person figures, revenue per patient, or a managerial evaluation which was based on all available productivity measures and management judgment as to which business units were most productive. In many cases, this was a dichotomous variable (top performing business units = 2, less successful units = 1).
Turnover data were available for fifteen (15) studies. These studies consisted of the annualized percentage of employee turnover for
each business unit.
The overall study involved 105,680 individual employee responses to surveys and 2,528 business units, an average of 42 employees per business unit and 90 business units per company.
Here is a summary of studies (per company) sorted by industry and type of business unit.
Twenty-eight percent of all business units in this meta-analysis were from financial organizations, 21 percent were from healthcare business units, and 18 percent were from restaurants. The remaining industries included in the meta-analysis were entertainment, grocery, research, telecommunications/publishing, medical sales, electronics, hospitality, government, and education.
Thirty-one percent of all business units were retail operations and 28 percent were financial organizations; 21 percent were healthcare units, 9 percent were education units, and 11 percent were other businesses.
There is considerable variation among companies in the extent to which employee perception data and business performance data can be aggregated at enough levels to provide comparable analyses. Retail businesses and financial organizations provide numerous opportunities for this type of analysis, as they typically include a large number of business units that use similar measures.
Meta-analytic Methods Used
Analyses included weighted average estimates of true validity, estimates of standard deviation of validities, and corrections made for sampling error and measurement error in the dependent variables for these validities. The most basic form of meta-analysis corrects variance estimates only for sampling error. Other corrections recommended by Hunter and Schmidt (1990) include correction for measurement artifacts, such as range restriction and measurement error in the performance variables gathered. The definitions of the above procedures are provided in the sections that follow.
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