Thomas H. Davenport - Keeping Up with the Quants: Your Guide to Understanding and Using Analytics

By analytics, we mean the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and add value.

Analytics can be classified as descriptive, predictive, or prescriptive according to their methods and purpose. Descriptive analytics involve gathering, organizing, tabulating, and depicting data and then describing the characteristics about what is being studied. This type of analytics was historically called reporting . It can be very useful, but doesnt tell you anything about why the results happened or about what might happen in the future.

Predictive analytics go beyond merely describing the characteristics of the data and the relationships among the variables (factors that can assume a range of different values); they use data from the past to predict the future. They first identify the associations among the variables and then predict the likelihood of a phenomenonsay, that a customer will respond to a particular product advertisement by purchasing iton the basis of the identified relationships. Although the associations of variables are used for predictive purposes, we are not assuming any explicit cause-and-effect relationship in predictive analytics. In fact, the presence of causal relationships is not always necessary to make accurate predictions.

Prescriptive analytics, including methods such as experimental design and optimization, go even further. Like a prescription from a doctor, they suggest a course of action. Experimental design tries to answer the questions of why something happened by conducting experiments. To make causal inferences with confidence in causal research, researchers must manipulate one or more independent variables and effectively control other extraneous variables. If the test groupthe one with the experimental condition presentperforms substantially better than the control groupthen the decision maker should apply that condition broadly.

Optimization, another prescriptive technique, attempts to identify the ideal level of a particular variable in its relationship to another. For example, we might be interested in identifying the price of a product that is most likely to lead to high profitability for a product. Similarly, optimization approaches could identify the level of inventory in a warehouse that is most likely to avoid stock-outs (no product to sell) in a retail organization.

Analytics can be classified as qualitative or quantitative according to the process employed and the type of data that are collected and analyzed. Qualitative analysis aims to gather an in-depth understanding of the underlying reasons and motivations for a phenomenon. Usually unstructured data is collected from a small number of nonrepresentative cases and analyzed nonstatistically. Qualitative analytics are often useful tools for exploratory researchthe earliest stage of analytics. Quantitative analytics refers to the systematic empirical investigation of phenomena via statistical, mathematical, or computational techniques. Structured data is collected from a large number of representative cases and analyzed statistically.