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Collecting and Analyzing Diagnostic information

Collecting and Analyzing Diagnostic information Dimensions to Consider in Diagnosis:

In addition to the importance of the consultant having descriptive, analytic, and diagnostic theories, a number of other dimensions are important for the consultant to consider. A description of seven such dimensions follows:
Timing of the diagnostic activities is a significant dimension. For example, it is one thing to collect and analyze data and then to develop a strategy for how to use it, but quite another to gather data about the perceived usefulness and timeliness of doing a survey in the first place. Much time and resources can be wasted if organizational participants are not prepared to work with the data.

Extent of participation is a key aspect of diagnosis. Who, in a preliminary way, decided that diagnosis should take place? Who decided how it should be done? Which people were systematically involved in supplying data, and further in analyzing and describing the dynamics revealed by the data? One person? Two people? The top team? The top team plus others? One or more people in conjunction with a consultant? All of the members of the system or subsystem? One of the underlying assumptions is the efficacy of participative problem identification and diagnosis in contrast to unilateral problem identification and diagnosis.

The dimension of confidentiality, or individual-anonymous vs. group surfacing of data, has important facets. In the early stages of an OD effort, when trust between group members may be low and their feedback skills inadequate, the situation may call for individual interviews, with responses kept anonymous and only reported to the group in terms of themes. As trust is earned and grows, people can become more open in terms of surfacing attitudes, feelings, and perceptions about organizational dynamics in group settings.

The degree to which there was pre-selection of variables vs. emergent selection of variables to be considered is another important dimension. For survey feedback different questionnaires which taps some 19 dimensions under three broad categories: leadership, organizational climate, and satisfaction, are used. Another, “Managerial Grid”, focuses on two dimensions: concern for people and concern for production. Some OD consultants use interviews asking two or three questions, such as: What things are going well in the organization? What problems do you see?

The extent to which data gathering and analysis are isolated events in contrast to being part of a long-range strategy is also important. One usual assumption in OD efforts is that diagnostic activities should be part of an overall plan. Diagnostic activities lead to action program that in turn call for diagnostic activities – this is the action research model.

Diagnostic activities that are not part of any such plan that are prompted by someone’s whim to know “what they are thinking” may produce resentment and resistance and can seriously hinder attempts to get valid data from system members.

The nature of the target population in both preliminary and later systematic data gathering and analysis is also a key dimension. The size and nature of the target group can affect the acceptability of the diagnostic process, what kind of interdependencies can be examined, and what kinds of issues can be worked successfully. The data-providing group can be different from the dataanalyzing group, but in OD, suppliers of the information usually work with their own data in intact work teams. And finally, the type of technique used obviously has a number of important ramifications. By type we mean questionnaire-versus-interview techniques, individual-versus-group surfacing of data, or other categories of techniques that can be differentiated in major ways. As another example of the importance of technique selection an interview can be used for trust building as well as collecting data; a face-to-face conversation is a better vehicle building a relationship than sending someone a questionnaire. Concerns can be expressed and responded to, questions can be answered, and assurances can be provided as how the data will be used, and so on. As another example of the importance of the type of technique selected, giving diagnostic assignments to subgroups in a workshop setting can be a powerful diagnostic technique. But the way these groups are constituted- for example, heterogeneous versus homogenous in terms of rank, position, or aggressiveness-resistance – can be crucial to the amount and candor of the data generated.

Collecting and Analyzing Diagnostic information:

Organization development is vitally dependent on organization diagnosis: the process of co1lecing information that will be shared with the client in jointly assessing how the organization is functioning and determining the best change intervention. The quality of the information gathered, therefore, is a critical part of the OD process.

Data collection involves gathering information on specific organizational features, such as the inputs, design components, and outputs as discussed earlier. The process begins by establishing an effective relationship between the OD practitioner and those from whom data will be collected and then choosing data-collection techniques. Four methods can be used to collect data: questionnaires, interviews, observations, and unobtrusive measures. Data analysis organizes and examines the information to make clear the underlying causes of an organizational problem or to identify areas for future development. The overall process of data collection, analysis, and feedbacks is shown in Figure 26.

The Data Collection and Feedback Cycle The Diagnostic Relationship:

In most cases of planned change, OD practitioners play an active role in gathering data from organization members for diagnostic purposes For example, they might interview members of a work team about causes of conflict among members; they might survey employees at a large industrial plant about factors contributing to poor product quality. Before collecting diagnostic information, practitioners need to establish a relationship with those who will provide and subsequently use it. Because the nature of that relationship affects the quality and usefulness of the data collected, it is vital that OD practitioners clarify for organization members who they are, why the data are being collected, what the data gathering will involve, and how the data will be used. That information can help allay people’s natural fears that the data might be used against them and gain members’ participation and support, which are essential to developing successful interventions. Establishing the diagnostic relationship between the consultant and relevant organization members is similar to forming a contract. It is meant to clarity expectations and to specify the conditions of the relationship. In those cases where members have been directly involved in the entering and contracting process described earlier, the diagnostic contract will typically be part of the initial contracting step. In situations where data will be collected from members who have not been directly involved in entering and contracting, however, OD practitioners will need to establish a diagnostic contract as a prelude to diagnosis. The answers to the following questions provide the substance of the diagnostic contract:

1. Who am I

? The answer to this question introduces the OD practitioner to the organization, particularly to those members who do not know the consultant and yet will be asked to provide diagnostic data.

2. Why am I here, and what am I doing?

These answers are aimed at defining the goals of the diagnosis and data-gathering activities. The consultant needs to present the objectives of the action research process and to describe how the diagnostic activities fit into the overall developmental strategy. 3.

Who do I work for?

This answer clarifies who has hired the consultant, whether it is a manager, a group of managers, or a group of employees and managers. One way to build trust and support for the diagnosis is to have those people directly involved in establishing the diagnostic contract. Thus, for example, if the consultant works for a joint labor—management committee, representatives from both sides of that group could help the consultant build the proper relationship with those from whom data will be gathered.

4. What do I want from you, and why?

Here, the consultant needs to specify how much time and effort people will need to give to provide valid data and subsequently to work with these data in solving problems. Because some people may not want to participate in the diagnosis, it is important to specify that such involvement is voluntary. 5.

How will I protect your confidentiality?

This answer addresses member concerns about who will see their responses and in what form. This is especially critical when employees are asked to provide information about their attitudes or perceptions. OD practitioners can either ensure confidentiality or state that full participation in the change process requires open information sharing. In the first case, employees are frequently concerned about privacy and the possibility of being punished for their responses. To alleviate concern and to increase the likelihood of obtaining honest responses, the consultant may need to assure employees of the confidentiality of their information, perhaps through explicit guarantees of response anonymity. In the second case, full involvement of the participants in their own diagnosis may be a vital ingredient of the change process. If sensitive issues arise, assurances of confidentiality can co-opt the OD practitioner and thwart meaningful diagnosis. The consultant is bound to keep confidential the issues that are most critical for the group or organization to understand. OD practitioners must think carefully about how they want to handle confidentiality issues.

6. Who will have access to the data?

Respondents typically want to know whether they will have access to their data and who else in the organization will have similar access. The OD practitioner needs to clarify access issues and, in most cases, should agree to provide respondents with their own results. Indeed, the collaborative nature of diagnosis means that organization members will work with their own data to discover causes of problems and to devise relevant interventions. 7.

What’s in it for you?

This answer is aimed at providing organization members with a clear delineation of the benefits they can expect from the diagnosis. This usually entails describing the feedback process and how they can use the data to improve the organization.

8. Can I be trusted?

The diagnostic relationship ultimately rests on the trust established between the consultant and those providing the data. An open and honest exchange of information depends on such trust, and the practitioner should provide ample time and face-toface contact during the contracting process to build this trust. This requires the consultant to listen actively and discuss openly all questions raised by participants. Careful attention to establishing the diagnostic relationship helps to promote the three goals of data collection. The first and most immediate objective is to obtain valid information about organizational functioning. Building a data-collection contract can ensure that organization members provide honest, reliable, and complete information. Data collection also can rally energy for constructive organizational change. A good diagnostic relationship helps organization members start thinking about issues that concern them, and it creates expectations that change is possible. When members trust the consultant, they are likely to participate in the diagnostic process and to generate energy and commitment for organizational change. Finally, data collection helps to develop the collaborative relationship necessary for effecting organizational change. The diagnostic stage of action research is probably the first time that most organization members meet the OD practitioner, and it can be the basis for building a longer-term relationship. The datacollection contract and subsequent data-gathering and feedback activities provide members with opportunities for seeing the consultant in action and for knowing her or him personally. If the consultant can show employees that she or he is trustworthy, is willing to work with them, and is able to help improve the organization, then the data-collection process will contribute to the longer-term collaborative relationship so necessary for carrying out organizational changes.

The Data-Collection Process:

The process of collecting data is an important and significant step in an OD program. During this stage, the practitioner and the client attempt to determine the specific problem requiring solution. After the practitioner has intervened and has begun developing a relationship, the next step is acquiring data and information about the client system. This task begins with the initial meeting and continues throughout the OD program. The practitioner is, in effect, gathering data and deciding which data are relevant whenever he or she meets with the client, observes, or asks questions. Of all the basic OD techniques, perhaps none is a fundamental as data collection. The practitioner must be certain of the facts before proceeding with an action program. The probability that an OD program will be successful is increased if it is based upon accurate and in-depth knowledge of the client system. Information quality is a critical factor in any successful organization. Developing an innovative culture and finding new ways to meet customer needs are strongly influenced by the way information is gathered and processed. Organization development is a data-based change activity. The data collected are used by the members who provide the data, and often lead to insights into ways of improving effectiveness. The datacollection process itself involves an investigation, a body of data, and some form of processing information. For our purposes, the word


, which is derived from the Latin verb dare, meaning “to give, is most appropriately applied to unstructured, unformed facts. It is an aggregation of all signs, signals, clues, facts, statistics, opinions, assumptions, and speculations, including items that are accurate and inaccurate, relevant and irrelevant. The word


is derived from the Latin verb informare, meaning “to give form to,” and is used here to mean data that have form and structure. A common problem in organizations is that they are data-rich but information poor: lots of data, but little or no information. An OD program based upon a systematic and explicit investigation of the client system has a much higher probability of success because a careful data collect on phase initiates the organization’s problem solving process and provides a foundation for the following stages. This section discusses the steps involved in the data-collection process.

The Definition of Objectives:



and most obvious step in data collection is defining the objectives of the change program. A clear understanding of these broad goals is necessary to determine what information is relevant. Unless the purpose of data collection is clearly defined, it becomes difficult to select methods and standards. The OD practitioner must first obtain enough information to allow a preliminary diagnosis and then decide what further information is required to verify the problem conditions. Usually, some preliminary data gathering is needed simply to clarify the problem conditions before further large-scale data collection is undertaken. This is usually accomplished by investigating possible problem areas and ideas about what an ideal organization might be like in a session of interviews with key members of the organization. These conversations enable the organization and the practitioner to understand the way things are, as opposed to the way members would like them to be. Most practitioners emphasize the importance of collecting data as a significant step in the OD process. First, data gathering provides the basis for the organization to begin looking at its own processes, focusing upon how it does things and how this affects performance. Second, data collection often begins a process of self-examination or assessment by members and work teams in the organization, leading to improved problem solving capabilities.

The Selection of Key Factors:



step in data collection is to identity the central variables involved in the situation (such as turnover, breakdown in communication and isolated management). The practitioner and the client decide which factors are important and what additional information is necessary for a systematic diagnosis of the client system’s problems. The traditional approach was to select factors along narrow issues, such as pay and immediate supervisors, more recently; the trend has been to gauge the organization’s progress and status more broadly. Broader issues include selecting factors that determine the culture and values of the organization. Organizations normally generate a considerable amount of “hard” data internally, including production reports, budgets, turnover ratio, sales per square foot, sales or profit per employee and so forth, which may be useful as indicators of problems. This internal data can be compared with competitor’s data and industry averages. The practitioner may find, however, that it is necessary to increase the range of depth of data beyond what is readily available. The practitioner may wish to gain additional insights into other dimensions of the organizational system, particularly those dealing with the quality of the transactions or relationships between individuals or groups. This additional data gathering may examine the following dimensions:

What is the degree of dependence between operating teams, departments or units? What is the quantity and quality of the exchange of information and communication between units? What is the degree to which the vision, mission, and the goals of the organization are shared and understood by members? What are the norms, attitudes, and motivations of organization members? What are the effects of the distribution of power and status within the system? In this step, the practitioner and client determine which factors are important and which factors can and should be investigated.

The Selection of a Data-Gathering Method:

The third step in data collection is selecting a method of gathering data. There are many different types of data and many different methods of tapping data sources. There is no one best way to gather data - the selection of a method depends on the nature of the problem. Whatever method is adopted data should be acquired in a systematic manner thus allowing quantitative or qualitative comparison between elements of the system. The task in this step is to identify certain characteristics that may be measured to help in the achievement of the OD program objective and then to select an appropriate method to gather the required data. Some major data collecting methods follow.

Methods for Collecting Data:


four major techniques

for gathering diagnostic data are questionnaires, interviews, observations, and unobtrusive measures. Table 3 briefly compares the methods and lists their major advantages and problems. No single method can fully measure the kinds of variables important to OD because each has certain strengths and weaknesses. For example, perceptual measures, such as questionnaires and surveys, are open to self-report biases, such as respondents’ tendency to give socially desirable answers rather than honest opinions. Observations, on the other hand, are susceptible to observer biases, such as seeing what one wants to see rather than what is really there. Because of the biases inherent in any data-collection method, we recommend that more than one method be used when collecting diagnostic data. If data from the different methods are compared and found to be consistent, it is likely that the variables are being measured validly. For example, questionnaire measures of job discretion could be supplemented with observations of the number and kinds of decisions employees are making. If the two kinds of data support one another, job discretion is probably being accurately assessed. If the two kinds of data conflict, then the validity of the measures should be examined further— perhaps by using a third method, such as interviews.

Table 3: A Comparison of Different Methods of Data Collection A Comparison of Different Methods of Data Collection Method Major Advantages Major Potential Problems

Questionnaires Responses can be quantified and easily summarized Easy to use with large samples Relatively inexpensive Can obtain large volume of data non-empathy Predetermined questions/missing issues Over-interpretation of data Response bias Interviews adaptive-allows data collection on a range of possible subjects Source of “rich” data Empathic Process of interviewing can build rapport Expense Bias in interviewer responses coding and interpretation difficulties self-report bias Observations collects data on behavior, rather than reports of behavior Real time, not retrospective Adaptive coding and interpretation difficulties Sampling inconsistencies Observer bias and questionable reliability Expense

Unobtrusive measures Non-reactive- no response bias High face validity Easily quantified Access and retrieval difficulties Validity concerns Coding and interpretation difficulties


One of the most efficient ways to collect data is through questionnaires. Because they typically contain fixed-response queries about various features of an organization, these paper-and-pencil measures can be administered to large numbers of people simultaneously. Also, they can be analyzed quickly, especially with the use of computers, thus permitting quantitative comparison and evaluation. As a result, data can easily be fed back to employees. Numerous basic resource books on survey methodology and questionnaire development are available. Questionnaires can vary in scope, some measuring selected aspects of organizations and others assessing more comprehensive organizational characteristics. They also can vary in the extent to which they are either standardized or tailored to a specific organization. Standardized instruments generally are based on an explicit model of organization group, or individual effectiveness and contain a predetermined set of questions that have been developed and refined over time. Several research organizations have been highly instrumental in developing and refining surveys. The institute for Social Research at the University of Michigan and the Center for Effective Organizations at the University of Southern California are two prominent examples. Two of the institute’s most popular measures of organizational dimensions are the Survey of Organizations and the Michigan Organizational Assessment Questionnaire. Few other instruments are supported by such substantial reliability and validity data. Other examples of packaged instruments include Weisbord’s Organizational Diagnostic Questionnaire, Dyer’s Team Development Survey, and Hackman and Oldham’s Job Diagnostic Survey. In fact, so many questionnaires are available that rarely would an organization have to create a totally new one. However, because every organization has unique problems and special jargon for referring to them, almost any standardized instrument will need to have organization-specific additions, modifications, or omissions. Customized questionnaires, on the other hand, are tailored to the needs of a particular client. Typically, they include questions composed by consultants or organization members, receive limited use, and do not undergo longer-term development. They can be combined with standardized instruments to provide valid and reliable data focused toward the particular issues facing an organization. Questionnaires, however, have a number of draw backs that need to be taken into account in choosing whether to employ them for data collection. First, responses are limited to the questions asked in the instrument. They provide little opportunity to probe for additional data or to ask for points of clarification, second, questionnaires tend to be impersonal, and employees may not be willing to provide honest answers. Third, questionnaires often elicit response biases, such as the tendency to answer questions in a socially acceptable manner. This makes it difficult to draw valid conclusions from employees’ self-reports.


A study of 245 OD practitioners found that interviewing is the most widely used data- gathering technique in OD programs. Interviews are more direct, personal, and flexible than surveys and are very well suited for studies of interaction and behavior. Two advantages in particular set interviewing apart from other techniques. First, interviews are flexible and can be used in many different situations. For example, they can be used to determine motives, values, and attitudes. Second, interviewing is the only technique that provides two-way communication. This permits the interviewer to learn more about the problems, challenges, and limitations of the organization. Interviewing usually begins with the initial intervention and is best administered in a systematic manner by a trained interviewer. Data-gathering interviews usually last at least one hour; the purpose is to get the interviewees to talk freely about things that are important to them and to share these perceptions in an honest and straightforward manner. In the author’s experience, people really want to talk about things that they feel are important. If the OD practitioner asks appropriate questions, interviewing can yield important results. The advantage of the interview method is that it provides data that are virtually unobtainable through other methods. Subjective data, such as norms, attitudes, and values, which are largely inaccessible through observation, may be readily inferred from effective interviews. The disadvantages of the interview are the amount of time involved, the training and skill required of the interviewer, the biases and resistances of the respondent and the difficulty of ensuring comparability of data across respondents. The interview itself may take on several different formats. It can be directed or non-directed. In a

directed interview,

certain kinds of data are desired, and therefore specific questions are asked. The questions are usually formulated in advance to ensure uniformity of responses. The questions themselves may be open

Organization Development – MGMT 628 VU

ended or closed.

Open- ended

questions allow the respondent to be free and unconstrained in answering, such as “How would you describe the work atmosphere of this organization?” The responses may be very enlightening, but may also be difficult to record and quantify.

Closed questions,

which can be answered by a yes, no. or some other brief response, are easily recorded and are readily quantifiable. In a

non-directed interview

the interview’s direction is chosen by the respondent, with little guidance or direction by the interviewer. If questions are used in a non-directed interview, open-ended questions will be more appropriate than closed questions. A non-directed interview could begin with the interviewer saying, “Tell me about your job here.” This could be followed by “You seem to be excited about your work.” The data from such an interview can be very detailed and significant, but difficult to analyze because the interview is unstructured. Interviews may be highly structured, resembling questionnaires, or highly unstructured, starting with general questions that allow the respondent to lead the way. Structured interviews typically derive from a conceptual model of organization functioning; the model guides the types of questions that are asked. For example, a structured interview based on the organization-level design components would ask managers specific questions about organization structure, measurement systems, human resources systems, and organization culture. Unstructured interviews are more general and include broad questions about organizational functioning, such as: What are the major goals or objectives of the organization or department? How does the organization currently perform with respect to these purposes? What are the strengths and weaknesses of the organization or department? What barriers stand in the way of good performance? Although interviewing typically involves one-to-one interaction between an OD practitioner and an employee, it can be carried out in a group context. Group interviews save time and allow people to build on others’ responses. A major drawback, however, is that group settings may inhibit some people from responding freely. A popular type of group interview is the focus group or sensing meeting. These are unstructured meetings conducted by a manager or a consultant. A small group of ten to fifteen employees is selected representing a cross section of functional areas and hierarchical levels or a homogenous grouping, such as minorities or engineers. Group discussion is frequently started by asking general questions about organizational features and functioning, an intervention’s progress, or current performance. Group members are then encouraged to discuss their answers more fully. Consequently, focus groups and sensing meetings are an economical way to obtain interview data and are especially effective in understanding particular issues in greater depth. The richness and validity of the information gathered will depend on the extent to which the manager or consultant develops a trust relationship with the group and listens to member opinions. Another popular unstructured group interview involves assessing the current state of an intact work group. The manager or consultant generally directs a question to the group, calling its attention to some part of group functioning. For example, group members may be asked how they feel the group is progressing on its stated task. The group might respond and then come up with its own series of questions about barriers to task performance. This unstructured interview is a fast, simple way to collect data about group behavior. It allows members to discuss issues of immediate concern and to engage actively in the questioning and answering process. This technique is limited, however, to relatively small groups and to settings where there is trust among employees and managers and a commitment to assessing group processes. Interviews are an effective method for collecting data in OD. They are adaptive, allowing the interviewer to modify questions and to probe emergent issues during the interview process. They also permit the interviewer to develop an empathetic relationship with employees, frequently resulting in frank disclosure of pertinent information. A major drawback of interviews is the amount of time required to conduct and analyze them. Interviews can consume a great deal of time, especially if interviewers take full advantage of the opportunity to hear respondents out and change their questions accordingly. Personal biases also can distort the data. Like questionnaires, interviews are subject to the self-report biases of respondents and, perhaps more important, to the biases of the interviewer. For example, the nature of the questions and the interactions between the interviewer and the respondent may discourage or encourage certain kinds of responses. These problems suggest that interviewing takes considerable skill to gather valid data. Interviewers must be able to understand their own biases, to listen and establish empathy with respondents, and to change questions to pursue issues that develop during the course of the interview.)


One of the more direct ways of collecting data is simply to observe organizational behaviors in their functional settings. The OD practitioner may do this by walking casually through a work area and looking around or by simply counting the occurrences of specific kinds of behavior (for example, the number of times a phone call is answered after three rings in a service department). Observation can range from complete participant observation, in which the OD practitioner becomes a member of the group under study, to more detached observation, in which the observer is clearly not part of the group or situation itself and may use film, videotape, and other methods to record behaviors. Observations have a number of advantages. They are free of the biases inherent in self-report data. They put the practitioner directly in touch with the behaviors in question, without having to rely on others’ perceptions. Observations also involve real-time data, describing behavior occurring in the present rather than the past. This avoids the distortions that invariably arise when people are asked to recollect their behaviors. Finally, observations are adaptive in that the consultant can modify what he or she chooses to observe, depending on the circumstances. Among the problems with observations are difficulties interpreting the meaning underlying the observations. Practitioners may need to devise a coding scheme to make sense out of observations, and this can be expensive, take time, and introduce biases into the data. Because the observer is the data-collection instrument, personal bias and subjectivity can distort the data unless the observer is trained and skilled in knowing what to look for; how, where, and when to observe; and how to record data systematically. Another problem concerns sampling: observers not only must decide which people to observe; they also must choose the time periods, territory, and events in which to make those observations. Failure to attend to these sampling issues can result in highly biased samples of observational data. When used correctly, observations provide insightful data about organization and group functioning, intervention success, and performance. For example, observations are particularly helpful in diagnosing the interpersonal relations of members of work groups. As discussed earlier, interpersonal relationships are a key component of work groups; observing member interactions in a group setting can provide direct information about the nature of those relationships.

Unobtrusive Measures:

Unobtrusive data are not collected directly from respondents but from secondary sources, such as company records and archives. These data are generally available in organizations and include records of absenteeism or tardiness; grievances; quantity and quality of production or service; financial performance; meeting minutes; and correspondence with key customers, suppliers, or governmental agencies. Unobtrusive measures are especially helpful in diagnosing the organization, group, and individual outputs, talked earlier. At the organization level, for example, market share and return on investment usually can be obtained from company reports. Similarly, organizations typically measure the quantity and quality of the outputs of work groups and individual employees. Unobtrusive measures also can help to diagnose organization-level design components—structures work systems, control systems, and human resources systems. A company’s organization chart, for example, can provide useful information about organization structure. Information about control systems usually can be obtained by examining the firm’s management information system, operating procedures, and accounting practices. Data about human resources system often are included in a company’s personnel manual. Unobtrusive measures provide a relatively objective view of organizational functioning. They are free from respondent and consultant biases and are perceived as being “real” by many organization members. Moreover, unobtrusive measures tend to be quantified and reported at periodic intervals, permitting statistical analysis of behaviors occurring over time. Examining monthly absenteeism rates, for example, might reveal trends in employee withdrawal behavior. The major problems with unobtrusive measures occur in collecting such information and drawing valid conclusions from it. Company records may not include data in a form that is usable by the consultant. If, for example, individual performance data are needed, the consultant may find that many firms only record production information at the group or departmental level. Unobtrusive data also may have their own builtin biases. Changes in accounting procedures and in methods of recording data are common in organizations, and such changes can affect company records independently of what is actually happening in the organization. For example, observed changes in productivity over time might be caused by modifications in methods of recording production rather than by actual changes in organizational functioning. Despite these drawbacks, unobtrusive data serve as a valuable adjunct to other diagnostic measures, such as interviews and questionnaires. For example, if questionnaires reveal that employees in a department are dissatisfied with their jobs, company records might show whether that discontent is manifested in heightened withdrawal behaviors, in lowered quality work, or in similar counterproductive behaviors.

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