steps in business research process design

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Research Process Steps: What they are + How To Follow

There are various approaches to conducting basic and applied research. This article explains the research process steps you should know. Whether you are doing basic research or applied research, there are many ways of doing it. In some ways, each research study is unique since it is conducted at a different time and place.

Conducting research might be difficult, but there are clear processes to follow. The research process starts with a broad idea for a topic. This article will assist you through the research process steps, helping you focus and develop your topic.

Research Process Steps

The research process consists of a series of systematic procedures that a researcher must go through in order to generate knowledge that will be considered valuable by the project and focus on the relevant topic.

To conduct effective research, you must understand the research process steps and follow them. Here are a few steps in the research process to make it easier for you:

Step 1: Identify the Problem

Finding an issue or formulating a research question is the first step. A well-defined research problem will guide the researcher through all stages of the research process, from setting objectives to choosing a technique. There are a number of approaches to get insight into a topic and gain a better understanding of it. Such as:

• A preliminary survey
• Case studies
• Interviews with a small group of people
• Observational survey

Step 2: Evaluate the Literature

A thorough examination of the relevant studies is essential to the research process . It enables the researcher to identify the precise aspects of the problem. Once a problem has been found, the investigator or researcher needs to find out more about it.

This stage gives problem-zone background. It teaches the investigator about previous research, how they were conducted, and its conclusions. The researcher can build consistency between his work and others through a literature review. Such a review exposes the researcher to a more significant body of knowledge and helps him follow the research process efficiently.

Step 3: Create Hypotheses

Formulating an original hypothesis is the next logical step after narrowing down the research topic and defining it. A belief solves logical relationships between variables. In order to establish a hypothesis, a researcher must have a certain amount of expertise in the field. 

It is important for researchers to keep in mind while formulating a hypothesis that it must be based on the research topic. Researchers are able to concentrate their efforts and stay committed to their objectives when they develop theories to guide their work.

Step 4: The Research Design

Research design is the plan for achieving objectives and answering research questions. It outlines how to get the relevant information. Its goal is to design research to test hypotheses, address the research questions, and provide decision-making insights.

The research design aims to minimize the time, money, and effort required to acquire meaningful evidence. This plan fits into four categories:

• Exploration and Surveys
• Data Analysis
• Observation

Step 5: Describe Population

Research projects usually look at a specific group of people, facilities, or how technology is used in the business. In research, the term population refers to this study group. The research topic and purpose help determine the study group.

Suppose a researcher wishes to investigate a certain group of people in the community. In that case, the research could target a specific age group, males or females, a geographic location, or an ethnic group. A final step in a study’s design is to specify its sample or population so that the results may be generalized.

Step 6: Data Collection

Data collection is important in obtaining the knowledge or information required to answer the research issue. Every research collected data, either from the literature or the people being studied. Data must be collected from the two categories of researchers. These sources may provide primary data.

• Questionnaire

Secondary data categories are:

• Literature survey
• Official, unofficial reports
• An approach based on library resources

Step 7: Data Analysis

During research design, the researcher plans data analysis. After collecting data, the researcher analyzes it. The data is examined based on the approach in this step. The research findings are reviewed and reported.

Data analysis involves a number of closely related stages, such as setting up categories, applying these categories to raw data through coding and tabulation, and then drawing statistical conclusions. The researcher can examine the acquired data using a variety of statistical methods.

Step 8: The Report-writing

After completing these steps, the researcher must prepare a report detailing his findings. The report must be carefully composed with the following in mind:

• The Layout: On the first page, the title, date, acknowledgments, and preface should be on the report. A table of contents should be followed by a list of tables, graphs, and charts if any.
• Introduction: It should state the research’s purpose and methods. This section should include the study’s scope and limits.
• Summary of Findings: A non-technical summary of findings and recommendations will follow the introduction. The findings should be summarized if they’re lengthy.
• Principal Report: The main body of the report should make sense and be broken up into sections that are easy to understand.
• Conclusion: The researcher should restate his findings at the end of the main text. It’s the final result.

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The research process involves several steps that make it easy to complete the research successfully. The steps in the research process described above depend on each other, and the order must be kept. So, if we want to do a research project, we should follow the research process steps.

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Research Design Steps: Comprehensive Guide

Markets are constantly changing, and it’s important to have a sound research plan in place if you want your company or business’ product stand out from the competition. This article will help you understand the 11 steps that need to be followed to execute a sound market research study. This formal process can also be called “Research Design”. 

Table of Contents

11 steps of research design, comprehensive guide, 1. define the research problem or opportunity.

The first step in any research process is to clearly define the research problem or opportunity. This can be done through a number of different methods, including interviews, focus groups , and surveys.

While it may seem like a simple task, defining the research problem or opportunity is crucial to the success of any research project. Without a clear definition, it can be difficult to determine which research methods to use and how to interpret the results.

If you’re not sure where to start, there are a number of resources available to help you define the research problem or opportunity. The following articles offer some helpful tips:

• How to Define a Research Problem or Opportunity
• How to Identify a Research Problem or Opportunity
• How to Write a Problem Statement for Your research Project
• How to Develop a research Questionnaire

Once you’ve taken some time to define the research problem or opportunity, you can move on to the next step in the research process. 

2. Conduct a literature review

Once the research problem has been defined, the next step is to conduct a literature review. This helps to provide a foundation for the study and determine what has already been studied in this area.

A literature review is an important step in conducting research. It helps to define the problem and determine what has already been studied in this area. This process should be unbiased and objective. It should identify gaps in the literature and make suggestions for further research.

The process of reviewing  literature  can be a daunting task, but it is important to remember that it does not need to be exhaustive. The goal is to identify relevant literature and synthesize the information into a cohesive overview.

Tips to conduct a literature review

The following tips will help you conduct a literature review:

• Define your research question before you begin your search. This will help you focus your search and save time.
• Use keyword searching to find relevant articles. Try different combinations of keywords until you find what you are looking for.
• Use databases such as Google Scholar, PubMed, and Web of Science. These databases will help you find peer-reviewed articles.
• Read the abstracts of the articles to determine if they are relevant to your topic. If the abstract is not available, read the full text of the article.
• Organize your literature review using a table or concept map. This will help you see the relationships between different concepts and ideas.
• Write a summary of what you have found in each article. This will help you remember the main points of each article and synthesize the information into a cohesive overview.

Conducting a literature review can seem to be a tedious  task, though it is an important step in conducting research. By following these tips, you can make the literature review process easier and more efficient. Once you have completed your literature review, you will be one step closer to writing your research paper!

3. Develop research objectives (aka Hypothesis)

After conducting the literature review, it is important to develop clear research objectives. This will help guide the rest of the research process and ensure that all steps are aligned with the goals of the study.

There are a few different ways to go about developing research objectives. One approach is to start with the research question, and then develop hypotheses that can be tested through data collection and analysis. Another approach is to think about the overall goal of the research project and what needs to be accomplished in order to achieve that goal.

Whichever approach you choose, it is important to be clear and concise when writing your research objectives. They should be specific enough that they can be measured, but not so specific that they limit the scope of your study. Once you have developed your research objectives, you can use them to guide the rest of your research process.

If you’re stuck on where to start, try brainstorming a list of potential objectives and then narrowing down the list to the most important or relevant ones. You can also consult with your supervisor or other experts in your field to get their input on what objectives would be most appropriate for your research project.

Once you have your research objectives, you can begin thinking about how to operationalize them. This means determining how you will measure the variables that are mentioned in your objectives. For example, if one of your objectives is to examine the relationship between two variables, you will need to decide which type of data collection and analysis methods will be best suited for measuring that relationship.

Operationalizing your research objectives is an important step in ensuring that your study is well-designed and that all of its components are aligned with its overall goals. By taking the time to develop clear and concise research objectives, you can set your study up for success.

4. Formulate your research design

The fourth step is to identify the research design. This will determine the overall approach of the study and include information such as the type of study, the population, and the sampling method.

When formulating your research design, it is important to consider the type of study, the population, and the sampling method. The type of study will determine the overall approach of the research, while the population and sampling method will help to identify the target audience and how best to collect data. By taking all of these factors into consideration, you can develop a well-rounded research design that will be able to address your research question effectively.

There are a variety of different research designs that you can choose from, so it is important to select one that is best suited for your particular study. For example, if you are interested in investigating a specific phenomenon, you may want to choose a case study design. On the other hand, if you are interested in comparing two groups of people, you may want to choose a comparative research design. Once you have selected a research design, you will need to determine the population and sampling method. The population is the group of individuals that you are interested in studying, while the sampling method is the process by which you will select individuals from the population to participate in your study.

By formulating your research design before beginning your study, you can ensure that your data will be collected and analyzed effectively. This will ultimately help you to answer your research question and draw conclusions about your topic of interest. So, take some time to consider all of these factors before moving on to the next step in your research journey!

5. Select the research method

Once the research design has been selected, the next step is to select the research method. This will determine how data will be collected and can include methods such as interviews, focus groups, and surveys.

The research method should be selected based on the research design and the research question. As mentioned, some of the most common research methods are interviews, focus groups, and surveys. Each research method has its own advantages and disadvantages. For example, interviews are good for getting in-depth information from a small number of people, but they can be time-consuming and expensive. Focus groups are good for exploring ideas with a group of people, but they can be difficult to control. Surveys are good for collecting large amounts of data quickly, but they can be subject to bias.

Once the research method has been selected, the next step is to develop the research instruments . These will be used to collect data from participants in the study. The most common research instruments are questionnaires and interview protocols.

Questionnaires are a type of research instrument that is used to collect data from participants in a study. They can be used to collect both quantitative and qualitative data. Questionnaires can be administered in person, by mail, or online.

Interview protocols are another type of research instrument that is used to collect data from participants in a study. They are typically used to collect qualitative data. Interview protocols can be administered in person or by telephone.

6. Collect data

After selecting the research method, it is time to start collecting data. This can be done through a number of different methods, depending on the type of study and research objectives.

There are a few things to keep in mind when collecting data. First, you need to decide what type of data you need. Second, you need to choose the right methods for Collecting that data. And third, you need to make sure that the data you collect is high quality. let’s take a closer look at each of these points.

When deciding what type of data you need, it is important to consider what type of research questions you are trying to answer. If your research questions are qualitative in nature, then you will likely want to collect qualitative data. Qualitative data includes things like interviews, focus groups, and observations. If your research questions are quantitative in nature, then you will want to Collect quantitative data. Quantitative data includes things like surveys, experiments, and demographic information.

Once you have decided what type of data you need, you need to choose the right Collecting methods. There are many different Collecting methods, and the right method will depend on the type of data you are Collecting and your research goals. Some common Collecting methods include interviews, focus groups, online surveys, experiments, and observations.

When Collecting data, it is important to make sure that the data is high quality. This means that the data should be accurate, reliable, and valid. Data quality is important because it affects the validity of your research findings. If your data is not high quality, then your research findings might not be accurate. Collecting high quality data takes time and effort, but it is worth it to make sure that your research findings are accurate.

7. Clean and code data

After data has been collected, it must be cleaned and coded. This process helps to ensure that the data is ready for analysis. There are a few things to keep in mind when collecting data. 

• First, make sure that the data is accurate and reliable. This means choosing a method that will produce valid results. 
• Second, the data should be representative of the population being studied. 
• Third, collect enough data to answer the research question(s).

There are a few different ways to collect data. Some common methods include surveys, interviews, focus groups, and observations. Collecting data can be a time-consuming process, so it is important to plan ahead and allow enough time to gather all the necessary information. Once the data has been collected, it is time to analyze it. This will be covered in the next section.

8. Analyze data

Once the data has been cleaned and coded, it is time to begin analyzing it. This can be done through a number of different methods, such as descriptive statistics, t-tests, and regression analysis.

The first step in analysis is to decide what type of analysis is best suited for the research question. Descriptive statistics can be used to summarize the data and give an overall picture of what is going on. T-tests can be used to compare means between two groups, and regression analysis can be used to examine the relationships between variables.

You can use tools like IMB SPSS Software to perform all sorts of statical tests and that way “bridge the gap between data science and data understanding”. We’ve found the bellow “SPSS Tutorial for data analysis | SPSS for Beginners” tutorial video quite useful and comprehensive. 

Once the appropriate analyses have been selected, they need to be conducted. This involves running the analyses and interpreting the results. Results should be reported in a clear and concise manner, with enough detail that someone else could replicate the analyses if they wanted to.

After the data has been analyzed, it is time to write up the results. This usually takes the form of a research paper or report. The results should be presented in a way that is easy to understand, and the implications of the findings should be discussed.

This is just a brief overview of data analysis; there are many resources available that can provide more detailed information. The important thing is to get started and to keep learning as you go. With practice, analyzing data will become easier and more enjoyable.

9. Interpret data and test hypotheses

After the data has been analyzed, it is important to interpret it. This includes understanding the results of the study and what they mean for the research problem or opportunity.

When interpreting data, it is important to consider the following:

• The results of the study and what they mean for the research problem or opportunity
• The reliability and validity of the data
• The limitations of the study
• The implications of the findings

Once the data has been interpreted, it is then time to test hypotheses. This involves using statistical techniques to test whether there is a significant relationship between two or more variables.

Testing hypotheses is an important part of any scientific research as it allows researchers to determine whether their results are statistically significant. If a hypothesis is found to be statistically significant, it means that there is a real relationship between the variables being tested. If a hypothesis is not statistically significant, it means that there is no real relationship between the variables being tested.

When testing hypotheses, it is important to consider the following:

• The null hypothesis
• The alternative hypothesis
• The level of significance
• The statistical test used

Once the hypotheses have been tested, it is then time to draw conclusions. This involves Interpret data and test hypotheses reviewing the findings of the study and determining what they mean for the research problem or opportunity. When drawing conclusions, it is important to consider the following:

• The implications of the findings.

Interpret data and test hypotheses are two important steps in scientific research process. By understanding and applying these steps, researchers can ensure that their findings are accurate and reliable.

10. Write the report

After analyzing and interpreting the data, it is time to write the report. This should include a detailed description of the research process, findings, and conclusions of the study.

The research report should be written in a clear, concise, and easy-to-understand manner. It should be free of jargon and technical language, and should be accessible to a wide audience. The report should also be well-organized and well- structured.

When writing the research report, it is important to keep in mind the purpose of the research. The research report should answer the research question(s), and should address the objectives of the study. The findings of the research should be presented in a logical and coherent manner.

The conclusion of the research report should summarize the findings of the study, and should discuss their implications. The recommendations of the study should also be included in the conclusion section.

11. Present the findings

The final step is to present the findings of the study. This can be done through a number of different methods, such as presentations, posters, and reports.

The findings of the research should be presented in a way that is clear and concise. The presentation should be designed to engage the audience and encourage them to ask questions. The findings should be tailored to the specific audience, taking into account their background knowledge and understanding.

One method of presenting research findings is through a poster. Posters are a great way to summarise complex information and allow people to take away key points. They can also be used as a starting point for discussions. Another option is to give a presentation, which can be done either in person or online. Presentations offer the opportunity to go into more detail than a poster, and they can also be recorded so that they can be shared with people who were not able to attend.

Whatever method is used, it is important to remember that the research findings should be the focus of the presentation. The aim is to communicate the findings clearly and effectively, not to simply show off the work that has been done. With this in mind, it is often best to keep things simple and avoid using jargon or complex terminology.

Things to consider when presenting research findings

• Keep the audience in mind
• Present findings in a clear and concise manner
• Engage the audience and encourage questions
• Use simple language and avoid jargon whenever possible. Try explaining concepts in everyday terms.
• Focus on the research findings themselves, not on other aspects of the project.

Remember that the goal is to communicate the findings effectively.

There are a number of different ways to present research findings. Some common methods include:

• Presentations (in person or online)

Choose the method that best suits the audience and the message you want to communicate. And don’t forget – keep it simple!

Try explaining concepts in everyday terms. This will make it easier for your audience to understand your research findings.

Another important tip is to focus on the research findings themselves, not on other aspects of the project. The goal is to communicate the findings effectively, so avoid getting sidetracked by other details.

When presenting research findings, it is also important to use simple language and avoid jargon whenever possible. Try explaining concepts in everyday terms. This will make it easier for your audience to understand your research findings.

Remember that the goal is to communicate the findings effectively. With this in mind, it is often best to keep things simple and avoid using jargon or complex terminology.

One final tip: focus on the research findings themselves, not on other aspects of the project. The aim is to communicate the findings clearly and effectively, not to simply show off the work that has been done.

Keep these tips in mind when presenting research findings, and you’ll be sure to engage and inform your audience. 

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Article contents

Business research process.

• James A. Muncy James A. Muncy Marketing, Bradley University
•  and  Alice M. Muncy Alice M. Muncy Accounting, Baylor University
• https://doi.org/10.1093/acrefore/9780190224851.013.215
• Published online: 27 October 2020

Business research is conducted by both businesspeople, who have informational needs, and scholars, whose field of study is business. Though some of the specifics as to how research is conducted differs between scholarly research and applied research, the general process they follow is the same. Business research is conducted in five stages. The first stage is problem formation where the objectives of the research are established. The second stage is research design . In this stage, the researcher identifies the variables of interest and possible relationships among those variables, decides on the appropriate data source and measurement approach, and plans the sampling methodology. It is also within the research design stage that the role that time will play in the study is determined. The third stage is data collection . Researchers must decide whether to outsource the data collection process or collect the data themselves. Also, data quality issues must be addressed in the collection of the data. The fourth stage is data analysis . The data must be prepared and cleaned. Statistical packages or programs such as SAS, SPSS, STATA, and R are used to analyze quantitative data. In the cases of qualitative data, coding, artificial intelligence, and/or interpretive analysis is employed. The fifth stage is the presentation of results . In applied business research, the results are typically limited in their distribution and they must be addressed to the immediate problem at hand. In scholarly business research, the results are intended to be widely distributed through journals, books, and conferences. As a means of quality control, scholarly research usually goes through a double-blind review process before it is published.

• business research
• research design
• scholarly research
• applied research
• data collection
• data analysis
• data quality

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Chapter 6: Marketing Research

6.1 Steps in the Marketing Research Process

Learning Objectives

• Describe the basic steps in the marketing research process and the purpose of each step.

The basic steps used to conduct marketing research are shown in figure 6.1 . Next, we discuss each step.

Step 1: Define the Problem (or Opportunity)

There’s a saying in marketing research that a problem half defined is a problem half solved. Defining the “problem” of the research sounds simple, doesn’t it? Suppose your “product” is tutoring other students in a subject you enjoy. You have been tutoring for a while, and people have begun to realize you’re very good at it. Then, suddenly, your business declines. Or it explodes, and you can’t cope with the number of students you’re being asked to help. If the business has exploded, should you try to expand your services? Perhaps you should subcontract with some other smart students. You would send them students to be tutored, and they would give you a cut of their pay for each student you referred to them.

Both of these scenarios would be a problem for you, wouldn’t they? They are problems insofar as they cause you headaches. But are they really the problem? Or are they the symptoms of something bigger? For example, maybe your business has dropped off because your school is experiencing decreased enrollment so there are fewer total students on campus who need your services. Conversely, if you’re swamped with people who want you to tutor them, perhaps your school has increased enrollment so there are a greater number of students who need your services. Alternately, perhaps you posted your services on social media and that led to the influx of students wanting you to tutor them.

Businesses are in the same boat. They take a look at symptoms and try to narrow down the potential causes. If you approach a marketing research company with either scenario—either too much or too little business—the firm will seek more information from you such as the following:

• In what semester(s) did your tutoring revenues fall (or rise)?
• In what subject areas did your tutoring revenues fall (or rise)?
• In what sales channels did revenues fall (or rise): Were there fewer (or more) referrals from professors or other students? Did the social media post result in fewer (or more) referrals this month than in the past months?
• Among what demographic groups did your revenues fall (or rise)— people with certain majors, or first-year, second-, third-, or fourth-year students, local or international students?

The key is to look at all potential causes so as to narrow the parameters of the study to the information you actually need to make a good decision about how to fix your business if revenues have dropped or whether or not to expand it if your revenues have exploded.

The next task for the researcher is to put the research objective into writing. The research objective is the goal(s) the research is supposed to accomplish. The marketing research objective for your tutoring business might read as follows:

To survey university professors who teach 100- and 200-level math courses to determine why the number of students referred for tutoring dropped in the second semester.

This is admittedly a simple example designed to help you understand the basic concept. If you take a marketing research course, you will learn that research objectives get a lot more complicated than this. The following is an example:

“To gather information from a sample representative of the U.S. population among those who are ‘very likely’ to purchase an automobile within the next 6 months, which assesses preferences (measured on a 1–5 scale ranging from ‘very likely to buy’ to ‘not likely at all to buy’) for the model diesel at three different price levels. Such data would serve as input into a forecasting model that would forecast unit sales, by geographic regions of the country, for each combination of the model’s different prices and fuel configurations.” (Burns & Bush, 2010) [1]

Now do you understand why defining the problem is complicated and half the battle? Many a marketing research effort has been doomed from the start because the problem was improperly defined. Coke’s ill-fated decision to change the formula of Coca-Cola in 1985 is a case in point: Pepsi had been creeping up on Coke in terms of market share over the years as well as running a successful promotional campaign called the “Pepsi Challenge,” in which consumers were encouraged to do a blind taste test to see if they agreed that Pepsi was better. Coke spent four years researching “the problem.” Indeed, people seemed to like the taste of Pepsi better in blind taste tests. Thus, the formula for Coke was changed. But the outcry among the public was so great that the new formula didn’t last long—a matter of months—before the old formula was reinstated. Some marketing experts believe Coke incorrectly defined the problem as “How can we beat Pepsi in taste tests?” instead of “How can we gain market share against Pepsi?” (Burns & Bush, 2010) [2]

Video 6.1 documents the Coca-Cola Company’s ill-fated launch of New Coke in 1985.

Video 6.1. New Coke Is It! 1985. Source: The 1985 launch of New Coke on Christian Budtz .

Video 6.2 shows how Pepsi tried to capitalize on the mistake.

Video 6.2. 1985 Pepsi Commercial “They Changed My Coke”. Source: 1985 Pepsi commercial: They changed my Coke on eyeh8cbs .

Step 2: Design the Research

The next step in the marketing research process is to do a research design. The research design outlines what data you are going to gather and from whom, how and when you will collect the data, and how you will analyze them once they’ve been obtained. Let’s look at the data you’re going to gather first.

There are two basic types of data you can gather. The first is primary data. Primary data is information you collect yourself, using hands-on tools such as interviews or surveys, specifically for the research project you’re conducting. Secondary data are data that have already been collected by someone else, or data you have already collected for another purpose. Collecting primary data is more time-consuming, work-intensive, and expensive than collecting secondary data. Consequently, you should always try to collect secondary data first to solve your research problem, if you can. A great deal of research on a wide variety of topics already exists. If this research contains the answer to your question, there is no need for you to replicate it. Why reinvent the wheel?

Sources of Secondary Data

Your company’s internal records are a source of secondary data. So are any data you collect as part of your regular marketing intelligence-gathering efforts. You can also purchase syndicated research. Syndicated research is primary data that marketing research firms collect on a regular basis and sell to other companies. J.D. Power & Associates is a provider of syndicated research. The company conducts independent, unbiased surveys of customer satisfaction, product quality, and buyer behaviour for various industries. The company is best known for its research in the automobile sector. One of the best-known sellers of syndicated research is the Nielsen Company, which produces the Nielsen ratings. The Nielsen ratings measure the size of television, radio, and newspaper audiences in various markets. You have probably read or heard about TV shows that get the highest (Nielsen) ratings (Arbitron does the same thing for radio ratings). Nielsen, along with its main competitor, Information Resources, Inc. (IRI), also sells businesses scanner-based research . Scanner-based research is information collected by scanners at checkout stands in stores. Each week, Nielsen and IRI collect information on the millions of purchases made at stores. The companies then compile the information and sell it to firms in various industries that subscribe to their services. The Nielsen Company has also recently teamed up with Facebook to collect marketing research information. Via Facebook, users will see surveys in some of the spaces in which they used to see online ads (Rappeport & Gelles, 2009). [3]

By contrast, MarketResearch.com is an example of a marketing research aggregator. A marketing research aggregator is a marketing research company that doesn’t conduct its own research and sell it; instead, it buys research reports from other marketing research companies and then sells the reports in their entirety or in pieces to other firms. Check out MarketResearch.com’s website ( figure 6.2 ). As you will see, there are a huge number of studies in every category imaginable that you can buy for relatively small amounts of money.

Your school library is a good place to gather free secondary data. It has searchable databases as well as handbooks, dictionaries, and books, some of which you can access online. Government agencies also collect and report information on demographics, economic and employment data, health information, and balance-of-trade statistics, among a lot of other information. Statistics Canada collects census data every ten years to gather information about who lives where. Basic demographic information about sex, age, race, and types of housing in which people live in each province, metropolitan area, and rural area is gathered so that population shifts can be tracked for various purposes.

The World Bank and the United Nations are two international organizations that collect a great deal of information. Their websites contain many free research studies and data related to global markets. Table 6.1 shows some examples of primary versus secondary data sources.

Gauging the Quality of Secondary Data

When you are gathering secondary information, it’s always good to be a little skeptical. Sometimes, studies are commissioned to produce the result a client wants to hear—or wants the public to hear. For example, throughout the twentieth century, numerous studies found that smoking was good for people’s health. The problem was the studies were commissioned by the tobacco industry. Web research can also pose certain hazards. There are many biased sites that try to fool people into thinking they are providing good data. Often, the data are favourable to the products they are trying to sell. Beware of product reviews as well. Unscrupulous sellers sometimes get online and create bogus ratings for products. See below for questions you can ask to help gauge the credibility of secondary information.

Gauging the Credibility of Secondary Data: Questions to Ask

• Who gathered this information?
• For what purpose?
• What does the person or organization that gathered the information have to gain by doing so?
• Was the information gathered and reported in a systematic manner?
• Is the source of the information accepted as an authority by other experts in the field?
• Does the article provide objective evidence to support the position presented?

Types of Research Designs

Now let’s look at the most common type of research design: exploratory.

An exploratory research design is useful when you are initially investigating a problem but you haven’t defined it well enough to do an in-depth study of it. Perhaps via your regular market intelligence, you have spotted what appears to be a new opportunity in the marketplace. You would then do exploratory research to investigate it further. Exploratory research is less structured than other types of research, and secondary data are often utilized.

One form of exploratory research is qualitative research. Qualitative research is any form of research that includes gathering data that are not quantitative, and it often involves exploring questions such as why as much as what or how much . Different forms, such as in-depth interviews and focus group interviews, are common in marketing research.

Interviews —engaging in detailed, one-on-one, question-and-answer sessions with potential buyers—is an exploratory research technique. However, unlike surveys, the people being interviewed aren’t asked a series of standard questions. Instead, the interviewer is armed with some general topics and asks questions that are open ended, meaning that they allow the interviewee to elaborate. “How did you feel about the product after you purchased it?” is an example of a question that might be asked. An interview also allows a researcher to ask logical follow-up questions such as “Can you tell me what you mean when you say you felt uncomfortable using the service?” or “Can you give me some examples?” to help dig further and shed additional light on the research problem. Interviews can be conducted in person or over the phone. The interviewer either takes notes or records the interview.

Focus groups and case studies are often utilized for exploratory research as well. A focus group is a group of potential buyers who are brought together to discuss a marketing research topic with one another. A moderator is used to focus the discussion, the sessions are recorded, and the main points of consensus are later summarized by the market researcher. Textbook publishers often gather groups of professors at educational conferences to participate in focus groups. However, focus groups can also be conducted on the telephone or online using meeting software like Zoom. The basic steps of conducting a focus group are outlined below.

The Basic Steps of Conducting a Focus Group

• Establish the objectives of the focus group. What is its purpose?
• Identify the people who will participate in the focus group. What makes them qualified to participate? How many of them will you need and what they will be paid?
• Obtain contact information for the participants and send out invitations (e-mails are usually most efficient).
• Develop a list of questions.
• Choose a facilitator.
• Choose a location in which to hold the focus group and the method by which it will be recorded.
• Conduct the focus group. If the focus group is not conducted electronically, include name tags for the participants, pens and notepads, any materials the participants need to see, and refreshments. Record participants’ responses.
• Summarize the notes from the focus group and write a report for management.

A case study looks at how another company solved the problem that’s being researched. Sometimes, multiple cases, or companies, are used in a study. Case studies nonetheless have a mixed reputation. Some researchers believe it’s hard to generalize, or apply, the results of a case study to other companies. Nonetheless, collecting information about companies that encountered the same problems your firm is facing can give you a certain amount of insight about what direction you should take. In fact, one way to begin a research project is to carefully study a successful product or service.

Two other types of qualitative data used for exploratory research are ethnographies and projective techniques. In ethnography , researchers interview, observe, and often videotape people while they work, live, shop, and play. The Walt Disney Company has recently begun using ethnographers to uncover the likes and dislikes of boys aged six to fourteen, a financially attractive market segment for Disney, but one in which the company has been losing market share. The ethnographers visit the homes of boys, observe the things they have in their rooms to get a sense of their hobbies, and accompany them and their mothers when they shop to see where they go, what the boys are interested in, and what they ultimately buy (Barnes, 2009). [4]

Projective techniques are used to reveal information research respondents might not reveal by being asked directly. Asking a person to complete sentences such as the following is one technique:

People who buy Gucci handbags __________. (Will he or she reply with “are cool,” “are affluent,” or “are pretentious,” for example?)

KFC’s grilled chicken is ______.

Or the person might be asked to finish a story that presents a certain scenario. Word associations are also used to discern people’s underlying attitudes toward goods and services. When using a word-association technique, a market researcher asks a person to say or write the first word that comes to his or her mind in response to another word. If the initial word is “fast food,” what word does the person associate it with or respond with? Is it “McDonald’s”? If many people reply that way, and you’re conducting research for Burger King, that could indicate Burger King has a problem. However, if the research is being conducted for Wendy’s, which recently began running an advertising campaign with the message that Wendy’s offerings are “better than fast food,” it could indicate that the campaign is working.

In some cases, your research might end with exploratory research. Perhaps you have discovered your organization lacks the resources needed to produce the product. In other cases, you might decide you need more in-depth, quantitative research such as descriptive research or causal research, which are discussed next. Most marketing research professionals suggest using both types of research, if it’s feasible. On the one hand, the qualitative type of research used in exploratory research is often considered too “lightweight.” On the other hand, relying solely on quantitative information often results in market research that lacks ideas.

Watch video 6.3 to see a funny spoof on the usefulness—or lack of usefulness—of focus groups.

Video 6.3. The Stone Wheel: What One Focus Group Said. Source: stone and stone wheel on smack1313 .

Step 3: Design the Data-Collection Forms

If the behaviour of buyers is being formally observed and a number of different researchers are conducting observations, the data obviously need to be recorded on a standardized data-collection form that’s either paper or electronic; otherwise, the data collected will not be comparable. The items on the form could include a shopper’s sex; his or her approximate age; whether the person seemed hurried, moderately hurried, or unhurried; and whether or not he or she read the label on products, used coupons, and so forth.

The same is true when it comes to surveying people with questionnaires. Surveying people is one of the most commonly used techniques to collect quantitative data. Surveys are popular because they can be easily administered to large numbers of people fairly quickly. However, to produce the best results, the questionnaire for the survey needs to be carefully designed.

Questionnaire Design

Most questionnaires follow a similar format: They begin with an introduction describing what the study is for, followed by instructions for completing the questionnaire and, if necessary, returning it to the market researcher. The first few questions that appear on the questionnaire are usually basic, warm-up questions their respondent can readily answer, such as the respondent’s age, level of education, place of residence, and so forth. The warm-up questions are then followed by a logical progression of more detailed, in-depth questions that get to the heart of the question being researched. Lastly, the questionnaire wraps up with a statement that thanks the respondent for participating in the survey and providing information and explains when and how they will be paid for participating.

How the questions themselves are worded is extremely important. It’s human nature for respondents to want to provide the “correct” answers to the person administering the survey so as to seem agreeable. Therefore, there is always a hazard that people will try to tell you what you want to hear on a survey. Consequently, care needs to be taken that the survey questions are written in an unbiased, neutral way. In other words, they shouldn’t lead a person taking the questionnaire to answer a question one way or another by virtue of the way you have worded it. The following is an example of a leading question.

Do you agree that teachers should be paid more ?

The questions also need to be clear and unambiguous. Consider the following question:

Which brand of toothpaste do you use ?

The question sounds clear enough, but is it really? What if the respondent recently switched brands? What if she uses Crest at home, but while away from home or travelling she uses Colgate’s Wisp portable toothpaste-and-brush product? How will the respondent answer the question? Rewording the question as follows so it’s more specific will help make the question clearer:

Which brand of toothpaste have you used at home in the past six months? If you have used more than one brand, please list each of them (“Questionnaire Design,” n.d.). [5]

Sensitive questions have to be asked carefully. For example, asking a respondent, “Do you consider yourself a light, moderate, or heavy drinker?” can be tricky. Few people want to admit to being heavy drinkers. You can “soften” the question by including a range of answers, as the following example shows:

How many alcoholic beverages do you consume in a week ?

• __0–5 alcoholic beverages
• __5–10 alcoholic beverages
• __10–15 alcoholic beverages

Many people don’t like to answer questions about their income levels. Asking them to specify income ranges rather than divulge their actual incomes can help.

Other research question “don’ts” include using jargon and acronyms that could confuse people. “How often do you Snap?” is an example. Also, don’t confuse people by asking two questions in the same question, something researchers refer to as a double-barrelled question . “Do you think parents should spend more time with their children and/or their teachers?” is an example of a double-barrelled question.

Open-ended questions , or questions that ask respondents to elaborate, can be included. However, they are harder to tabulate than closed-ended questions , or questions that limit a respondent’s answers. Multiple-choice, true/false and yes/no questions are examples of closed-ended questions.

Testing the Questionnaire

If the questions are bad, the information gathered will also be bad. One way to avoid this is to test the questionnaire before sending it out to find out if there are any problems with it. Is there enough space for people to elaborate on open-ended questions? Is the font readable? To test the questionnaire, marketing research professionals first administer it to a number of respondents face to face. This gives the respondents the chance to ask the researcher about questions or instructions that are unclear or don’t make sense to them. The researcher then administers the questionnaire to a small subset of respondents in the actual way the survey is going to be disseminated, whether it’s delivered via phone, in person, by mail, or online.

Getting people to participate and complete questionnaires can be difficult. If the questionnaire is too long or hard to read, many people won’t complete it. So, by all means, eliminate any questions that aren’t necessary. Of course, including some sort of monetary incentive for completing the survey can increase the number of completed questionnaires a market researcher will receive.

Step 4: Specify the Sample

Once you have created your questionnaire or other marketing study, how do you figure out who should participate in it? Obviously, you can’t survey or observe all potential buyers in the marketplace; instead, you must choose a sample. A sample is a subset of potential buyers that are representative of your entire target market or population being studied. Sometimes market researchers refer to the population as the universe to reflect the fact that it includes the entire target market, whether it consists of a million people, a hundred thousand, a few hundred, or a dozen. “All single people over the age of eighteen who purchased an air fryer in Canada during 2020” is an example of a population that has been defined.

Obviously, the population has to be defined correctly. Otherwise, you will be studying the wrong group of people. Not defining the population correctly can result in flawed research or a sampling error. A sampling error is any type of marketing research mistake that occurs because a sample was utilized. One criticism of Internet surveys is that the people who take these surveys don’t really represent the overall population. On average, Internet survey takers tend to be more educated and tech savvy. Consequently, if they solely constitute your population, even if you screen them for certain criteria, the data you collect could end up being skewed.

There are two main categories of samples in terms of how they are drawn: probability samples and nonprobability samples. A probability sample is one in which each would-be participant has a known and equal chance of being selected. The chance is known because the total number of people in the sampling frame is known. For example, if every other person from the sampling frame were chosen, each person would have a 50 percent chance of being selected.

A nonprobability sample is any type of sample that’s not drawn in a systematic way, so the chances of each would-be participant being selected can’t be known. A convenience sample is one type of nonprobability sample. It is a sample a researcher draws because it’s readily available and convenient to do so. Surveying people on the street as they pass by is an example of a convenience sample. The question is, are these people representative of the target market?

Lastly, the size of the sample has an effect on sampling error. Larger samples generally produce more accurate results. The larger your sample is, the more data you will have, which will give you a more complete picture of what you’re studying. However, the more people surveyed or studied, the more costly the research becomes.

Statistics can be used to determine a sample’s optimal size. If you take a marketing research or statistics class, you will learn more about how to determine the optimal size.

Of course, if you hire a marketing research company, much of this work will be taken care of for you. Many marketing research companies maintain panels of prescreened people they draw upon for samples. In addition, the marketing research firm will be responsible for collecting the data or contracting with a company that specializes in data collection. Data collection is discussed next.

Step 5: Collect the Data

As we have explained, primary marketing research data can be gathered in a number of ways. Surveys, taking physical measurements, and observing people are just three of the ways we discussed. If you’re observing customers as part of gathering the data, keep in mind that if shoppers are aware of the fact, it can have an effect on their behaviour. For example, if a customer shopping for feminine hygiene products in a supermarket aisle realizes she is being watched, she could become embarrassed and leave the aisle, which would adversely affect your data. To get around problems such as these, some companies set up cameras or two-way mirrors to observe customers. Organizations also hire mystery shoppers to work around the problem. A mystery shopper is someone who is paid to shop at a firm’s establishment or one of its competitors to observe the level of service, cleanliness of the facility, and so forth and report his or her findings to the firm.

Watch the YouTube video 6.4 to get an idea of how mystery shopping works.

Video 6.4. Make Extra Money as a Mystery Shopper by KSSAyisha .

Survey data can be collected in many different ways and combinations of ways. The following are the basic methods used:

• Face-to-face (can be computer aided)
• Telephone (can be computer aided or completely automated)
• Mail and hand delivery
• E-mail and the Web

A face-to-face survey is, of course, administered by a person. The surveys are conducted in public places such as in shopping malls, on the street, or in people’s homes if they have agreed to it. In years past, it was common for researchers to knock on people’s doors to gather survey data. However, randomly collected door-to-door interviews are less common today, partly because people are afraid of crime and are reluctant to give information to strangers (McDaniel & Gates, 1998). [6]

Nonetheless, knocking on doors is still a legitimate way questionnaire data are collected. When Statistics Canada collects data on the nation’s population, it hand delivers questionnaires to rural households that do not have street-name and house-number addresses. And workers personally survey the homeless to collect information about their numbers. Face-to-face surveys are also commonly used in some countries to collect information from people who cannot read or lack phones and computers.

An advantage of face-to-face surveys is that they allow researchers to ask lengthier, more complex questions because the people being surveyed can see and read the questionnaires. The same is true when a computer is utilized. For example, the researcher might ask the respondent to look at a list of ten retail stores and rank the stores from best to worst. The same question wouldn’t work so well over the telephone because the person couldn’t see the list. The question would have to be rewritten. Another drawback with telephone surveys is that even though federal and state “do not call” laws generally don’t prohibit companies from gathering survey information over the phone, people often screen such calls using answering machines and caller ID.

Probably the biggest drawback of both surveys conducted face-to-face and administered over the phone by a person is that they are labour intensive and therefore costly. Mailing out questionnaires is costly, too, and the response rates can be rather low. Think about why that might be so: if you receive a questionnaire in the mail, it is easy to throw it in the trash; it’s harder to tell a market researcher who approaches you on the street that you don’t want to be interviewed.

By contrast, gathering survey data collected by a computer, either over the telephone or on the Internet, can be cost-effective and in some cases free. SurveyMonkey and Qualtrics are two websites that will allow you to create online questionnaires, e-mail them to up to one hundred people for free, and view the responses in real time as they come in. For larger surveys, you have to pay a subscription price of a few hundred dollars. But that still can be extremely cost-effective. See how easy it is to put together a survey in SurveyMonkey .

Like a face-to-face survey, an Internet survey can enable you to show buyers different visuals such as ads, pictures, and videos of products and their packaging. Web surveys are also fast, which is a major plus. While face-to-face and mailed surveys often take weeks to collect, you can conduct a web survey in a matter of days or even hours. And, of course, because the information is electronically gathered it can be automatically tabulated. You can also potentially reach a broader geographic group than you could if you had to personally interview people.

Another plus for web and computer surveys (and electronic phone surveys) is that there is less room for human error because the surveys are administered electronically. For instance, there’s no risk that the interviewer will ask a question wrong or use a tone of voice that could mislead the respondents. Respondents are also likely to feel more comfortable inputting the information into a computer if a question is sensitive than they would divulging the information to another person face to face or over the phone. Given all of these advantages, it’s not surprising that the Internet is quickly becoming the top way to collect primary data. However, like mail surveys, surveys sent to people over the Internet are easy to ignore.

Lastly, before the data collection process begins, the surveyors and observers need to be trained to look for the same things, ask questions the same way, and so forth. If they are using rankings or rating scales, they need to agree as to what constitutes a high ranking or a low ranking. The goal of training is to avoid a wide disparity between how different observers and interviewers record the data.

For example, if an observation form asks the observers to describe whether a shopper’s behaviour is hurried, moderately hurried, or unhurried, they should be given an idea of what defines each rating. Does it depend on how much time the person spends in the store or in the individual aisles? Is how fast they walk taken into account? In other words, the criteria and ratings need to be spelled out.

Step 6: Analyze the Data

Step 6 involves analyzing the data to ensure they’re as accurate as possible. If the research is collected by hand using a pen and pencil, it’s entered into a computer. Or respondents might have already entered the information directly into a computer. For example, when Toyota goes to an event such as a car show, the automaker’s marketing personnel ask would-be buyers to complete questionnaires directly on computers. Companies are also beginning to experiment with software that can be used to collect data using mobile phones.

The information generated by the programs can be used to draw conclusions, such as what all customers might like or not like about an offering based on what the sample group liked or did not like. The information can also be used to spot differences among groups of people. For example, the research might show that people in one area of the country like the product better than people in another area. Trends to predict what might happen in the future can also be spotted.

If there are any open-ended questions respondents have elaborated upon—for example, “Explain why you like the current brand you use better than any other brand”—the answers to each are pasted together, one on top of another, so researchers can compare and summarize the information. As we have explained, qualitative information such as this can give you a fuller picture of the results of the research.

Part of analyzing the data is to see if they seem sound. Does the way in which the research was conducted seem sound? Was the sample size large enough? Are the conclusions reached from it reasonable?

Step 7: Write the Research Report and Present Its Findings

If you end up becoming a marketing professional and conducting a research study after you graduate, hopefully you will do a great job putting the study together. You will have defined the problem correctly, chosen the right sample, collected the data accurately, analyzed them, and your findings will be sound. At that point, you will be required to write the research report and perhaps present it to an audience of decision makers. You will do so via a written report and, in some cases, a slide or PowerPoint presentation based on your written report.

The six basic elements of a research report are as follows.

• Title Page . The title page explains what the report is about, when it was conducted and by whom, and who requested it.
• Table of Contents . The table of contents outlines the major parts of the report as well as any graphs and charts and their page numbers.
• Executive Summary . The executive summary summarizes all the details in the report in a quick way. Many people who receive the report—both executives and nonexecutives—won’t have time to read the entire report. Instead, they will rely on the executive summary to quickly get an idea of the study’s results and what to do about those results.
• Methodology and Limitations . The methodology section of the report explains the technical details of how the research was designed and conducted. The section explains, for example, how the data were collected and by whom, the size of the sample, how it was chosen, and whom or what it consisted of (e.g., the number of women versus men or children versus adults). It also includes information about the statistical techniques used to analyze the data. Every study has errors—sampling errors, interviewer errors, and so forth. The methodology section should explain these details so decision makers can consider their overall impact. The margin of error is the overall tendency of the study to be off kilter—that is, how far it could have gone wrong in either direction. Remember how newscasters present the presidential polls before an election? They always say, “This candidate is ahead 48 to 44 percent, plus or minus 2 percent.” That “plus or minus” is the margin of error. The larger the margin of error is, the less likely the results of the study are accurate. The margin of error needs to be included in the methodology section.
• Findings . The findings section is a longer, fleshed-out version of the executive summary that goes into more detail about the statistics uncovered by the research that bolster the study’s findings. If you have related research or secondary data on hand that back up the findings, they can be included to help show the study did what it was designed to do.
• Recommendations . The recommendations section should outline the course of action you think should be taken based on the findings of the research and the purpose of the project. For example, if you conducted a global market research study to identify new locations for stores, make a recommendation for the locations (Mersdorf, 2009). [7]

As we have said, these are the basic sections of a marketing research report. However, additional sections can be added as needed. For example, you might need to add a section on the competition and each firm’s market share. If you’re trying to decide on different supply chain options, you will need to include a section on that topic.

As you write the research report, keep your audience in mind. Don’t use technical jargon decision makers and other people reading the report won’t understand. If technical terms must be used, explain them. Also, proofread the document to identify any grammatical errors and typos and ask a couple of other people to proofread it to catch any mistakes you might have missed. If your research report is riddled with errors, its credibility will be undermined, even if the findings and recommendations you make are extremely accurate.

Many research reports are presented via PowerPoint. If you’re asked to create a slideshow presentation from the report, don’t try to include every detail in the report on the slides. The information will be too long and tedious for people attending the presentation to read through. And if they do go to the trouble of reading all the information, they probably won’t be listening to the speaker who is making the presentation.

Instead of including all the information from the study in the slides, boil each section of the report down to key points and add some “talking points” only the presenter will see. After or during the presentation, you can give the attendees the longer, paper version of the report so they can read the details at a convenient time.

Key Takeaways

• Step 1 in the marketing research process is to define the problem. Businesses look at what they believe are symptoms and drill down to the potential causes so as to precisely define the problem. The next task for the researcher is to put into writing the research objective, or goal, the research is supposed to accomplish.
• Step 2 in the process is to design the research. The research design is the “plan of attack.” It outlines what data you are going to gather, from whom, how, and when, and how you’re going to analyze it once it has been obtained.
• Step 3 is to design the data-collection forms, which need to be standardized so the information gathered on each is comparable. Surveys are a popular way to gather data because they can be quickly and easily administered to large numbers of people. However, to produce the best results, survey questionnaires need to be carefully designed and pretested before they are used.
• Step 4 is drawing the sample, or a subset of potential buyers who are representative of your entire target market. If the sample is not correctly selected, the research will be flawed.
• Step 5 is to actually collect the data, whether they’re collected by a person face to face, over the phone, or with the help of computers or the Internet. The data-collection process is often different in foreign countries.
• Step 6 is to analyze the data collected for any obvious errors, tabulate the data, and then draw conclusions from them based on the results. The last step in the process,
• Step 7 is writing the research report and presenting the findings to decision makers.

Review and Reflect

• Explain why it’s important to carefully define the problem or opportunity a marketing research study is designed to investigate.
• Describe the different types of problems that can occur when marketing research professionals develop questions for surveys.
• What sections should be included in a marketing research report? What is each section designed to do?

Media Attributions

• Steps in the Marketing Research Process © University of Minnesota Libraries Publishing is licensed under a CC BY-NC-SA (Attribution NonCommercial ShareAlike) license
• Burns, A., & Bush, R. (2010). Marketing research (6th ed.). Prentice Hall. ↵
• Rappeport, A., & Gelles, D. (2009, September 23). Facebook to form alliance with Nielsen. Financial Times, 16 . ↵
• Barnes, B. (2009, April 15). Disney expert uses science to draw boy viewers . New York Times . Accessed December 14, 2009. ↵
• Questionnaire design . (n.d.). QuickMBA. Accessed December 14, 2009. ↵
• McDaniel, C. D., & Gates, R. H. (1998). Marketing research essentials (2nd ed.). South-Western College Publishing. ↵
• Mersdorf, S. (2009, August 24). How to organize your next survey report . Cvent. Accessed July 31, 2023). ↵

the goal(s) the research is supposed to accomplish

what data you are going to gather and from whom, how and when you will collect the data, and how you will analyze them once they’ve been obtained

information you collect yourself, using hands-on tools such as interviews or surveys, specifically for the research project you’re conducting

data that have already been collected by someone else, or data you have already collected for another purpose

primary data that marketing research firms collect on a regular basis and sell to other companies

information collected by scanners at checkout stands in stores

a marketing research company that buys research reports from other marketing research companies and then sells the reports in their entirety or in pieces to other firms

when you are initially investigating a problem but you haven’t defined it well enough to do an in-depth study of it

any form of research that includes gathering data that are not quantitative, and it often involves exploring questions such as why as much as what or how much

engaging in detailed, one-on-one, question-and-answer sessions with potential buyers

a group of potential buyers who are brought together to discuss a marketing research topic with one another

analyzes how another company solved the problem that’s being researched

researchers interview, observe, and often videotape people while they work, live, shop, and play

used to reveal information research respondents might not reveal by being asked directly

asking two questions in the same question

questions that ask respondents to elaborate

questions that limit a respondent’s answers

a subset of potential buyers that are representative of your entire target market

from which you derive your target market

any type of marketing research mistake that occurs because a sample was utilized

each would-be participant has a known and equal chance of being selected

any type of sample that’s not drawn in a systematic way

a sample a researcher draws because it’s readily available and convenient to do so

someone who is paid to shop at a firm’s establishment or one of its competitors to observe the level of service, cleanliness of the facility, and so forth and report his or her findings to the firm

the overall tendency of the study to be off kilter

Introduction to Marketing Copyright © 2024 by Pamela Ip is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Business Research Process Design

Learning objectives.

Upon completion of this chapter, you will be able to:

• Understand the steps in conducting research
• Understand the types of research
• Learn the purposes and methods of conducting exploratory research
• Learn about descriptive research and the types of descriptive research
• Have a preliminary idea about causal research
• Establish a difference between exploratory research, descriptive research, and causal research

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The ultimate guide to research design for business.

17 min read To get the information you need to drive key business decisions and answer burning questions, you need a research methodology that works — and it all starts with research design. But what is it? In our ultimate guide to research design for businesses, we breakdown the process, including research methods, examples, and best practice tips to help you get started.

If you have a business problem that you’re trying to solve — from product usage to customer engagement — doing research is a great way to understand what is going wrong.

Yet despite this, less than 40% of marketers use consumer research to drive decisions [1] .

So why are businesses missing out on vital business insights that could help their bottom line?

One reason is that many simply don’t know which research method to use to correctly investigate their problem and uncover insights.

This is where our ultimate guide to research design can help. But first…

What is research design?

Research design is the overall strategy (or research methodology) used to carry out a study. It defines the framework and plan to tackle  established problems  and/or questions through the collection, interpretation, analysis, and discussion of data.

While there are several types of research design (more on that later), the research problem defines which should be used — not the other way around. In working this way, researchers can be certain that their methods match their aims — and that they’re capturing useful and actionable data.

For example, you might want to know why sales are falling for a specific product. You already have your context and other research questions to help uncover further insights. So, you start with your research problem (or problem statement) and choose an approach to get the information you need.

Download our free eBook: How to get inclusive research design right

Key considerations before a research project

After you have your research problem and research questions to find out more information, you should always consider the following elements:

• Do you want to use a qualitative or quantitative approach ?
• What type of research would you like to do (e.g. — create a survey or conduct telephone interviews)?
• How will you choose your population and sample size fairly?
• How will you choose a method to collect the data for ease of operation? The research tool you use will determine the validity of your study
• How will you analyse data after collection to help the business concern?
• How will you ensure your research is free from bias and neutral?
• What’s your timeline?
• In what setting will you conduct your research study?
• Are there any challenges or objections to conducting your research — and if so, how can you address them?

Ultimately, the data received should be unambiguous, so that the analysts can find accurate and trustworthy insights to act upon. Neutrality is key!

Types of approaches in research design

There are two main approaches to research design that we’ll explore in more detail — quantitative and qualitative.

Qualitative research design

Qualitative research designs tend to be more flexible and inductive (broad generalisations rather than specific observations), allowing you to adjust your approach based on the information you find throughout the research process. It looks at customer or prospect data (X data).

For example, if you want to generate new ideas for content campaigns, a qualitative approach would make the most sense. You can use this approach to find out more about what your audience would like to see, the particular challenges they are facing (from a business perspective), their overall experiences, and if any topics are under-researched.

To put it simply, qualitative research design looks at the whys and hows — as well as participants’ thoughts, feelings, and beliefs. It seeks to find reasons to explain decisions using the data captured.

However, as the data collected from qualitative research is typically written rather than numerical, it can be difficult to quantify information using statistical techniques.

When should you use qualitative research design?

It is best used when you want to conduct a detailed investigation of a topic to understand a holistic view. For example, to understand cultural differences in society, qualitative research design would create a research plan that allowed as many people from different cultures to participate and provided space for elaboration and anecdotal evidence.

If you want to incorporate a qualitative research design, you may choose to use methods like semi-structured focus groups,  surveys  with open-ended questions, or  in-depth interviews  in person or on the phone.

Quantitative research design

Quantitative research design looks at data that helps answer the key questions beginning with ‘Who’, ‘How’, ‘How many’ and ‘What’. This can include business data that explores operation statistics and sales records and quantifiable data on preferences.

Unlike qualitative research design, quantitative research design can be more controlled and fixed. It establishes variables, hypotheses, and correlations and tests participants against this knowledge. The aim is to explore the numerical data and understand its value against other sets of data, providing us with a data-driven way to measure the level of something.

When should you use quantitative research design?

If you want to quantify attitudes, opinions, behaviours, or any other defined variable (and general results from a large sample population), a quantitative approach is a way to go.

You could use quantitative research to validate findings from qualitative research. One provides depth and insight into the whys and hows, while the other delivers data to support them.

If you want to incorporate a quantitative research design, you may choose to use methods like secondary research collection or surveys with closed-ended questions.

Now that you know the differences between the two research approaches ( though you can find out more ), we can go further and address their sub-categories.

Research methods: the subsets of qualitative and quantitative research

Depending on the aim/objective of your research, there are several research methods (for both qualitative and quantitative research) for you to choose from:

Types of quantitative research design:

• Descriptive –  provides information on the current state of affairs, by observing participants in a natural situation
• Experimental  – provides causal relationship information between variables within a controlled situation
• Quasi-experimental  – attempts to build a cause and effect relationship between an independent variable and a dependent variable
• Correlational  – as the name suggests, correlational design allows the researcher to establish some kind of relation between two closely related topics or variables

Types of qualitative research design:

• Case studies  – a detailed study of a specific subject (place, event, organization)
• Ethnographic research  – in-depth observational studies of people in their natural environment (this research aims to understand the cultures, challenges, motivations and settings of those involved)
• Grounded theory  – collecting rich data on a topic of interest and developing theories inductively
• Phenomenology  – investigating a phenomenon or event by describing and interpreting the shared experiences of participants
• Narrative research  – examining how stories are told to understand how participants perceive and make sense of their experiences

Other subsets of qualitative and quantitative research design

• Exploratory  – explores a new subject area by taking a holistic viewpoint and gathering foundational insights
• Cross-sectional  – provides a snapshot of a moment in time to reflect the state
• Longitudinal  – provides several snapshots of the same sample over a period to understand causal relationships
• Mixed methods  – provide a bespoke application of design subsets to create more precise and nuanced results
• Observational  – involves observing participants’ ongoing behavior in a natural situation

Let’s talk about these research methods in more detail.

Experimental

As a subset of  quantitative  research design types, experimental research design aims to control variables in an experiment to test a hypothesis. Researchers will alter one of the variables to see how it affects the others.

Experimental research design provides an understanding of the causal relationships between two variables – which variable impacts the other, to what extent they are affected, and how consistent is the effect if the experiment is repeated.

To incorporate experimental research design, researchers create an artificial environment to more easily control the variables affecting participants. This can include creating two groups of participants – one acting as a control group to provide normal data readings, and another that has a variable altered. Therefore, having representative and random groups of participants can give better results to compare.

Image source: World Bank Blogs

Descriptive

Descriptive research design is a subset of  qualitative  design research and, unlike experimental design research, it provides descriptive insights on participants by observing participants in an uncontrolled, geographically-bound natural environment.

This type gives information on the current state of participants when faced with variables or changing circumstances. It helps answer who, what, when, where, and how questions on behaviour, but it can’t provide a clear understanding of the why.

To incorporate a descriptive research design, researchers create situations where observation of participants can happen without notice. In capturing the information, researchers can analyse data to understand the different variables at play or find additional research areas to investigate.

Exploratory

Exploratory research design aims to investigate an area where little is known about the subject and there are no prior examples to draw insight from. Researchers want to gain insights into the foundational data (who, what, when, where, and how) and the deeper level data (the why).

Therefore, an exploratory research design is flexible and a subset of both  quantitative  and  qualitative  research design.

Like descriptive research design, this type of research method is used at the beginning stages of research to get a broader view, before proceeding with further research.

To incorporate exploratory research design, researchers will use several methods to gain the right data. These can include focus groups, surveys, interviews in person or on the phone, secondary desk research, controlled experiments, and observation in a natural setting.

Cross-sectional

Just like slicing through a tomato gives us a slice of the whole fruit, cross-sectional research design gives us a slice representing a specific point in time. Researchers can observe different groups at the same time to discover what makes the participant behaviour different from one another and how behaviour correlates. This is then used to form assumptions that can be further tested.

There are two types to consider. In descriptive cross-sectional research design, researchers do not get involved or influence the participants through any controls, so this research design type is a subset of  quantitative  research design. Researchers will use methods that provide a descriptive (who, what, when, where, and how) understanding of the cross-section. This can be done by survey or observation, though researcher bias can be an undesirable outcome if the method is not conscious of this.

Analytical cross-sectional research design looks at the why behind the outcome found in the cross-section, aligning this as a subset of  qualitative  research design. This understanding can be gained through emailed surveys. To gain stronger insights, group sample selection can be altered from a random selection of participants to researchers selecting participants into groups based on their differences.

Since only one cross-section is taken, this can be a cheaper and quicker way to carry out research when resources are limited. Yet, no causal relationships can be gained by comparing data across time, unlike longitudinal research design.

Longitudinal

Longitudinal research design takes multiple measures from the same participants or groups over an extended period. These repeated observations enable researchers to track variables, identify correlations and see if there are causal relationships that can confirm hypothesis predictions.

As the research design is focused on understanding the why behind the data, this is a subset of  qualitative  research design. However, the real-time data collection at each point in time will also require analysis based on the quantitative markers found through  quantitative  research design.

Researchers can incorporate longitudinal research design by using methods like panel studies for collecting primary data first-hand. The study can be retrospective (based on event data that has already occurred) or prospective (based on event data that is yet to happen).

While being the most useful method to get the data you need to address your business concern, this can be time-consuming and there can be issues with maintaining the integrity of the sample over time. Alternatively, you can use existing data sets to provide historical trends (which could be verified through a cross-sectional research design).

Mixed methods

Mixed methods aim to provide an advanced and bespoke response to solving your business problem. It combines the methods and subsets above to create a tailored method that gives researchers flexibility and options for carrying out research.

The mixed-method research design gives a thorough holistic view of the layers of data through  quantitative  and  qualitative subset design methods. The resulting data is strengthened by the application of context and scale (quantitative) in alignment with the meaning behind behaviour (qualitative), giving a richer picture of participants.

Mixed method research design is useful for getting greater ‘texture’ to your data, resulting in precise and meaningful information for analysis. The disadvantages and boundaries of a single subset can be offset by the benefits of using another to complement the investigation.

This subset does place more responsibility on the researcher to apply the subset designs appropriately to gain the right information. The data is interpreted and assessed by the researcher for its validity to the end results, so there is potential for researcher bias if they miss out on vital information that skews results.

Image Source: Full Stack Researcher

Find the research design method(s) that work for you

No matter what information you want to find out — there’s a research design method that’s right for you.

However, it’s up to you to determine which of the methods above are the most viable and can deliver the insight you need. Remember, each research method has its advantages and disadvantages.

It’s also important to bear in mind (at all times), the key considerations before your research project:

• Do you want to use a qualitative or quantitative approach?
• Are there any challenges or objections to conducting your research — and if so, how can you address them?.

But if you’re unsure about where to begin, start by answering these questions with our decision tree:

Image Source: Research Gate

If you need more help, why not try speaking to one of our Qualtrics team members?

Our team of experts can help you with all your  market research  needs — from designing your study and finding respondents, to fielding it and reporting on the results.

[1] https://www.thinkwithgoogle.com/consumer-insights/consumer-trends/marketing-consumer-research-statistics/

eBook: How to get inclusive research design right

Related resources

Market intelligence 9 min read, qualitative research questions 11 min read, ethnographic research 11 min read, business research methods 12 min read, qualitative research design 12 min read, business research 10 min read, qualitative research interviews 11 min read, request demo.

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Business Research Process

• Post author: MyLibrary24
• Post published: January 9, 2019
• Post category: Business Research
• Post comments: 0 Comments

The research process consists of a series of steps necessary to carry out the research efficiently & effectively. The research process may vary based on the types of research. But in general, The research process may involve the following sequential steps-

• Problem Definition: The first step in the Business Research Process Is to choose a problem to investigate. Problem is concise and well-defined.
• Literature survey: Literature survey is especially important because it obviates the need to re-invent the wheel for every new research question.
• Developing of working hypothesis: Hypothesis should be developed. It provides directions to research.
• Research design: It is the most important task because research design is the conceptual framework within which research is conducted. It is a blue print of for collection, measurement & analysis of data.
• Determining sample design: Sample is the representative part of population .
• Primary Data: Primary data can be collected either through experiment or through survey .
• Secondary Data: Secondary data mean data that are already available.
• Data processing & analysis: Data analysis is the application of reasoning to understand the data that have been gathered In its simplest form, analysis may involve determining patterns and summarizing the relevant details revealed in the investigation.
• Testing hypothesis: After analyzing the data as stated above, the researcher is an a position to test the hypotheses, if any, he had formulated earlier.
• Generalizations & interpretation: If a hypothesis is tested and upheld several times, it may be possible for the researcher to arrive at generalization and interpretation.
• Preparing the research report: Finally, the researcher has to prepare the report of what has been done by him.

Formulating the research problem:

There are two types of Business Research Process problems. At the terribly start the investigator should single out the matter he needs to review. at first, the matter could also be declared during a broad general method and so the ambiguities if any, regarding the matter, be resolved.

Then the feasibleness of a selected resolution must be thought about before an operating formulation of the matter will come upon. The formulation of a general topic into a specific research problem constitutes the first step in a scientific inquiry. Essentially two steps are involved in formulating the research problem such as:

• Understanding the problem
• Rephrasing the problem

By understanding and rephrasing the problem, the researchers try to formulate the research problem and make success solution.

Literature Review:

After defining the research problem the next step in the research process is to make an extensive literature review [The Literature Review: A Step-by-Step Guide for Students (SAGE Study Skills Series) Second Edition by Diana Ridley (Author)] . In This stage, the researcher needs to review previous studies that have been made on the problem or topic defined by the researcher.

An extensive literature view helps the researcher to define the problem clearly and provides guidelines regarding how to conduct the study. This also makes the justification of the topic undertaken by the researcher. Good library management can contribute a lot in this regard.

Developing Working Hypothesis:

After an intensive literature survey, analysis ought to state in clear terms the operating hypothesis or hypotheses. The operating hypothesis is a tentative assumption created so as to extend and check its logical or empirical consequences. Working hypotheses are developed by using the following approaches:-

• Discussions with colleagues and experts about the problem, its origin and the objectives for getting its solution.
• Examination of data and records.
• Review of similar studies in the area of similar problems.
• Exploratory personal investigation that involves original field interviews on a restricted scale with interested parties and people.

What is research Design?

A research design is a plan of the suggested research work. The decision regarding what, where, when, how, what means regarding the study constitutes research design [Research Design and Statistical Analysis: Third Edition 3rd Edition. by Jerome L. Myers (Author), Arnold D. Well (Author), Robert F. Lorch Jr (Author)] . This is the most difficult and formidable task in the research process.

At the same time; it is the most important task because research design is the conceptual framework within which research is conducted. It is a blueprint for the collection, measurement & analysis of data. A good research design tries to answer the following questions:

• What is the study about?
• Why is the study being made?
• Where will the study be carried out?
• What is the scope of the study?
• What types of data is required?
• Where can the required data be found?
• What periods of time will the study include?
• What will be the approx. expenditure?
• What will be the sample design?
• In what style will the report be prepared?
• What will be the methodology for research?
• What techniques of data collection will be used?
• How will the data be analys?

Determining Sample Design:

The sample is the representative part of the Population. All the things into consideration in any field of inquiry represent a ‘universe’ or ‘population’. A complete enumeration of all the items in the ‘population’ is known as census inquiry.

It can be presumed that in such an inquiry when all the items are covered no element of chances is left and the highest accuracy is obtained. But in practice, it may not be true.

The research worker should decide the means of choosing a sample of what’s popularly called the sample style. In different words, a sample style may be a definite setup determined before any date is literally collected for getting a sample from a given population.

Sample design can be of two types:

Samples are either likelihood samples or non-probability samples. With probability samples, each element has a known probability of being included in the sample. But the node-probability sample doesn’t enable the scientist to work out this likelihood.

Probability samples are those based on simple random sampling, systematic sampling, stratified sampling, cluster/area sampling, whereas non-probability samples are those based on convenience sampling, judgment sampling, and quota sampling techniques. [Sampling Techniques, 3rd Edition 3rd Edition. by William G. Cochran (Author)]

Data Collection:

After determining the sample design, the researcher needs to collect data. Data can be collected from different sources. We can classify the data into two types:

• Primary Data : Primary information may be collected either through experiment or through a survey. If the man of science conducts associate degree experiment, the reality contained in his hypothesis.
• Various publication of the central, state area unit native governments.
• Various publication of foreign governments or international bodies and their subsidiary organizations.
• Technical and trade journals.
• Books, magazines and newspapers.
• Reports and publications of various associations connected with business, industry, banks and stock exchanges etc.
• Reports ready by analysis students, universities, economists etc. in several fields and documents and different sources of printed info.
• Public records and statistics history

The sources of unpublished data are many. They may be found in diaries, letters, unpublished biographies and autobiographies and conjointly could also be accessible with students and analysis staff, trade associations, labor bureaus, and alternative public/private people and organizations.

Data Processing & Analysis:

After the fieldwork has been completed, the data must be converted into a format that will answer the manager’s questions. This is a part of the data processing and analysis stage. Here, the information content will be determined from the raw data.

Data processing generally begins with editing and coding the data. Editing involves checking the data collection forms for omissions, legibility, and consistency in the classification.

Before knowledge may be tabulated, pregnant classes and character symbols should be established for teams of responses. The rules for interpreting, categorizing, recording, and transferring the data to the data storage media are called codes.

The coding process facilities computer and had tabulation. If computer analysis is to be used, the data are entered into the computer and verified. Computer-assisted (online) interviewing is an example of the impact of technological change on the research process. Telephone interviewers, seated at computer terminals, read survey questions displayed on the monitor.

The interviewer asked the question and then types in the respondent’s answer. Thus, answers are collected and processed into the computer at the same time, eliminating intermediate steps that could introduce errors.

Data Analysis:

Data analysis is that the application of reasoning to know the information that is gathered. In its simplest form, the analysis may involve determining consistent patterns and summarizing the relevant details revealed in the investigation. [Data Analysis for Business Decisions: A Laboratory Manual 2nd Edition. by Andres Fortino (Author)]

The appropriate analytical technique for knowledge analysis is determined by management’s info necessities, the characteristics of the analysis style, and also the nature of the information gathered. Statistical analysis may range from prettying simple frequency distribution to more complex multivariate analyses approaches, such as multiple regression.

Preparing the Research Report:

Finally, the research has to make a report of what has been done by him. Writing of report must be done great cake keeping in view the following:

• The preliminary pages.
• The main text, and
• The end matter.
• Introduction : It should contain a clean statement of the objective of the research and an interpretation of the methodology accepted in accomplishing the research.Summary of findings: After introduction there would appear a statement of findings and recommendations in not-technical language.
• Main report: The primary body of the report should be presented in logical sequence and broken-down into easily identifiable sections.
• Conclusion: Towards the end of the main text researcher should again put down the results of this research clearly and precisely. In fact, it is the final summing up of the report.
• Report should be written in a concise.
• Charts and illustrations in the main report should be used clearly.
• Calculated confidence limits must be mentioned.

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Research Process: 8 Steps in Research Process

The research process starts with identifying a research problem and conducting a literature review to understand the context. The researcher sets research questions, objectives, and hypotheses based on the research problem.

A research study design is formed to select a sample size and collect data after processing and analyzing the collected data and the research findings presented in a research report.

What is the Research Process?

There are a variety of approaches to research in any field of investigation, irrespective of whether it is applied research or basic research. Each research study will be unique in some ways because of the particular time, setting, environment, and place it is being undertaken.

Nevertheless, all research endeavors share a common goal of furthering our understanding of the problem, and thus, all traverse through certain primary stages, forming a process called the research process.

Understanding the research process is necessary to effectively carry out research and sequence the stages inherent in the process.

How Research Process Work?

Eight steps research process is, in essence, part and parcel of a research proposal. It is an outline of the commitment that you intend to follow in executing a research study.

A close examination of the above stages reveals that each of these stages, by and large, is dependent upon the others.

One cannot analyze data (step 7) unless he has collected data (step 6). One cannot write a report (step 8) unless he has collected and analyzed data (step 7).

Research then is a system of interdependent related stages. Violation of this sequence can cause irreparable harm to the study.

It is also true that several alternatives are available to the researcher during each stage stated above. A research process can be compared with a route map.

The map analogy is useful for the researcher because several alternatives exist at each stage of the research process.

Choosing the best alternative in terms of time constraints, money, and human resources in our research decision is our primary goal.

Before explaining the stages of the research process, we explain the term ‘iterative’ appearing within the oval-shaped diagram at the center of the schematic diagram.

The key to a successful research project ultimately lies in iteration: the process of returning again and again to the identification of the research problems, methodology, data collection, etc., which leads to new ideas, revisions, and improvements.

By discussing the research project with advisers and peers, one will often find that new research questions need to be added, variables to be omitted, added or redefined, and other changes to be made. As a proposed study is examined and reexamined from different perspectives, it may begin to transform and take a different shape.

This is expected and is an essential component of a good research study.

Besides, examining study methods and data collected from different viewpoints is important to ensure a comprehensive approach to the research question.

In conclusion, there is seldom any single strategy or formula for developing a successful research study, but it is essential to realize that the research process is cyclical and iterative.

What is the primary purpose of the research process?

The research process aims to identify a research problem, understand its context through a literature review, set research questions and objectives, design a research study, select a sample, collect data, analyze the data, and present the findings in a research report.

Why is the research design important in the research process?

The research design is the blueprint for fulfilling objectives and answering research questions. It specifies the methods and procedures for collecting, processing, and analyzing data, ensuring the study is structured and systematic.

8 Steps of Research Process

Identifying the research problem.

The first and foremost task in the entire process of scientific research is to identify a research problem .

A well-identified problem will lead the researcher to accomplish all-important phases of the research process, from setting objectives to selecting the research methodology .

But the core question is: whether all problems require research.

We have countless problems around us, but all we encounter do not qualify as research problems; thus, these do not need to be researched.

Keeping this point in mind, we must draw a line between research and non-research problems.

Intuitively, researchable problems are those that have a possibility of thorough verification investigation, which can be effected through the analysis and collection of data. In contrast, the non-research problems do not need to go through these processes.

Researchers need to identify both;

Non-Research Problems

Statement of the problem, justifying the problem, analyzing the problem.

A non-research problem does not require any research to arrive at a solution. Intuitively, a non-researchable problem consists of vague details and cannot be resolved through research.

It is a managerial or built-in problem that may be solved at the administrative or management level. The answer to any question raised in a non-research setting is almost always obvious.

The cholera outbreak, for example, following a severe flood, is a common phenomenon in many communities. The reason for this is known. It is thus not a research problem.

Similarly, the reasons for the sudden rise in prices of many essential commodities following the announcement of the budget by the Finance Minister need no investigation. Hence it is not a problem that needs research.

How is a research problem different from a non-research problem?

A research problem is a perceived difficulty that requires thorough verification and investigation through data analysis and collection. In contrast, a non-research problem does not require research for a solution, as the answer is often obvious or already known.

Non-Research Problems Examples

A recent survey in town- A found that 1000 women were continuous users of contraceptive pills.

But last month’s service statistics indicate that none of these women were using contraceptive pills (Fisher et al. 1991:4).

The discrepancy is that ‘all 1000 women should have been using a pill, but none is doing so. The question is: why the discrepancy exists?

Well, the fact is, a monsoon flood has prevented all new supplies of pills from reaching town- A, and all old supplies have been exhausted. Thus, although the problem situation exists, the reason for the problem is already known.

Therefore, assuming all the facts are correct, there is no reason to research the factors associated with pill discontinuation among women. This is, thus, a non-research problem.

A pilot survey by University students revealed that in Rural Town-A, the goiter prevalence among school children is as high as 80%, while in the neighboring Rural Town-A, it is only 30%. Why is a discrepancy?

Upon inquiry, it was seen that some three years back, UNICEF launched a lipiodol injection program in the neighboring Rural Town-A.

This attempt acted as a preventive measure against the goiter. The reason for the discrepancy is known; hence, we do not consider the problem a research problem.

A hospital treated a large number of cholera cases with penicillin, but the treatment with penicillin was not found to be effective. Do we need research to know the reason?

Here again, there is one single reason that Vibrio cholera is not sensitive to penicillin; therefore, this is not the drug of choice for this disease.

In this case, too, as the reasons are known, it is unwise to undertake any study to find out why penicillin does not improve the condition of cholera patients. This is also a non-research problem.

In the tea marketing system, buying and selling tea starts with bidders. Blenders purchase open tea from the bidders. Over the years, marketing cost has been the highest for bidders and the lowest for blenders. What makes this difference?

The bidders pay exorbitantly higher transport costs, which constitute about 30% of their total cost.

Blenders have significantly fewer marketing functions involving transportation, so their marketing cost remains minimal.

Hence no research is needed to identify the factors that make this difference.

Here are some of the problems we frequently encounter, which may well be considered non-research problems:

• Rises in the price of warm clothes during winter;
• Preferring admission to public universities over private universities;
• Crisis of accommodations in sea resorts during summer
• Traffic jams in the city street after office hours;
• High sales in department stores after an offer of a discount.

Research Problem

In contrast to a non-research problem, a research problem is of primary concern to a researcher.

A research problem is a perceived difficulty, a feeling of discomfort, or a discrepancy between a common belief and reality.

As noted by Fisher et al. (1993), a problem will qualify as a potential research problem when the following three conditions exist:

• There should be a perceived discrepancy between “what it is” and “what it should have been.” This implies that there should be a difference between “what exists” and the “ideal or planned situation”;
• A question about “why” the discrepancy exists. This implies that the reason(s) for this discrepancy is unclear to the researcher (so that it makes sense to develop a research question); and
• There should be at least two possible answers or solutions to the questions or problems.

The third point is important. If there is only one possible and plausible answer to the question about the discrepancy, then a research situation does not exist.

It is a non-research problem that can be tackled at the managerial or administrative level.

Research Problem Examples

Research problem – example #1.

While visiting a rural area, the UNICEF team observed that some villages have female school attendance rates as high as 75%, while some have as low as 10%, although all villages should have a nearly equal attendance rate. What factors are associated with this discrepancy?

We may enumerate several reasons for this:

• Villages differ in their socio-economic background.
• In some villages, the Muslim population constitutes a large proportion of the total population. Religion might play a vital role.
• Schools are far away from some villages. The distance thus may make this difference.

Because there is more than one answer to the problem, it is considered a research problem, and a study can be undertaken to find a solution.

Research Problem – Example #2

The Government has been making all-out efforts to ensure a regular flow of credit in rural areas at a concession rate through liberal lending policy and establishing many bank branches in rural areas.

Knowledgeable sources indicate that expected development in rural areas has not yet been achieved, mainly because of improper credit utilization.

More than one reason is suspected for such misuse or misdirection.

These include, among others:

• Diversion of credit money to some unproductive sectors
• Transfer of credit money to other people like money lenders, who exploit the rural people with this money
• Lack of knowledge of proper utilization of the credit.

Here too, reasons for misuse of loans are more than one. We thus consider this problem as a researchable problem.

Research Problem – Example #3

Let’s look at a new headline: Stock Exchange observes the steepest ever fall in stock prices: several injured as retail investors clash with police, vehicles ransacked .

Investors’ demonstration, protest and clash with police pause a problem. Still, it is certainly not a research problem since there is only one known reason for the problem: Stock Exchange experiences the steepest fall in stock prices. But what causes this unprecedented fall in the share market?

Experts felt that no single reason could be attributed to the problem. It is a mix of several factors and is a research problem. The following were assumed to be some of the possible reasons:

• The merchant banking system;
• Liquidity shortage because of the hike in the rate of cash reserve requirement (CRR);
• IMF’s warnings and prescriptions on the commercial banks’ exposure to the stock market;
• Increase in supply of new shares;
• Manipulation of share prices;
• Lack of knowledge of the investors on the company’s fundamentals.

The choice of a research problem is not as easy as it appears. The researchers generally guide it;

• own intellectual orientation,
• level of training,
• experience,
• knowledge on the subject matter, and
• intellectual curiosity.

Theoretical and practical considerations also play a vital role in choosing a research problem. Societal needs also guide in choosing a research problem.

Once we have chosen a research problem, a few more related steps must be followed before a decision is taken to undertake a research study.

These include, among others, the following:

• Statement of the problem.
• Justifying the problem.
• Analyzing the problem.

A detailed exposition of these issues is undertaken in chapter ten while discussing the proposal development.

A clear and well-defined problem statement is considered the foundation for developing the research proposal.

It enables the researcher to systematically point out why the proposed research on the problem should be undertaken and what he hopes to achieve with the study’s findings.

A well-defined statement of the problem will lead the researcher to formulate the research objectives, understand the background of the study, and choose a proper research methodology.

Once the problem situation has been identified and clearly stated, it is important to justify the importance of the problem.

In justifying the problems, we ask such questions as why the problem of the study is important, how large and widespread the problem is, and whether others can be convinced about the importance of the problem and the like.

Answers to the above questions should be reviewed and presented in one or two paragraphs that justify the importance of the problem.

As a first step in analyzing the problem, critical attention should be given to accommodate the viewpoints of the managers, users, and researchers to the problem through threadbare discussions.

The next step is identifying the factors that may have contributed to the perceived problems.

Issues of Research Problem Identification

There are several ways to identify, define, and analyze a problem, obtain insights, and get a clearer idea about these issues. Exploratory research is one of the ways of accomplishing this.

The purpose of the exploratory research process is to progressively narrow the scope of the topic and transform the undefined problems into defined ones, incorporating specific research objectives.

The exploratory study entails a few basic strategies for gaining insights into the problem. It is accomplished through such efforts as:

Pilot Survey

A pilot survey collects proxy data from the ultimate subjects of the study to serve as a guide for the large study. A pilot study generates primary data, usually for qualitative analysis.

This characteristic distinguishes a pilot survey from secondary data analysis, which gathers background information.

Case Studies

Case studies are quite helpful in diagnosing a problem and paving the way to defining the problem. It investigates one or a few situations identical to the researcher’s problem.

Focus Group Interviews

Focus group interviews, an unstructured free-flowing interview with a small group of people, may also be conducted to understand and define a research problem .

Experience Survey

Experience survey is another strategy to deal with the problem of identifying and defining the research problem.

It is an exploratory research endeavor in which individuals knowledgeable and experienced in a particular research problem are intimately consulted to understand the problem.

These persons are sometimes known as key informants, and an interview with them is popularly known as the Key Informant Interview (KII).

Reviewing of Literature

A review of relevant literature is an integral part of the research process. It enables the researcher to formulate his problem in terms of the specific aspects of the general area of his interest that has not been researched so far.

Such a review provides exposure to a larger body of knowledge and equips him with enhanced knowledge to efficiently follow the research process.

Through a proper review of the literature, the researcher may develop the coherence between the results of his study and those of the others.

A review of previous documents on similar or related phenomena is essential even for beginning researchers.

Ignoring the existing literature may lead to wasted effort on the part of the researchers.

Why spend time merely repeating what other investigators have already done?

Suppose the researcher is aware of earlier studies of his topic or related topics . In that case, he will be in a much better position to assess his work’s significance and convince others that it is important.

A confident and expert researcher is more crucial in questioning the others’ methodology, the choice of the data, and the quality of the inferences drawn from the study results.

In sum, we enumerate the following arguments in favor of reviewing the literature:

• It avoids duplication of the work that has been done in the recent past.
• It helps the researcher discover what others have learned and reported on the problem.
• It enables the researcher to become familiar with the methodology followed by others.
• It allows the researcher to understand what concepts and theories are relevant to his area of investigation.
• It helps the researcher to understand if there are any significant controversies, contradictions, and inconsistencies in the findings.
• It allows the researcher to understand if there are any unanswered research questions.
• It might help the researcher to develop an analytical framework.
• It will help the researcher consider including variables in his research that he might not have thought about.

Why is reviewing literature crucial in the research process?

Reviewing literature helps avoid duplicating previous work, discovers what others have learned about the problem, familiarizes the researcher with relevant concepts and theories, and ensures a comprehensive approach to the research question.

What is the significance of reviewing literature in the research process?

Reviewing relevant literature helps formulate the problem, understand the background of the study, choose a proper research methodology, and develop coherence between the study’s results and previous findings.

Setting Research Questions, Objectives, and Hypotheses

After discovering and defining the research problem, researchers should make a formal statement of the problem leading to research objectives .

An objective will precisely say what should be researched, delineate the type of information that should be collected, and provide a framework for the scope of the study. A well-formulated, testable research hypothesis is the best expression of a research objective.

A hypothesis is an unproven statement or proposition that can be refuted or supported by empirical data. Hypothetical statements assert a possible answer to a research question.

Step #4: Choosing the Study Design

The research design is the blueprint or framework for fulfilling objectives and answering research questions .

It is a master plan specifying the methods and procedures for collecting, processing, and analyzing the collected data. There are four basic research designs that a researcher can use to conduct their study;

• experiment,
• secondary data study, and
• observational study.

The type of research design to be chosen from among the above four methods depends primarily on four factors:

• The type of problem
• The objectives of the study,
• The existing state of knowledge about the problem that is being studied, and
• The resources are available for the study.

Deciding on the Sample Design

Sampling is an important and separate step in the research process. The basic idea of sampling is that it involves any procedure that uses a relatively small number of items or portions (called a sample) of a universe (called population) to conclude the whole population.

It contrasts with the process of complete enumeration, in which every member of the population is included.

Such a complete enumeration is referred to as a census.

A population is the total collection of elements we wish to make some inference or generalization.

A sample is a part of the population, carefully selected to represent that population. If certain statistical procedures are followed in selecting the sample, it should have the same characteristics as the population. These procedures are embedded in the sample design.

Sample design refers to the methods followed in selecting a sample from the population and the estimating technique vis-a-vis the formula for computing the sample statistics.

The fundamental question is, then, how to select a sample.

To answer this question, we must have acquaintance with the sampling methods.

These methods are basically of two types;

• probability sampling , and
• non-probability sampling .

Probability sampling ensures every unit has a known nonzero probability of selection within the target population.

If there is no feasible alternative, a non-probability sampling method may be employed.

The basis of such selection is entirely dependent on the researcher’s discretion. This approach is called judgment sampling, convenience sampling, accidental sampling, and purposive sampling.

The most widely used probability sampling methods are simple random sampling , stratified random sampling , cluster sampling , and systematic sampling . They have been classified by their representation basis and unit selection techniques.

Two other variations of the sampling methods that are in great use are multistage sampling and probability proportional to size (PPS) sampling .

Multistage sampling is most commonly used in drawing samples from very large and diverse populations.

The PPS sampling is a variation of multistage sampling in which the probability of selecting a cluster is proportional to its size, and an equal number of elements are sampled within each cluster.

Collecting Data From The Research Sample

Data gathering may range from simple observation to a large-scale survey in any defined population. There are many ways to collect data. The approach selected depends on the objectives of the study, the research design, and the availability of time, money, and personnel.

With the variation in the type of data (qualitative or quantitative) to be collected, the method of data collection also varies .

The most common means for collecting quantitative data is the structured interview .

Studies that obtain data by interviewing respondents are called surveys. Data can also be collected by using self-administered questionnaires . Telephone interviewing is another way in which data may be collected .

Other means of data collection include secondary sources, such as the census, vital registration records, official documents, previous surveys, etc.

Qualitative data are collected mainly through in-depth interviews, focus group discussions , Key Informant Interview ( KII), and observational studies.

Process and Analyze the Collected Research Data

Data processing generally begins with the editing and coding of data . Data are edited to ensure consistency across respondents and to locate omissions if any.

In survey data, editing reduces errors in the recording, improves legibility, and clarifies unclear and inappropriate responses. In addition to editing, the data also need coding.

Because it is impractical to place raw data into a report, alphanumeric codes are used to reduce the responses to a more manageable form for storage and future processing.

This coding process facilitates the processing of the data. The personal computer offers an excellent opportunity for data editing and coding processes.

Data analysis usually involves reducing accumulated data to a manageable size, developing summaries, searching for patterns, and applying statistical techniques for understanding and interpreting the findings in light of the research questions.

Further, based on his analysis, the researcher determines if his findings are consistent with the formulated hypotheses and theories.

The techniques used in analyzing data may range from simple graphical techniques to very complex multivariate analyses depending on the study’s objectives, the research design employed, and the nature of the data collected.

As in the case of data collection methods, an analytical technique appropriate in one situation may not be suitable for another.

Writing Research Report – Developing Research Proposal, Writing Report, Disseminating and Utilizing Results

The entire task of a research study is accumulated in a document called a proposal or research proposal.

A research proposal is a work plan, prospectus, outline, offer, and a statement of intent or commitment from an individual researcher or an organization to produce a product or render a service to a potential client or sponsor .

The proposal will be prepared to keep the sequence presented in the research process. The proposal tells us what, how, where, and to whom it will be done.

It must also show the benefit of doing it. It always includes an explanation of the purpose of the study (the research objectives) or a definition of the problem.

It systematically outlines the particular research methodology and details the procedures utilized at each stage of the research process.

The end goal of a scientific study is to interpret the results and draw conclusions.

To this end, it is necessary to prepare a report and transmit the findings and recommendations to administrators, policymakers, and program managers to make a decision.

There are various research reports: term papers, dissertations, journal articles , papers for presentation at professional conferences and seminars, books, thesis, and so on. The results of a research investigation prepared in any form are of little utility if they are not communicated to others.

The primary purpose of a dissemination strategy is to identify the most effective media channels to reach different audience groups with study findings most relevant to their needs.

The dissemination may be made through a conference, a seminar, a report, or an oral or poster presentation.

The style and organization of the report will differ according to the target audience, the occasion, and the purpose of the research. Reports should be developed from the client’s perspective.

A report is an excellent means that helps to establish the researcher’s credibility. At a bare minimum, a research report should contain sections on:

• An executive summary;
• Background of the problem;
• Literature review;
• Methodology;
• Discussion;
• Conclusions and
• Recommendations.

The study results can also be disseminated through peer-reviewed journals published by academic institutions and reputed publishers both at home and abroad. The report should be properly evaluated .

These journals have their format and editorial policies. The contributors can submit their manuscripts adhering to the policies and format for possible publication of their papers.

There are now ample opportunities for researchers to publish their work online.

The researchers have conducted many interesting studies without affecting actual settings. Ideally, the concluding step of a scientific study is to plan for its utilization in the real world.

Although researchers are often not in a position to implement a plan for utilizing research findings, they can contribute by including in their research reports a few recommendations regarding how the study results could be utilized for policy formulation and program intervention.

Why is the dissemination of research findings important?

Dissemination of research findings is crucial because the results of a research investigation have little utility if not communicated to others. Dissemination ensures that the findings reach relevant stakeholders, policymakers, and program managers to inform decisions.

How should a research report be structured?

A research report should contain sections on an executive summary, background of the problem, literature review, methodology, findings, discussion, conclusions, and recommendations.

Why is it essential to consider the target audience when preparing a research report?

The style and organization of a research report should differ based on the target audience, occasion, and research purpose. Tailoring the report to the audience ensures that the findings are communicated effectively and are relevant to their needs.

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Marketing91

The 11 Important Steps in Research Design

June 12, 2023 | By Hitesh Bhasin | Filed Under: Marketing

Research design is critical to the Market Research Process . In a previous article, we have discussed in detail about Research design and the 12 types of Research Design .

In this article, We discuss the 11 steps to make up your Market research process. These steps can also be called as the steps of Research Design. Without further ado, let us check the steps required to conduct a market research study or to design our research.

Table of Contents

11 Steps of Research Design

1) formulation of the research problem.

Necessity is the mother of all inventions, and accordingly, it is a problem which necessitates research. A general area of interest is selected by the researcher initially to indicate the problem.

The problem is evaluated by the program, which helps to shed new light on the facts and collecting of useful fact to plan social or even policy-making purposes. Social scientists involved their values as well as the social conditions which are prevalent in order to select the problem for the research.

It is suggested that this influence should be avoided as much as possible. The use of variation and topics of research because scientists also differ in their values and their preferences. This is the reason why the topics of the research very wide with different scientists.

The need for a specific problem is always fat by the scientist’s sensor general topic fails twin sure that the ability to examine the data resides and the methods that are needed to adapt and organize them along with the formulation of the specific problem is always there.

This helps the researcher to sharpen his goal and to make it clear cut. The purpose of this is not only to guide the researcher but also to sharpen for narrow is questions like a pinpoint.

For example, if a general topic of any industry or domain is compared with a pyramid base and the specific topic is exactly opposite to it which resembles the apex of the pyramid.

It is not an easy task to formulate a problem which has arisen out of a practical or theoretical situation. Even if it appears easy to do so, it is not the case, and in fact, it is more of a herculean task. Significant people by Charles Darwin have said that ‘looking back it seems that seeing and understanding the problem is more difficult than solving them. ‘

since the problem itself poses a lot of difficulties and the same is experienced by the researchers, one should ensure that the formulation of the problem is done in such a way that it should be explained and put in an efficient way so that it justifies the saying that a problem well put is half solved.

There are three general questions which are considered as three important components that are involved in the process of problem formulation

• What does one want to know?
• What could be the probable answers to the originating questions?

There should be a rational base for the problems of the solution that is provided itself has a more rational base. The answers that are provided justify the concerns of the problem, which are theoretical or practical in nature.

The answers that are provided by the theoretical rationale in terms of enlargement or propagation of the existing ideas or theory . It helps to shed light on the consistency is which are observed in the existing theories and ensures them to examine those inconsistencies and determine their nature in terms of reality.

On the other hand, to bring desired values, the practical rationale should be able to justify the answers to the questions of the researcher. It is very crucial that the formation of the problem is done in an efficient way so that the solution is found in the same manner.

If there is a flaw in the problem, the solution itself will be full of flaws, and it won’t be good research.

2) Literature review

The research is based on pastor knowledge, and the researcher should always make sure to take advantage of the north, which is already available or preserved earlier.

This not only helps the investigator to avoid replicating the hypothesis of earlier research but also enables him and provides evidence that he knows the current research which has already been done and can work on the untested and unknown field.

The literature review also means that the summary of writings how the earlier researchers and recognize the authority is in the particular area have been analyzed and summarised.

Books and libraries are the best places to find all human knowledge which is accumulated in the past. The published literature provides dear approaches which have been selected and helps the current researcher to study those approaches and take the baton from thereon.

The primary function of the literature review is that the research is given direction and information update related to the problem and the multiple ways that have already been tried to solve the problem and probably failed. This also helps the researcher to find his own hypothesis and save time doing what the earlier researchers had done.

The primary objectives of literature reviews are

• To avoid the studies which are overlapping with each other
• How to provide explanations ideas of the theory is which will be helpful in writing and defining the nature of the research problem.
• To formulate hypothesis by being a fertile source for it.
• To find out and suggest different methods in order to collect data and to explore different sources of data and techniques which are appropriate for the problem.
• To study and analyze what the earlier researchers had done.
• To ensure that the researcher is kept known of the current developments with regards to his area of activity.

Following are a few of the principles that the researcher has to follow for the review of the literature:

• The researcher should ensure that he has obtained an overall view from a source which is general and which has materials which are likely to provide the nature along with the meaning of concept and variables.
• After that, the researcher should also ensure that the reviewing that is conducted in the concerned field should review empirical researches.
• A systematic manner is approached in order to review the library materials, and also it should be thorough in nature.
• If at all he has mentioned any references, the researcher should ensure that it is mentioned in the bibliographic data.

3) Formation of Hypothesis in Research Design

The next step in the research is to formulate a hypothesis which will be tentative with nature and which would explain the nature of the problem. This explanation is tentative in nature refers to the statement of relation and relates two or more variables.

In order to formulate a hypothesis, the researcher collects information from multiple sources such as previous reports, existing theories, and literature which have worked with you on a similar problem.

Some of the studies test the hypothesis while others are formulating the hypothesis. The hypothesis for marketing studies are the ones which are exploratory studies since these end up with the formulation of hypothesis.

On the other hand, researches, which are hypothesis testing, start with a clearly defined and formulated hypothesis. The researcher has to state the definitions of concept so that they translate to the official and formal definitions and convey the nature of the problem into observables references.

In order to develop a hypothesis, it is essential to explain the nature of the relationship between two or more variables.

If one of the variable influences the other in the first variable is called as independent while the second is termed as the dependent variable. A correlation exists when one variable changes and influences another variable. It is very crucial that the researcher separates the dependent and independent variables from each other.

4) Formulating a Research Design

Once the problem has been defined, and the literature review is completed after formatting of the hypothesis, the researcher then starts to work on the design of the research. The design of research must be a blueprint for the general collection.

It acts as a standard guidepost by providing answers to multiple questions. It also helps in carrying out research accurately, objective, the economically and validity and is therefore fail-proof.

The research designs vary according to their need and the purpose of the research as well as the point of view working procedure.

There are basically four categories of research design:

• Exploration
• Description
• Diagnosis and
• Experimentation

There are four parts of Research design according to the realizable working procedure.

• Sampling design which is used to physically for sampling and selection of the units for the research purposes.
• The observational design describes the method in which observations are to be collected.
• The statistical design which describes the techniques statistically which are used in the analysis of data along with its interpretation.
• The operational design which deals with the techniques by which entire research can be carried out. The handset has all the three designs which are mentioned above, such as observational statistical and sampling designs.

5) Defining the nature of the study

The nature of the study as the cause of the individual items which are under consideration in the field of study. Nature refers to the sum of units for individuals from which a sample is another east in order to find out results, and that analysis is applied to it.

The researcher also separates the target and server population in order to define the scope of the study. Target units are the one which is applied to the results of the research. On the other hand, survey units are the ones which are included in sampling and all the ones from which the sample is taken.

In most of the purposes, this distinction is not significant, and the entire population must be defined in clear terms.

6) Sample design

It is not possible under different circumstances to enumerate all of the atoms included in the universe because it requires the result of resources like Mani time and energy which is why the researcher decides to select a representative from the population known as a sample and the process is known as simple design.

It is useful how to predetermine a sample before going for the entire research.

There are different types of samples which are as follows:

• Probability samples
• Purposive or judgment or subjective sampling
• Mixed sampling.

The probability samples are the ones which are drawn from the universe which is according to the laws of chance and are based on on the proper scientific technique in which every sample in the unit has a predefined probability of being selected.

In case of Subjective or Purposive or judgment sampling, the units are purposefully our desperately drawn depending on the investigation objectives, and these include only the important ones which represent it the population completely.

These units are selected in mixed sampling according to fixed sampling rule for according to fixed sampling rule, which does not depend on chance.

Simple random sampling, stratified random sampling, complex random sampling, haphazard or convenience sampling , cluster and area sampling, judgment sampling, and quota sampling a few of the important types of sampling.

7) Administration of the tools of Data collection in Research Design

Appropriate data is required for any research work. Along with appropriateness, the data should also be adequate. Considering the financial and time and other resources which are available, the data may differ considerably.

Things like nature of the investigation, scope of the inquiry, objective and financial resources along with the desired degree of accuracy and the time which is available after of the things that the researcher has to take into consideration.

Apart from this, the ability and experience of the researcher also have very much importance in the data collection that is required.

Journals newspapers reports published earlier and books are of the sources from which secondary data can be collected, and the primary data can be collected by survey or experimentation. In order to conduct a survey, the data is gathered by personal interviews observations making of the questionnaire on telephonic interviews and nowadays via the Internet.

8) Data analysis

After the collection of data is completed the investigator then has to analyze the collected data which involves operations like segregating the data into different categories and application of coding for deposition to the raw data that is collected.

Statistical conclusions were drawn after that. These operations are supervised very closely, and at the beginning, it is the researchers who have to classify some of the raw data into different categories based on similar purposes.

The coding is done in order to change the categories of data and make them tabulated and countable. After that, during the postcoding stage, the data which is collected is put into tabulated form, and this is done in the technical your manually with the devices such as computers.

If the data is very is ours than computers are used wisely in case of small data, manual mode is used. Standard statistical formulas and methods are applied in order to test the validity of the data by the researchers so that he arrives at some definite conclusion.

9) Hypothesis testing in Research Design

The studies do not always confirm the original hypothesis, and in many cases, the hypothesis may be refused, and the researcher in such cases mastery for a visit there results and conclusions. It is not possible in case of behavioral sciences to test multiple hypotheses.

The scientist can test the research hypothesis by making a sample for direct observation. On this observable basis, they determine if the hypothesis is consistent or not with the logical consequences, and that is why the indirect test of this hypothesis can be made.

The research hypothesis that is derived from the theory helps to provide an inconclusive test. A much stronger logical test is formed if the rejection of the null hypothesis. It is defined as a hypothesis of no difference, which is why the rejection of it results in the acceptance of the alternative hypothesis.

Various tests have been developed by statisticians like t-test, F-test, chi-square test in order to test the hypothesis. If there is no hypothesis, to begin with, then the generalizations are the only way to serve as the basis of hypothesis.

10) Interpretation and generalization

After the test of hypothesis is completed in Research Design, and the validity is confirmed, the researcher has reached a stage of generalization, which is generally seen as a real value to the research.

Only in case of hypothesis testing studies is this possible but thing hypothesis formulating studies where there is an absence of hypothesis the researcher has to you interpret his findings.

In other words, the theoretical framework may be used by the researcher in order to explain the findings of his research, which may raise new questions.

11) Preparing the report of the Research

The final product of all the research activity is the report which gives a written account of the entire journey along with the path to find new knowledge. This type requires a technical task, which is why writing research is not only but also tests patients and efforts on the part of the researcher.

The overall approach to the problem along with the analysis of the data and superior grasp over language all of it has to be used in case of preparing the report. The report has a foreword or the title page along with Preface, and list of tables and contents.

It may also contain a list of charts or illustrations. in the second section of the report; there will be an introduction to the research report along with the purpose of the study and statement of the problem.

Then the researcher will write about the hypothesis and the definitions along with the methodology by which the research is conducted. A section for secondary data analysis and primary data analysis is kept.

The final part of the research has conclusions and results. The end of the research will be filled with the bibliography and appendix and glossary.

Learn More – Research design and the 12 Types of Research Design

Liked this post? Check out the complete series on Market research

Related posts:

• What is Research Design? Type of Research Designs
• What is Experimental Research? Definition, Design Types & Examples
• What is a Design Brief and How to Write it in 9 Easy Steps?
• Sampling and Sample Design – Types and Steps Involved
• What are Research Skills? And Why are they Important?
• The 7 Important Steps Retail Planning Process you Should know
• Brand Strategy – Steps, Components and Why it is Important for Business
• 7 Key Differences between Research Method and Research Methodology
• Qualitative Research: Meaning, and Features of Qualitative Research
• Research Ethics – Importance and Principles of Ethics in Research

About Hitesh Bhasin

Hitesh Bhasin is the CEO of Marketing91 and has over a decade of experience in the marketing field. He is an accomplished author of thousands of insightful articles, including in-depth analyses of brands and companies. Holding an MBA in Marketing, Hitesh manages several offline ventures, where he applies all the concepts of Marketing that he writes about.

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A Beginner's Guide to Starting the Research Process

When you have to write a thesis or dissertation , it can be hard to know where to begin, but there are some clear steps you can follow.

The research process often begins with a very broad idea for a topic you’d like to know more about. You do some preliminary research to identify a  problem . After refining your research questions , you can lay out the foundations of your research design , leading to a proposal that outlines your ideas and plans.

This article takes you through the first steps of the research process, helping you narrow down your ideas and build up a strong foundation for your research project.

Table of contents

Step 1: choose your topic, step 2: identify a problem, step 3: formulate research questions, step 4: create a research design, step 5: write a research proposal.

First you have to come up with some ideas. Your thesis or dissertation topic can start out very broad. Think about the general area or field you’re interested in—maybe you already have specific research interests based on classes you’ve taken, or maybe you had to consider your topic when applying to graduate school and writing a statement of purpose .

Even if you already have a good sense of your topic, you’ll need to read widely to build background knowledge and begin narrowing down your ideas. Conduct an initial literature review to begin gathering relevant sources. As you read, take notes and try to identify problems, questions, debates, contradictions and gaps. Your aim is to narrow down from a broad area of interest to a specific niche.

Make sure to consider the practicalities: the requirements of your programme, the amount of time you have to complete the research, and how difficult it will be to access sources and data on the topic. Before moving onto the next stage, it’s a good idea to discuss the topic with your thesis supervisor.

>>Read more about narrowing down a research topic

Prevent plagiarism, run a free check.

So you’ve settled on a topic and found a niche—but what exactly will your research investigate, and why does it matter? To give your project focus and purpose, you have to define a research problem .

The problem might be a practical issue—for example, a process or practice that isn’t working well, an area of concern in an organization’s performance, or a difficulty faced by a specific group of people in society.

Alternatively, you might choose to investigate a theoretical problem—for example, an underexplored phenomenon or relationship, a contradiction between different models or theories, or an unresolved debate among scholars.

To put the problem in context and set your objectives, you can write a problem statement . This describes who the problem affects, why research is needed, and how your research project will contribute to solving it.

>>Read more about defining a research problem

Next, based on the problem statement, you need to write one or more research questions . These target exactly what you want to find out. They might focus on describing, comparing, evaluating, or explaining the research problem.

A strong research question should be specific enough that you can answer it thoroughly using appropriate qualitative or quantitative research methods. It should also be complex enough to require in-depth investigation, analysis, and argument. Questions that can be answered with “yes/no” or with easily available facts are not complex enough for a thesis or dissertation.

In some types of research, at this stage you might also have to develop a conceptual framework and testable hypotheses .

>>See research question examples

The research design is a practical framework for answering your research questions. It involves making decisions about the type of data you need, the methods you’ll use to collect and analyze it, and the location and timescale of your research.

There are often many possible paths you can take to answering your questions. The decisions you make will partly be based on your priorities. For example, do you want to determine causes and effects, draw generalizable conclusions, or understand the details of a specific context?

You need to decide whether you will use primary or secondary data and qualitative or quantitative methods . You also need to determine the specific tools, procedures, and materials you’ll use to collect and analyze your data, as well as your criteria for selecting participants or sources.

>>Read more about creating a research design

Finally, after completing these steps, you are ready to complete a research proposal . The proposal outlines the context, relevance, purpose, and plan of your research.

As well as outlining the background, problem statement, and research questions, the proposal should also include a literature review that shows how your project will fit into existing work on the topic. The research design section describes your approach and explains exactly what you will do.

You might have to get the proposal approved by your supervisor before you get started, and it will guide the process of writing your thesis or dissertation.

>>Read more about writing a research proposal

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Research Design – Types, Methods and Examples

Table of Contents

Research Design

Definition:

Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.

Types of Research Design

Types of Research Design are as follows:

Descriptive Research Design

This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.

Correlational Research Design

Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.

Quasi-experimental Research Design

Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.

Case Study Research Design

Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.

Longitudinal Research Design

Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.

Structure of Research Design

The format of a research design typically includes the following sections:

• Introduction : This section provides an overview of the research problem, the research questions, and the importance of the study. It also includes a brief literature review that summarizes previous research on the topic and identifies gaps in the existing knowledge.
• Research Questions or Hypotheses: This section identifies the specific research questions or hypotheses that the study will address. These questions should be clear, specific, and testable.
• Research Methods : This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques.
• Data Collection: This section describes how the data will be collected, including the sample size, data collection procedures, and any ethical considerations.
• Data Analysis: This section describes how the data will be analyzed, including the statistical techniques that will be used to test the research questions or hypotheses.
• Results : This section presents the findings of the study, including descriptive statistics and statistical tests.
• Discussion and Conclusion : This section summarizes the key findings of the study, interprets the results, and discusses the implications of the findings. It also includes recommendations for future research.
• References : This section lists the sources cited in the research design.

Example of Research Design

An Example of Research Design could be:

Research question: Does the use of social media affect the academic performance of high school students?

Research design:

• Research approach : The research approach will be quantitative as it involves collecting numerical data to test the hypothesis.
• Research design : The research design will be a quasi-experimental design, with a pretest-posttest control group design.
• Sample : The sample will be 200 high school students from two schools, with 100 students in the experimental group and 100 students in the control group.
• Data collection : The data will be collected through surveys administered to the students at the beginning and end of the academic year. The surveys will include questions about their social media usage and academic performance.
• Data analysis : The data collected will be analyzed using statistical software. The mean scores of the experimental and control groups will be compared to determine whether there is a significant difference in academic performance between the two groups.
• Limitations : The limitations of the study will be acknowledged, including the fact that social media usage can vary greatly among individuals, and the study only focuses on two schools, which may not be representative of the entire population.
• Ethical considerations: Ethical considerations will be taken into account, such as obtaining informed consent from the participants and ensuring their anonymity and confidentiality.

How to Write Research Design

Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:

• Define the research question or hypothesis : Before beginning your research design, you should clearly define your research question or hypothesis. This will guide your research design and help you select appropriate methods.
• Select a research design: There are many different research designs to choose from, including experimental, survey, case study, and qualitative designs. Choose a design that best fits your research question and objectives.
• Develop a sampling plan : If your research involves collecting data from a sample, you will need to develop a sampling plan. This should outline how you will select participants and how many participants you will include.
• Define variables: Clearly define the variables you will be measuring or manipulating in your study. This will help ensure that your results are meaningful and relevant to your research question.
• Choose data collection methods : Decide on the data collection methods you will use to gather information. This may include surveys, interviews, observations, experiments, or secondary data sources.
• Create a data analysis plan: Develop a plan for analyzing your data, including the statistical or qualitative techniques you will use.
• Consider ethical concerns : Finally, be sure to consider any ethical concerns related to your research, such as participant confidentiality or potential harm.

When to Write Research Design

Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.

Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.

Purpose of Research Design

The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.

Some of the key purposes of research design include:

• Providing a clear and concise plan of action for the research study.
• Ensuring that the research is conducted ethically and with rigor.
• Maximizing the accuracy and reliability of the research findings.
• Minimizing the possibility of errors, biases, or confounding variables.
• Ensuring that the research is feasible, practical, and cost-effective.
• Determining the appropriate research methodology to answer the research question(s).
• Identifying the sample size, sampling method, and data collection techniques.
• Determining the data analysis method and statistical tests to be used.
• Facilitating the replication of the study by other researchers.
• Enhancing the validity and generalizability of the research findings.

Applications of Research Design

There are numerous applications of research design in various fields, some of which are:

• Social sciences: In fields such as psychology, sociology, and anthropology, research design is used to investigate human behavior and social phenomena. Researchers use various research designs, such as experimental, quasi-experimental, and correlational designs, to study different aspects of social behavior.
• Education : Research design is essential in the field of education to investigate the effectiveness of different teaching methods and learning strategies. Researchers use various designs such as experimental, quasi-experimental, and case study designs to understand how students learn and how to improve teaching practices.
• Health sciences : In the health sciences, research design is used to investigate the causes, prevention, and treatment of diseases. Researchers use various designs, such as randomized controlled trials, cohort studies, and case-control studies, to study different aspects of health and healthcare.
• Business : Research design is used in the field of business to investigate consumer behavior, marketing strategies, and the impact of different business practices. Researchers use various designs, such as survey research, experimental research, and case studies, to study different aspects of the business world.
• Engineering : In the field of engineering, research design is used to investigate the development and implementation of new technologies. Researchers use various designs, such as experimental research and case studies, to study the effectiveness of new technologies and to identify areas for improvement.

Advantages of Research Design

Here are some advantages of research design:

• Systematic and organized approach : A well-designed research plan ensures that the research is conducted in a systematic and organized manner, which makes it easier to manage and analyze the data.
• Clear objectives: The research design helps to clarify the objectives of the study, which makes it easier to identify the variables that need to be measured, and the methods that need to be used to collect and analyze data.
• Minimizes bias: A well-designed research plan minimizes the chances of bias, by ensuring that the data is collected and analyzed objectively, and that the results are not influenced by the researcher’s personal biases or preferences.
• Efficient use of resources: A well-designed research plan helps to ensure that the resources (time, money, and personnel) are used efficiently and effectively, by focusing on the most important variables and methods.
• Replicability: A well-designed research plan makes it easier for other researchers to replicate the study, which enhances the credibility and reliability of the findings.
• Validity: A well-designed research plan helps to ensure that the findings are valid, by ensuring that the methods used to collect and analyze data are appropriate for the research question.
• Generalizability : A well-designed research plan helps to ensure that the findings can be generalized to other populations, settings, or situations, which increases the external validity of the study.

Research Design Vs Research Methodology

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Program Management

The research process entails systematically acquiring knowledge, resolving issues, or addressing particular inquiries. It is a series of systematic procedures that a researcher must undertake to generate valuable knowledge relevant to the project and focused on the relevant subject matter. The process is iterative, with each subsequent step influenced by the preceding one. The successful execution of this task necessitates meticulous strategic planning, meticulous attention to intricate particulars, and an unwavering dedication to acquiring knowledge and comprehension.

5 Steps in the Research Process Overview

The following steps outline a simple and effective process for conducting both basic and practical research. The five (5) steps in the research process are: [1]

• Step 1: Locating and Defining Issues or Problems – Understanding the questions that need to be answered or studied
• Step 2: Designing the Research Project – Creating a research plan
• Step 3: Collecting Data – Obtaining the information needed to solve the identified issue or problem
• Step 4: Interpreting Research Data – examining the research data and coming up with a conclusion that solves the problem
• Step 5: Report Research Findings – Presenting the information

Step 1 – Locating and Defining Issues or Problems

This step focuses on uncovering the nature and boundaries of a situation or question that needs to be answered or studied. In defining the issues or problems, the researcher should take into account the purpose of the study, the relevant background information, what information is needed, and how it will be used in decision-making. A well-defined problem will help the researcher through all steps of the research process, from setting goals to choosing a method. There are a number of ways to learn more about a subject and get a better grasp on it in Step 2.

Step 2 – Designing the Research Project

This step is focused on creating a research plan or overall approach to how you are going to solve the issue or problem identified.  A research plan or approach is a framework or blueprint for conducting a research project. It details the procedures necessary for obtaining the required information, and its purpose is to design a study that will test the hypotheses of interest, determine possible answers to the research questions, and provide the information needed for decision-making.

The research design involves the following steps:

• Step 1: Conduct secondary data analysis
• Step 2: Do qualitative research
• Step 3: Determine methods of collecting quantitative data (survey, observation, and experimentation)
• Step 4: Determine the definition of the information needed
• Step 5: Determine measurement and scaling procedures
• Step 6: Design a questionnaire
• Step 7: Sampling process and sample size
• Step 8: Plan of data analysis

Step 3 – Collecting Data

This step revolved around obtaining the information needed to solve the identified issue or problem.  Data collection can involve experiments, observations, personal interviewing (in-home, mall intercept, or computer-assisted personal interviewing), from an office by telephone (telephone or computer-assisted telephone interviewing), or through the mail (traditional mail and mail panel surveys with recruited households). The two groups of researchers must provide data.

Data collection techniques can include:

• Interviews: Asking people questions about their known information
• Observations: collecting data without asking questions.
• Questionnaires: Ask questions among a group of people
• Focus Groups: Interviewing and observing a group of people
• Documents and Records: Old-fashioned research
• Literature review: Old-fashioned research
• Library Sources: Old reports and articles/books

Step 4 – Interpreting Research Data

This step is focused on interpreting and examining the research data and coming up with a conclusion that solves the problem. Make sure the conclusion is easy to understand and well thought out based on the data collected.

Analysis Steps

• Step A: Review your research plan
• Step B: Organize your findings and the information you have collected from Step 3.
• Step C: Create a rough draft of your findings, recommendations, and conclusion. The rough draft will help you get your thoughts organized.
• Step D: Polish the rough draft into your final research finding. You will most likely revise the draft many times before the final product is ready for Step 5.

Step 5 – Report Research Findings

The final step is to report the research findings to those who need the data to make decisions. The findings should be presented in an understandable format so that they can be readily used in the decision-making process. In addition, an oral presentation should be made to management using tables, figures, and graphs to enhance clarity and impact.

Research Reporting Formats:

• Formal Paper
• Published Article
• PowerPoint Presentation
• Audio or Video
• Spreadsheet

Typical Formal Research Report Format

A formal research report typically consists of several sections organized in a specific order to present the research findings clearly and structured. Here is a notional format of a research report, including the typical sections:

• Title Page: – Title of the Research Report – Name(s) of the Author(s) – Affiliation(s) of the Author(s) – Date of Submission
• Abstract: – A brief summary of the research objectives, methods, key findings, and conclusions. – Usually limited to a specific word count or length.
• Table of Contents: – A list of the main sections, subsections, and page numbers in the report. – Helps readers navigate through the report easily.
• Introduction: – Provides an overview of the research topic, including background information, context, and significance. – States the research problem, objectives, and research questions. – Outlines the scope and limitations of the study.
• Literature Review: – Reviews relevant literature and previous studies related to the research topic. – Summarizes existing knowledge, theories, and methodologies. – Identifies gaps, controversies, or unresolved issues that the current research aims to address.
• Methodology: – Describes the research design, methods, and procedures used to collect and analyze data. – Includes information on the sample size, data sources, data collection tools, and data analysis techniques. – Provides sufficient details for replication and validation of the study.
• Results: – Presents the findings of the research in a clear and organized manner. – Utilizes tables, figures, charts, or graphs to present data. – Includes descriptive statistics, qualitative analysis, or any other relevant analysis outputs.
• Discussion: – Interprets and discusses the research findings in relation to the research objectives. – Compares the results with existing literature and theories. – Analyzes patterns, trends, correlations, or discrepancies in the data. – Provides explanations, justifications, or hypotheses to support the findings.
• Conclusion: – Summarizes the main findings of the research. – Restates the research objectives and addresses the research questions. – Highlights the contributions and implications of the study. – Suggests recommendations for future research or practical applications.
• References: – Lists all the sources cited within the research report. – Follows a specific referencing style (e.g., APA, MLA, IEEE) as per the guidelines.
• Appendices: – Includes supplementary information or additional data that supports the research findings but is not necessary for the main body of the report. – May include survey questionnaires, interview transcripts, data tables, software code, or any other relevant materials.

It’s important to note that the structure and specific section names may vary depending on the discipline, research field, or journal requirements. Always refer to the specific guidelines your institution or publisher provided when preparing a research report.

AcqNotes Tutorial

Research Process Lessons Learned

Embarking on a research journey is a dynamic and enlightening experience that often leads to a multitude of lessons learned. The research process is not merely a sequence of steps but a complex exploration that demands critical thinking, adaptability, and perseverance. Through the course of conducting research, individuals encounter challenges, make discoveries, and refine their methodologies. These lessons extend beyond the acquisition of academic knowledge, encompassing skills such as effective communication, time management, and the ability to navigate through the vast sea of information.

• Define the research challenge and goals in detail: It’s crucial to grasp exactly what you’re attempting to learn and what you want to achieve. This will make it easier to direct your research efforts and guarantee that you are gathering pertinent facts.
• Select the best research design possible: Various research designs are applicable for various research topics. Choosing the proper design will help ensure your study’s validity and reliability.
• Collect reliable information: because it will directly impact how well your research turns out. Use the right data-gathering techniques, and make sure the data is gathered reliably and consistently.
• Analyze the data correctly: If you want to draw reliable findings from your research, your data analysis must be done correctly. It is crucial to employ the proper statistical methods and interpret the findings cautiously.
• Effectively explain your findings: It’s critical to provide your research’s conclusions in a clear, succinct manner. Writing a research report, presenting your findings at a conference, or publishing your study in a journal are all examples of how to do this.

Qualitative Research in the Research Process

Information, industry experts, and secondary data may not be sufficient to define the research problem. Sometimes qualitative research must be undertaken to gain a qualitative understanding of the problem and its underlying factors. Qualitative research is unstructured, exploratory in nature, based on small samples, and may utilize popular qualitative techniques such as focus groups (group interviews), word association (asking respondents to indicate their first responses to stimulus words), and depth interviews (one-on-one interviews which probe the respondents’ thoughts in detail). Other exploratory research techniques, such as pilot surveys with small samples of respondents, may also be undertaken.

There are various steps in the research process, which makes it simple to accomplish the research successfully. The above-described steps in the research process are interdependent, hence the order must be followed. So, if we want to conduct research, we should adhere to the steps of the research process to obtain good and reliable results.

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• [1] Pride, Ferel (2010). Marketing. South-Western Cengage Learning

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Research Design and Process

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Research design aims to provide a rationale, framework and structure before engaging with data collection and data analysis (Vaus, Research design in social research, Sage, 2001). A reasonable research design defines the structure of the research process, arrangement of the different methods required to respond to the research questions and the different outputs at each of the stages established.

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Chen, H., Baptista Nunes, M. (2023). Research Design and Process. In: Professional Empowerment in the Software Industry through Experience-Driven Shared Tacit Knowledge. Springer, Singapore. https://doi.org/10.1007/978-981-99-1486-9_4

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Published: 17 April 2024 Contributors: Matthew Finio, Amanda Downie

Business process reengineering (BPR) is the radical redesign of business processes to achieve dramatic improvements in performance, efficiency, and effectiveness.

Business process engineering (BPR) is a strategic management approach that is focused on fundamentally rethinking and redesigning core business processes to achieve significant improvements in performance and efficiency. 

BPR focuses on optimizing end-to-end processes and eliminating redundancies. By critically examining and redesigning business processes, BPR improves efficiency, effectiveness, and performance. These improvements can impact various aspects of the business including cost, output, service, speed, and quality. BPR is not a one-time project, but a continuous journey of innovation and optimization. Organizations must continuously evaluate and refine their processes to adapt to evolving business environments and maintain a competitive edge.

BPR implementation spans organizations of all sizes and industries. Its purpose is to streamline workflows, eliminate unnecessary steps and improve resource utilization to optimize efficiency and effectiveness. BPR involves radical changes that challenge existing norms and methods within an organization. It should not be confused with  business process management (BPM)  or business process improvement (BPI), which initiate more incremental change.

To implement BPR, companies first analyze processes to identify gaps and opportunities for improvement. Techniques such as  artificial intelligence (AI) -powered  process mining  analyze information systems for insights. This assessment guides decision-making about how work should be performed, including consideration of using  business process outsourcing (BPO)  and redefining third-party roles. BPR aims to fundamentally reshape how work is run. Using IT for  automation  and integration to optimize workflows, eliminate tasks that don’t add value and restructure or replace existing processes.

Successful implementation of BPR requires strong leadership, effective change management and a commitment to continuous improvement. Leaders must champion the BPR initiative and provide the necessary resources, support, and direction to enable meaningful change. Also, organizations must invest in change management strategies to mitigate resistance and ensure that employees are engaged and empowered throughout the process.

Read this report that investigates the potential of generative AI and automation and explores the practices of generative AI leaders.

What is business process automation (BPA)?

Business process reengineering (BPR) emerged in the early 1990s as a management approach aimed at radically redesigning business operations to achieve business transformation. 

BPR methodology gained prominence with the publication of the book  Reengineering the Corporation  by Michael Hammer and James Champy in 1993. Hammer, a management theorist and professor, is often credited as one of the founding figures of BPR.  Process Innovation , a book written by Thomas Davenport published in the same year, also contributed to the BPR discourse. Davenport emphasized the importance of innovation in the process model and the systematic approach to identifying opportunities for improvement within business processes.

One of the early adopters of BPR was Ford Motor Company, which implemented reengineering initiatives in the 1990s to streamline its manufacturing processes and improve competitiveness. By reorganizing workflows, reducing layers of management, and using technology, Ford achieved significant cost savings and operational efficiencies.

As BPR gained attention in the business world in the 1990s, it also faced criticism. Its emphasis on lean workforces can overlook the human factors that are involved in organizational change. Its association with the downsizing and outsourcing trends that were unpopular at the time brought negative attention to the template’s methods. Despite the criticisms, BPR has continued to evolve, incorporating new methods and new technologies that are associated with  digital transformation  to further overhaul and enhance business operations. Today, BPR remains a relevant and influential approach to driving organizational innovation and performance. 

Implementing BPR is a strategic decision for organizations seeking to drive transformative change and improve their operational performance. Some of the reasons an organization might implement BPR include:

• Dissatisfied staff  with high turnover 
• High operational costs  due to wasted time and resources
• Inadequate technology  that renders current processes inefficient or obsolete
• Inefficient processes  with redundant steps and delays
• Organizational growth  and existing processes that don’t align with the new scale
• Poor quality  products or services that consistently fail to meet industry standards or customer needs and expectations 
• Unhappy customers  who make complaints and request refunds

Here are the common steps of the reengineering process organizations use to achieve significant improvements in performance, efficiency, and competitiveness:

The first step in BPR is for senior management and process owners to clearly define the goals or wanted outcomes. Understand what needs to be achieved from the reengineering effort, such as faster delivery times or improved customer satisfaction.

Map the current state of business processes. Gather data and interview stakeholders about existing workflows to determine inefficiencies, bottlenecks, and areas for improvement. Analyze performance metrics to fully understand the state of the process.

Once the current state is understood, identify gaps between the current performance and wanted outcomes. Check whether all steps of the process are necessary. Set up key performance indicators (KPIs) to measure progress and identify improvement opportunities.

Based on the analysis, develop a future state for the business processes that aligns with the organization's strategic objectives. Design a cutting-edge  process map  that addresses the identified gaps and incorporates innovative solutions. If necessary, design a new process. Ensure that KPIs are designated for every step of the process to track performance.

Implement the changes outlined in the future state process map, ensuring that all stakeholders are informed and on board with the new processes. Be mindful of dependencies and resource requirements to successfully roll out the changes. Constantly monitor KPIs to assess the impact of the changes compared to the original workflows.

Continuously evaluate the performance of the redesigned processes and iterate as needed to further improve efficiency and effectiveness. Solicit feedback from stakeholders and adjust based on lessons learned. BPR is an iterative process—ongoing evaluation and optimization are essential for long-term success.

BPR offers organizations the opportunity to achieve dramatic improvements in performance, competitiveness, and profitability. Potential benefits include:

Competitive advantage:  By driving significant improvements in efficiency, quality management and customer satisfaction, BPR can provide organizations with a sustainable competitive advantage within their industry. As BPR drives significant improvements in efficiency, quality, and customer satisfaction, it provides organizations with a sustainable competitive advantage within their industry.

Enhanced quality:  The objective of BPR is to improve the quality of products and services by redesigning processes to eliminate errors and defects. By standardizing processes, enforcing best practices and integrating quality checks, organizations can deliver higher-quality outcomes to customers, leading to increased satisfaction and loyalty.

Faster time-to-market:  BPR helps organizations accelerate time-to-market for new products and services by streamlining product development, manufacturing, and delivery processes. By reducing cycle times and increasing agility, organizations can respond more quickly to market demand.

Improved customer satisfaction:  BPR focuses on delivering value to customers by redesigning processes with their needs in mind. By improving the delivery of services and increasing responsiveness and quality, organizations can enhance customer loyalty and retention. 

Increased efficiency:  BPR focuses on radical redesigning of processes, leading to streamlined workflows, reduced cycle times and better use of resources. By eliminating redundant tasks and non-value-adding activities, organizations can accomplish more with fewer resources, resulting in increased efficiency.

Reduced costs:  Reducing unnecessary steps, automating manual tasks and improving resource allocation can lower operational costs and lead to significant savings for organizations.

Strategic alignment:  BPR enables organizations to align their processes with strategic objectives and business goals. By rethinking how work is done and focusing on activities that add the most value, organizations can ensure that resources are allocated effectively to support their strategic priorities.

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Business process reengineering takes a critical look at core processes to spot and redesign areas that need improvement. By curating your business's data, you can create powerful, one-of-a-kind processes with intelligent workflows that drive profitability, weed out redundancies and prioritize cost savings.

MIT Technology Review

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Taking AI to the next level in manufacturing

Reducing data, talent, and organizational barriers to achieve scale.

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In partnership with Microsoft

Few technological advances have generated as much excitement as AI. In particular, generative AI seems to have taken business discourse to a fever pitch. Many manufacturing leaders express optimism: Research conducted by MIT Technology Review Insights found ambitions for AI development to be stronger in manufacturing than in most other sectors.

Manufacturers rightly view AI as integral to the creation of the hyper-automated intelligent factory. They see AI’s utility in enhancing product and process innovation, reducing cycle time, wringing ever more efficiency from operations and assets, improving maintenance, and strengthening security, while reducing carbon emissions. Some manufacturers that have invested to develop AI capabilities are still striving to achieve their objectives.

This study from MIT Technology Review Insights seeks to understand how manufacturers are generating benefits from AI use cases—particularly in engineering and design and in factory operations. The survey included 300 manufacturers that have begun working with AI. Most of these (64%) are currently researching or experimenting with AI. Some 35% have begun to put AI use cases into production. Many executives that responded to the survey indicate they intend to boost AI spending significantly during the next two years. Those who haven’t started AI in production are moving gradually. To facilitate use-case development and scaling, these manufacturers must address challenges with talents, skills, and data. Following are the study’s key findings:

• Talent, skills, and data are the main constraints on AI scaling. In both engineering and design and factory operations, manufacturers cite a deficit of talent and skills as their toughest challenge in scaling AI use cases. The closer use cases get to production, the harder this deficit bites. Many respondents say inadequate data quality and governance also hamper use-case development. Insufficient access to cloud-based compute power is another oft-cited constraint in engineering and design.
• The biggest players do the most spending, and have the highest expectations. In engineering and design, 58% of executives expect their organizations to increase AI spending by more than 10% during the next two years. And 43% say the same when it comes to factory operations. The largest manufacturers are far more likely to make big increases in investment than those in smaller—but still large—size categories.
• Desired AI gains are specific to manufacturing functions. The most common use cases deployed by manufacturers involve product design, conversational AI, and content creation. Knowledge management and quality control are those most frequently cited at pilot stage. In engineering and design, manufacturers chiefly seek AI gains in speed, efficiency, reduced failures, and security. In the factory, desired above all is better innovation, along with improved safety and a reduced carbon footprint.
• Scaling can stall without the right data foundations. Respondents are clear that AI use-case development is hampered by inadequate data quality (57%), weak data integration (54%), and weak governance (47%). Only about one in five manufacturers surveyed have production assets with data ready for use in existing AI models. That figure dwindles as manufacturers put use cases into production. The bigger the manufacturer, the greater the problem of unsuitable data is.
• Fragmentation must be addressed for AI to scale. Most manufacturers find some modernization of data architecture, infrastructure, and processes is needed to support AI, along with other technology and business priorities. A modernization strategy that improves interoperability of data systems between engineering and design and the factory, and between operational technology (OT) and information technology (IT), is a sound priority.

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