By Jon Montgomery and Michael Lieberman
Becoming a measurement-managed organization is a process which involves defining a strategic model that clearly articulates the relationships between business objectives and the factors that drive them. In the financial services sector these factors typically include people, customer/market, operational, and financial issues, which compliance and regulatory issues often accompany. The role that employees play in an organization’s success in leveraging the brand among customers and constituents can be significant. Part of the process of developing a measurement-managed organization is to understand better the effect that employee satisfaction has on business results.

Large financial organizations spend a lot of money and effort trying to understand and manage the hundreds or even thousands of employees in many different operating areas or physical locations. Performance results are typically evaluated on a company level as part of an annual business review. This, however, is not the whole picture. When one is looking at the company, all units are assumed to be “average” — the company picture is really a composite of all the “local” operations.

This misses significant inter-unit variation and the opportunity to improve performance or correct problems within a specific business unit. A basic problem is that we can always “know more than we can prove”. HR managers at large financial services organizations “know” that:
•    Management teams of different business units are not equally effective.
•    Unit management impacts employee performance.
•    Employee performance impacts sales and client satisfaction.
•    Management performance impacts employee turnover and morale.

How do they “prove” it? More importantly, how do they identify the specific areas that each business unit management needs to improve? Most importantly, what do they need to do differently that will improve employee performance, which can improve overall business results? The case study below demonstrates proven employee satisfaction methodologies to measure employee attitudes and how to gauge important factors to keep employees happy and productive. The article will set up a framework within which employee satisfaction can be measured, then describe a concrete methodology to apply these findings to the workplace.

The Test
The company has more than 100 business units/locations and employs several thousand people worldwide. In our survey, more than 40 questions were initially asked which covered training, management, personal development, the company and clients. The test objectives were to identify the issues that are most important for employee retention and lower turnover. We sought to demonstrate that significant employee differences can be measured between individual operating units, and to develop action reports for management that highlight differences between units.

The Basics
Key-driver analysis measures the strength of descriptive attributes or performance ratings in relation to a strategic characteristic. What is driving your brand in its market segment? What would make its market share rise? What makes your employees happy at work? Why? In regression analysis, the strategic characteristic is called the dependent variable. What we are looking for is significance. If an attribute is positively significant, this indicates that it has a positive relationship with the dependent variable. If the attribute is high, the dependent variable is high. If the attribute is low, the dependent variable is low. If an attribute is negatively significant, the opposite is true. High attribute, low dependent variable.

Within HR the dependent variable should not only be defined as the goal of the employer — that is, employee retention, employee satisfaction, etc. It should also include an evaluation of the impact on customer satisfaction. What we are looking for is the “why”. Why are employees going to remain with the company? Why are they satisfied with their jobs? What aspects of their employment drives their satisfaction? How does their performance impact the company’s overall business objectives?

The survey is constructed as a series of statements within five different categories. Employees are asked to rate on a one to seven scale whether a particular aspect of the business unit is important, and whether they agree or disagree with statements about their business unit or the company in general.

Results
Table one shows the relative area or category importance that contributes to employee “intent to stay”. These normalized relative importance give an indication of the importance of the overall areas of employee concerns.

After running regressions of the individual questions on the employee survey, the results indicate that there are eight attributes that positively drive intent to stay. Five are negatively significant.

Figure one shows the eight main question drivers for employee retention. The beta scores are to be interpreted relative to each other. If “identifying, nurturing and promoting top performers” has a beta of .26, and “I receive regular feedback about my performance” has a beta of .12, for example, we can say that nurturing top performers is roughly twice as important as receiving regular feedback.

Figure One: Intent To Stay Drivers

There are also five attributes that are negatively related to intent to stay. To interpret negative drivers, it is useful to insert a “not” within the attribute. In figure two we have inserted this to further illuminate the findings.

Figure Two: Intent To Stay Drivers

Looking closely at figure two, we were able to advise our client on immediate actions that need to be undertaken to improve employee perceptions and performance. The company needs to reinvest in management communication, employee benefits and training

Functional Diverse Results
Length of employment, for example, directly affects intent to stay priorities. Employees with more than five years tenure put more emphasis on:

1. Manager teamwork.
2. Receive regular feedback.
3. Boss treats them fairly.
4. Products are well received.

Employees with five or fewer years of tenure are more concerned with:

1. Staff is happy.
2. Company pride.
3. High standards at the company.
4. Receive enough training.
5. Business unit management cares.

Differences between staff positions also have differing priorities that are linked to employee retention. It is often important to filter the regression by key groups to produce more precise, actionable results.

Real World Impact
Beyond the statistical “proof” that we developed in our initial testing and development of the employee survey, we also tracked business unit revenue, client satisfaction, and employee retention over 12 months. Business unit management teams who were able to drive their employee ratings consistently higher also:
1.    Out-performed the company results on client satisfaction.
2.    Out-performed the company on sales results.
3.    Improved their employee retention and beat the overall company results, which also improved.

HR managers know that turnover is expensive, but many were unable to quantify the cost of turnover when asked in a recent poll. The cost of hiring and training a new employee can vary greatly — from several thousand dollars for entry-level employees to over $100,000 for top executives. Costs that are more difficult to estimate include client service disruption, emotional costs, loss of morale, burnout/absenteeism among remaining employees, loss of experience, continuity, and “corporate memory”.

Measuring and improving employee retention is an increasingly vital challenge which is essential to the smooth function of “multi-location” operations that involve far flung managers and staff personnel. The power of key-driver analyses not only identifies what is important to improving employee performance; it provides a measurable basis for each business unit to target the specific areas that needed to improve. Not all management teams are equally good at communication, training, etc. The employee survey system that was developed lets managers know their real effectiveness on the important issues that impact employee performance, and how to improve the company-employee relationship.

Jon Montgomery is a partner at Hudson Group, a marketing research and consulting firm in New York City. He can be reached at +1 212 724 2566, or jonmont@hudsongroup.net..
Michael Lieberman is founder and president of Multivariate Solutions, a statistical and marketing research consulting firm that works with major advertising, public relations, and political strategy firms. He can be reached at 1 646-257-3794, or at michael@mvsolution.com.