DATA COLLECTION

For IB1-ITGS

By Indrani

Tuesday, October 30, 2012

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WHAT IS DATA COLLECTION ? Data collection is any process of preparing and

collecting data, for example, as part of a process improvement or similar project. The purpose of data collection is to obtain information to keep on record, to make decisions about important issues, or to pass information on to others. Data are primarily collected to provide information regarding a specific topic.

Data collection usually takes place early on in an improvement project, and is often formalized through a data collection plan which often contains the following activity.

Pre collection activity — agree on goals, target data, definitions, methods

Collection — data collection Present Findings — usually involves some form of

sorting analysis and/or presentation.

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WHERE DO DATA COME FROM?

All nice and collated in a database comes from: Insurance companies (claims, medications,

procedures, diagnoses, etc.)

Firms (demographic data, productivity data, etc.)

Institution (student name, subject, marks)

Offices (Employee name, address, phone, salary)

Telephone Companies (Customer name, Interest) And from many other sources

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WHERE DO DATA COME FROM?

Take a step back – if we’re starting from scratch, how do we collect / find data? Secondary data Primary data

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SECONDARY DATA

Secondary data – data someone else has collected This is what you were looking for in your

assignment.

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SECONDARY DATA – EXAMPLES OF SOURCES

Health departments Vital Statistics – birth, death

certificates Hospital, clinic, school, nurse records Private and foundation databases Central and State governments Surveillance data from state

government programs Federal agency statistics - Census,

NIH, etc.

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SECONDARY DATA – LIMITATIONS

What did you find on the frustrating side as you looked for data on the state’s websites?

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SECONDARY DATA – LIMITATIONS

When was it collected? For how long? May be out of date for what you want to analyze. May not have been collected long enough for

detecting trends. E.g. Have new anticorruption laws impacted

Russia’s government accountability ratings?

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SECONDARY DATA – LIMITATIONS

Is the data set complete? There may be missing information on some

observations Unless such missing information is caught and

corrected for, analysis will be biased.

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SECONDARY DATA – LIMITATIONS

Are there confounding problems? Sample selection bias? Source choice bias? In time series, did some observations drop out

over time?

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SECONDARY DATA – LIMITATIONS

Are the data consistent/reliable? Did variables drop out over time? Did variables change in definition over time?

E.g. number of years of education versus highest degree obtained.

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SECONDARY DATA – LIMITATIONS

Is the information exactly what you need? In some cases, may have to use “proxy

variables” – variables that may approximate something you really wanted to measure. Are they reliable? Is there correlation to what you actually want to measure?

E.g. gauging student interest in U.W. by their ranking on FAFSA – subject to gamesmanship.

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SECONDARY DATA – ADVANTAGES

No need to reinvent the wheel. If someone has already found the data, take

advantage of it.

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SECONDARY DATA – ADVANTAGES

It will save you money. Even if you have to pay for access, often it is

cheaper in terms of money than collecting your own data. (more on this later.)

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SECONDARY DATA – ADVANTAGES

It will save you time. Primary data collection is very time consuming.

(More on this later, too!)

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SECONDARY DATA – ADVANTAGES

It may be very accurate. When especially a government agency has

collected the data, incredible amounts of time and money went into it. It’s probably highly accurate.

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SECONDARY DATA – ADVANTAGES

It has great exploratory value Exploring research questions and formulating

hypothesis to test.

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PRIMARY DATA

Primary data – data you collect

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PRIMARY DATA - EXAMPLES

Surveys Focus groups Questionnaires Personal interviews Experiments and observational study

3 METHODS FOR COLLECTING DATAMgt. 450

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THREE MAJOR TECHNIQUES FOR COLLECTING DATA:1. Questionnaires2. Interviews3. Observation

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USING THESE DATA GATHERING METHODS

Each method has advantages and problems. No single method can fully measure the variable important to OD

Examples: Questionnaires and surveys are open to

self-report biases, such as respondents’ tendency to give socially desirable answers rather than honest opinions.

Observations are susceptible to observer biases, such as seeing what one wants to see rather than what is actually there.

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USE MORE THAN ONE

Because of the biases inherent in any data-collection method, it is best to use more than one method when collecting diagnostic data.

The data from the different methods can be compared, and if consistent, it is likely the variables are being validly measured.

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DEMOGRAPHICS

Information about the people you are gathering data from is important.

Collect the specific demographics necessary. Some examples Age Gender Income level Ethnic background Status (student, teacher, visitor)

Be careful not to collect demographics that are not specific to your data collection purpose.

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QUESTIONNAIRES: Questionnaires are one of the most efficient

ways to collect data. They contain fixed-response questions about

various features of an organization. These on-line or paper-and pencil measures

can be administered to large numbers of people simultaneously.

They can be analyzed quickly. They can be easily be fed back to employees. Questionnaires can be standard based on

common research or they can be customized to meet the specific data gathering need.

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QUESTIONNAIRES; THERE ARE DRAWBACKS;

Responses are limited to the questions asked in the instrument.

They provide little opportunity to probe for additional data or ask for points of clarification.

They tend to be impersonal. Often elicit response biases – tend to answer

in a socially acceptable manner.

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INTERVIEWS Interviews are probably the most widely used

technique for collecting data in OD. They permit the interviewer to ask the

respondent direct questions. Further probing and clarification is possible

as the interview proceeds. This flexibility is invaluable for gaining

private views and feelings about the organization and exploring new issues that emerge during the interview.

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INTERVIEWS Interviews may be highly structured,

resembling questionnaires, or highly unstructured, starting with general questions that allow the respondent to lead the way.

Interviews are usually conducted one-to-one but can be carried out in a group.

Group interviews save time and allow people to build on other’s responses.

Group interviews may, however, inhibit respondent’s answers if trust is an issue.

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INTERVIEWS / FOCUS GROUPS Another unstructured group meeting

conducted by a manager or a consultant. A small group of 10-15 people is selected

representing a larger group of people Group discussion is started by asking general

questions and group members are encouraged to discuss their answers in some depth.

The richness and validity of this information will depend on the extent that trust exists.

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DRAWBACK TO INTERVIEWS

They can consume a great deal of time if interviewers take full advantage of the opportunity to hear respondents out and change their questions accordingly.

Personal biases can also distort the data. The nature of the question and the interactions

between the interviewer and the respondent may discourage or encourage certain kinds of responses.

It take considerable skill to gather valid data.

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SAMPLE INTERVIEW QUESTIONS

1. How do management and non-management employees interact in the office?

2. How do you know when you have done an excellent job?

3. How do non-management employees learn about organizational change?

4. If you could change one or two things about the way management and non-management personnel interact, what would you change?

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OBSERVATIONS

Observing organizational behaviors in their functional settings is one of the most direct ways to collect data.

Observation can range from complete participant observation, where the OD practitioner becomes a member of the group under study to a more detached observation using a casually observing and noting occurrences of specific kinds of behaviors.

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ADVANTAGES TO OBSERVATION: They are free of the biases inherent in the

self-report data. They put the practitioner directly in touch

with the behaviors in question. They involved real-time data, describing

behavior occurring in the present rather than the past.

They are adapting in that they can be modified depending on what is being observed.

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PROBLEMS WITH OBSERVATION

Difficulties interpreting the meaning underlying the observations.

Observers must decide which people to observe; choose time periods, territory and events

Failure to attend to these sampling issues can result in a biased sample of data.

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OBSERVATION PROTOCOL

A decision needs to be made on what to observe.

Example:Observe how managers and employees

interact in the office.Observe who has lunch with whom. (Do

managers and non-managers eat together? Do executives have a private lunch area?)

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PRIMARY DATA - LIMITATIONS

Uniqueness May not be able to compare to other populations

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PRIMARY DATA - LIMITATIONS

Do you have the time and money for: Designing your collection instrument? Selecting your population or sample? Pretesting/piloting the instrument to work out

sources of bias? Administration of the instrument? Entry/collation of data?

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PRIMARY DATA - LIMITATIONS

Researcher error Sample bias Other confounding factors

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DATA COLLECTION CHOICE

What you must ask yourself: Will the data answer my research question?

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DATA COLLECTION CHOICE

To answer that You much first decide what your research

question is Then you need to decide what data/variables are

needed to scientifically answer the question

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DATA COLLECTION CHOICE

If that data exist in secondary form, then use them to the extent you can, keeping in mind limitations.

But if it does not, and you are able to fund primary collection, then it is the method of choice.

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END OF PACK

Thank you