An Overview of Business Analytics - Descriptive, Predictive and Prescriptive Analytics

What is Business Analytics?

Analytics is the use of: data, information technology,   statistical analysis,  quantitative methods, and   mathematical or computer-based models  to help managers gain improved insight about their business operations and make better, fact-based decisions.

Business analytics is “a process of transforming data into actions through analysis and insights in the context of organizational decision making and problem solving.”

 

Business Analytics Applications

}Management of customer relationships

}Financial and marketing activities

}Supply chain management

}Human resource planning

}Pricing decisions

}Sport team game strategies

Evolution of Business Analytics

Much of modern business analytics stems from the analysis and solution of complex decision problems using mathematical or computer-based models—a discipline known as operations research, which was essentially a dicipline created due to necessacity duting world war. This was further developed into many management science disciplines for optimising business process. Then came the combination of mathemetical models and computer science which lead to Business Intelligence and that led to DSS and now it rests in its current position as a software available in personal computers.

Modern business analytics can be viewed as an integration of BI/IS, statistics, and modelling and optimization as illustrated in Figure.

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Listed below are some of the important aspects of Business Analytics as shown in the figure

 Data Mining is focused on better understanding characteristics and patterns among variables in large databases using a variety of statistical and analytical tools. Many standard statistical tools as well as more advanced ones are used extensively in data mining.

Simulation and Risk Analysis relies on spreadsheet models and statistical analysis to examine the impacts of uncertainty in the estimates and their potential interaction with one another on the output variable of interest. Spreadsheets and formal models allow one to manipulate data to perform what-if analysis—how specific combinations of inputs that reflect key assumptions will affect model outputs.

 What-If Analysis is also used to assess the sensitivity of optimization models to changes in data inputs and provide better insight for making good decisions.

Visualization- Visualizing data and results of analyses provide
a way of easily communicating data at all levels of a business and can reveal surprising patterns and relationships.

Tools used in Business Analytics:

A wide variety of tools are used to support business analytics. These include:

• Database queries and analysis
• Dashboards
• Data visualization
• Statistical methods
• Spreadsheets and predictive models
• Scenario and “what-if” analyses
• Simulation
• Forecasting
• Data and text mining
• Optimization
• Social media, Web, and text analytics 

Descriptive, Predictive and Prescriptive Analytics

Business analytics begins with the collection, organization, and manipulation of data and is supported by three major components:

1. Descriptive Analytics
2. Predictive Analytics
3. Prescriptive Analytics

S.No		Descriptive analytics	Predictive analytics	Prescriptive analytics
1	Definition	The use of data to understand past and current business performance and make informed decisions.	Predictive analytics seeks to predict the future by examining Historical data, detecting patterns or relationships in these data, and then extrapolating these relationships forward in time.	Prescriptive analytics factors information about possible situations or scenarios, available resources, past performance, and current performance, and suggests a course of action or strategy.
2	Hierarchy	Descriptive Analytics is the first part of any model building exercise. We analyze the historical data to identify patterns and trends of the dependent and independent variables.	Predictive Analytics is the next stage of analytics. Here, we leverage the cleaned and/or transformed data and fit a model on that data to predict the future behavior of the dependent variable.	Prescriptive Analytics is the last stage where the predictions are used to prescribe (or recommend) the next set of things to be done.
3	Process	Categorize, characterize, consolidate, and classify data to convert it into useful information for the purposes of understanding and analyzing business performance.	Using advanced techniques, predictive analytics can help to detect hidden patterns in large quantities of data to segment and group data into coherent sets to predict behaviour and detect trends.	Prescriptive analytics relies on artificial intelligence techniques, such as machine learning, to understand and advance from the data it acquires, adapting all the while.
4	Output	This process allows managers to obtain standard and customized reports and then drill down into the data and make queries to understand the impact of an advertising campaign, for example, review business performance to find problems or areas of opportunity, and identify patterns and trends in data.	This process allows a bank manager to identify the most profitable customers Or predict the chances that a loan applicant will default, or alert a credit-card customer to a potential fraudulent charge.	Prescriptive analytics is used in many areas of business, including  operations, marketing, and finance. For example, we may determine the best pricing and advertising strategy to maximize revenue, the optimal amount of cash to store in ATMs.
5	Application	Typical questions that descriptive analytics helps answer are “How much did we sell in each region?” “What was our revenue and profit last quarter?”	Predictive analytics helps to answer questions such as “What will happen if demand falls by 10% or if supplier prices go up 5%?” “What do we expect to pay for fuel over the next several months?” “What is the risk of losing money in a new business venture?”	Prescriptive analytics addresses questions such as “How much should we produce to maximize profit?” “What is the best way of shipping goods from our factories to minimize costs?” “Should we change our plans if a natural disaster closes a supplier’s factory: if so, by how much?”
6	Practical Usage	Descriptive analytics can help to identify the areas of strength and weakness in an organization.	Predictive analytics look at patterns in data to determine if those patterns are likely to emerge again, which allows businesses and investors to adjust where they use their resources to take advantage of possible future events.	Prescriptive analytics can simulate the probability of various outcomes and show the probability of each, helping organizations to better understand the level of risk and uncertainty they face than they could be relying on averages.