Utilizing Data Analytics to Assess Organizational Performance and Decision-Making

Abstract

[University] Instructor’s Name Due Date Introduction Data Is a powerful tool in any organization for decision-making, formulation of strategies, and organizational performance. The benefits of data are inexplainable by increasing competitive advantage, productivity and efficiency of a company, Customer satisfaction hence customer loyalty, increase in profit margins, and the creation of new products and services (Khadka & Maharjan, 2017). The company’s ability to learn how to effectively analyze data guarantees actionable insights on better decision-making, future predictions, and organization scrutiny. Data allows a company to identify trends and derive insights through business analytics. There are various data analytic software such as MS Excel, Google Charts, and many others that create visualizations of various data sets giving illumination of a company’s state of affairs. The use of algorithms and machine learning is also a viable criterion in gathering, sorting, and analysis of huge volumes of data that humans cannot perform. They are sources of data-driven decision-making credible for any company. This paper examines the importance of data in assessing organizational performance and performing decision analytics. Types of data in assessing Organizational Performance An example of data in an organization is financial data. Financial data is concerned with the financial well-being of an organization. Through financial analysis, a company can evaluate financial data to ascertain organizational performance. Corporate authorities and investors use financial statements to determine the company’s viability in business. For instance, corporations use internal financial data to examine organizational performance while investors use external data to check if the company is fit for investment. There are various metrics that provide various insights into the efficiency of the company. They include; profits, revenue, return on investment, earnings per share, and other key performance indicators. These data can be derived from income statements, balance sheets, annual reports, and cash flow statements all derived from the company’s financial earnings. The balance sheet is used to determine the operational efficiency of the company by assessing the assets, liabilities, and equity of the company. The income statements are used to ascertain the present and future predictions of the company’s profitability. Comparing the profits and revenues of the previous fiscal years deduces the trends in revenue and expenses, an important aspect of future profitability. Cashflows explain where money generated by the company is spent. For instance, a segment of an organization may be experiencing outflow than another hence calculating cash inflow and outflow is necessary for the viability of the company. Financial data helps justify an organization’s overall financial performance. The other source of data in an organization is a customer satisfaction data survey. Numbers are very important for an organization’s performance. Understanding consumer behavior and customer needs helps the company make informed decisions promoting customer loyalty. Information about customer loyalty can be calculated in numbers (quantitative data); it is measurable and convertible making it easier for organizations to conduct surveys. This can be achieved through Google Analytics by calculating the number of customers that return while shopping; a basic check on customer satisfaction. Collecting qualitative data is also a survey on customer satisfaction, where customers express their opinions and attitudes towards the service of the company. The Net Promoter Score (NPS), is a popular customer satisfaction metric that is used to gauge customer loyalty. The customer satisfaction data survey is used to justify consumer behavior which is essential for the performance of a company. Data Visualization Graphic Data visualization is an important way in data analysis to simplify data in an easy and efficient manner. For instance, an employee in an organization may want to show its top management critical information in certain months of a year that need assessment, however, the management will not understand the prevalent issues at hand and this can only be justified through visualization. Visualizations can be achieved through the use of charts, graphs, or color for easy understanding and reporting. The following is an example of a visualization graphic (bar graph) showing a 3-month company comparison of profit, expenses, and Revenue. Financial Data Analysis; Comparing Monthly Revenue and Profit Margin Y-axis- Revenue, Profit, and Expenses in dollars X-axis- Months Here are several other tools that perform data visualization and they include; Microsoft Power BI, MS Excel, Graphs, Tableau, and Charts. Analytical software enhances business software and propels an organization's operation and processes. A renowned company like Coca-Cola uses Tableau in its data visualization. Benefits of the data analysis methods Data analytics is essential in the marketing, human resource, professional, and product management of a company. Data analytic methods are essential to maximize the benefits of a company’s data; the two data analytic methods for this discussion include; Descriptive Analytics and Predictive Analytics. Descriptive Analytics These types of analytics answer the question ‘What happened?’. It analyzes and interprets historical data providing businesses a baseline to track their actions using past trends and information. This type of analytics finds meaning in data. Descriptive analytics provide information on inventory,...