eBusiness Weekly
Dr Linda Haj Omar
Research is an organised and systematic method of finding answers to questions.
It is systematic because it’s broken up into clear steps that lead to conclusions, and it’s organised because there is a planned structure or methods that are used to reach conclusion.
This systematic inquiry process entails data collection, analysis, interpretation of findings from data analysis and documentation of critical information, in accordance with the suitable methodologies set by the researcher.
On the other hand, data collection is the process of gathering and measuring data/information on variables of interest, in an established systematic fashion that enables one to answer stated research questions, test hypotheses and evaluate outcomes.
There are many methods for collecting data which include surveys, observations, experiments, etc, and the collected data maybe primary or secondary data.
Primary data, also known as raw data, is the data collected directly from a first-hand source by the researcher for specific research purpose. Secondary data is the data that has already been collected and made readily available by the primary data collector.
Generally, there are two types of data in research which are qualitative data and/or quantitative data.
Qualitative data refers to non-numeric information such as interviews, transcripts, photographs, text documents, case studies, etc, that cannot be quantified, measured, or expressed using numbers. Quantitative data is, quite simple, information that can be counted or measured and given a numerical value.
Quantitative data collection tools
- Surveys — involves close-ended surveys where respondents are asked to answer yes or no and/or multiple-choice questions. Surveys also gather demographic data such as age, gender, income, or occupation. Respondents may also be asked to rate something along a certain scale such as use of strongly agrees, agrees, disagrees, or strongly disagrees. Participants can respond to surveys online or through the mail.
- Interviews — quantitative interviews are much more structured than a qualitative interviews, with interviewers asking respondents a standard set of close-ended questions that don’t allow for responses with detailed context.
3.Structured — Observation — researchers observe or count subjects attending a specific event or using a service in a designated locale. It’s a way to retrieve numerical data that focuses on the “what” rather than the “why.”
- Existing Data — is a method to gather verifiable and quantifiable data from existing data. These records are easily accessible. The researcher can add new information along with the data derived from the existing documents.
Qualitative data collection tools
- One-on-one interviews- they are a great approach when the researcher aims to gather highly personalised information. Informal, conversational interviews are ideal for open-ended questions that allows the researcher to gain rich, detailed context.
- Open ended surveys and questionnaires — this method allows the participants to answer questions freely at length, rather than choosing from a set number of responses.
- Focus groups — they are like interviews, except that the researcher conducts them in a group set up.
A researcher might use focus group when one-on-one interviews are too difficult or time consuming to schedule.
- Observations — in this method the data collector observes subjects during their regular routine, takes detailed field notes and/or records subjects via video or audio.
- Case studies — the researcher analyse a combination of multiple qualitative data sources to draw inferences and come to conclusions.
Effective data collection will allow you to make informed business decisions, ensure quality assurance, direct scarce resources where they are most needed and keep research integrity.
There are many benefits that comes with effective data collection in research organisations and many other organisations which include the following:
Improving precision in targeting customers
Finding new customers
Understanding customer behaviour
Increasing customer retention
Improving decision making
Reducing errors
Enhancing marketing efforts
Predicting market trends, etc
Data collection is quite simple but there may be constraints in collecting data. These constraints include:
Inability to connect with people from remote areas.
High chances of survey fraud
Sampling issues
Response bias
Survey fatigue
Increase in errors, etc.
Data Analysis
Data analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense, recap, and evaluate data. There are two primary methods for
Data analysis which are qualitative data analysis techniques and quantitative data analysis techniques. These data analysis techniques can be used independently or in combination with each other to help business insights from different data types.
Qualitative data analysis is the process of organising, analysing, and interpreting non-numeric data, and conceptual information to capture themes and patterns, answer research questions and identify key measures to be implemented.
Qualitative data analysis can be divided into the following categories:
Content Analysis
Narrative Analysis
Discourse Analysis
Framework Analysis
Grounded Analysis
Qualitative data analysis can be conducted through the following steps:
Developing and Applying Codes
Identifying themes, patterns and relationships
Summarising the data
Quantitative data analysis involves analysis of quantitative data or numeric data using statistical methods and software such as R, SAS, STATA, and IBM SPSS (Statistical Package for Social Sciences). The data are coded and presented as graphs, cross-tabulations, and statistical models.
Data interpretation
Data interpretation refers to the process of using diverse analytical methods to review data and arrive at relevant conclusions.
The interpretation of data helps researchers to categorise, manipulate and summarise the information to answer critical research questions that are aimed at achieving research objectives.
Data is critical to the success of any organisation, while the same can reveal the true position of a company’s products or services in the marketplace, it can also help in policy and strategy formulation.
Medlico as a Research and Training facility made sure to have a team that comprised of highly experienced personnel in data collection and analysis. As well as we are better placed as the ideal partner for Government Ministries and Departments, Civil Societies, private companies and even individuals who might need such services to render and evaluate their work on a regular base.
For more information/inquiries: Visit: 4 Lanark Belgravia, Harare — Zimbabwe, Tel: (+263) 242 702326/7; WhatsApp: +263 777 553011/12, Email: [email protected]
