Analytics is a general term that refers to the systematic statistical analysis of quantitative information. It’s used for the discovery, identification, and communication of useful patterns in numerical data. It also involves applying statistical methods towards effective, efficient decision-making. These methods may involve any one of the following techniques:
Data science, a branch of mathematics, has developed many methods to analyze data. Among these methods are optimization, fuzzy logic, greedy finite agents, neural networks, decision trees, decision logic, decision calculus, decision sciences, etc. Analytics combine the best of these techniques to provide insightful insights into the underlying mathematical structure of the data. This allows the analysts to provide better solutions to business problems by identifying the required actions to take.
Many business leaders believe that a successful analytics strategy should be based on relevant data and mathematical formulations. However, business owners often face a perplexing situation when faced with challenges in implementing analytics strategies because of insufficient knowledge or time to devote to the task. Some business leaders see analytics as an impediment to achieving organizational objectives, while others view it as a supportive tool to optimize business performance. A key question therefore is whether business leaders can apply analytics effectively to enhance business performance and address business issues.
In an effort to assess the effectiveness of business analytics strategies, four key factors need to be taken into consideration. First, the type of analytical problem to be solved must be identified. This includes e.g., demand-side and supply-side analysis. Next, the type of analytical methodologies used must be selected to match the nature of the problem to maximize the potential of analytical insights. These include traditional problem-solving approaches, such as cost management, operational economics, marketing, customer service, etc; new approaches, such as social, technological, financial, geographical and analytical approaches; and hybrid approaches, such as social and non-profit perspectives.
Market decisions cannot be made without the collaboration of various stakeholders. Therefore, the decision maker must decide how to integrate tactical and strategic decisions together to achieve overall business objective. Without proper analytics, it is difficult to determine where strategic decisions should begin and end and how to align the necessary actions to achieve desired results. Marketing analytics provides the necessary information to allow decision makers to make correct decisions without unnecessarily impeding organizational objectives.
Another way to use analytics to boost business performance is by properly evaluating and improving current processes. Proper analytics solutions help businesses improve process improvement by providing detailed information about processes, users, roles and interactions. Such information can be used to create processes improvement plans, identify recommended practices, design improved processes, evaluate data needs and determine resources needed to implement new processes. Moreover, companies may also use these solutions to implement changes that eliminate wasted time and money, as well as help to reduce employee turnover and improve productivity.
Another practical application of people analytics tools is in the HR context. Many HR managers and HR professionals have limited understanding about the processes that drive the HR business. This limited insight creates problems for HR managers when it comes to implementing solutions and making better decisions about talent acquisition, management and succession planning. As a result, many companies and organizations have turned to outside people analytics solutions to better understand their employees’ preferences and behaviors and to build loyalty and engagement.
In summary, data analytics provides business information that can be used to make better informed decisions. It can provide insights into both strategic and tactical decisions and help to build business strategies by providing descriptive and predictive models. Companies may use predictive and descriptive models in different areas including customer and enterprise applications, sales and marketing, supply chain management and human resources. Data analysis is now an integral part of business decision making and contributes to improving performance.