Organizational Effectiveness Tools:
Employee Surveys and Linkage Analysis

Balanced Scorecard | Change Management | Customer Surveys
> Employee Surveys | Process Management

Surveys are one of the most common tools of the trade. Unfortunately, there are many surveys which do not collect the information their writers intended; which raise false expectations; which are not used to generate action; or which bias the information they are supposed to collect.

Some surveys are designed to collect information about a single, specific topic; others are more global in nature. There are satisfaction, benefits, and cultural surveys. Sometimes, they are called "assessments" or "instruments," but they are still surveys, and the goal is still actionable information.

Types of Surveys

Whether they are given to employees, customers, or suppliers, surveys can be roughly divided into several types.

Tactical Surveys

The Tactical Survey is designed to answer a specific question. For example:

• Is this a good policy?
• Do people understand this process?
• Is this process working for customers?
• Did the change effort get rolled out properly at each level?

For example, one company used a tactical survey to confirm that an ethic program was not needed; and found out that it was, indeed, important and provided a substantial competitive advantage. Thus, tactical surveys can shed light on key issues and confirm (or deny) assumptions, preventing fiascos.

The tactical survey should be very short and to the point, sent out and collected quickly.

Using tactical surveys to follow through on change efforts can help to find where change has and has not gone well, so that the change agents can learn from the best and help the rest.

Thanks to electronics, tactical surveys are easier, less expensive, and faster to conduct. They should become part and parcel of the decision-making and change management processes - if used with care.

Focused Omnibus Surveys ("Strategic Surveys")

Gathering information on a larger number of issues is the focused omnibus, or strategic, survey. This covers issues related to an organization's key goals and strategies, so it is considerably larger than a tactical survey, but it is still relatively focused. These surveys can be used as part of a strategic measurement system (e.g. balanced scorecard), or as a general diagnostic and motivation-for-change tool.

General Omnibus Surveys

Less common now are relatively unfocused omnibus surveys which cover a large number of topics. While these topics may be directly relevant to the organization, these surveys are generally "off the shelf" and only a few questions are customized. They can also be a good diagnostic tool, but are often too long to be time and cost effective. Respondents may also get careless on a longer survey, and make mistakes or rate many attributes the same way to finish without "wasting too much time."

Comparative Surveys

While not technically a separate category, comparative surveys are often used in customer research to find the relative value of a product or service. In a comparative survey, the products and services (or working environment, or brand image, etc.) of different organizations are compared. This provides a greater perspective than simply asking about a single organization.

Pulse Surveys

Specifically designed to measure how well a change effort is going and provide advance warning of problems, pulse surveys are usually very short and have the same questions each time they are given. Pulse surveys are used to examine trends, and immediately catch changes so the organization can react quickly. They can be used with employees, customers, or suppliers, and generally are only given to samples to avoid "over-surveying."

Survey Advantages

Surveys are relatively fast and cheap. A single survey can be used to obtain a great deal of information in a short span of time. Development takes much more time than administration, coding, and analysis, so once a survey is developed, it can easily and cheaply be used again.

They allow statistical analysis and quick, easy-to-understand reporting of relatively unambiguous results. They can be kept bias-free with greater ease than some other methods.

Survey Disadvantages

Whereas a good interviewer can establish rapport and trust, surveys rely entirely on previously established trust and cultural norms. They may not be able to elicit honest responses, especially regarding sensitive issues. Respondents can fill out one part of the survey but not others, leading to questions of validity and bias.

Surveys cannot change themselves to explore interesting areas.

There are self-report biases (people may incorrectly report information about their feelings, attitudes, and actions for a variety of reasons). There are usually many people who do not respond, who may be different from the general population. Since a "good" response rate is about 50%, one must wonder what the "other half" really things.

Surveys cannot measure actual behavior, only the behavior people report.

Many surveys use inappropriate scales or questions, which allow too respondents too much room for interpretation.

Survey Options - Question Types

Most surveys should include both open-ended and closed questions. Open-ended questions allow people to express themselves more completely, which is more satisfying, and also let them set the agenda more (especially general questions).

Closed-ended questions (e.g. "How satisfied are you? 1 = very dissatisfied to 5 = very satisfied) are easy to deal with statistically, take little time to complete, and take little time to enter into a computer. Therefore, there are usually quite a few of these.

Some questions ask people to check one or more relevant items (e.g., "What motivates you the most? 1. Money. 2. Benefits. 3. Satisfaction of a job well done. 4. Like to see chocolate bunnies coming out of the big shiny machine.")

Where Possible...

• Avoid "binary" questions that "lose" information.

  Example: "Are you satisfied?" should be "How satisfied are you?" and "Do you want this service?" should be "How much do you want this service?" or, better, "How much would you pay for this service?"

• Use "behavioral" anchors to avoid messy results and inferences.

  This way, you can avoid having to guess whether all respondents interpret "very often" the same way - much less whether they interpret it the same way you do.

  Example: "Several times a day" to "Never" rather than "Very frequently" to "Never." 

• When necessary, define the anchors completely.

  While this creates a statistical violation (you can no longer simply assume the distance between each number is identical in size), the effects may be minimal, and you may be able to avoid a great deal of bias and guessing whether respondents are interpreting the scales the same way.

  Example: Rather than simply asking "How well does the organization's mission guide your actions? -- Completely to Not at all," define each step, e.g. "I refer to it each time I make a decision," to "I never use the mission to make real decisions," with intermediate steps also filled in.

Off-the-Shelf?

Pre-manufactured surveys may or may not be useful for you. They can save development time and provide you with a "normed group" to compare your organization with (assuming various response biases are similar across organizations). However, they may also be expensive and the questions may not be completely usable.

Ask to see a dummy report before you order a survey if it comes with reporting. If you cannot understand the implications and next steps, ask about customized reports, or don't buy the reporting feature.

Customized Surveys can include pre-manufactured surveys with optional items for your use, home-grown surveys, or surveys used by consultants and modified for your purposes.

They are often the best solution when resolving internal issues is more important than benchmarking and finding out how "normal" your organization is. To create your own survey, it is best to hire a consultant with experience in survey development first. Explore the issues with a small interview project and establish content areas before making up questions. The content should guide the nature of the survey.

The golden rule is to look at every question and ask, "What will I do with this information when I get it? How will I use it?". Then ask if the survey answers all of your questions and concerns. Few pass this test the first time around.

Business Builders Consulting Survey Services

Our survey practice is flexible and able to work on any or all parts of a project. We always design surveys that include the four key issues for effective action.

We can work with you to design and administer a survey which provides you with actionable information to be an effective tool for change.

Linkage Analysis and Driver Analysis 

One of the more interesting tools to arrive in recent years has been linkage analysis. One way to describe linkage analysis is through examples:

• One item of an employee survey is known to be highly correlated with employee retention. Issues which seem to predict retention are statistically identified.
• An employee survey from 1998 is combined with customer survey data from 1999. Using the same methods, we can try to find the employee survey items (or categories) which best predict customer satisfaction or loyalty.
• Using an enrollment database and student survey data, along with any of the techniques listed above, predicting retention and academic achievement based on student satisfaction, SAT scores, high school GPA, age, and other factors.

Statistically, there are many important issues to consider with regard to linkage analysis. Most of the time, people use cross-sectional data - that is, we look at different locations or people at the same time. Generally, I have tried to have the predictors from one year and the outcomes from a later year, but this is not always possible, and is only a partial answer in any case. We are making many assumptions about causality.

Note: I am not making a distinction between driver analysis and linkage analysis. Driver analysis can refer to the attempt to find drivers of one factor, such as intention to leave the company, within a single data source, such as an employee survey; linkage analysis is similar but uses more than one data source (hence "linkage").

Some of the methods used are:

• LISREL - essentially, models are statistically tested to see how well they fit the data. One could generate models using theory or other statistical techniques and check them for goodness-of-fit using LISREL. This tests the entire model rather than a single relationship. (A model could be as simple as employee satisfaction increases customer satisfaction which increases revenue).
• CHAID, CART, and many other "tree-building" systems - using a wide variety of techniques, the data are analyzed to see which splits can best predict the outcomes. For example, the decision to buy an Acme widget can best be predicted first by a customer's prior widget purchase, then (for purchasers) by their satisfaction and (for nonpurchasers) by their position in an organization.
• MULTIPLE REGRESSION -Regression is the most accessible method, as well as one of the most robust. In most cases, regression will be enough to show a relationship.
• DISCRIMINANT ANALYSIS - This tends to have similar results as regression, but is used to "work backwards."
• PATH ANALYSIS - Not covered by this site.

One problem which is generally not covered refers to the real life use of linkage. Often, corporations and other organizations use the "linkage map" to focus their actions on issues which will have the highest impact on some outcome - customer service, profit, turnover, etc. If this is the end goal, then most methods, which are concerned with the "truth" (or goodness of fit) between the whole model and the data, may not be appropriate, because you really want to know what you can do to get the most change in the outcome. Sometimes, it pays to ignore the issue of shared variance and work on the major contributors to an outcome individually.

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