Analytics is the structured, analytical approach to the study of data that can reveal patterns and relationships. It is typically used for the identification, interpretation, and determination of relevant information. It also involves applying statistical methods towards effective decision making. Analytics falls under two main categories: Business Processes and Consumer Insights. The Business Processes sub-field of analytics studies and research in business processes and organizations; it studies and validates business process approaches, practices, and tools.
Analytics is a subset of data science. Data science is an umbrella term for a set of research techniques and methods that analyze large sets of unprocessed data. A data scientist may apply advanced statistical techniques to previously analyzed data, taking traditional methods and modifying them to fit the scientific model. Data science is a general field and each sub-field is responsible for formulating and testing their own proprietary methods. While most data scientists use some or all of these strategies, many more fall beneath these broad classifications.
Operations research refers to the area of optimizing specific operations within an organization. Operations research aims to improve quality and decrease costs. Analytics is vital for operations research and includes modeling, monitoring, and analyzing. Analytics provides tools to build better decisions about what resources to invest in and what tools to eliminate. By providing better decision making about resources and operations, analytics provides a competitive advantage. Data has become an essential part of business strategy, and analytics helps managers make better decisions about their organizations.
While some think of analytics as a tool for prediction, this is far from true. Analytics does not provide predictions; rather, business analytics provides methods for making better predictions. The analysis presented by business analytics provides insight into the past and present trends and data that allowed managers to make better decisions for the future. For example, business analytics provides statistics on customer satisfaction to predict whether a new product will meet the desires of customers. Business analytics provides data on product recall and customer loyalty to predict which commercials will be successful and which won’t.
Another way to compare analytical techniques is through cluster analysis and time series analysis. clusters are groups of points that can be compared using statistical methods. Time series analysis provides data on a common time period over time. Examples of time series data are: average gas prices over a three-month period; employment rate over a two-to-five-year period; and trends in the stock market over a one-year period. However, cluster analysis and time series analysis often require specialized software to analyze the information.
Businesses often turn to statistical methods of analytics and sometimes to a combination of analytics and statistical analysis. Data scientists create models and statistical methods to analyze large amounts of unstructured data. They then attempt to discover relationships between variables that are not considered individually. These relationships allow researchers to explore relationships among variables using a mathematical approach. Many advances in statistical analysis have come from the insights offered by data analysts. Researchers have used statistical methods and insights to predict patterns, discover relationships, reduce model complexity, and design better policies and procedures.
Analytics is not just for the big guns on Wall Street. If you want your company to go the distance and stay competitive, you need the insights and analysis of business intelligence analysts to help you make decisions. The best companies have a wide array of perspectives, each bringing something different to the table. In addition to using analytics to improve their bottom line, businesses must also use them to drive growth, streamline operations, cut costs, and reduce risk. Ultimately, if your company wants to succeed, it all starts with having the right managers, consultants, and analytics experts working side by side to achieve the mission.
In summary, four types of analytics are available to business managers today: descriptive, predictive, mixed, and quantitative. Each has its own strengths and limitations, but all of them can be applied in a variety of ways to improve business. Analytics should form the foundation for your analytics strategy and should be used to support and guide your other business intelligence analyses.