1. Institute of Management Studies, Davangere University.
Presented By:
Shruti Malipatil
Research Scholar
Provisional Reg No: 23PHDMBA06
Seminar Topic: Data Collection Sources
2. Contents
• Data
• Four Characteristics of Data
• Methods of Collecting Data
1) Primary Data Collection Methods - Observation, Interview, Schedules and
Questionnaire
2) Secondary Data Research in Digital Age
3. Introduction
• The task of data collection begins after a research problem has been
defined and research design plan is chalked out.
• While deciding about the method of data collection to be used for the
study, the researcher should keep in mind two types of data viz., primary
and secondary.
• The methods of collecting primary and secondary data differ since
primary data are to be originally collected, while in case secondary data
the nature of data collection work is merely that of compilation.
4. Data
• Data are simply facts and recorded measures of certain phenomena(things or events).
• Information is a data formatted (structured) to support decision making or to define the relationship
between two facts.
• Business Intelligence is the subset of data or information that actually has some explanatory power
enhancing.
So, there is more data than information, and more information than intelligence.
For Ex: Home Depot (it is an American multinational home improvement retail corporation that sell tools,
construction products, appliances, and services etc.)
1. Thousands and thousands of unsummarized facts each time a product is scanned at checkout.
2. The fact is recorded and becomes data.
3. Customers transactions are simultaneously entered into store’s computerized inventory system.
4. Stock report is generated and orders of the stores can be placed.
5. Automated inventory system turns data into information.
6. store’s sales and inventory records may be harvested by analysts.
7. Analyst analyze trends and prepares reports.
5. Four characteristics help determine how useful
data may be:
1. Relevance
• Relevance is one of the characteristics of data reflecting how pertinent these
particular facts are to the situation at the hand.
• The facts are logically connected to the situation.
• Unfortunately, irrelevant data and information often creep into decision
making.
• One particular way to distinguish relevance form irrelevance is to think about
how things that can be changed, it will materially alter the situation.
• This simple question arises “will a change in the data coincide with a change in
some important outcome?”
6. 2. Quality
• Data quality is the degree to which data represent the true situation.
• High quality data are accurate, valid and reliable., it represents reality faithfully.
• Data quality is the critical issue in business research.
3. Timeliness
• Business in a dynamic field in which out-of-date information can lead to poor decisions.
• Business information must be timely - that is, provided at right time.
• A great deal of business information becomes available almost at the moment that a
transaction occurs.
• Timeliness means that the data are current enough to still be relevant.
• Computer technology has redefined standards for timely information.
• For Ex: At Home Depot, the point-of-scale checkout system uses UPC scanners and satellite
communicators to link individual stores to the headquarters computer systems, form which
managers can retrieve and analyze up-to-the minute sales on all merchandise in each store
7. 4. Completeness
• Information incompleteness refers to having the right amount of
information.
• Managers/ Decision makers must have sufficient information about all
aspects of their decisions.
• Often, incomplete information leads decision makers to conduct their own
business research.
• For Ex: A Company considering establishing a product facility in Eastern
Europe may plan to analyze four former soviet bloc countries. Population
statistics, GDP and information on inflation rates may be available for only
three countries. If information about unemployment, or other
characteristics cannot be obtained , the information is incomplete
8. Primary Data
• Primary data is gathered and assembled specifically for the project at hand.
• Primary data collection methods refer to the process of gathering original
data directly from individuals, organizations, or sources specifically for a
particular research study or project.
• These methods involve collecting data at firsthand instead of relying on
existing data sources or secondary data.
• Primary data collection methods provide researchers with accurate, up-to-
date, and specific information that is tailored to their research objectives.
• We collect primary data during the course of doing experiments in an
experimental research but in case we do research of the descriptive type
and perform surveys, whether sample surveys or census surveys, then we
can obtain primary data either through observation or through direct
communication with respondents in one form or another or through
personal interviews.
9. 1. Observations
• Observation involves systematically watching and recording behaviors,
actions, or events in their natural setting.
• Researchers can observe individuals, groups, or phenomena to gather data.
Observations can be structured, where predefined behaviors or events are
recorded, or unstructured, where the researcher notes any relevant
behaviors or events.
• Observations can be done in person or remotely using technology, such as
video cameras or live streaming. This method is particularly useful for
studying human behavior, interactions, and social dynamics.
• For Ex: To understand the behavior of shoppers in a retail store.
10. 2. Interviews
• Interviews involve direct interaction between the researcher and the
respondent. They can be structured (where the questions are pre-
determined) or unstructured (where the questions evolve based on the
conversation).
• Interviews can be conducted face-to-face, over the phone, or via video
conferencing.
• Interviews provide researchers with in-depth qualitative data, allowing
them to explore complex topics, understand motivations, and gain
insights into participants' experiences and perspectives.
• For Ex: To explore the experiences and perspectives of employees
regarding organizational culture.
11. 3. Schedules
• This method of data collection is very much like the collection of data through
questionnaire, with little difference which lies in the fact that schedules (proforma
containing a set of questions) are being filled in by the enumerators who are
specially appointed for the purpose.
• These enumerators along with schedules, go to respondents, put to them the
questions from the proforma in the order the questions are listed and record the
replies in the space meant for the same in the proforma.
• Enumerators explain the aims and objects of the investigation and also remove the
difficulties which any respondent may feel in understanding the implications of a
particular question or the definition or concept of difficult terms.
• This method requires the selection of enumerators for filling up schedules or
assisting respondents to fill up schedules and as such enumerators should be very
carefully selected.
12. • The enumerators should be trained to perform their job well and the
nature and scope of the investigation should be explained to them
thoroughly so that they may well understand the implications of
different questions put in the schedule.
• Enumerators should be intelligent and must possess the capacity of
cross examination in order to find out the truth. Above all, they should
be honest, sincere, hardworking and should have patience and
perseverance.
• This method of data collection is very useful in extensive enquiries and
can lead to fairly reliable results. It is, however, very expensive and is
usually adopted in investigations conducted by governmental agencies
or by some big organizations. Population census all over the world is
conducted through this method.
For Ex: To assess customer satisfaction with new mobile application.
13. 4. Questionnaire
• A questionnaire is a widely used primary data collection method that involves the
use of a set of structured questions to gather information from a targeted sample
of respondents.
• Questionnaires can be administered through various mediums, such as paper-
based surveys, online surveys, or even phone interviews.
• It is being adopted by private individuals, research workers, private and public
organizations and even by governments.
• The method of collecting data by mailing the questionnaires to respondents is
most extensively employed in various economic and business surveys.
14. Here are some key aspects to consider when designing and administering a questionnaire:
1. Objective and Research Questions: Clearly define the objective of your research and the
specific research questions you want to address. This will guide the development of your
questionnaire and ensure that it gathers relevant data.
2. Question Design: Craft clear and concise questions that are easy for respondents to
understand. Use simple and unambiguous language to avoid confusion. The questions
should be relevant to the research objectives and framed in a way that elicits the desired
information.
• Closed-Ended Questions: These questions provide a set of predefined response options
for respondents to choose from (e.g., multiple-choice questions, Likert scales, rating
scales). Closed-ended questions are useful for obtaining quantitative data and analyzing
responses statistically.
• Open-Ended Questions: These questions allow respondents to provide detailed,
narrative responses in their own words. Open-ended questions are valuable for gathering
qualitative data, exploring in-depth perspectives, and capturing unique insights.
15. 3. Question Sequence and Flow: Organize the questions in a logical order to ensure a
smooth flow of the survey. Begin with introductory or demographic questions to engage
respondents and gradually move towards more specific and in depth questions. Group
related questions together to maintain coherence and aid respondents' understanding.
4. Response Options: If using closed-ended questions, provide response options that cover
all possible answers and avoid overlapping or ambiguous categories. Consider using a
neutral response option (e.g., "Neither agree nor disagree") to allow for neutral opinions.
Ensure that the response options are exhaustive and mutually exclusive.
5. Skip Patterns and Branching: In some cases, certain questions may only be relevant to a
specific subset of respondents. Incorporate skip patterns or branching logic in your
questionnaire to guide respondents to relevant questions based on their previous
responses. This helps to personalize the survey experience and reduce respondent burden.
6. Length and Time Considerations: Keep the questionnaire concise and focused to
maintain respondents' interest and prevent survey fatigue. Long surveys may lead to higher
dropout rates or incomplete responses. Consider the time required to complete the
questionnaire and communicate this to respondents upfront.
16. 7. Piloting and Pretesting: Before administering the questionnaire to the target population,
conduct a pilot study with a small sample of respondents. This helps identify any issues with
question clarity, response options, survey flow, or technical aspects. Make necessary
revisions based on the feedback received during the pilot phase.
8. Administration and Data Collection: Determine the most appropriate mode of
administration for your questionnaire (e.g., online, paper-based, phone interviews).
Consider factors such as accessibility, reach, data security, and respondent convenience.
Ensure that the data collection process adheres to ethical considerations, including
informed consent, confidentiality, and anonymity.
9. Data Analysis: Once the data collection is complete, analyze the collected data using
appropriate statistical techniques for closed-ended questions. For open-ended questions,
thematic analysis or qualitative coding methods may be employed to identify patterns,
themes, and key insights.
Questionnaires are valuable tools for collecting a wide range of information from a large
number of respondents. However, it is important to design and administer them carefully to
ensure the validity and reliability of the data collected.
17. Secondary Data Research In Digital Age
• Business Researchers are always working under time and budget
constraints. So, they are wise to ask if the data needed to examine the
research question already exists.
• If the data exists, the analysis can proceed quickly, efficiently and at
minimum cost
• Therefore, Research Projects should begin with secondary data, which are
gathered and recorded by someone else prior to, and for purposes other
than, the current project.
• Secondary data usually are already assembled. They require no access to
respondents.
18. Some common business problems that can be addressed with secondary
research designs are useful . The three general categories of research
objectives are as follows:
1. Fact Finding
• Identification of consumer behavior for a product category.
• Trend Analysis.
2. Model Building
• Estimating market potential for geographical areas.
• Sales forecasting
• Analysis of trend areas and site analysis techniques
3. Database and Customer Relationship Management.
19. Sources of Secondary Data
• Secondary data can be classified as either internal to the organization or
external
• Some accounting documents are indisputably internal records of the
organizations. Researchers in other organizations cannot have access to
them. Clearly a book published by the federal govt and located at the
public library is external.
20. • Internal data is defined as data that originated in the organizations, or data
gathered, created, recorded or generated by the organization.
• An organizations accounting system can usually provide a wealth of
information. Routine documents such as sales invoices allows external
financial reporting, which in turn can be a source of data for further
analysis.
• Sales information can be broken down by account or by product and
region; information related to orders received, back orders, and unfulfilled
orders can be identified; and sales can be forecast on the basis of past
data.
• Other useful sources of internal data include sales people’s call reports,
customer complaints, service records, warranty card returns, and other
records.
• Companies are setting up intranets so that employees can use web tools to
store and share data within the organizations.
21. External Data: The Distribution System
• External data are generated or recorded by an entity other than the
researcher’s organization. The govt, newspapers, and journals, trade
associations, and other organizations create or produce information.
• Traditionally, this information has been in published form, perhaps
available from public library, trade association, or government agency.
• Today, however, computerized data archives and electronic data
interchange make external data as accessible as internal data.
