Analyzing Data
Your analysis of a given data set, whether internal or external, is based on the data gathered. Anthropology tends to view the following as types of data:
- the types of interactions, often called “transactions” that the population engages in
- topics and themes of the transactions
- occurrence/recurrence of the transactions
- tensions between what the group represents as “truth” versus observations the researcher or analyst perceives differently
Anthropologists attempt to make connections and meaning by linking these data to stories and accounts of a given culture or experience. Although this data might sometimes seem subjective or heavily dependent on the researcher’s perspective, such studies are incredibly valuable in many business contexts. If the person writing the business report or conducting the research is conscious of their own biases and has considered the ethical implications of their work, the insights gained can be particularly beneficial.
Read more about how bias can influence your research through the questions you ask, the people you survey, your data collection method, or your data interpretation.
Sociological data sets can be similar, but the analysis will be more quantitative and broken down into categories and variables for statistical analysis. Surveys are the most common tool to gain sociological data. You’d naturally be familiar with many of them, for example, customer satisfaction surveys, expressing your opinion about a particular product. Usually, you’re asked to express the opinion along a Likert scale: something like “7 means you’re extremely satisfied, 1 means you’re extremely dissatisfied.”
Depending on how elaborate you would like your analysis to be, working with statistical data sets can become quite complex. There are also issues around quantifying human behavior and opinion. One person’s 7 is likely to be different from another’s, even if they are similar enough conceptually. For our purposes here, we recommend you emphasize simplicity in your business data analysis.
If you decide to analyze data sets using statistical methods, manipulating the data through a third-party platform like Qualtrics or Survey Monkey can be helpful. Develop simple surveys, and use very simple Likert scales to help quantify your data. Note that surveys present qualitative data in a quantified form; take care when representing these types of data as accurate and representative of human sentiment or behavior.
Named after American social psychologist, Rensis Likert, the Likert scale is a survey tool that asks people to rate their level of agreement with statements, typically on a scale from "strongly agree" to "strongly disagree." Sometimes numbers might be assigned to the degree of sentiment.