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Data Collection Process

Organization development is vitally dependent on organization diagnosis: the process of collecting 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.

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The process of collecting data is an important and significant step in an OD program. During this stage, thepractitioner and the client attempt to determine the specific problem requiring solution. After thepractitioner has intervened and has begun developing a relationship, the next step is acquiring data andinformation about the client system.This task begins with the initial meeting and continues throughout the OD program. The practitioner is, ineffect, 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 datacollection. The practitioner must be certain of the facts before proceeding with an action program. Theprobability that an OD program will be successful is increased if it is based upon accurate and in-depthknowledge of the client system.Information quality is a critical factor in any successful organization. Developing an innovative culture andfinding new ways to meet customer needs are strongly influenced by the way information is gathered andprocessed. Organization development is a data-based change activity. The data collected are used by themembers 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 processinginformation. For our purposes, the word data, which is derived from the Latin verb dare, meaning “togive, 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 inform are, 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.

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. 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.

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