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Collecting and Analyzing Diagnostic information:Methods for Collecting Data, Observations

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Lesson 20
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:
1. 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.
2. 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.
3. 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.
4. 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?
5. 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.
6. 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.
7. 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 data-
analyzing 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.
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Organization Development ­ MGMT 628
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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.
Fig 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:
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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-to-
face 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 data-
collection 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.
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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 data-
collection process itself involves an investigation, a body of data, and some form of processing
information. For our purposes, the word data, 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 information 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:
The first 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:
The second 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:
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·
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:
The 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
·Responses can be quantified and ·non-empathy
Questionnaires
·Predetermined questions/missing
easily summarized
·Easy to use with large samples
issues
·Relatively inexpensive
·Over-interpretation of data
·Can obtain large volume of data  ·Response bias
·adaptive-allows data collection on ·Expense
Interviews
·Bias in interviewer responses
a range of possible subjects
·Source of "rich" data
·coding
and
interpretation
·Empathic
difficulties
·Process of interviewing can build ·self-report bias
rapport
·collects data on behavior, rather ·coding
Observations
and
interpretation
than reports of behavior
difficulties
·Real time, not retrospective
·Sampling inconsistencies
·Adaptive
·Observer bias and questionable
reliability
·Expense
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·Non-reactive- no response bias
·Access and retrieval difficulties
Unobtrusive measures
·High face validity
·Validity concerns
·Easily quantified
·Coding
and
interpretation
difficulties
Questionnaires:
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.
Interviews:
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-
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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.)
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Observations:
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 built-
in 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.
Table of Contents:
  1. The Challenge for Organizations:The Growth and Relevance of OD
  2. OD: A Unique Change Strategy:OD consultants utilize a behavioral science base
  3. What an “ideal” effective, healthy organization would look like?:
  4. The Evolution of OD:Laboratory Training, Likert Scale, Scoring and analysis,
  5. The Evolution of OD:Participative Management, Quality of Work Life, Strategic Change
  6. The Organization Culture:Adjustment to Cultural Norms, Psychological Contracts
  7. The Nature of Planned Change:Lewin’s Change Model, Case Example: British Airways
  8. Action Research Model:Termination of the OD Effort, Phases not Steps
  9. General Model of Planned Change:Entering and Contracting, Magnitude of Change
  10. The Organization Development Practitioner:External and Internal Practitioners
  11. Creating a Climate for Change:The Stabilizer Style, The Analyzer Style
  12. OD Practitioner Skills and Activities:Consultant’s Abilities, Marginality
  13. Professional Values:Professional Ethics, Ethical Dilemmas, Technical Ineptness
  14. Entering and Contracting:Clarifying the Organizational Issue, Selecting an OD Practitioner
  15. Diagnosing Organizations:The Process, The Performance Gap, The Interview Data
  16. Organization as Open Systems:Equifinality, Diagnosing Organizational Systems
  17. Diagnosing Organizations:Outputs, Alignment, Analysis
  18. Diagnosing Groups and Jobs:Design Components, Outputs
  19. Diagnosing Groups and Jobs:Design Components, Fits
  20. Collecting and Analyzing Diagnostic information:Methods for Collecting Data, Observations
  21. Collecting and Analyzing Diagnostic information:Sampling, The Analysis of Data
  22. Designing Interventions:Readiness for Change, Techno-structural Interventions
  23. Leading and Managing Change:Motivating Change, The Life Cycle of Resistance to Change
  24. Leading and managing change:Describing the Core Ideology, Commitment Planning
  25. Evaluating and Institutionalizing Organization Development Interventions:Measurement
  26. Evaluating and Institutionalizing Organization Development Interventions:Research Design
  27. Evaluating and Institutionalizing Organization Development Interventions
  28. Interpersonal and Group Process Approaches:Group Process
  29. Interpersonal and Group Process Approaches:Leadership and Authority, Group Interventions
  30. Interpersonal and Group Process Approaches:Third-Party Interventions
  31. Interpersonal and Group Process Approaches:Team Building, Team Building Process
  32. Interpersonal and Group Process Approaches:Team Management Styles
  33. Organization Process Approaches:Application Stages, Microcosm Groups
  34. Restructuring Organizations:Structural Design, Process-Based Structures
  35. Restructuring Organizations:Downsizing, Application Stages, Reengineering
  36. Employee Involvement:Parallel Structures, Multiple-level committees
  37. Employee Involvement:Quality Circles, Total Quality Management
  38. Work Design:The Engineering Approach, Individual Differences, Vertical Loading
  39. Performance Management:Goal Setting, Management by Objectives, Criticism of MBO
  40. Developing and Assisting Members:Career Stages, Career Planning, Job Pathing
  41. Developing and Assisting Members:Culture and Values, Employee Assistance Programs
  42. Organization and Environment Relationships:Environmental Dimensions, Administrative Responses
  43. Organization Transformation:Sharing the Vision, Three kinds of Interventions
  44. The Behavioral Approach:The Deep Assumptions Approach
  45. Seven Practices of Successful Organizations:Training, Sharing Information