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Statistical Modeling
There are a variety of procedures used for statistical modeling. While we will not dwell on their range and specifications here, this section will take you through how we use one such approach, referred to as Path Analysis, to help tell a more complete story of a company's business and the important relationships that drive it.

Path analysis allows us to look at the relationships among a number of interrelated areas on a survey and see how they work individually and together in helping to produce desired outcomes.  The diagram below is a sample path diagram similar to the ones that we often obtain when we use modeling procedures to understand the findings we obtain on employee surveys.  This approach is also very useful in customer surveys.  Sound statistical modeling, however, requires that you have a fairly large sample size, generally of several hundred or more survey respondents.

Sample Path Diagram
A sample path diagram is presented below.  The boxes represent the factors in the model that are influencing employee loyalty and commitment.  Within each box is a statistical value labeled R2.  This value is an expression of the amount of variability in that factor that is accounted for in the data.  It can vary from 0 (none at all) to 1.0 (completely accounted for).  When these values are low (well below 0.5), then we are not accounting for that factor or dimension well and we may wish to add or refine the questions in that area on future surveys.

Each box or each line of text has arrows associated with it.  With each arrow (or with each line of text on the right hand side) there is a value labeled "r".  This is the correlation that the factor or survey item has with the other factors or outcome variables that it is associated with.  These values also vary between 0 and 1.0.  But, they will tend to be a bit lower than the R2 values because they are linking only a single item or a single factor to another.  Generally, correlations of 0.2 are considered low (modest), those around 0.4-0.6 are moderate, and those approaching or exceeding 0.8 are considered high (strong).

Path modeling requires that we define a desired outcome.  In this case, we selected employee commitment and loyalty, which was assessed using a series of questions that asked employees about how committed they are to a career with the company and how likely they would be to stay with the company even though they were offered a comparable job elsewhere. 

Analysis of a Path Diagram
What does the path diagram tell us?  First, we are accounting for a respectable 67% of the variation in our outcome measure - labeled Employee Commitment and Loyalty in the yellow box on the left hand side of the diagram above.  This, combined with some statistical tests that we can run, helps us to have confidence that we have a good model.

The path diagram, or statistical model, will not include all items included on a survey.  Rather, it will help us to identify the most important dimensions related to our desired outcomes and to pinpoint which items are contributing the most to those dimensions.  This helps us to identify action areas and to make strategic recommendations to companies on how to move their key relationships forward.  The items in text only (not enclosed in boxes) represent those that best captured each dimension uncovered in the current survey.  The correlations in the parentheses that follow give an indication of which items have the most impact.

Second, we can see that job satisfaction (in this case assessed by items on how much employees say they like their jobs and on how likely they would be to recommend the company to others as a good place to work) is an important predictor of loyalty and commitment.  Obviously, it is important that employees like their jobs.  But, simply liking one's job is not the only the only dimension that accounts for loyalty and commitment.  Other important factors are views of leadership, perceptions of their managers, having a sense of empowerment, satisfaction with compensation and benefits, opportunities for advancement, and a feeling of teamwork.  Day-to-day job satisfaction , however, is a necessary precursor to employee loyalty and commitment so leadership will need to address areas in which weaknesses are contributing to suboptimal levels of employees' job satisfaction.

Examine Strengths & Weaknesses
Views of leadership have relatively little impact on job satisfaction per se, but they have a moderate impact on employee loyalty and commitment.  In order for employees to be committed to long term careers with the company, they need to have confidence in their leadership.  This is especially true for how well leadership addresses and manages issues internal to the company, but it is also influenced by how well they address external issues and the degree of trust that employees have in them.  By looking at how the company fares on these individual items and examining open-ended comments, we can see where the company's strengths and weaknesses are in the employees' eyes and we can get an idea of some of the issues that employees consider most pressing and how they feel about how leadership is or is not addressing these issues.

Perceptions of one's manager, in contrast, have a relatively strong impact on job satisfaction.  It is important to the satisfaction of employees that their managers are effective team leaders, that they mentor and guide them in the work and careers, and that they are both accessible to them and are open to the employees' input.  Conversely, satisfaction with managers, on its own,  has a relatively smaller impact on loyalty and satisfaction.  This may be because managers are mobile in this company and are not considered by the employees to be a relatively fixed parts of their long term work environment.  Again, by looking at the strengths and weaknesses among the ratings of managers on individual items (and open-ended comments if they are available) we can tell a fuller story.  Perhaps, for example, managers are not fairing well overall on items reflecting team leadership or in mentoring their employees (suggesting the need for more in-service training and management review in these areas).

It is also interesting to note that perceptions of leadership and of managers are not correlated very strongly with each other.  Having a good manager, or good leadership, is viewed as relatively independent by the employees.  A good manager is not going to have a very strong influence on views of corporate leadership nor is strong leadership likely to ensure that employees are happy with their managers.  This may be the result of having collected data from employees with a large, multinational firm where there are quite a few levels separating most managers from upper level corporate leadership.

Employee Empowerment
A sense of empowerment among employees is also important, both for their job satisfaction and for their loyalty and commitment to the company.  Employees in this survey are saying that they value having the authority to do their jobs and having input into decision making.  Interestingly, the path suggests (see the correlation between ratings of managers and of empowerment) that managers play a key role in enabling a sense of empowerment among employees.  This then becomes an area worth focusing on with managers in helping them to improve how they work with their direct reports.

As we would expect, compensation and benefits are important as well.  Of note, however, is the fact that opportunities for promotion are even more important for job satisfaction and for long term commitment.  By looking at how the company is faring on individual ratings on the items that feed into these dimensions, and by reviewing the comments received for any open-ended questions in these areas, leadership may find ways to increase satisfaction and loyalty without actually having to re-adjust compensation or benefits.  Another interesting point to note is that items relating to perceptions of equal opportunity and opportunities for advancement are correlated with each other, though not highly.  This suggests that further analyses are in order to explore differences in employees' perceptions of opportunities for advancement among relevant employee subgroups (e.g., to look for gender or ethnic differences, to explore potential differences among job types or levels, etc.) and if there are differences, to pay particular attention to the comments made by respondents in groups that view themselves as having less opportunity for advancement in the company.  Other conjoint analyses (looking at the relationship among two or more items) might be run to evaluate the extent to which this appears to be a problem among high performers in particular.  If so, this would be further impetus for addressing these issues within the company.

The last dimension identified is the sense of teamwork among employees.  This is especially important for job satisfaction and it also impacts on employee loyalty and commitment.  This suggests that it is important for managers to foster collaboration within and across workgroups and that internal communications that bolster company spirit can serve to boost satisfaction and retention among employees.  These, in turn, represent important areas to investigate in other company-wide research, including communications audits and management reviews (e.g., 360o feedback studies).

This rather long discussion actually represents only the tip-of-the-iceberg in what we can learn from statistical modeling of the data obtained with well-designed surveys.  Indeed, in addition to surfacing important relationships and suggesting areas for tactical and strategic initiatives, a good statistical model can raise important questions for future investigations.  These questions might suggest the need for further interviews or focus group work and redesign of survey content in future rounds.  The accompanying analyses of strengths and weaknesses and the identification of differences among subgroups also help to identify areas to track in future surveys and to guide leadership towards addressing the most critical issues and those that are most likely to have the greatest impact on improving business relationships.

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