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130 Part 2 • InformatIon requIrements analysIs

Sampling
Sampling is the process of systematically selecting representative elements of a population.
When these selected elements are examined closely, it is assumed that the analysis will reveal
useful information about the population as a whole.
A systems analyst has to make decisions on two key issues. First, people in the organization
have generated many reports, forms, output documents, memos, and websites. Which of these
should the systems analyst pay attention to, and which should the systems analyst ignore?
Second, a great many employees can be affected by the proposed information system.
Which people should the systems analyst interview, seek information from via questionnaires, or
observe in the process of carrying out their decision-making roles?

The Need for Sampling
There are many reasons a systems analyst would want to select either a representative sample of
data to examine or representative people to interview, question, or observe. They include:
1. Containing costs
2. Speeding up the data gathering
3. Improving effectiveness
4. Reducing bias

Examining every scrap of paper, talking with everyone, and reading every web page from the
organization would be far too costly for the systems analyst. Copying reports, asking employees
for valuable time, and duplicating unnecessary surveys would result in much needless expense.
Sampling helps accelerate the process by gathering selected data rather than all data for the
entire population. In addition, the systems analyst is spared the burden of analyzing data from
the entire population.
Effectiveness in data gathering is an important consideration as well. Sampling can help
improve effectiveness if information that is more accurate can be obtained. Such sampling
is accomplished, for example, by talking to fewer employees but asking them questions that
are more detailed. In addition, if fewer people are interviewed, the systems analyst can afford
the time to follow up on missing or incomplete data, thus improving the effectiveness of data
gathering.
Finally, data gathering bias can be reduced by sampling. When the systems analyst inter-
views an executive of the corporation, for example, the executive is involved with the project
because this person has already given a certain amount of time to the project and would like it to
succeed. When the systems analyst asks for an opinion about a permanent feature of the installed
information system, the executive interviewed may provide a biased evaluation because there is
little possibility of changing it.

Sampling Design
A systems analyst must follow four steps to design a good sample:

1. Determine the data to be collected or described.
2. Determine the population to be sampled.
3. Choose the type of sample.
4. Decide on the sample size.
These steps are described in detail in the following subsections.

DETERMINING THE DATA TO BE COLLECTED OR DESCRIBED. A systems analyst needs a realistic
plan about what will be done with the data once they are collected. If irrelevant data are gathered,
then time and money are wasted in the collection, storage, and analysis of useless data.
The duties and responsibilities of the systems analyst at this point are to identify the vari-
ables, attributes, and associated data items that need to be gathered in the sample. The objectives
of the study must be considered, as well as the type of data-gathering method (for example, inves-
tigation, interviews, questionnaires, observation) to be used. The kinds of information sought
when using each of these methods are discussed in more detail in this and subsequent chapters.

DETERMINING THE POPULATION TO BE SAMPLED. Next, a systems analyst must determine what
the population is. In the case of hard data, the systems analyst needs to decide, for example, if