ee overriding perceptions commonly held by each customer population that are driving behavior. With appropriate interventions to just these one to three issues, Clients experience increases in 40% to 80% of all issues addressed by the customer survey.

The 'third leg of the stool,' so to speak, is to identify those employee attitudes, opinions, or beliefs (perceptions) that drive employee behaviors directly impacting customer intent to return. This analysis process is similar, although all employee data is correlated and regressed against only the customer data relating to intent to return. These root causes are almost always

It is well known that high employee satisfaction contributes significantly to high customer satisfaction, which drives intent to return, and therefore, financial results. High employee satisfaction expresses itself as enthusiasm in one's work, which directly impacts the experience of the customer. Likewise, high customer satisfaction expresses itself as enthusiasm toward a particular organization, its products or services, which directly impacts the intent to return rate. It is a short leap, then, to understand how a high intent to return rate among customers impacts financial results. But with so many variables affecting employee and customer satisfaction, how does one determine those of greatest importance, so that interventions aimed at increasing satisfaction are of maximum effectiveness? The answer is in the root cause analysis derived from employee and customer survey data.

We begin by acknowledging the fact that we are assessing 'human perceptions' when we conduct customer surveys and employee satisfaction surveys and that to each person, perceptions of the way things are create a personal reality. Right or wrong, Perception = Reality. In addition, some perceptions dominate and propel ('drive') other perceptions, and perceptions as a whole determine human behavior. The employee root cause analysis is designed to identify those perceptions in the employee population that drive the greatest number of other perceptions to the greatest extents, because it is those core, or root, perceptions that are driving employee behavior. With appropriate interventions to the root perceptions, or root causes of employee behavior, we change the perceptions and therefore, the behavior.

The Root Cause Analysis involves high-level statistical analyses, such as correlations, stepwise linear regression analyses (modified, proprietary), and psychological path analyses. We require a confidence level of 99.99% and a sampling error of less than 1% in these analyses. From this process, we are able to identify the one, two, or three overriding perceptions commonly held by each population that are driving behavior, and with appropriate interventions to just these one to three issues, Clients experience increases in 40% to 80% of all issues addressed by the employee survey.

The same is true of customer surveys. The customer root cause analysis can assess the perceptions of customers and identify those that drive customer behavior. From the correlations, regressions, and path analyses, we identify the one, two, or three overriding perceptions commonly held by each customer population that are driving behavior. With appropriate interventions to just these one to three issues, Clients experience increases in 40% to 80% of all issues addressed by the customer survey.

The 'third leg of the stool,' so to speak, is to identify those employee attitudes, opinions, or beliefs (perceptions) that drive employee behaviors directly impacting customer intent to return. This analysis process is similar, although all employee data is correlated and regressed against only the customer data relating to intent to return. These root causes are almost always

and customer satisfaction, how does one determine those of greatest importance, so that interventions aimed at increasing satisfaction are of maximum effectiveness? The answer is in the root cause analysis derived from employee and customer survey data.

We begin by acknowledging the fact that we are assessing 'human perceptions' when we conduct customer surveys and employee satisfaction surveys and that to each person, perceptions of the way things are create a personal reality. Right or wrong, Perception = Reality. In addition, some perceptions dominate and propel ('drive') other perceptions, and perceptions as a whole determine human behavior. The employee root cause analysis is designed to identify those perceptions in the employee population that drive the greatest number of other perceptions to the greatest extents, because it is those core, or root, perceptions that are driving employee behavior. With appropriate interventions to the root perceptions, or root causes of employee behavior, we change the perceptions and therefore, the behavior.

The Root Cause Analysis involves high-level statistical analyses, such as correlations, stepwise linear regression analyses (modified, proprietary), and psychological path analyses. We require a confidence level of 99.99% and a sampling error of less than 1% in these analyses. From this process, we are able to identify the one, two, or three overriding perceptions commonly held by each population that are driving behavior, and with appropriate interventions to just these one to three issues, Clients experience increases in 40% to 80% of all issues addressed by the employee survey.

The same is true of customer surveys. The customer root cause analysis can assess the perceptions of customers and identify those that drive customer behavior. From the correlations, regressions, and path analyses, we identify the one, two, or three overriding perceptions commonly held by each customer population that are driving behavior. With appropriate interventions to just these one to three issues, Clients experience increases in 40% to 80% of all issues addressed by the customer survey.

The 'third leg of the stool,' so to speak, is to identify those employee attitudes, opinions, or beliefs (perceptions) that drive employee behaviors directly impacting customer intent to return. This analysis process is similar, although all employee data is correlated and regressed against only the customer data relating to intent to return. These root causes are almost always

mine human behavior. The employee root cause analysis is designed to identify those perceptions in the employee population that drive the greatest number of other perceptions to the greatest extents, because it is those core, or root, perceptions that are driving employee behavior. With appropriate interventions to the root perceptions, or root causes of employee behavior, we change the perceptions and therefore, the behavior.

The Root Cause Analysis involves high-level statistical analyses, such as correlations, stepwise linear regression analyses (modified, proprietary), and psychological path analyses. We require a confidence level of 99.99% and a sampling error of less than 1% in these analyses. From this process, we are able to identify the one, two, or three overriding perceptions commonly held by each population that are driving behavior, and with appropriate interventions to just these one to three issues, Clients experience increases in 40% to 80% of all issues addressed by the employee survey.

The same is true of customer surveys. The customer root cause analysis can assess the perceptions of customers and identify those that drive customer behavior. From the correlations, regressions, and path analyses, we identify the one, two, or three overriding perceptions commonly held by each customer population that are driving behavior. With appropriate interventions to just these one to three issues, Clients experience increases in 40% to 80% of all issues addressed by the customer survey.

The 'third leg of the stool,' so to speak, is to identify those employee attitudes, opinions, or beliefs (perceptions) that drive employee behaviors directly impacting customer intent to return. This analysis process is similar, although all employee data is correlated and regressed against only the customer data relating to intent to return. These root causes are almost always

nce level of 99.99% and a sampling error of less than 1% in these analyses. From this process, we are able to identify the one, two, or three overriding perceptions commonly held by each population that are driving behavior, and with appropriate interventions to just these one to three issues, Clients experience increases in 40% to 80% of all issues addressed by the employee survey.

The same is true of customer surveys. The customer root cause analysis can assess the perceptions of customers and identify those that drive customer behavior. From the correlations, regressions, and path analyses, we identify the one, two, or three overriding perceptions commonly held by each customer population that are driving behavior. With appropriate interventions to just these one to three issues, Clients experience increases in 40% to 80% of all issues addressed by the customer survey.

The 'third leg of the stool,' so to speak, is to identify those employee attitudes, opinions, or beliefs (perceptions) that drive employee behaviors directly impacting customer intent to return. This analysis process is similar, although all employee data is correlated and regressed against only the customer data relating to intent to return. These root causes are almost always

ee overriding perceptions commonly held by each customer population that are driving behavior. With appropriate interventions to just these one to three issues, Clients experience increases in 40% to 80% of all issues addressed by the customer survey.

The 'third leg of the stool,' so to speak, is to identify those employee attitudes, opinions, or beliefs (perceptions) that drive employee behaviors directly impacting customer intent to return. This analysis process is similar, although all employee data is correlated and regressed against only the customer data relating to intent to return. These root causes are almost always different from those driving employee satisfaction.

So, clients are now armed with extremely powerful means of simply and directly impacting customer intent to return, and therefore, financials:

· Root causes of employee perceptions that will increase employee satisfaction (and indirectly increase customer satisfaction),

· Root causes of customer perceptions that will increase customer satisfaction and intent to return, and

· Root causes of employee perceptions that will increase customer intent to return.

Each Root Cause Analysis, whether employee or customer or both, is unique to the client organization. No two RCAs are the same. As Organizational Psychologists, we understand that these all-important employee and customer perceptions are a function of the culture, climate, management style, communication styles, and other dynamics within each unique organization. In addition, as targeted interventions improve certain organizational dynamics, root causes will change. It is imperative, therefore, that action be taken quickly in order to attain the intrinsic dramatic gains of the process, and that the momentum of continuous improvement be ingrained in the psyche of the organization, beginning with Senior Management.

When recommendations are followed, the Total Organization Scores from the Employee and Customer Surveys will each increase a minimum of five (5) normative percentiles within 6 months, which represents a statistically significant difference, i.e., not due to chance, but rather, caused by direct intervention.