- Identify types of primary sources and internal data
- Discuss methods for collecting and analyzing internal data
Ithaca College Library defines primary sources as:
[Direct] or first hand evidence about an event, object, [or person, and could include] historical and legal documents, eyewitness accounts, results of experiments, statistical data, pieces of creative writing, audio and video recordings, speeches, and art objects. Interviews, surveys, fieldwork, and Internet communications via email, blogs, listservs, and newsgroups are also primary sources.
Internal data are data about your organization derived from internal primary sources. A report by HR about turnover and hiring or financials from Accounting or Finance are common examples. Note how an article in a business magazine about your organization’s talent management would be a secondary source, even if it referenced internal data–originally a primary source. Internal data are usually not available outside the organization unless the organization is mandated to produce such reports, for example publicly-traded companies must file a variety of reports with the U.S. Securities and Exchange Commission (SEC). Depending on the size of your organization, its own public filings may be a great source of material for your business reports.
Let’s take a look at Apple’s 10-K, which is a report that publicly traded companies must make annually about their organizations. Apple’s annual 10-K reports can be found online.
While Apple’s data are published publicly for large investor oriented firms (i.e., “publicly traded”), similar data would be interesting and meaningful for other companies in any business environment. We might argue that the most fundamental data are the financials, but other data, such as those around employee hiring practices, leadership bios, and other more qualitative information would still prove beneficial. In this, we can argue that quantitative and qualitative data are both desirable; both are needed to gain the best picture of the reality of a given firm’s situation.
Collecting Internal Data
Gathering data on your own organization is a much more complicated phenomenon than we might suspect. Depending on your project or business report, the politics of the event may be quite substantial. Internal data can come from a variety of sources and departments—from sales reports, financial documents, human resources information, or elsewhere.
If we return to Martha’s case, we remember that her project involves studying The Human Fund’s impact on people who are homeless in downtown Chicago. Her background reading would certainly involve looking at any available data on-hand in her own organization. Depending on where she sits, and for whom she works, this data may be readily available, or using it might necessitate some sort of cross-divisional—or at least team—privilege and access. Hopefully she can get her hands on internal information such as the number of participants in the Human Fund, find information about how long individuals participate in the program, or get numbers on the cost of the program to the company, etc.
Research in the Social Sciences
Access is a key concept in social science research. Anthropologists, who often immerse themselves with sub-cultures to observe their lives, probably understand access issues better than most other researchers. If they do not have good access to a group, their ability to conduct their study is compromised. Anthropologists studying the homeless population in Chicago might live among them for a time. Since this is impractical for Martha, she decides to do research more like a sociologist, who tend to use surveys and have less need for direct, prolonged access. Surveys can be difficult to use, however, as they may be completed incorrectly, incompletely, or not at all. When you are participating in “How did we do?” surveys after a customer service phone call or other service event, you are participating in sociological research.
Check out the following two videos that discuss anthropological and sociological data gathering:
Note the difference in attitude and goals. While this explanation is a bit simplified, the anthropologist is interested in observing and understanding culture; the sociologist surveys and tests ideas through the use of less personal, but more structured, tools. For our purposes, we may consider how both types of data collection, and both types of attitudes towards data, are useful for business report writing. The goal is getting as much insight into a problem as possible. Depending on your time available, using multiple methods is wise.
Your analysis of a given data set, whether internal or external, is based off of 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. In an interview with CBS News, Dr. Genevieve Bell, an anthropologist, discusses her interest in people and how studying them is, “about spending time with them.” While these data can appear “squishy” at times, or too reliant on the researcher’s interpretation, this type of study is very useful for most business circumstances. Provided the business report writer or researcher is aware of their bias(es), and has thought about the ethics of their research (i.e., stakeholder analysis), the type of insights derived can be quite helpful.
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 around 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. Clearly 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. Professional sociologists, trained in skills such as multivariate analysis, can help when required, but generally this type of analysis is unnecessary for day to day decision-making and information dissemination.
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.