Business analytics (BA)
Business analytics (BA) is a strategic practice employed by organizations to utilize historical data for informed decision-making and future planning. By analyzing past performance, companies can identify trends and patterns that aid in improving operations, enhancing customer satisfaction, and increasing growth opportunities. Notable companies like Ford and Amazon leverage BA to refine their business strategies, optimize product offerings, and drive competitive advantage. BA encompasses various industries, including retail, healthcare, and telecommunications, demonstrating its versatility and importance across sectors.
Business analysts play a crucial role in this process by investigating organizational challenges and interpreting data to develop actionable insights. For instance, a restaurant might hire an analyst to resolve customer dissatisfaction, using data to identify and rectify wait times in service. The analytical approach emphasizes data-driven decision-making, enabling organizations to allocate resources effectively and minimize risks associated with non-analytical choices. Overall, business analytics not only enhances operational efficiency but also fosters a culture of informed decision-making, ultimately contributing to long-term business success.
Business analytics (BA)
Business analytics (BA) is a practice used by companies, industries, and other organizations to determine future business planning. Analytics is the study of an object or concept to learn about all aspects of it, such as its parts, how they work, and how they are related. In BA, a company uses its past data to determine ways to grow future business, improve performance, and gain customers.
Overview
Businesses analyze past data to solve a variety of problems and answer questions such as why a problem happened, whether it may happen again, what will happen if changes are made, and what else the data shows. For example, a marketing professional might examine past marketing campaigns to determine methods that have worked previously, who the target consumer base is, and whether other methods should be implemented.
BA is employed extensively by big players in industries such as retail, automotive, telecommunications, healthcare, technology, and more. Major companies such as Ford, Amazon, Google, and Capital One cite the use of analytics for their success. For example, Ford used BA practices to study the trends of consumers to help it maintain success in the automobile industry. Large corporations are not the only ones that use analytics to grow their companies and keep them successful. Many startups utilize the skills of business analysts to get their companies up and running. In addition, the advent of new technology has led more companies to rely on BA to examine data from sources such as smartphones, tablets, social-networking sites, blogs, and more.
Studying BA helps companies drive business and compete with other successful companies. Business analysts use a company’s data to solve problems and to look for ways to improve. They research any problems a company may have and then study the company’s data to form strategies for solving these problems.
For example, a restaurant many hire a business analyst to address customer complaints about its drive-thru service. The business analyst conducts a study of the restaurant’s data and determines customers are not satisfied because they have to wait too long in the drive-thru. The analyst then comes up with ways to resolve the problem such as hiring more employees to reduce wait times. In addition, business analysts may be able to spot other problems within a company and help resolve these problems.
How Does Business Analytics Work?
Analytics can be used in any data-based decision. For example, purchasing a new home is a huge decision that can be approached analytically by looking at facts and other criteria and basing a decision on these factors. Before a person even begins to look at new home listings, he or she can make a list of criteria that matters the most. The person could put the most important details about the new home under a “needs” heading and the less important details under a “wants” heading.
In this example, a person with a family of four might need a home with at least three bedrooms, so this would be a “need.” Perhaps having a fenced-in yard is less important, so the individual would place this under “wants.” Next, the person conducts research based on the criteria set forth and narrows house options to several choices. Then, the individual tours potential houses and chooses one based on the original criteria. This is an example of analytics because the person made a choice based on needs and facts about the house rather than mere feelings.
On the other hand, people also can buy a home using a non-analytical approach. In this way, people might view new houses before determining what—if any—criteria they may have. In this way, they figure out what they want while seeing the homes and without conducting any research. This approach may lead to buyer’s remorse, or regret felt after making a purchase. If people examine data before making a decision, they are more likely to make a well-informed and sound decision and less likely to regret their choice.
This same approach can be applied to business decisions. For instance, marketing managers have specific budgets they must adhere to during a particular period. They try to use this money to get the best return on whatever they invest in. Doing so can be a difficult task with many questions, such as whether to spend money on acquiring new customers or spend it on new products to retain current customers. Marketing managers have to make decisions that will most effectively help the company.
An analytical approach would involve examining past data, such as older marketing campaigns, to determine what has worked previously. If data indicates that current customers are satisfied with current products, marketing managers may decide to earmark money toward attracting new customers rather than designing new products. They took an analytical approach and based their decision on data that has shown to provide good returns.
A non-analytical approach might include choosing what was done in the past, regardless of outcome, or making a decision based on feelings or guesses. Decisions that are not based on data generally do not provide the best returns and can lead to regrets, and in this case, lost revenue for the company. For that reason, it is generally best for businesses to make decisions using an analytical approach.
Bibliography
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