I would be writing today about different analytical tools used by professional to analyze both qualitative and quantitative data in an organization.
Two different types of data generated by an organization in the course of their operation are qualitative and quantitative data. These data could come in many forms and in many instances, professionals find it hard to make use of these data in its raw forms. They therefore have to employ tools that would help them make sense of the data generated by the organization. Before I go further, I would like us to have a brief understand of what quantitative and qualitative data are.
Quantitative data are data that can be counted and measured in numerical values. These can be further sub-divided into discrete and continuous data. Professionals make use of different analytical tools to analyze quantitative data viz: graphs, linear regression, hypothesis testing and ratio analysis. These tools provide analysts with statistical methods of organizing and examining data. Financial analysts mostly make use of linear regression and ratio analysis to find: (a). the relationship between two or more variables say between profit and cost and (b). comparison of firm’s performance over a period of time and its performance against a company of comparable size respectively. Linear regression analysis would help analysis understand relationship between say advertisement cost on and sales and would help management understand clearly drivers that could help increase sales in an organization. Ratio analysis help analysis understand organization’s performance over a period of time and could help identify patterns that have major changes in their bottom lines. Comparing ratio of two companies of comparable size could reveals so many things that ordinarily looking at the financial statement could not have revealed. Analysts also use ratio to estimate the value of a target company especially if the company is under consideration for acquisition. Ratio also help analysts understand trends over time of items in the financial statement and could possibly reveal drivers of those changes if it occurs. Comparison of company’s performance over time help management understand if their strategy is working or not.
Qualitative data are information or data that cannot be counted or measured easily using numbers. These types of data are usually collected from different sources including audios, text and sometimes images and mostly shared using visualization tools such as graph data base infographics and timelines. Analysts make use of certain tools to analyze qualitative data, thus:
- Cauliflower. This is mostly use in understanding the differences and similarities between different items in the customers feedback. It helps management understand customers concern using the review of their feedbacks, help product development personnel prioritize product testing and help in visualizing results and sharing them with your teams.
- Dovetail. It’s a customer’s research tool used mostly by a growing organization to understand a meaningful pattern in a contextual data, highlight and tag customer’s interviews and in many cases, run sentiment analysis.
- Delve. Is a tool use by organization that have large volume of data use mostly for an extended customer’s interview.
Using all the tools therefore help organization make sense as to major drivers to changes in the financial statement or other company’s data.
