Business Analytics: How it Helps Businesses in Decision Making Process

What is Business Analytics and how does it Help Businesses in their Decisions Making Process
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What is Business Analytics and how does it Help Businesses in their Decisions Making Process
In the digital age, organizations continue to generate vast amounts of data during their operations. Such data portrays the daily routine and offers information on different aspects of the business. As a result, analyzing such data provides an opportunity for such organizations to improve their processes, increase efficiency, reduce costs and monitor progress (Bag, 2016). Consequently, business analytics involves the use of professionals in evaluating and analyzing business data through statistical methods and available technology to gain insights. Changing technology thus offers businesses an opportunity to use analytics to improve their position on a globally competitive market.
The Concept of Business Analytics
Data collection and tracking has become an important aspect of business in the world today due to the advanced technologies such as artificial intelligence that allow the personalization of such data. In most cases, businesses with an online presence tend to interact with their clients through social media and advertisements. In this case, consumers clicking ion such links leave crucial data that may be collected by such companies. Such data on consumer trends can significantly improve the business operations if properly analyzed and used to make decisions (Gavan, 2019). Data ultimately plays an essential role in business since it provides evidence-based information. The use of numbers to provide models and predictions significantly outweighs any other forms of interpretation to provide a basis for future actions.
Being a scientific method, business analytics provide objectivity to organizations using available data in their field. Statistical designs used in the process can provide mathematical models that can accurately be used to make business decisions Therefore, different fields may utilize such information in different ways to achieve their goals. For instance, while some businesses may implement strategies to increase their profits, others may opt to use such information to improve workflows and efficiency. As a result, the uses of business analytics are wide and can be applied across different sectors to achieve better results. Ultimately, the aim of business analytics lies in providing personalized data and analysis to individual organizations.
Elements of Business Analytics
Data Mining
Data mining involves the sifting through large tracts of data to identify patterns and trends that may be not be visible through other means. The current digital world creates numerous data points that are useful for businesses searching for data insights.
Text Mining
In text mining, information is collected from a huge database of textual data available on the internet. In this case, data is collected from social media sites and any other communication channels that consumers may use to interact with the organization. From such data, information on consumer preferences, product reviews and performance may be extracted to inform decision making (Vigen et al., 2019).
Data Aggregation
Aggregation involves the collection and gathering of data into related groups that can be easily analyzed. This involves summarizing the data, centralizing it in a single format, cleaning to remove any duplicates and filtering to capture any inaccuracies. Accuracy plays an essential role at this stage since the ultimate decisions will rely on this data to create insights.
Forecasting
At this point of forecasting, the data is analyzed to find meaningful patterns that portray a future trend in the organization. Based on historical and current data, a business can further predict specific aspects such as sales that can be important in the overall strategic planning. The identification of triggers during specific periods or events can enable the business to tailor their services towards such occurrences to increase interactions and sales.
Data visualization
Data visualization forms an essential aspect of business analytics since it portrays the results of the analysis to the business. This displays the metrics and KPIs of the business in a simple an understandable mode that allows all employees in the organization to comprehend them. Data visualization can be done through the use of interactive graphs and charts that display the individual aspects analyzed (Bag, 2016).
Types of Business Analytics
Business analytics can occur in 4 distinct stages with each playing a specific role in the overall goal of the organization. These include descriptive analytics, diagnostic analytics, predictive analytics and prescriptive analytics. Firstly, descriptive analytics refers to the use of historical data in the company to analyze and assess the KPIs (Power et al., 2018). This enables the organization to keep track of past trends. For instance, this type of business analytics may use customer data to identify behaviors to enable targeted marketing that would ultimately increase sales.
Secondly, diagnostic analysis checks the past performance of the firm to identify factors that affect it. Understanding the trends that occurred leading up to a particular performance can enable the identification of specific problems that can be rectified to improve performance (Power et al., 2018). Repeating the same methods over years yielding the same results leads to wastage of resources hence diagnostic analysis searches for the root causes of problems to provide viable solutions. Therefore, diagnostic analysis provides businesses with the possible outcomes and likelihood of certain events to occur based on available data from the past.
Apart from that, predictive analytics assess the possibility of future outcomes through forecasting models. Forecasting plays an important role in gaining knowledge that would affect decision making for critical aspects of the business. For example, sales and marketing forecasts can enable the organization to set up budgets for these functions in line with predicted growth patterns.
Lastly, prescriptive analytics is used to recommend future remedies to prevent similar problems based on past data. This type of business analytics can be used to determine the best possible outcomes by putting in place a particular action plan (Power et al., 2018). For instance, based on consumer data, organizations can be able to match the various options that consumers may need in a particular product or service.
Implementation of Business Analytics in Organizations
With business analytics being a growing field, a number of companies are investing in systems to enable them use the available data in decision making. Furthermore, the increasing trend of business operations online shows the need for further investments in data management and analysis. Proper utilization of business analytics can ensure that the management can derive maximum benefits from interpretations, improve problem solving and gain new insights from the data (Gavan, 2019). Therefore, the implementation of business analytics depends on the organization to diligently put in place systems that can support its optimal usage.
Firstly, a business must identify its needs and products in full depth to ensure that a correct criterion can be developed from the onset. This means that the business should be able to document all relevant information including its basic requirements from which the analytics would produce valid results. Identifying the type of...