other survey items must be conducted. This is a time-consuming exercise for large bodies of data. The correlations are used to identify the items to be used in the regression analyses, which are conducted stepwise, and then linearly on the data. The stepwise regression analyses eliminate those items that exert lesser amounts of influence over the data, and the linear regression analyses provides input to the path analysis, the final 'line up' of the primary, causal factors, and the levels of significance of each.

In our real world example above, it was found that the management style present in the division of the company experiencing the difficulty with turnover was responsible for the low job satisfaction. In particular, it wa

The sole purpose of the root cause analyses is to identify the smallest number of issues that can be shown to drive, control, or predict the largest number of issues within an organization. Few survey research firms have the capability of determining an organization's root causes because the capability stems from an intimate understanding of psychological research and higher order statistics, and few firms employ individuals with such education and training.

As a result of conducting empirical research through NBRI, management is challenged by both the advantage of incisive, astute intelligence of the psychology of the target population, and what is often the overwhelming task of relating, organizing, and prioritizing a large number of issues.

Some organizations choose to limit the amount of information they obtain in an attempt to avoid 'information overload'. However, it is clearly best to gather all of the customer survey and/or employee survey information one can while expending the time and effort to do so, as the costs associated with total inclusion are minimal as compared to conducting additional, follow-up research studies. Of greater importance, limiting the amount of information necessitates choosing between issues, often resulting in the omission of certain issues that may, in fact, prove to be key to the organization's success or failure.

Still, gathering comprehensive information is of little value if it is not used to benefit the organization. It is imperative that the information be turned into action as expeditiously as possible. The task of relating, organizing, and prioritizing a large number of issues is subject to time and manpower constraints within any organization, and is best completed by the research consulting firm. Without immediate direction for action plans, research data represents wasted funds, wasted information, unfulfilled expectations, frustrated managers, and an organization that has failed to maximize the opportunity to develop to its full potential.

To turn massive amounts of information into action quickly and effectively, management needs to know the dominant, primary causal factors for the results of the study. For example, we may find that job satisfaction is low and turnover is high in a particular division of a company, while we also find that the same employees feel their compensation and benefits, working relationships, and life balance issues are all at satisfactory levels. Interventions aimed at addressing low job satisfaction, through better job descriptions, training, or career planning, may well decrease the high turnover, but unless it is the root cause of the turnover, the effect will soon fade, and the organization will be faced with the same difficulties it had before the research.

To conduct root cause analyses, correlations between each survey item and all other survey items must be conducted. This is a time-consuming exercise for large bodies of data. The correlations are used to identify the items to be used in the regression analyses, which are conducted stepwise, and then linearly on the data. The stepwise regression analyses eliminate those items that exert lesser amounts of influence over the data, and the linear regression analyses provides input to the path analysis, the final 'line up' of the primary, causal factors, and the levels of significance of each.

In our real world example above, it was found that the management style present in the division of the company experiencing the difficulty with turnover was responsible for the low job satisfaction. In particular, it was

mber of issues.

Some organizations choose to limit the amount of information they obtain in an attempt to avoid 'information overload'. However, it is clearly best to gather all of the customer survey and/or employee survey information one can while expending the time and effort to do so, as the costs associated with total inclusion are minimal as compared to conducting additional, follow-up research studies. Of greater importance, limiting the amount of information necessitates choosing between issues, often resulting in the omission of certain issues that may, in fact, prove to be key to the organization's success or failure.

Still, gathering comprehensive information is of little value if it is not used to benefit the organization. It is imperative that the information be turned into action as expeditiously as possible. The task of relating, organizing, and prioritizing a large number of issues is subject to time and manpower constraints within any organization, and is best completed by the research consulting firm. Without immediate direction for action plans, research data represents wasted funds, wasted information, unfulfilled expectations, frustrated managers, and an organization that has failed to maximize the opportunity to develop to its full potential.

To turn massive amounts of information into action quickly and effectively, management needs to know the dominant, primary causal factors for the results of the study. For example, we may find that job satisfaction is low and turnover is high in a particular division of a company, while we also find that the same employees feel their compensation and benefits, working relationships, and life balance issues are all at satisfactory levels. Interventions aimed at addressing low job satisfaction, through better job descriptions, training, or career planning, may well decrease the high turnover, but unless it is the root cause of the turnover, the effect will soon fade, and the organization will be faced with the same difficulties it had before the research.

To conduct root cause analyses, correlations between each survey item and all other survey items must be conducted. This is a time-consuming exercise for large bodies of data. The correlations are used to identify the items to be used in the regression analyses, which are conducted stepwise, and then linearly on the data. The stepwise regression analyses eliminate those items that exert lesser amounts of influence over the data, and the linear regression analyses provides input to the path analysis, the final 'line up' of the primary, causal factors, and the levels of significance of each.

In our real world example above, it was found that the management style present in the division of the company experiencing the difficulty with turnover was responsible for the low job satisfaction. In particular, it wa

rganization. It is imperative that the information be turned into action as expeditiously as possible. The task of relating, organizing, and prioritizing a large number of issues is subject to time and manpower constraints within any organization, and is best completed by the research consulting firm. Without immediate direction for action plans, research data represents wasted funds, wasted information, unfulfilled expectations, frustrated managers, and an organization that has failed to maximize the opportunity to develop to its full potential.

To turn massive amounts of information into action quickly and effectively, management needs to know the dominant, primary causal factors for the results of the study. For example, we may find that job satisfaction is low and turnover is high in a particular division of a company, while we also find that the same employees feel their compensation and benefits, working relationships, and life balance issues are all at satisfactory levels. Interventions aimed at addressing low job satisfaction, through better job descriptions, training, or career planning, may well decrease the high turnover, but unless it is the root cause of the turnover, the effect will soon fade, and the organization will be faced with the same difficulties it had before the research.

To conduct root cause analyses, correlations between each survey item and all other survey items must be conducted. This is a time-consuming exercise for large bodies of data. The correlations are used to identify the items to be used in the regression analyses, which are conducted stepwise, and then linearly on the data. The stepwise regression analyses eliminate those items that exert lesser amounts of influence over the data, and the linear regression analyses provides input to the path analysis, the final 'line up' of the primary, causal factors, and the levels of significance of each.

In our real world example above, it was found that the management style present in the division of the company experiencing the difficulty with turnover was responsible for the low job satisfaction. In particular, it wa

ay find that job satisfaction is low and turnover is high in a particular division of a company, while we also find that the same employees feel their compensation and benefits, working relationships, and life balance issues are all at satisfactory levels. Interventions aimed at addressing low job satisfaction, through better job descriptions, training, or career planning, may well decrease the high turnover, but unless it is the root cause of the turnover, the effect will soon fade, and the organization will be faced with the same difficulties it had before the research.

To conduct root cause analyses, correlations between each survey item and all other survey items must be conducted. This is a time-consuming exercise for large bodies of data. The correlations are used to identify the items to be used in the regression analyses, which are conducted stepwise, and then linearly on the data. The stepwise regression analyses eliminate those items that exert lesser amounts of influence over the data, and the linear regression analyses provides input to the path analysis, the final 'line up' of the primary, causal factors, and the levels of significance of each.

In our real world example above, it was found that the management style present in the division of the company experiencing the difficulty with turnover was responsible for the low job satisfaction. In particular, it wa

other survey items must be conducted. This is a time-consuming exercise for large bodies of data. The correlations are used to identify the items to be used in the regression analyses, which are conducted stepwise, and then linearly on the data. The stepwise regression analyses eliminate those items that exert lesser amounts of influence over the data, and the linear regression analyses provides input to the path analysis, the final 'line up' of the primary, causal factors, and the levels of significance of each.

In our real world example above, it was found that the management style present in the division of the company experiencing the difficulty with turnover was responsible for the low job satisfaction. In particular, it was found that supervisory training in communications skills would reduce turnover to a greater extent than any other intervention. This intervention was implemented, and the desired results were obtained. Indeed, with root cause analyses, turnover as well as several other concerns not mentioned herein were effectively and efficiently treated with optimal results and minimal interventions.

Clearly, time is of the essence. Organizations must act while the information is fresh, expectations and receptivity are high, and gains from the research can be realized. The Root Cause Analyses provide management with the bottom line of their research studies, so that organizations can be developed comprehensively, to the highest levels possible, as quickly as possible, surpassing the competition in all regards.