The Relationship Between Engagement at Work and Organizational Outcomes

Introduction

In the 1930s, George Gallup began a worldwide study of human needs and satisfactions. He pioneered the development of scientific sampling processes to measure public opinion. In addition to his polling work, Dr. Gallup completed landmark research on wellbeing, studying the factors common among people who lived to be 95 and older (Gallup & Hill, 1959). Over the next several decades, Dr. Gallup and his colleagues conducted numerous polls throughout the world, covering many aspects of people’s lives. His early world polls dealt with topics such as family, religion, politics, personal happiness, economics, health, education, safety and attitudes toward work. In the 1970s, Dr. Gallup reported that less than half of those employed in North America were highly satisfied with their work (Gallup, 1976). Work satisfaction was even lower in Western Europe, Latin America, Africa and the Far East.

Satisfaction at work has become a widespread focus for researchers. In addition to Dr. Gallup’s early work, the topic of job satisfaction has become one of the most commonly studied job attitudes (Judge, Zhang, & Glerum, 2020).

Because most people spend a high percentage of their waking hours at work, studies of the workplace are of great interest to psychologists, sociologists, economists, anthropologists and physiologists. The process of managing and improving the workplace is crucial and presents great challenges to nearly every organization. So, it is vital that the instruments used to create change do, in fact, measure workplace dynamics that predict key outcomes — outcomes that a variety of organizational leaders would consider important. After all, organizational leaders are in the best position to create interest in and momentum for job satisfaction research.

Parallel to Dr. Gallup’s early polling work, Don Clifton, a psychologist and professor at the University of Nebraska, began studying the causes of success in education and business. Dr. Clifton founded Selection Research, Inc. (SRI) in 1969. While most psychologists were busy studying dysfunction and the cause of disease, Dr. Clifton and his colleagues focused their careers on the science of strengths-based psychology, the study of what makes people flourish.

Their early discoveries led to hundreds of research studies focused on successful individuals and teams across a broad spectrum of industries and job types. In particular, research on successful learning and workplace environments led to numerous studies of successful teachers and managers. This work included extensive research on individual differences and the environments that best facilitate success. Early in their studies, the researchers discovered that simply measuring employees’ satisfaction was insufficient to create sustainable change. Satisfaction needed to be specified in terms of its most important elements, and it needed to be measured and reported in a way that could be used by the people who could take action and create change.

Further research revealed that change happens most efficiently at a local level — at the level of the frontline, manager-led team. For executives, frontline teams are their direct reports, and for plant managers, frontline teams are the people they manage each day. Studying great managers, Gallup scientists learned that optimal decision-making happens when information regarding decisions is collected at a local level, close to the everyday action.

Dr. Clifton’s work merged with Dr. Gallup’s work in 1988, when Gallup and SRI combined, enabling the blending of progressive management science with top survey and polling science. Dr. Gallup and Dr. Clifton spent much of their lives studying people’s opinions, attitudes, talents and behaviors. To do this, they wrote questions, recorded the responses and studied which questions elicited differential responses and related to meaningful outcomes. In the case of survey research, some questions are unbiased and elicit meaningful opinions, while others do not. In the case of management research, some questions elicit responses that predict future performance, while others do not.

Developing the right questions is an iterative process in which scientists write questions and conduct analysis. The research and questions are refined and rephrased. Additional analysis is conducted. The questions are refined and rephrased again. And the process is repeated. Gallup has followed the iterative process in devising the survey tool that is the subject of this report, Gallup’s Q¹² instrument, which is designed to measure employee engagement conditions.

The next section provides an overview of the many decades of research that have gone into the development and validation of Gallup’s Q¹² employee engagement instrument. Following this overview, we present a meta-analysis of 736 research studies, exploring the relationship between employee engagement and performance across 347 organizations and 183,806 business/work units that include 3,354,784 employees.

Beginning in the 1950s, Dr. Clifton started studying work and learning environments to determine the factors that contribute positively to those environments and that enable people to capitalize on their unique talents. It was through this early work that Dr. Clifton began using science and the study of strengths to research individuals’ frames of reference and attitudes.

From the 1950s to the 1970s, Dr. Clifton continued his research of students, counselors, managers, teachers and employees. He used various rating scales and interview techniques to study individual differences, analyzing questions and factors that explain dissimilarities in people. The concepts he studied included “focusing on strengths versus weaknesses,” “relationships,” “personnel support,” “friendships” and “learning.” Various questions were written and tested, including many early versions of the Q¹² items. Ongoing feedback techniques were first developed with the intent of asking questions, collecting data and encouraging ongoing discussion of the results to provide feedback and potential improvement — a measurement-based feedback process. To learn causes of employee turnover, exit interviews were conducted with employees who left organizations. A common reason for leaving an organization focused on the quality of the manager.

In the 1980s, Gallup scientists continued the iterative process by studying highperforming individuals and teams. Studies involved assessments of individual talents and workplace attitudes. As a starting point for questionnaire design, numerous qualitative analyses were conducted, including interviews and focus groups. Gallup researchers asked topperforming individuals or teams to describe their work environments and their thoughts, feelings and behaviors related to success.

The researchers used qualitative data to generate hypotheses and insights into the distinguishing factors leading to success. From these hypotheses, they wrote and tested questions. They also conducted numerous quantitative studies throughout the 1980s, including exit interviews, to continue to learn causes of employee turnover. Qualitative analyses such as focus groups and interviews formed the basis for lengthy and comprehensive employee surveys, called “Organizational Development Audits” or “Managing Attitudes for Excellence” surveys. Many of these surveys included 100 to 200 items. Quantitative analyses included factor analyses to assess the dimensionality of the survey data; regression analyses to identify uniqueness and redundancies in the data; and criterion-related validity analyses to identify questions that correlate with meaningful outcomes such as overall satisfaction, commitment and productivity. The scientists developed feedback protocols to facilitate the feedback of survey results to managers and employees. Such protocols and their use in practice helped researchers learn which items were most useful in creating dialogue and stimulating change.

One outgrowth of a management research practice that was focused on talent and environment was the theory of talent maximization in an organization:

Per-Person Productivity = Talent x (Relationship + Right Expectation + Recognition/Reward)

These concepts would later become embedded in the foundational elements of the Q¹².

Over time, SRI and Gallup researchers conducted numerous studies of manager success patterns that focused on the talents of the manager and the environments that best facilitated success. By integrating knowledge of managerial talent with survey data on employee attitudes, scientists had a unique perspective on what it takes to build a successful workplace environment. Themes such as “individualized perception,” “performance orientation,” “mission,” “recognition,” “learning and growing,” “expectations” and “the right fit” continued to emerge. In addition to studies of management, researchers conducted numerous studies with successful teachers, students and learning environments.

In the 1990s, the iterative process continued. During this time, Gallup researchers developed the first version of the Q¹² (“The Gallup Workplace Audit” or GWA) in an effort to efficiently capture the most important workplace attitudes. Qualitative and quantitative analyses continued. In that decade, more than 1,000 focus groups were conducted and hundreds of instruments were developed, many of them with several additional items. Scientists also continued to use exit interviews; these revealed the importance of the manager in retaining employees. Studies of the Q¹² and other survey items were conducted in various countries throughout the world, including the United States, Canada, Mexico, Great Britain, Japan and Germany. Gallup researchers obtained international crosscultural feedback on Gallup’s core items, which provided context on the applicability of the items across different cultures. Various scale types were also tested, including variations of 5-point and dichotomous response options.

Quantitative analyses of survey data included descriptive statistics, factor analyses, discriminant analyses, criterion-related validity analyses, reliability analyses, regression analyses and other correlational analyses. Gallup scientists continued to study the core concepts that differentiated successful from less successful work units and the expressions that best captured those concepts. In 1997, the criterion-related studies were combined into a meta-analysis to study the relationship of employee satisfaction and engagement (as measured by the Q¹²) to business/work unit profitability, productivity, employee retention and customer satisfaction/loyalty across 1,135 business/work units (first edition; Harter & Creglow, 1997). Meta-analysis also enabled researchers to study the generalizability of the relationship between engagement and outcomes. Results of this confirmatory analysis revealed substantial criterion-related validity for each of the Q¹² items.

As criterion-related validity studies are ongoing, the meta-analysis was updated in 1998 (second edition; Harter & Creglow, 1998) and included 2,528 business/work units; in 2000 (third edition; Harter & Schmidt, 2000), when it included 7,939 business/work units; in 2002 (fourth edition; Harter & Schmidt, 2002), when it included 10,885 business/work units; in 2003 (fifth edition; Harter, Schmidt, & Killham, 2003), when it included 13,751 business/work units; in 2006 (sixth edition; Harter, Schmidt, Killham, & Asplund, 2006), when it included 23,910 business/work units; in 2009 (seventh edition; Harter, Schmidt, Killham, & Agrawal, 2009), when it included 32,394 business/work units; in 2013 (eighth edition; Harter, Schmidt, Agrawal, & Plowman, 2013), when it included 49,928 business/ work units; in 2016 (ninth edition; Harter, Schmidt, Agrawal, Plowman, & Blue, 2016), when it included 82,248 business/work units; and in 2020 (10^th edition; Harter, Schmidt, Agarwal, Blue, Plowman, Josh, & Asplund, 2020), when it included 112,312 business/work units. This report provides the 11^th published iteration of Gallup’s Q¹² meta-analysis of the relationship between employee engagement and performance.

Since its final wording and order were completed in 1998, the Q¹² has been administered to nearly 64 million employees in 228 different countries or territories and in 77 languages. Additionally, a series of studies was conducted to examine the cross-cultural properties of the instrument (Harter & Agrawal, 2011).

The quality of an organization’s human resources is perhaps the leading indicator of its growth and sustainability. The attainment of a workplace with high-caliber employees starts with the selection of the right people for the right jobs. Numerous studies have documented the utility of valid selection instruments and systems in the selection of the right people (Sackett, Zhang, Barry, & Lievens, 2023; Schmidt, Hunter, McKenzie, & Muldrow, 1979; Hunter & Schmidt, 1983; Huselid, 1995; Schmidt & Rader, 1999; Harter, Hayes, & Schmidt, 2004; Schmidt, Oh, & Shaffer, 2016).

After employees are hired, they make decisions and take actions every day that can affect the success of their organizations. Many of these decisions and actions are influenced by their own internal motivations and drives. One can also hypothesize that the way employees are treated and the way they treat one another can positively affect their actions — or can place their organizations at risk. For example, researchers have found positive relationships between general workplace attitudes and service intentions, customer perceptions (Schmit & Allscheid, 1995), and individual performance outcomes (Iaffaldano & Muchinsky, 1985). An updated meta-analysis has revealed a substantial relationship between individual job satisfaction and individual performance (Judge, Thoresen, Bono, & Patton, 2001). Additional and more recent research illustrates that individual job attitudes are a substantial predictor of individual employee effectiveness, defined by both performance and withdrawal behaviors and intentions (Harrison, Newman, & Roth, 2006; Mackay, Allen, & Landis, 2017). Both of these more recent studies found that employee engagement is best conceptualized as a higher order job attitudes construct. This is further reinforced by Newman, Harrison, Carpenter, & Rariden (2016).

There is also evidence at the business or work unit level that employee attitudes relate to various organizational outcomes. Organization-level research has focused primarily on cross-sectional studies. Independent studies found relationships between employee attitudes and performance outcomes such as safety (Zohar, 1980, 2000), customer experiences (Schneider, Parkington, & Buxton, 1980; Ulrich, Halbrook, Meder, Stuchlik, & Thorpe, 1991; Schneider & Bowen, 1993; Schneider, Ashworth, Higgs, & Carr, 1996; Schmit & Allscheid, 1995; Reynierse & Harker, 1992; Johnson, 1996; Wiley, 1991), financials (Denison, 1990; Schneider, 1991) and employee turnover (Ostroff, 1992). A study by Batt (2002) used multivariate analysis to examine the relationship between human resource practices (including employee participation in decision-making) and sales growth. Gallup has conducted large-scale meta-analyses — in the 10^th edition studying 112,312 business and work units regarding the concurrent and predictive relationship of employee attitudes (satisfaction and engagement) with safety, customer attitudes, financials, employee retention, absenteeism, quality metrics and merchandise shrinkage (Harter et al., 2020; Harter et al., 2016; Harter et al., 2013; Harter et al., 2009; Harter et al., 2006; Harter et al., 2003; Harter, Schmidt, & Hayes, 2002; Harter & Schmidt, 2002; Harter & Schmidt, 2000; Harter & Creglow, 1998; Harter & Creglow, 1997). This meta-analysis, repeated across time, has found consistently that there are positive concurrent and predictive relationships between employee attitudes and various important business outcomes. It has also found that these relationships generalize across a wide range of situations (industries, business/ work unit types and countries). Additional independent studies have found similar results (Whitman, Van Rooy, & Viswesvaran, 2010; Edmans, 2012). A recent meta-analysis of employee engagement data found somewhat stronger correlations between job attitudes and business performance during past economic recessions compared to nonrecession years (Harter, Schmidt, Agrawal, Plowman, & Blue, 2020). Like the studies of individual job attitudes, this study also found that the best predictor of overall business/work unit performance was a higher order job attitude-engagement construct.

Even though it has been much more common to study employee opinion data at the individual level, studying data at the business or work unit level is critical because that is where the data are typically reported (because of confidentiality concerns, employee surveys are reported at a broader business or work unit level). In addition, business-unit-level research usually provides opportunities to establish links to outcomes that are directly relevant to most businesses — outcomes like customer loyalty, profitability, productivity, turnover, safety incidents, merchandise shrinkage and quality variables that are often aggregated and reported at the business/work unit level.

Another advantage to reporting and studying data at the business/work unit level is that instrument item scores are of similar reliability to dimension scores for individual-level analysis. This is because at the business or work unit level, each item score is an average of many individuals’ scores. This means that employee surveys reported at a business or work unit level can be more efficient or parsimonious in length because item-level measurement error is less of a concern. See Harter and Schmidt (2006) for a more complete discussion of job satisfaction research and the advantages of conducting unit-level analyses.

One potential problem with such business-unit-level studies is limited data as a result of a limited number of business/work units (the number of business/work units becomes the sample size) or limited access to outcome measures that one can compare across business/work units. For this reason, many of these studies are limited in statistical power. As such, results from individual studies may appear to conflict with one another. Metaanalysis techniques provide the opportunity to pool such studies together to obtain more precise estimates of the strength of effects and their generalizability.

This paper’s purpose is to present the results of an updated meta-analysis of the relationship between employee workplace perceptions and business/work unit outcomes based on currently available data collected with Gallup clients. The focus of this study is on Gallup’s Q¹² instrument. The Q¹² items — which were selected because of their importance at the business or work unit level — measure employee perceptions of the quality of people-related management practices in their business/work units.

The development of the GWA (Q¹²) was based on more than 30 years of accumulated quantitative and qualitative research. Its reliability, convergent validity and criterionrelated validity have been extensively studied. It is an instrument validated through prior psychometric studies as well as practical considerations regarding its usefulness for managers in creating change in the workplace.

In designing the items included in the Q¹², researchers took into account that, from an actionability standpoint, there are two broad categories of employee survey items: those that are reflective measures of attitudinal outcomes (satisfaction, loyalty, pride, customer service perceptions and intent to stay with the company) and those that are formative measures of actionable issues that drive these outcomes. The Q¹² measures the actionable issues for management — those predictive of attitudinal outcomes such as satisfaction, loyalty, pride and so on. On Gallup’s standard Q¹² instrument, after an overall satisfaction item, are 12 items measuring issues we have found to be actionable (changeable) at the supervisor or manager level — items measuring perceptions of elements of the work situation, such as role clarity, resources, fit between abilities and requirements, receiving feedback, and feeling appreciated. The Q¹² is a formative measure of “engagement conditions,” each of which is a contributor to engagement through the measure of its causes.

The Q¹² statements are:

1. Q00. (Overall Satisfaction) On a 5-point scale, where 5 means extremely satisfied and 1 means extremely dissatisfied, how satisfied are you with (your company) as a place to work?

2. Q01. I know what is expected of me at work.

3. Q02. I have the materials and equipment I need to do my work right.

4. Q03. At work, I have the opportunity to do what I do best every day.

5. Q04. In the last seven days, I have received recognition or praise for doing good work.

6. Q05. My supervisor, or someone at work, seems to care about me as a person.

7. Q06. There is someone at work who encourages my development.

8. Q07. At work, my opinions seem to count.

9. Q08. The mission or purpose of my company makes me feel my job is important.

10. Q09. My associates or fellow employees are committed to doing quality work.

11. Q10. I have a best friend at work.

12. Q11. In the last six months, someone at work has talked to me about my progress.

13. Q12. This last year, I have had opportunities at work to learn and grow.

The Gallup Q¹² items (Q01-Q12) are Gallup proprietary information and are protected by law. You may not administer a survey with the Q¹² items or reproduce them without written consent from Gallup. Copyright © 1993-1998 Gallup, Inc. All rights reserved.

The current standard is to ask each employee (a census survey; median participation rate is 84%) to rate the Q¹² statements using six response options, from 5 = strongly agree to 1 = strongly disagree, and the sixth response option — don’t know/does not apply — is unscored. Because it is a satisfaction item, the first item (Q00) is scored on a satisfaction scale rather than on an agreement scale. Regression analyses (Harter et al., 2002) indicate that employee engagement accounts for nearly all of the performance-related variance (composite performance) accounted for by the overall satisfaction measure. Therefore, the focus of this report is on employee engagement, as measured by statements Q01-Q12.

While these items measure issues that the manager or supervisor can influence, only one item contains the word “supervisor.” This is because it is realistic to assume that numerous people in the workplace can influence whether someone’s expectations are clear, whether the employee feels cared about and so on. The manager’s or supervisor’s position, though, allows them to take the lead in establishing a culture that values behaviors that support these perceptions.

The following is a brief discussion of the conceptual relevance of each of the 13 items:

Q00. Overall satisfaction

The first item on the survey measures affective satisfaction on a scale from “extremely dissatisfied” to “extremely satisfied.” It is an attitudinal outcome or direct reflective measure of how people feel about their organization. Given that it is a direct measure of affective satisfaction, on its own, it is difficult to act on the results of this item. Other issues, like those measured in the following 12 items, explain why people are satisfied and why they become engaged and produce outcomes.

Q01. Expectations

Defining and clarifying the outcomes that are to be achieved is perhaps the most basic of all employee needs and manager responsibilities. How these outcomes are defined and acted on will vary across business/work units, depending on the goals of the business/work unit.

Q02. Materials and equipment

Getting people what they need to do their work is important in maximizing efficiency, demonstrating to employees that their work is valued and showing that the company is supporting them in what they are asked to do. Great managers help employees see how their requests for materials and equipment connect to important organizational outcomes.

Q03. Opportunity to do what I do best

Helping people get into roles in which they can most fully use their inherent talents and strengths is the ongoing work of great managers. Learning about individual differences through experience and assessment can help the manager position people efficiently within and across roles and remove barriers to high performance.

Q04. Recognition for good work

Employees need constant feedback to know if what they are doing matters. Ongoing management challenges include understanding how each person prefers to be recognized, making recognition objective and real by basing it on performance, and recognizing employees frequently.

Q05. Someone at work cares about me

For each person, feeling cared about may mean something different. The best managers listen to individuals and respond to their unique needs. In addition, they find the connection between the needs of the individual and the needs of the organization.

Q06. Someone at work encourages my development

How employees are coached can influence how they perceive their future. If the manager is helping the employee improve as an individual by providing opportunities that are in sync with the employee’s talents, both the employee and the company will profit.

Q07. Opinions count

Asking for the employee’s input and considering that input can often lead to better decision-making. This is because employees are often closer than the manager is to many factors that affect the overall system, whether that is the customer or the products they are producing every day. In addition, when employees feel they are involved in decisions, they take greater ownership for the outcomes.

Q08. Mission or purpose

Great managers help people see not only the purpose of their work, but also how each person’s work influences and relates to the purpose of the organization and its outcomes. Reminding employees of the big-picture effect of what they do each day is important, whether it is how their work influences the customer, safety or the public.

Q09. Associates committed to quality

Managers can influence the extent to which employees respect one another by selecting conscientious employees, providing some common goals and metrics for quality, and increasing associates’ frequency of opportunity for interaction.

Q10. Best friend at work

Managers vary in the extent to which they create opportunities for people at work to get to know one another and in how much they value close, trusting relationships at work. The best managers do not subscribe to the idea that there should be no close friendships at work; instead, they free people to get to know one another, which is a basic human need. This, then, can influence communication, trust and other outcomes.

Q11. Progress

Providing a structured time to discuss each employee’s progress, achievements and goals is important for managers and employees. Great managers regularly meet with individuals, both to learn from them and to give them guidance. This give-and-take helps managers and employees make better decisions.

Q12. Opportunities to learn and grow

In addition to having a need to be recognized for doing good work, most employees need to know that they are improving and have opportunities to build their knowledge and skills. Great managers choose training that will benefit the individual and the organization.

As a total instrument (sum or mean of items Q01-Q12), the Q¹² has a Cronbach’s alpha of 0.91 at the business/work unit level. The meta-analytic convergent validity of the equally weighted mean (or sum) of items Q01-Q12 (GrandMean) to the equally weighted mean (or sum) of additional items in longer surveys (measuring all known facets of job satisfaction and engagement) is 0.91. This provides evidence that the Q¹², as a composite measure, captures the general factor in longer employee surveys. Individual items correlate to their broader dimension true-score values, on average, at approximately 0.70. While the Q¹² is a measure of actionable engagement conditions, its composite has high convergent validity with affective satisfaction and other direct measures of work engagement (see Harter and Schmidt, 2008, for further discussion of convergent and discriminant validity issues and the construct of “engagement”).

As previously mentioned, this is the 11^th published iteration of the Q¹² business-unit-level meta-analysis. Compared with the previous meta-analysis, the current meta-analysis includes:

• a larger number of studies and business/work units

• more than triple the number of business/work units with wellbeing data and double the number of business/work units with turnover data

• 4,880 more business/work units with productivity data, 2,851 more business/work units with profitability data, 2,093 more business/work units with safety incidents data, 1,768 more business/work units with absenteeism data, 1,236 more business/work units with organizational citizenship data, 1,195 more business/work units with customer loyalty/engagement data, and 281 more business/work units with quality/defects data

As such, this study provides a substantial update of new and recent data.

The coverage of research studies includes business/work units in 90 countries, including Australia and New Zealand, and countries in Asia, Europe, Post-Soviet Eurasia, Latin America, the Middle East, North America, Africa and the Caribbean. Sixty-eight companies included in the current meta-analysis operate exclusively in countries outside the U.S.

This meta-analysis includes all available Gallup studies (whether published or unpublished) and has no risk of publication bias.

Utility Analysis: Practicality of the Effects

In the past, studies of job satisfaction’s relationship to performance have had limited analysis of the utility of the reported relationships. Correlations have often been discounted as trivial without an effort to understand the potential utility, in practice, of the relationships. The Q¹² includes items that Gallup researchers have found to be changeable by the local manager and others within the business/work unit. As such, understanding the practical utility of potential changes is crucial.

The research literature includes a great deal of evidence that numerically small or moderate effects often translate into large practical effects (Abelson, 1985; Carver, 1975; Lipsey, 1990; Rosenthal & Rubin, 1982; Sechrest & Yeaton, 1982). As shown in Table 5, this is, in fact, the case here. Effect sizes referenced in this study are consistent with or above other practical effect sizes referenced in other reviews (Lipsey & Wilson, 1993).

A more intuitive method of displaying the practical value of an effect is that of binomial effect size displays, or BESDs (Rosenthal & Rubin, 1982; Grissom, 1994). BESDs typically depict the success rate of a treatment versus a control group as a percentage above the median on the outcome variable of interest.

BESDs can be applied to the results of this study. Table 5 shows the percentage of business/work units above the median on composite performance for high- and lowscoring business/work units on the employee engagement (Q¹²) composite measure. True validity estimates (correcting for measurement error only in the dependent variable) were used for analysis of business/work units both within and across organizations.

One can see from Table 5 that there are meaningful differences between the top and bottom halves. The top half is defined as the average of business/work units scoring in the higher 50% on the Q¹², and business/work units scoring in the lower 50% constitute the bottom half. It is clear from Table 5 that management would learn a great deal more about success if it studied what was going on in top-half business/work units rather than bottom-half units.

With regard to composite business/work unit performance, business/work units in the top half on employee engagement have an 86% higher success rate in their own organization and a 133% higher success rate across business/work units in all companies studied. In other words, business/work units with high employee engagement nearly double their odds of above-average composite performance in their own organizations and increase their odds for above-average success across business/work units in all organizations by 2.33 times.

To illustrate this further, Table 6 shows the probability of above-average performance for various levels of employee engagement. Business/work units at the highest level of employee engagement across all business/work units in Gallup’s database have an 83% chance of having high (above average) composite performance. This compares with a 17% chance for those with the lowest level of employee engagement. So, it is possible to achieve high performance without high employee engagement, but the odds are substantially lower (in fact, more than five times as low).

Other forms of expressing the practical meaning behind the effects from this study include utility analysis methods (Schmidt & Rauschenberger, 1986). Formulas have been derived for estimating the dollar-value increases in output as a result of improved employee selection. These formulas take into account the size of the effect (correlation), the variability in the outcome being studied and the difference in the independent variable (engagement in this case) and can be used in estimating the difference in performance outcomes at different levels in the distribution of Q¹² scores. Previous studies (Harter et al., 2002; Harter & Schmidt, 2000) provided utility analysis examples, comparing differences in outcomes between the top and bottom quartiles on the Q¹². For companies included in the fourth edition of the meta-analysis, it was typical to see differences between top and bottom engagement quartiles of 2 to 4 percentage points on customer loyalty/ engagement, 1 to 4 points on profitability, hundreds of thousands of dollars on productivity figures per month, 4 to 19 points in turnover for low-turnover companies, and 14 to 51 points for high-turnover companies.

Gallup researchers recently conducted utility analysis across multiple organizations with similar outcome metric types (an update of analyses presented in Harter et al., 2002, p. 275, Table 6). Comparing top-quartile with bottom-quartile engagement, business/work units resulted in median percent differences of:

• 10% in customer loyalty/engagement
• 23% in profitability
• 18% in productivity (sales)
• 14% in productivity (production records and evaluations)
• 21% in turnover for high-turnover organizations (those with more than 40% annualized turnover)
• 51% in turnover for low-turnover organizations (those with 40% or lower annualized turnover)
• 63% in safety incidents (accidents)
• 78% in absenteeism
• 28% in shrinkage (theft)
• 58% in patient safety incidents (mortality and falls)
• 32% in quality (defects)
• 70% in wellbeing (thriving employees)
• 22% in organizational citizenship (participation)

The above differences and their utility in dollar terms should be calculated for each organization, given the organization’s unique metrics, situation and distribution of outcomes across business/work units. The median estimates represent the midpoint in the distribution of utility analyses conducted across 736 studies based on organizational data with similar outcome types.

One can see that the above relationships are nontrivial if the business has many business/work units. The point of the utility analysis, consistent with the literature that has taken a serious look at utility, is that the relationship between employee engagement and organizational outcomes, even conservatively expressed, is meaningful from a practical perspective.

References & Acknowledgements

• James K. Harter, Ph.D.
• Corey E. Tatel, Ph.D.
• Sangeeta Agrawal, M.S.
• Anthony Blue, M.A.
• Stephanie K. Plowman, M.A.
• Jim Asplund, M.A.
• Sabrina Yu, M.S.
• Andy Kemp, M.A.

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The authors thank the following people for contributing important new research studies to the ongoing meta-analysis, for communicating important details regarding the studies and data, or for leading efforts to compile the data needed for the meta-analysis: Don Allen, Bryan Bierwirth, Jil Buchanan, Jeevika Galhotra, McKensey Johnson, Michele Kern, Marco Nink, John Pitonyak, John Reimnitz, Puneet Singh, Andy Stewart and Tom Voorheis.

The authors of this report would like to thank Dr. Frank L. Schmidt (1944-2021), whose contributions to Gallup’s regularly updated meta-analysis of the relationship between employee engagement and organizational outcomes were invaluable. Dr. Schmidt coauthored each of the ten previous editions of the meta-analysis and his research and teachings have heavily influenced Gallup’s meta-analytic approach. This report would not have been possible without Dr. Schmidt.

Revised July 2024: Updated artifact distributions and use of correction of correlations for small sample size bias.