Advantages and limitations of quantitative data collection methods

By Ashni walia & Priya Chetty on May 12, 2020

Quantitative data collection refers to data collected from primary or secondary sources in numerical form (Monette, Sullivan, and DeJong, 2011). This type of data is used in mathematical calculations and statistical analysis, such that certain real-life decisions can be made based on these observations. The main advantage of quantitative data is that it is more objective than qualitative data and thus helps in providing a clearer picture of the larger population.

Importance of quantitative data

For instance, if a researcher wants to know the customer satisfaction rate of a brand, data can be collected from a group of people using a questionnaire. The questionnaire can consist of questions pertaining to their experience with the brand on a scale of 1 to 5. The data so collected will be numeric in nature. It can be used to draw conclusions about the participants’ satisfaction by using statistical techniques of analysis.

Quantitative data collection methods in a research that is deductive in nature (Byrne and Neville, 2010). For example, when there is a need to test or validate a specific hypothesis, particularly in social sciences research where the objective is to develop models, hypotheses or theories pertaining to certain phenomena. Furthermore, this can also be widely used in studies relating to economics, psychology, demography, sociology, marketing, health, and human development or studies relating to gender.

Collecting data by survey

The survey technique is the most popular quantitative data collection method (Muijs, 2011). Generally, for the purpose of the quantitative research close-ended questionnaires are used. These close-ended questionnaires include answers that the researcher thinks are most appropriate. A major characteristic of quantitative data is generalisability. This means it should be such that its findings can be generalized to the entire population without much variation. Surveys can be conducted by either using a paper or a web-based questionnaire (Gordon, 2003).

• Paper questionnaire- This is frequently used for quantitative data collection. Under this method, the pollster holds the printed-out questionnaire, reads the question to the respondents and then fills the answers in the questionnaire on their behalf, or asks them to fill the questionnaire manually. This method is most suitable when there are multiple-choice questions.
• Web-based questionnaire- Web-based questionnaires represent a cost-effective way of quantitative data collection. Under this approach, the researcher can directly email the questionnaire to a large number of respondents instead of interviewing each respondent individually. The major advantage of this method is that respondents tend to be more honest due to the fact that all the responses will be anonymous. It lets respondents reply without the fear of being judged.

Quantitative data collection by observation

The observation technique represents another method of collecting the quantitative data in primary form. Under this approach, the researcher can collect data by using the systematic observation approach (Michaels, 1983). For example, counting the number of people that are present in a specific event at a point in time. Another example of an observation method is observing the buying behaviour of multiple people towards a certain product. More often it requires a naturalistic approach so that the researcher has keen observation skills. The structured observation method is the most popular method of primary data collected through the observation method.

Under the structured observation method, the researcher must make observations on the basis of one or more specific behaviour in a more comprehensive and structured setting. The researcher must focus only on specific behaviours of interest. This allows them to quantify the behaviours they are observing.

Reviewing documents for data

It refers to the process that is used to collect data based on reviewing existing documents. It is considered an efficient way of data collection as the documents are manageable (Siddaway, Wood and Hedges, 2019). There are three primary document types that can be used for collecting the quantitative research data:

• Public records: In this type of document review, the researcher can review the ongoing records of an organization and analyze them for future research. Examples include annual reports and policy manuals.
• Personal documents: This is in contrast to public documents. Here the researcher deals with individual personal documents such as the accounts of individual actions, behaviours, and health data like height, weight, and distance travelled by an individual.
• Physical evidence: This includes physical evidence that deals with the previous achievements of an individual or organization. The information can be in terms of monetary or scalable growth.

The table below provides a comparative review of all the three methods of primary data collection in quantitative form.

Limitations of quantitative data

Each of the above-reviewed methods has limitations. In the case of surveys, the biggest drawback is the lack of flexibility, i.e. one questionnaire has to be followed for all respondents throughout the research. On the other hand, observation-based studies are heavily reliant on the researcher’s perspective of a situation, and there is no mechanism to check the data’s reliability. Lastly, document reviews are unidimensional, i.e. all assessments have to be drawn on the basis of limited information present in the documents. Therefore, a researcher must make a careful evaluation of the technique that is most appropriate for their research, based on the aim of the study and the resources available.

References

• Byrne, G. J. and Neville, C. C. (2010) Community Mental Health for Older People. Chatswood: Elsvier.
• Gordon, S. R. (2003) Computing Information Technology: The Human Side. Hershey: IRM Press.
• Michaels, J. (1983) ‘Systematic Observation as a Measurement Strategy’, Sociological Focus, 16(3), pp. 217–226.
• Monette, D. R., Sullivan, T. J. and DeJong, C. R. (2011) Applied Social Research: A Tool for the Human Services. Belmont: Cengage Learning.
• Muijs, D. (2011) Doing Quantitative Research in Education with SPSS. London: Sage.
• Siddaway, A. P., Wood, A. M. and Hedges, L. V. (2019) ‘How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-Analyses, and Meta-Syntheses’, Annual Review of Psychology, 70, pp. 747–770.

Priya is the co-founder and Managing Partner of Project Guru, a research and analytics firm based in Gurgaon. She is responsible for the human resource planning and operations functions. Her expertise in analytics has been used in a number of service-based industries like education and financial services.

Her foundational educational is from St. Xaviers High School (Mumbai). She also holds MBA degree in Marketing and Finance from the Indian Institute of Planning and Management, Delhi (2008).

Some of the notable projects she has worked on include:

• Using systems thinking to improve sustainability in operations: A study carried out in Malaysia in partnership with Universiti Kuala Lumpur.
• Assessing customer satisfaction with in-house doctors of Jiva Ayurveda (a project executed for the company)
• Predicting the potential impact of green hydrogen microgirds (A project executed for the Government of South Africa)

She is a key contributor to the in-house research platform Knowledge Tank.

She currently holds over 300 citations from her contributions to the platform.

She has also been a guest speaker at various institutes such as JIMS (Delhi), BPIT (Delhi), and SVU (Tirupati).

I am a master's in Economics from Amity university. Besides my keen interest in Economics i have been an active member of the team Enactus. Apart from the academics i love reading fictions.