using engagement analytics to improve organizational performance

57© 2013 Wiley Periodicals, Inc.Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/ert.21422

Employee engagement is the state of emo-tional and intellectual involvement that

motivates people to do their best work. Engage-ment is critical to organizational effectiveness—organizations must have engaged people in order to drive outcomes such as productivity, safety, innovation, employee retention, cus-tomer satisfaction and loyalty, sales growth, and profitability. Engagement analytics help to identify and measure the drivers of engagement, quantify the performance impli-cations of engagement in very specific terms, and help organizations focus their efforts to improve engagement.

Aon Hewitt has conducted in-depth research into engagement across its global client base, and as a result of this research defines engagement in terms of three factors that are measured by six survey questions. These three factors form an engagement measure that is reliable and significantly related to organizational performance. The three factors are:

1. Say: people consistently speaking posi-tively about the organization to coworkers, potential employees, and customers;

2. Stay: people having an intense desire to be part of the organization; and

3. Strive: people exerting extra effort and engaging in behaviors that contribute to business success.

Engagement analytics include several related analyses:

• What drives engagement, what is the cost of making improvements in engagement drivers, and how much might engagement improve if key drivers are improved?

• How much might organizational perfor-mance improve if engagement improves?

• What is the potential ROI of improving various engagement drivers, based on the cost of improving those drivers and the ultimate impact on engagement and orga-nizational performance?

ANALYZING LINKS BETWEEN ENGAGEMENT AND PERFORMANCE

Extensive research demonstrates the power of engagement to drive performance, and orga-nizations have become increasingly sophis-ticated in recent years in understanding the links between engagement and performance.1 One example of this research is from the Aon Hewitt global employee-survey database, which is a very large database that includes recent responses from over 4,600 companies and an employee population of over 18 mil-lion people. Companies in the top 25 percent of this database in engagement scores have total shareholder return that’s 50 percent above average. Conversely, companies in the

Using Engagement Analytics to Improve Organizational Performance

Darryl R. Roberts

Employment Relations Today

58 Darryl R. RobertsEmployment Relations Today DOI 10.1002/ert

DESIGNING A LINKAGE MODEL

Linkage work begins by gaining leadership support and identifying specific objectives. A next step is identifying variables of interest and the expected relationships among them, then gathering data and building a database that has engagement and performance data in one place. Once the database is in place, analysis can begin.

Identifying measures and building the database tends to be an iterative process, as some measures may not be useable for the analysis on further investigation (for example, they may not be measured in a consistent way across different countries) and, conversely, other measures may emerge as the linkage team learns more. Analyzing relationships between variables also tends to be iterative, as the original hypotheses may need to be modified in light of the data.

Exhibit 1 shows an example of a linkage model, with increases in engagement driving increases in customer satisfaction and sales growth. This is a simple example—some models have more variables and more complex relationships between variables—but it illustrates how relationships can be shown. In this example, engagement has both a direct effect on sales growth (higher engagement leads to higher sales growth) and an indirect effect through customer satisfaction (higher engagement leads to higher customer satisfaction, which in turn leads to higher sales growth).

The data will likely require cleaning to account for outliers, missing data, and other factors that can affect the performance metrics. For example, year-over-year sales-growth numbers can be affected by locations opening and closing during a year, and this should be taken into account in working with

bottom 25 percent for engagement scores have total shareholder return that’s 50 per-cent below average. Another recent Aon Hewitt analysis across 94 companies fur-ther proves the point.2 This analysis found a significant link between engagement and sales growth, specifically that each incre-mental percentage of employees who become engaged would predict an incremental 0.6 percent growth in sales.

Aon Hewitt’s work with individual clients also demonstrates linkages between engagement (and related measures) and performance. In this engagement-linkage analysis work, engagement data from employee surveys is linked to a variety of organizational performance metrics, using a unit (or units) of analysis where both engagement and performance indicators are available (such as business unit or location).

Performance indicators typically fall into one or more of the following categories:

• People metrics (such as employee turn-over);

• Customer metrics (such as customer satis-faction);

• Operational metrics (such as safety); and• Financial metrics (such as sales growth).

Some linkage analyses cover only one of these categories (such as financial metrics), but many Aon Hewitt clients look at measures across at least two of these categories (such as financial and customer metrics).

Extensive research demonstrates the power of engagement to drive performance, and organi-zations have become increasingly sophisticated in recent years in understanding the links between engagement and performance.

Fall 2013

59Using Engagement Analytics to Improve Organizational Performance Employment Relations Today DOI 10.1002/ert

Linkage involves a variety of analytical methods (t-test, chi square, correlation, multiple regression, logistic regression, structural equation modeling, etc.), and often involves longitudinal data collected over multiple time periods. Where the available data allow, using measures from multiple time periods and advanced analytical methods is preferable, as that supports more robust models of the relationships between variables and increases confidence that engagement now will lead to higher performance in the future. Simpler approaches such as correlation with measures from one time period can also provide very useful information on how engagement and performance are related, but it is harder to tell what is driving what with these techniques.

Although advanced techniques and rigorous analysis are critical to understanding linkages in an accurate way, the way results are presented is also important, and the presentation approach will need to vary depending on the intended audience. For research intended for academic publication, detailed results that provide an in-depth look at the data and methodology are important. On the other hand, when the work is conducted within an organization with a main goal of facilitating action, it is important to present results in a compelling way that decision makers can use to take action. Outside the research team, this often means presenting key conclusions, in a graphical way where possible, rather than the full details of the data and analytical methods used.

ILLUSTRATIONS OF CLIENT RESULTS

One example of Aon Hewitt’s linkage work with individual clients comes from a large retailer, Client A, with over 1,000 stores.

these numbers (such as by comparing only locations open 12 months in each year).

Building a team that includes expertise in each of the organizational-performance metrics is important, as detailed knowledge of the metrics is critical to analyzing linkages and interpreting results in a meaningful way. This is particularly true for metrics that are specific to the industry or organization. To give an example of this kind of detailed knowledge, one retailer finds that stores in certain affluent markets tend to have lower customer-satisfaction ratings than stores in less affluent markets, something that is well known to the company’s customer-research experts but that may not be obvious to others. The company’s research indicates this is largely due to higher expectations on the part of customers in the more affluent markets, rather than differences in how employees serve customers in different markets. Thus, for this company, it is important to take market into account in conducting linkage analysis involving customer satisfaction. One other data consideration is that in order to get an accurate sense of the relationship between engagement and performance, linkage analysis typically uses normalized measures that can be compared directly across units of different sizes (e.g., output per employee, percentage growth rate, profit as a percentage of sales) rather than measures that are related to unit size (e.g., sales growth in dollars, turnover in number of employees, absolute number of accidents).

Engagement CustomerSatisfaction

SalesGrowth

Exhibit 1. Illustrative Linkage Model


Darryl R. RobertsEmployment Relations Today DOI 10.1002/ert

60

that was nine percentage points higher than lower-engagement stores. This analysis also looked at the three components of engagement (say, stay, strive) and found that the strive component of engagement was especially powerful with regard to cost per unit sold. Stores with higher levels of strive had costs that were 33 percent lower than stores with lower levels of strive. In other words, stores were more cost-efficient when employees gave greater discretionary effort and were motivated to contribute more in their daily work.

Client C found a significant relationship between employee views and employee turnover, with a four-percentage-point difference in turnover between locations with the most favorable and least favorable employee views. This organization also found significant links with other outcomes, including inventory management, sales growth, and safety. For sales growth, there was a three-percentage-point difference between locations with the most favorable and least favorable employee views. Exhibit 3 shows the relationship between employee views and turnover for Client C.

Aon Hewitt’s clients recognize that engagement is not the only factor driving organizational performance—market

This organization found significant linkages between engagement and performance mea-sures, including sales growth (for the stores overall and for major departments), customer satisfaction, and loss prevention. The analy-sis also included the impact of key drivers of engagement—factors with the greatest potential to sustain and improve the level of engagement—on engagement and results. Higher-engagement stores had customer-satisfaction ratings that were five percent-age points higher than lower-engagement stores. Higher-engagement stores also had sales growth that was two percentage points higher than lower-engagement stores. Engage-ment linked to results even after controlling for factors beyond engagement that might have affected results, such as store type and region. This work included engagement and performance data from multiple years, so it was possible to look at relationships over time (such as the link between 2011 engage-ment and 2012 performance). Exhibit 2 sum-marizes some of the key findings at Client A.

Another client, Client B, with both manufacturing and retail operations, found significant relationships between engagement and performance measures, including market share and customer satisfaction. For example, higher-engagement stores had market share

Higher Engagement

CustomerViews +5%

Sales Growth+2%

Exhibit 2. Higher Engagement Drives Higher Customer Satisfaction and Sales Growth


Fall 2013

conditions, the regulatory environment, company financial structure, availability and cost of resources, amount and quality of competition, and other factors also influence performance, so there is generally not a one-to-one relationship between engagement and performance. When engagement moves five percentage points, for example, sales growth typically moves fewer than five percentage points. Notwithstanding the other factors that affect performance, the research consistently finds a strong relationship between engagement and performance, and organizations with higher levels of engagement have significantly better performance over time.

SUPPORTING RESEARCH LINKING ENGAGEMENT TO PERFORMANCE

In addition to the Aon Hewitt database research and individual client experience, there is considerable published research that shows the relationship between engagement

(and related measures) and organizational performance. A complete review is beyond the scope of this article, but a few examples illustrate the findings. One early study with bank tellers found links between job atti-tudes and outcomes, including absenteeism, turnover, and job performance.3 A statistical review (meta-analysis) across 7,939 business units in 36 companies found substantial rela-tionships between engagement and outcomes including customer satisfaction, productivity, profit, employee turnover, and accidents.4

Lowe’s found that the difference in sales between stores with high and low engage-ment amounted to a 4 percent difference in average transaction per store and over $1 million per store in annual sales.5

The link between engagement and performance also exists in the public sector and not-for-profit organizations. One study with primary school teachers found significant links between engagement and job performance.6 Also, Kaiser Permanente, a nonprofit health plan with over 9 million members, over 167,000 employees, and over 500 clinics and hospitals, found significant relationships between employee attitudes and outcomes including patient satisfaction, quality, workplace injuries, and employee attendance.7

The Importance of Employee and Manager Assessment and Selection

There is also evidence that there is a dis-positional or enduring personal aspect to job attitudes, such as from one study that tracked job attitudes with a lifetime lon-gitudinal study of people over the course of their careers, finding substantial consis-tency in job attitudes for individuals over nearly 50 years.8 Although in the short term organizations can most effectively increase

25%

0%

5%

10%

18%

Most FavorableLocations

Least FavorableLocations

22%

15%

20%

Employee Turnover

Exhibit 3. Favorable Employee Views Drive Lower Employee Turnover



engagement and performance by improving key drivers of engagement within the organi-zation, this research indicates that over time there is also an assessment and selection aspect to managing and increasing engage-ment and performance.

Aon Hewitt’s research and client work shows the power of employee and manager assessment and selection systems to improve engagement as well as outcomes such as sales, profit, customer service, and safety.9 For example, a quick-service restaurant company found that employees at restaurants led by highly qualified managers were five percentage points more favorable on the employee-engagement survey than employees at locations led by marginally qualified managers. Another client, a light-industrial company, found that accident rates

for newly hired employees were twice as high among lower-scoring employees on selection tests, compared with accident rates for higher-scoring employees. And a retail client found that highly qualified candidates had sales per hour that were 11 percent higher than marginally qualified candidates. In short, by better matching incoming employees with job requirements, effective assessment and selection complements efforts to manage and improve engagement with the existing workforce.

IDENTIFYING PRIORITIES THROUGH ENGAGEMENT ANALYTICS

Engagement-linkage analysis involves statisti-cally linking engagement and organizational

performance metrics. Combined with related analyses—engagement-drivers analysis and cost-of-improving-engagement-drivers analysis—organizations can estimate the return on investment of alternatives for improving engagement and organizational performance, and identify the most promising priorities for action. Exhibit 4 summarizes how organizations can build predictive ana-lytics focused on the best ways to improve engagement and organizational performance.

Engagement-Drivers Analysis

This analysis quantifies the links between key drivers and engagement based on survey data. For example, using the figures pre-sented in Exhibit 4, if views on recognition can be improved by five percentage points, engagement can be expected to improve by two percentage points. This analysis is con-ducted with statistical techniques (historically with correlation or regression analysis; more recently with relative weight analysis) that look at the relationship between engagement and various possible drivers measured on a survey. For the global workforce, the top driv-ers of engagement are career opportunities, organization reputation, pay, recognition, and communication.10 However, engagement driv-ers will vary by organization and for specific units within an organization, so engagement-drivers analysis should be conducted with organization-specific data to identify the most important drivers for the organization.

Cost-of-Improving-Engagement-Drivers Analysis

Data the company has on the cost and effec-tiveness of interventions (such as expanded recognition programs) can be used to

By better matching incoming employees with job requirements, effective assessment and selection complements efforts to manage and improve engagement with the existing workforce.


Fall 2013

estimate the cost of improving engagement drivers. For example, using the information in Exhibit 4, it would cost $200,000 to improve views on recognition by five percentage points and thus increase engagement by two percentage points. One way to estimate the cost of improving engagement drivers is by running pilot programs in a subset of the organization, tracking cost and impact on the drivers, and estimating cost and impact for the organization based on the pilot-program experience.

Engagement-Linkage Analysis

This analysis quantifies links between engagement and organizational performance. Using Exhibit 4 to illustrate this, if engage-ment improves by two percentage points, profits can be expected to improve by $400,000.

This data can be combined to assess ROI as in this illustrative example:

❏ The company estimates that it would have to spend $200,000 per year on recognition programs to improve employee views on recognition by fi ve percentage points (e.g., from 70 percent to 75 percent positive perceptions).

❏ The engagement-drivers analysis indicates that a fi ve-percentage-point increase in views on recognition can be expected to increase engagement by two percentage points.

❏ The engagement-linkage analysis indicates that a two-percentage-point increase in engagement can be expected to increase profi ts by $400,000 per year.

❏ Thus, the company can expect to increase profi ts by $400,000 per year by spend-ing $200,000 more per year on recogni-tion programs, for an ROI of 100 percent [($400,000 – $200,000)/$200,000].

❏ When this analysis is conducted for mul-tiple drivers of engagement, the company can compare the potential ROI of different

Quantifies linksbetween keydrivers andengagement

Estimates thecost of improvingkey drivers ofengagement

Quantifies linksbetweenengagement andorganizationalperformance

Estimates ROIfrom investmentsin improvingengagementdrivers

If views onrecognitionimprove by fivepoints,engagement canbe expected toincrease by twopoints.

A $200,000-per-year investmentin recognitionprograms can beexpected toimprove viewson recognition byfive points.

A two-pointincrease inengagement canbe expected toincrease profitsby $400,000 peryear.

The companycan increaseprofits by$400,000 peryear by spending$200,000 moreper year onrecognitionprograms, for anROI of 100percent.

Five-pointincrease inrecognition;$200,000 cost

Two-pointincrease inengagement

$400,000 inadditional profits

100% ROI

Engagement-Drivers

Analysis

Cost-of-Improving-

Engagement-DriversAnalysis

Engagement-LinkageAnalysis

ROI Analysis

What It Does

Example

Engagement Analytics Example: Holistic View

Exhibit 4. Using Engagement Analytics to Improve Performance



interventions and use the results to more effectively prioritize its actions.

Not all organizations measuring engagement are able to or choose to combine all of these analyses, but where possible the complete package of engagement analytics—engagement-drivers analysis, data on the cost of improving engagement drivers, engagement-linkage analysis, and ROI analysis—provides powerful information that can be used to improve engagement and organizational performance in a data-driven, cost-effective way. Engagement-linkage analysis provides powerful data by itself as well, quantifying the performance implications of engagement and helping organizations focus their improvement efforts even when the process for identifying cost, key drivers, and expected ROI is less detailed than in the example.

CONCLUSION

Engagement analytics are a powerful tool that organizations are using to quantify the value of engagement and improve their organiza-tional performance as measured by outcomes such as customer satisfaction, financial results, market share, safety, and employee turnover. Although many would agree at a general level that engagement is important for organiza-tional performance, engagement-linkage analy-sis takes this a step further by quantifying the performance implications of engagement in a very specific way and helping organizations focus their efforts to improve engagement and performance in ways that will yield the best results. When combined with engage-ment-drivers analysis and data on the cost of improving engagement drivers, engagement-linkage analysis is even more powerful in

helping organizations improve engagement and performance in a way that focuses on interventions with the highest ROI.

NOTES

1. Adair, C., Morewitz, C., Oehler, K., Parker, S., Roberts, D., Rubin, D., & Smith, R. (2013, April 12). Employee engagement linkage to business performance: Best practices and implications. Presented at the Society for Industrial and Organizational Psychology Annual Confer-ence, Houston, TX.

2. Aon Hewitt. (2013). 2013 trends in global employee engagement. Retrieved from http://www.aon.com/human-capital-consulting/thought-leadership/talent_mgmt/2013_Trends_in_Global_Employee_Engagement.jsp.

3. Mirvis, P. H., & Lawler, E. E. (1977). Measuring the financial impact of employee attitudes. Journal of Applied Psychology, 62, 1–8.

4. Harter, J. K., Schmidt, F. L., & Hayes, T. L. (2002). Business-unit-level relationship between employee satisfaction, employee engagement, and business out-comes: A meta-analysis. Journal of Applied Psychology, 87, 268–279.

5. Coco, C. T., Jamison, F., & Black, H. (2011). Connecting people investments and business outcomes at Lowe’s: Using value linkage analytics to link employee engagement to business performance. People & Strategy, 34(2), 28–33.

6. Bakker, A. B., & Bal, P. M. (2010). Weekly work engage-ment and performance: A study among starting teachers. Journal of Occupational and Organizational Psychology, 83, 189–206.

7. Konitsney, D. (2012, April). Leveraging data to create a framework for high performance and increase your organization’s competitive edge. Presented at the Human Capital Summit, Orlando, FL. Summary retrieved from http://www.hci.org/files/events/HCS2013-presentations /040813W_0200-0245_Deb-Konitsney.pdf.

8. Staw, B. M., Bell, N. E., & Clausen, J. A. (1986). The dispositional approach to job attitudes: A lifetime longitu-dinal approach. Administrative Science Quarterly, 31, 56–77.


Fall 2013

9. Aon Hewitt. (2012). Measuring the business impact of employee selection systems. Retrieved from http://www.aon.com/attachments/human-capital-consulting

/2012_Measuring_Business_Impact_Employee_Selection_Systems.pdf.

10. See note 2.

Darryl R. Roberts, PhD, is an associate partner with Aon Hewitt (see www.aonhewitt.com) in Newport Beach, California. His major focus is helping client organizations measure and manage employee engagement and drive improvements in engagement, productivity, safety, employee turnover, customer satisfaction, and financial results. He also has extensive experience with total rewards optimization, which blends employee research and financial analysis to optimize rewards spending. He has worked with over 200 client organizations in his consulting career, including over 100 Fortune 500 com-panies. He may be contacted via e-mail at [email protected].

using engagement analytics to improve organizational performance

Documents