WorkTango's Surveys & Insights Employee Engagement Survey methodology focuses on helping companies gain insight on employee engagement and factors that create workplaces where employees can succeed. There has been extensive academic research over the last few decades that has shown the evidence of employee engagement’s impact on positive workplace metrics, business outcomes, and several other key performance indicators (here’s one example).
The Employee Engagement Survey Model
Employee engagement is the sentiment that employees have for their jobs, organization, people leaders and co-workers that drives them to strive to do their best work and ensure the organization succeeds.- Engagement Index: a collection of questions to measure the attitudes and behaviors which define engaged employees.
- Engagement Factors: indices to support an understanding of the major factors that contribute to employee engagement.
- Employee Voice: WorkTango also uniquely layers in Natural Language Understanding to support understanding employee sentiment through our Employee Voice Index – supporting a deeper understanding of employee engagement through employee comments.
1. Engagement Index
Measuring employee engagement offers insight into the state of mind employees at a particular time. The focus of the Engagement Index is to understand overall employee sentiment, which is separate from asking questions to understand what influences employee engagement.WorkTango views employee engagement from the perspective of behaviors and attitudes. There are distinct differences between the behaviors and attitudes of employees versus the positive outcomes of those behaviors.- Behaviors – the way in which one acts or conducts oneself.
- Attitudes – the underlying sensation, beliefs and values that can impact behaviors and decision making
- PROMOTER: the concept of promoting something is defined by helping something flourish and publicizing someone’s satisfaction. Measuring whether an employee would recommend the organization as a place to work focuses on an action-oriented behavior of whether they are satisfied with their work experience and willing to promote it.
Statement: I would recommend this organization as a great place to work.
- INSPIRATION: inspiration involves admiration for something and a process of being stimulated to do something. Understanding an employee’s inspiration and motivation to go above and beyond at work supports an understanding of employee behaviors focused in a positive direction to support the organization.
Statement: My organization inspires me to give my very best at work.
Attitude Measures:- PRIDE: pride is the feeling of pleasure and satisfaction to something that a person feels closely connected with. Measuring an employee’s attitude towards their satisfaction and connection to an organization is an important factor in the current state of an employee’s engagement.
Statement: I am proud to work for our organization.
- LOYALTY: loyalty is a feeling of support or duty towards something. This measurement focuses on the attitude around a desire for the employee to be part of the organization moving forward.
Statement: I intend to be working at this organization a year from now.
2. Engagement Factors
3. Employee Voice
- Satisfaction/Dissatisfaction – quantitatively measuring whether employees are satisfied or not based on the statements in the survey
- Participative Management – the reasoning and context towards levels of satisfaction and recommended actions by an employee
WorkTango’s recommended survey methodology is what a majority of customers leverage, however, there are other considerations:
Frequency
Whether companies use the short (20-question) or long (60-question) model as a baseline to measure employee engagement, WorkTango recommends conducting shorter surveys more frequently to see trends, to understand the impact of actions focused on improving engagement have had, and to provide more data points around engagement throughout the employee life cycle and experience. Higher frequency creates more accountability for action, improves the accuracy of the engagement measure, and enables more real-time insight about the employee experience.Customization
WorkTango understands that not every question is applicable to every workplace. All questions in WorkTango can be modified. Although there are BEST practices, we help you focus on the RIGHT practices. For example, use the language that you use by using your company name or refer to managers as you address them in your business (i.e. people leaders or supervisors). We offer the ability for companies to eliminate questions or add questions that support the insights you need at that moment in time.Bringing it all together
- Approach – leveraging expertise in organizational development and statistical analysis to support the right method to hearing the voice of employees for customers
- Measurement - offering the ability to understand real-time insights from employees served to anyone within the organization and leverage data to predict the most impactful behaviors
- Organizational Impact - leverage correlative analysis, expert advisory services, and technology to focus on the right actions that will impact employee engagement and other critical business objectives.
4. The Science Behind It All
WorkTango’s methodology is rooted in third-party academic research, statistical analysis of proprietary data sets, and research techniques by survey methodologists. The combination of academic research on the outcomes of Employee Engagement, with the psychological conditions exhibited through The WorkTango Engagement Index and Engagement Factor questions have been statistically validated as the most critical questions to ask based on number of techniques which include regression analyses and factorial analyses.Factor Analysis
Concepts like engagement and job satisfaction are abstract and multi-faceted (i.e. there are different aspects of the idea). Consequently, it is rare to measure them with one single question. Engagement surveys use many questions in order to capture all aspects of the overall idea (e.g. engagement). When there are many questions in the survey, what is being measured by each single question tends to overlap. If the few questions that measure a similar idea are grouped together, the average score from these questions will be a more accurate index for that underlying idea than any individual question. Factor analysis is used to show, in a survey with many questions, from the perspective of survey respondents, which questions are measuring the same underlying idea. This can be achieved by essentially analyzing how responses to different questions co-vary (i.e. if respondents answer question 1 and question 2 in the same way such that scoring high on question 1 means also scoring high on question 2, these two questions have a high co-variance, thus they are likely measuring the same thing in the minds of respondents). The results of factor analysis help us to figure out which questions are actually measuring similar ideas, so we can group the responses in the most meaningful way and eliminate questions that are repetitive or irrelevant to make the survey more concise without sacrificing accuracy. The results of factor analysis show the number of "factors" (i.e. big ideas) that can be reliably measured from the current survey, as well as the questions that jointly measure each idea. It also shows how closely each question measures the big idea. Questions that have a high loading (e.g. 0.8) more closely measure the big idea than questions with a low loading (e.g. 0.4).Multiple Regression
After a few "big concepts" have been identified by factor analysis, multiple regression can help us to determine how much each big idea contributes to the key index of interest - Engagement, and as well as the relative weight each big idea has on the final index of interest. The results of multiple regression show us, in "percentage of unique variance explained", how much each question/factor uniquely contributes to the Engagement. Typically, each question/factor should contribute somewhere between 4% to 25% of the final index, with larger number indicating more contribution. Results from multiple regression should be valid when all assumptions of regression are met. These include:- Linearity: each predictor should be linearly related to the outcome variable, which can be checked by looking at the scatterplots.
- Multivariate normality: the residuals of the outcome variable should be normally distributed, which is usually not a big problem with large sample size.
- No multicollinearity: the predictors are not highly correlated with each other (this is where factor analysis is SUPER important, because by default, a factor analysis creates factors that are as distinct from each other as the data would allow), which can be checked by looking at Variance Inflation Factor values.
- Homoscedasticity (a.k.a. homogeneity of variance): the variance of error is similar across the values of the predictors, which can be checked by plotting standardized residuals against standardized predicted values.
The WorkTango Active Listening Model
The Workplace is changing, that's no surprise. But with it, the solutions we use to recruit, retain, and inspire our talent is also changing.
Just look at the evolution of reward and recognition strategies as an example. While employers used to reward employees every five years for long-service awards, rewards and recognition in organizations focus more on monthly, weekly, or daily timeframes and specific value-sets and behaviors to inspire employees. This positive progression in recognition and reward systems has resulted in greater employee fulfillment and engagement at work.