ORGANIZATION DEVELOPMENT
WEEK 6
Chapter 07 – Collecting and Analyzing Information
This chapter is an extension of the diagnosis process and entails data gathering and analysis of
organizational functioning. The areas covered here concern with the response to several queries
on the OD practitioner relationship with organization members. Information gathered is
regarding specific organizational features such as inputs, design components and outputs. Four
methods can be used to collect data: questionnaire, interviews, observations and unobstructive
measures. Data is analyzed using qualitative and quantitative methods.
.
Key Terms: Questionnaires, Interviews, Observations, Unobstructive measures, Focus
groups, Content analysis, Force-Field analysis, Quantitative tools
Topics covered in the chapter are:
1. The Diagnostic Relationship
2. Methods of Collecting Data: questionnaires, interviews, observations and unobstructive
measures
3. Techniques of Analyzing data:
a. Qualitative analysis (content analysis and force-field analysis)
b. Quantitative analysis (mean, standard deviation, frequency distribution,
scattergrams, correlation coefficient and difference test)
The Diagnostic Relationship:
Before collecting diagnostic information, practitioners need to establish a relationship with those
who will provide and subsequently use it. The reasons being the relationship’s nature will
determine the quantity and usefulness of the data collected, it’s 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. Such information can be used help allays
people’s natural fears that the data might be used against them and gain member’s 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 clarify expectations and to specify the
conditions of the relationships. In situations where data will be collected from members who
have not been directly involved in entering and contracting, 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 into the overall
development strategy.
3. Who do I work for? The answer clarifies who has hired the consultant, whether it’s 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.
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.
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 maintain
confidentiality or state that participation.
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.
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.
8. Can I be trusted? The diagnostic relationships ultimately rests on the trust established
between the consultant and those providing the data.
There are three goals of data collection. Firstly to obtain valid information about organizational
functioning. Second data collection also rally energy for constructive organizational change.
Finally, data collection helps to develop the collaborative relationship necessary for effecting
organizational change.
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Methods for Collecting Data:
The four major techniques for gathering diagnostic data are questionnaires, interviews,
observations and unobstructive measures. Each method provides advantages and disadvantages.
No single method can fully measure the kinds of variables important to OD because each has
certain strengths and weaknesses. Because of the biases inherent in any data collection method
more than one method should be used when collecting diagnostic data.
Questionnaires:
A cost effective and efficient method of collecting data is through questionnaires. There are
standard instruments and customized ones as well which are usually based on fixed-response
queries. They are useful for quantitative comparison and evaluation. Questionnaires can vary in
scope, some measuring selected aspects of organizations and others assessing more
comprehensive organizational characteristics.
These drawbacks associated questionnaires include:

Responses are limited to the questions asked in the instrument

Instruments are impersonal and employees may not be willing to provide honest answers

Elicit response biases such as the tendency to answer questions in a socially acceptable
manner
Interviews:
The second important measurement technique is the individual or group interview. This method provides
an invaluable for insight gaining private views and feelings about the organization for exploring new
issues that emerge during the interview.
Interview 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. Unstructured interviews are more general and include the
following broad questions about organizational functioning:

What are the major goals or objectives of the organization or department?

How does the organization currently perform with respect to these problems

What are the strengths and weaknesses of the organization or department?

What barriers stand in the way of good performance?
Interviews are one-to-one interaction between OD practitioners and an employee and can also be carried
out in group context. Group interviews save time and allow people to build on other’s responses. A major
drawback however, is that group settings inhibit some people from responding freely.
Group interviews include Focus group, these unstructured meetings conducted by a manager or
consultant involve a small group of 10 to 15 employees selected to represent a cross section of functional
areas and hierarchical levels or a homogenous grouping such as minorities and engineers.
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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 or sensing meetings are an economical way
to obtain interview data and are especially effective in understanding particular issues in depth.
Another 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 members may be asked how
they feel the group is functioning. This unstructured interview is a fast, simple way to collect data about
group behavior. It allows members to discuss issues of immediate concern and engage in the questioning
and answering process. It’s limited to small groups and requires high level of trust among managers and
employees.
Interviews are effective method, for collecting data in OD. They are adaptive, allowing the interviewer to
modify questions and 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. 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.
Observation:
One of the most 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 behaviors. Observation can range from
complete participant 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.
Advantages of observation, its free of the inherent biases in self-report data, the practitioners directly in
touch with the behaviors in question, without having to rely on other’s perceptions. Provide real-time data
describes behavior occurring in the present. It is adaptive as the consultant can choose to observe.
Disadvantages of observation include difficulty in interpreting the meaning underlying observations.
Coding scheme required to make sense of observations is expensive, time consuming and introduces
biases in the data. Sampling is another issue.
Unobstructive measures:
Unobstructive data are not collected directly from respondents but from secondary sources such as
organization records of absenteeism or tardiness, grievances, quantity and quality of production or
service; financial performance; meeting minutes; and correspondence with key customers, suppliers or
government agencies. Unobstructive measures also can help to diagnose organization level designcomponents structure, work system, control system and human resources systems. Unobstructive
measures provide a relatively objection view of organizational functioning. They are free from respondent
and consultant biases and are perceived as being “real” by many organization members.
The major problems with Unobstructive 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.
Unobstructive data also may have their own built in biases. Changes in accounting procedures and
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methods of recording data are common in organizations and such changes can affect company records
independently of what is actually happening in the organization.
Regardless of the draw backs Unobstructive data serve as a valuable adjunct to other diagnostic measures
archival data can be used in preliminary diagnosis. Conversely Unobstructive data can be used to crosscheck other forms of information.
Sampling:
Sampling isn’t a major issue in diagnosis or subsequent data gathering endeavors as information is
collected from entire organization. It’s only an issue if it is collected from selective members, in such
cases the issues which arise are sample size and sample selection. The greater the population the more
reliable and valid the response. Due to rise in complexity and cost involved sampling techniques such as
random sampling and stratified sampling are utilized.
Techniques for Analyzing data.
Data analysis techniques fall into two broad calories: qualitative and quantitative.
Qualitative Tools.
Content Analysis:
A popular technique for assuring qualitative data especially interview data is content analysis, which
attempts to summarize comments into meaningful categories. The process of content analysis can be quite
formal and specialized references describe this technique in detail. Firstly, responses to a particular
question are read to gain familiarity with the range of comments made and to determine whether come
consumers are occurring over and over again. Second based on this sampling of comments, themes are
generated that capture recurring comments. Third, the responded answers to a question are then placed
into one of the categories.
Force-Field Analysis.
A Second method for analyzing qualitative data in OD derives from Kurt Lewin’s three-step model of
change known as force-field analysis. This method organizes information pertaining to organizational
change into two major categories: forces for change and forces to maintain the status quo or resisting
change. Using data collected through interviews, observation, or unobstructive measures, the first step in
conducting a force-field analysis is to develop a list of all the forces promoting change and all those
resisting it. Then, based either on the OD practitioner’s personal belief or perhaps on input from several
members of the client organization, a determination is made of the power of positive and negative forces.
The reduction in the forces maintaining the status quo is likely to result in organizational change with
little of the tension or conflict typically accompanying change caused by increasing the forces of change.
Quantitative Tools.
Methods for analyzing quantitative data range from simple descriptive statistics of items or scales from
standards instruments to more sophisticated, multivariate analysis of the underlying instrument properties
and relationships many measured variables. The most common quantitative tools are means, standard
deviation and frequency distribution; scatter grams and correlation coefficient and difference test.
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Mean: represents respondent’s average score.
Standard deviation: the spread or variability of the responses.
Frequency distribution: a graphical method for displaying data that shows the number of times a
particular response was given.
Scatter gram: A diagram that visually displays. The relationship between two variables. It is
constructed by locating each case at the inter section of its value for each of the two variable being
compared.
Correlation coefficient: a number that summaries data in a scatter gram.
Difference test: The final technique for analyzing qualitative data is the difference test. It can be used to
compare a sample group against some standard or norm to determine whether the group is above or below
that standard. It can also be used to determine whether two samples are significantly different from each
other.
Textbook and Articles
Organization Development & Change by Thomas Cummings & Christopher G. Worley 9e
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