What is business analytics?

Business analytics combines processes, skills, and technologies to collect, analyze and present historical performance of the business, based on data, with the goal of driving business planning. Business analytics essentially uses large amounts of historical business data for the purpose of providing insights to evaluate a business. Business analytics reveal previously unknown insights or identify unanticipated issues to generate new business value. Business analytics can be leveraged to create new processes for solving business challenges and increase efficiency, productivity, and revenue.

What are the benefits of business analytics?

Enterprises seek to find and sustain a competitive advantage by creating an information advantage over business rivals with business analytics. This information advantage helps make the business more intelligent and responsive to market changes. It also helps to make analytics more business-friendly, giving business professionals the opportunity to effectively understand their company’s data and react in a smarter way. Therefore, companies look to business analytics for higher returns from information and expertise investments.

What can you do with business analytics?

Business analytics’ specific purpose is bringing information and expertise to help guide business decisions and create an “Information Advantage.” With business analytics, you can:

• Turn big data into insights
• Build statistical models to make projections about a business
• Pitch ideas to optimize performance
• Advise management around decision-making
• Leverage data to influence business outcomes

Business analytics enable you to choose opportunities with the highest propensity for success, calculate the strategy that would deliver the best return for the business, and it can help prepare your company for any upcoming changes or market trends that are on the horizon. Business analytics can help you understand the environment you are in, how you can become more competitive, streamline decision making and as a result, increase revenues and decrease risk.

Previously, only companies with high levels of risk, like insurance companies would apply business analytics. However, since data has revolutionized the world, business analytics has become a necessity for all businesses to remain competitive and succeed in a digital world.

Types of business analytics

There are basically four types of business analytics, each with its own importance. As you will see below, each category becomes increasingly more mature and more oriented towards real-time and future insight application.

By leveraging all four of these types, data can be properly analyzed and operationalized to create solutions for problems that many businesses face today.

Descriptive analytics

Descriptive analytics typically offer a rearview look into the past through the data of the present. They can tell a user what happened in the business. Descriptive analytics is usually performed in the preliminary stage of data processing to create a summary of historical events and a foundation for further analysis and understanding. Data aggregation and data mining are the primary methods used. Descriptive analytics is generally known as the simplest type of analytics. In fact, most businesses perform descriptive analytics in their everyday reporting such as inventory, workflow, and sales.

Diagnostic analytics

Diagnostic analytics (also known as discovery analytics), a type of advanced analytics enabled by machine learning, is used to find interesting patterns and correlations in the data, even without a user asking specific questions. It uses techniques like probabilities, data mining and correlations to uncover root causes and correlations. Although diagnostic analytics are excellent at discovering why events happened, they lack the ability to advise you how to proceed. They do however provide the context you might need to decide how to move forward.

Predictive analytics

Predictive analytics is focused on forecasting the likelihood of potential outcomes and events in your business and is modeled on historical data. Predictive analytics use techniques like statistical modeling and machine learning and typically need data scientists and statisticians to execute. Organizations can use patterns found in past and current data to forecast trends, detect risks, and opportunities in the near or far future. Predictive analytics offers a confidence level for businesses to look into the future to save and even earn more revenue. Examples of predictive analytics that are currently in use include retailers that use predictive models to forecast inventory, manage shipping and set up stores to maximize sales. Airlines often use predictive analytics to set ticket prices based on past demand and trends. Hotels can use predictive analytics to determine capacity to ensure they are prepared for any sudden surges in bookings.

Prescriptive analytics

Prescriptive analytics is the most mature stage of the analytics journey in business analytics. It tells the business what they should do and recommend next best actions or actions they should be taking given a variety of choices. This type of analytics can tell you the outcomes of each choice that you made and recommend the best action you should take based on all of the possibilities. Prescriptive analytics is related to descriptive and predictive analytics but focuses on actionable insights rather than just data monitoring. To perform prescriptive analytics, you need deep learning and complex neural networks. A great example of prescriptive analytics are recommendation engines.

Business analytics vs. business intelligence

Business analytics and business intelligence (BI) are often confused as the same thing, but business analytics is actually a subset of business intelligence. Business intelligence is the first step towards understanding what your business is currently going through and the state that it is in. Business analytics explains why your business is where it is. BI is traditionally concerned with monitoring business operations with routine, static reports and informing long-term business plans, while business analytics is concerned with understanding the business, asking any questions that business users need answered, and can be much more flexible and iterative.