Introduction
Business analytics is becoming more well-known in both academic and professional circles. It may be considered the meeting point of artificial intelligence, information systems, and operational research. This field examines how machine learning, mathematical, statistical, and network science techniques might improve decision-making (Carillo et al., 2018). This essay defines business analytics and assesses its relevance in the current business environment. An extensive examination of business analytics trends is included in the paper. Additionally, it describes the descriptive kind of business analytics and provides instances of how business analytics is employed in the current corporate context.
Meaning of Business Analytics
Business analytics uses statistical techniques and methods by firms to evaluate historical data to gain new insights and improve strategic decision-making. It is a subset of data management and business intelligence technology. Utilizing data mining, predictive analytics, and statistical analysis, it analyzes and converts data into valuable information, identifies and anticipates patterns and outcomes, and eventually enables businesses to make more informed, data-driven choices (“Business Analytics,” 2022). Business analytics is a firm’s forensic side that uses statistics to grow and advance the business or steer it in new ways.
Importance in Business Environment
Today’s firms face significant rivalry and are under obligation to make fast and effective choices. Customers are spoiled with alternatives. However, to retain customers, organizations must use analytics. Companies, for example, may evaluate customers’ online interactions and prior purchases. They may evaluate trends and enhance website performance using this data. It improves client experience and loyalty.
In addition, successful firms have moved away from intuition-based decision-making. Business analytics helps organizations make data-driven choices. It gives firms a good perspective and information on becoming more efficient, allowing them to streamline and automate operations (“Business Analytics,” 2022). Business analytics enables companies to foresee the possibility of particular results, explore more efficient business procedures, and understand why certain results are achieved, leading to better decisions and fewer bad results.
Business risks need analytics to forecast and avoid. Analytics may help firms reduce long- and short-term risk by helping them make the proper choices based on client preferences and trends. Besides, firms may cease operations when an issue emerges, causing a substantial loss. However, business analysts assist organizations in avoiding such scenarios by identifying possible risks and preventing damage (Carillo et al., 2018). Analytics professionals can utilize raw data to discover system malfunctions and assist company owners in solving them.
Trends in Business Analytics
Several trends characterize business analytics. For instance, there is mobile analytics that is significantly helping certain organizations succeed. Smartphones like the Blackberry and iPhone allow on-the-go business owners to monitor company metrics. For example, FourSquare is a mobile analytics application that lets company owners view web visitor stats on their phones. Companies may utilize user data to enhance products and advertising (Carillo et al., 2018). If the owner provides a mobile application and finds that many clients download it on a given phone, they may target their advertising to those people.
Another trend is business analytics software. The need for software for storing and analyzing data is increasing. Databases enable users to list data, and then execute searches and sorting, although some firms utilize more advanced analytic tools to manage information and trends within and outside the company. IBM’s Cognos software, for example, analyzes statistical data and employs predictive modeling capabilities to assist a business in anticipating and preparing for emerging market trends (“Business Analytics,” 2022).
Examples of how Business Analytics is used
Business analytics has several uses—The first is predictive analytics. For example, a gym may want to decrease client turnover. The organization may deploy a predictive analytics engine that identifies consumers likely to cancel and forecast incentives to boost client retention. The technology may inform gym personnel when at-risk consumers come so they can discuss incentives and prevent cancellations. Moreover, some companies utilize business analytics to improve procedures and boost efficiency. For example, an online meal-ordering firm wants to enhance efficiency and optimize processes. The organization can create a dashboard with real-time client lifecycle data. This data streamlined sales and marketing strategies, enhancing productivity. Finally, businesses may employ analytics to increase sales (Carillo et al., 2018). Online businesses can deploy a sales dashboard to stabilize and expand sales. From the results, the business can identify and rethink its sales strategy and target-setting mechanism, which can significantly increase sales.
Descriptive Analytics with Examples
Descriptive analytics identifies patterns and linkages in current and historical data. Demand trends and financial statement analysis are good examples of descriptive analytics. Financial statements are quarterly filings that detail a company’s financial condition. Analysis of financial statements includes ratio, vertical, and horizontal analysis. Each financial statement analysis approach provides descriptive analytics based on historical and current data.
Descriptive analytics may identify demand trends for particular products or services. For example, Netflix’s trend detection demonstrates descriptive analytics. Netflix’s data-driven team collects user activity data, which is used to decide on popular TV shows and movies and put them on the home screen. This data lets Netflix viewers know the top movies, and the company knows which media, topics, and celebrities are preferred at a given moment. According to Carillo et al. (2018), this may influence future content development, contracts with production firms, marketing, and retargeting strategies.
Conclusion
The desire to generate better and faster decisions in the current highly competitive business environment, with massive data sources and superior computing resources, is changing management decision-making. Business analytics have changed the dynamics and operation of firms. With more firms depending on it for decision-making, enterprises should consider incorporating it. Business analytics technologies may help firms succeed by predicting decision outcomes.
References
Business Analytics. Ibm.com. (2022). Web.
Carillo, K. D. A., Galy, N., Guthrie, C., & Vanhems, A. (2018). How to turn managers into data-driven decision-makers: Measuring attitudes towards business analytics. Business Process Management Journal, 25(3), 553–578. Web.