What is Business Analytics ?

Business analytics refers to new skills, naive practices, marketing, new technologies, and business tools algorithms for continuous iterative exploration. It is used for deep investigation of past business performance of the respective company and also the competitors of that company in the market to gain its own insight and of its competitors i.e what they do, how they do, what mistakes they do so far, what are the false commitments they do with their clients or consumer. This data is quite useful for an organization during market enhancement and drive the whole business planning in an effective way.
Indifference, intelligence in past time completely focuses on using a continuous set of metrics, stats to both calculating past performances and also act as complete hand guide for business planning, which is also based on data, statistical, probability and mathematical methods. But now the scenario is different we have a huge amount of data so we can use Data science, Data Analytics, etc. which can also be the part of a skilled Business Analyst.
Business Analytics makes large use of statistical analysis in a modern way. It also includes explanatory and predictive modeling methods, fact-based management, and fixed data/information driven based management to drive decision making in an effective manner. It is therefore very closely related to management science, data science, and data analytics. Analytics used as input for driven human decisions or may drive fully automated decisions. If we talk about Business intelligence then we can see querying, reporting, online analytical processing (OLAP), and alerts are there.

Types of Analytics

1. Descriptive:

Descriptive analytics is the application of earlier and simple statistical techniques that are used from the earlier period and also describe what is contained in a data set or database.
Example: An age bar chart which is used to depict customers for a Gaming company who wants to target the customers for new game production by age.

2. Diagnostic:

Diagnostic analytics is the successor of the Descriptive analytics which allows an analyst to dig deeper into a problem or issue to arrive at the source of the problem. It is generally characterized by techniques like data discovery, drill-down, data mining, etc.



3. Predictive:

Predictive analytics is an application of advanced statistical techniques and tools, methods, informatics software, we can also consider all the operations research methods to identify predictive variables and also which are used to build predictive models which are used in real time to identify trends and relationships which are not readily observed in a descriptive analysis.
Example: Multiple regression is used to show the relationship between working hours, work type, qualifications on hiring someone on payroll.

4. Prescriptive:

Prescriptive analysis is actually an application of decision science, management science, and operational research methodologies (which are also applied mathematical techniques) to make the best use of allocatable resources.
Example: A startup which has a limited advertising budget and who wants to advertise to target customers only. So the Linear programming models of prescriptive analysis can be used here to optimally allocate the budget of various advertising media for the company focusing on the Target Customer only.

Applications of Business Analytics

1. In the Finance Sector:

  • Budgeting
  • Financial Planning
  • Portfolio Management
  • Investment Banking
  • Forecasting etc.

Example: Financial companies nowadays have a huge amount of financial data because finance facilities are now easily reachable to all. Use of intelligent Business Analytics tools can help to use this data in a productive way to determine the right value of products. Also, we can use historical information, trained Business Analysts that can easily study the trends of the performance of a particular stock/product/asset and can give a bit of stronger advice to the clients on whether they retain it or sell out it.

2. In Marketing:
Deeply study the buying patterns of competitors sales, competitors market, competitors sellers, consumer behavior, analyzing appropriate trends, help in finding the audience which we can target, employing advertising techniques according to the target region and target audience, forecast supply requirements, etc.
Example: Use Business Analytics can be used to measure the effectiveness of a particular advertising strategy on the customers. And also can compare it with other multiple strategies and then find out the best strategy region wise, and Targeting Customer wise, etc.
Further on seeing this on large scale all these data can be used to build loyal customers by providing them exactly what they want as per their required specifications which are analyzed by proven tools and trained Business Analyst.

3. Human Resource (HR) Professionals:
Human Resource professionals can use Analytics tools to gather the data of Colleges to find out the minute details about the educational background of high performing candidates, to find details of students not only in field of academics but also in extracurricular and co-curricular activities or the activities which are related to there organization, for old employees HR can use to analyze the employee attrition rate, total number of years of service, gender, age, etc. These details can play a central role in the promotion of old employees and selection of a new candidate.
Example: HR manager can predict the employee promotion time, retention rate using the data of BA.

4. In Consumer Relationship Management
Business Analytics helps the organization to make a better and sustainable relationship with there customer by analyzing the key performance indicators of the product, which later on helps in making decisions and make lively and practical strategies to maintain the relationship with the consumers. The statistics, and the relevant data about the other socio-economic factors purchasing patterns of customer, the lifestyle of consumer, likes-dislikes of the consumer, etc., are of prior importance to the Consumer Relationship Management (CRM) department.
Example: The ABC Pvt. Ltd. which is an FMCG company who makes soft-drinks, wants to improve its service in a particular region of a country or we can say that particular geographical segment. With data analytics tools and using the Business Analytics, the organization can predict the customer’s preferences in each site of a particular segment, what appeals to them, and accordingly, improve relations with customers.

5. In Manufacturing
Business Analytics can help the manufacturing unit of an organization in

  • Supply-chain Management
  • Calculate the Performance of Targets
  • Inventory Management
  • Risk Mitigation Plans
  • Improve Efficiency on the Basis of Product Data, etc.

Example: The Manufacturing Director of ABC Pvt. Ltd. wants details on the performance of machines used to manufacture there product X which are used in the past 20 years. This historical data of the machinery will help him to evaluate the performance of the machinery and then can decide that the ABC Organization will be going to buy new machines or not this will going to decide on the basis of whether the cost of repair/maintenance of the machine will exceed the cost of buying new machine or not.

6. Credit Card Companies
This will be going to help in banking sectors also, because, ultimately Credit Cards are tied-up with banks. Business Analytics tools and Analyst will go through the credit card transactions of a customer in a period of time, the period may be in Months, years, 10 Years, weeks, etc. this will going to determine many factors such as:

  • The Financial Health of the Customer
  • The Financial Knowledge
  • The Lifestyle of the Customer
  • Preferences for Purchases
  • Behavioral Trends, etc.

Example: Credit card companies help the manufacturing and retail sector by selecting only the target audience on the basis of there transactions and geographical region. According to the transaction reports which were originally generated by the credit card companies and can sell to retail and manufacturing companies so that they can predict the choices of the consumers in a better way, their spending pattern, preference over buying competitor’s products, there like dislikes, etc. These former (old) informations, as well as current-time informations, helps them to make their advertising strategies, marketing strategies more appealing.

Other than the above-highlighted areas, Business Analytics is helpful in various areas such as biomedical, bioscience, health-care, IOT, fraud detection, defense sector, sales, Cybersecurity, FMCG sector, Niti Ayog, Election Commission, etc.



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