This article was contributed by Dr. Manoj Vanajakumari, Business Analaytics Associate Professor within CSB.
 
Unstructured data, which can take the form of text, numbers, or multimedia, often does not provide information that is useful for making important business decisions. Many organizations gather vast amounts of data, making them “data-rich.” For instance, Walmart collects a petabyte of unstructured data from a million customers every hour. However, collecting such volumes of data does not make these organizations “information-rich.” 
 
How can organizations transition such large volumes of unstructured data to actionable information in today’s highly competitive business environment? The answer lies in using Business Analytics tools and techniques. Many organizations utilize business analytics to make well-informed operational and strategic decisions.
 
Understanding Business Analytics and Its Key Areas

Business Analytics is a field of study that combines statistical techniques with information technology to help businesses make informed decisions from raw data. It has three core areas:
 
1. Descriptive Analytics: This area utilizes past data and, with the help of statistical tools and techniques, identifies trends of the past, such as sales trends, and draws inferences from them. 
 
2. Predictive Analytics: This area assumes that future outcomes will resemble past patterns. It forecasts future outcomes using techniques like machine learning algorithms. 
 
3. Prescriptive Analytics: Organizations use mathematical models to select the best course of action from various available options. For example, linear programming models, simulation, or algorithms are used to minimize the cost of truck routing for a package delivery company.
 
As businesses advance from descriptive to predictive to prescriptive analytics, the value gained and the challenges associated with implementation tend to increase.
 
Increasing Adoption of Business Analytics
 
Several success stories from the business world show that analytics enables organizations to gain data-driven insights, enhance efficiency and profitability, and respond proactively to market signals, thereby ultimately improving customer satisfaction and competitive advantage. 
 
Mckinsey and Company finds that analytics can improve the EBITDA by 15% to 25%. Walmart uses historical sales data, weather predictions, and consumer behavior trends to forecast demand. It has helped Walmart in inventory management. UPS’s ORION (On-Road Integrated Optimization and Navigation) is said to be the world’s largest prescriptive analytics project. ORION project has given UPS operational efficiency in terms of delivery cost, time, and other key operational metrics. After migrating and consolidating data in the cloud, business analysts at McKesson are now focusing on deriving real-time insights into business performance. This data migration to the cloud has also helped analysts focus on the next level of analytics using predictive and prescriptive techniques. The accelerated emergence of artificial intelligence has widened the scope and applications of Business Analytics, making it essential in today’s data-centric environment. 
 
 
Tools and Techniques
 
Business analysts use several tools and techniques to make informed decisions. The popular tools in Business Analytics are:
 
1. Spreadsheet Software (Excel, Google Sheets): Spreadsheets are widely accessible and easy to use for basic analytics tasks. Spreadsheets are suitable for startups and small businesses due to their low cost and minimal learning curve
2. Business Intelligence (BI) Tools (Tableau, Power BI): BI tools are used to create live interactive dashboards. They help users identify trends and anomalies and make informed, actionable decisions. These tools are ideal for medium to large businesses looking for real-time, user-friendly insights. 
3. Programming Languages (R, Python): While the off-shelf systems have limitations as they need to be customized to business processes or vice-versa, these programs help the organization to make fully home-grown analytics products or customize the off-shelf products. Programming expertise is required to use these tools.  
4. Data Platforms (SQL Server, Snowflake): Data platforms are used to manage and use structured data. They are used to retrieve and organize data stored in relational databases. 
5. Enterprise Analytics (SAS, CPLEX): These systems are used for data management, advanced analytics tasks, and reporting. 

Organizations utilize various techniques to analyze data effectively. For instance, they employ data visualization to convert raw data into graphs, charts, and dashboards, making it easier to understand the information hidden in the data. 
 
Statistical analyses help determine factors influencing sales and can be used to forecast demand. Additionally, organizations group customers based on similar characteristics, using techniques like clustering to create targeted marketing strategies for each segment. 
 
Optimization techniques are used to identify cost-effective delivery routes. Furthermore, analysts can use machine learning methods to detect fraudulent financial transactions.
 
Data-Driven Information Culture
 
Organizations should not find the adoption of Business Analytics overwhelming. Cost and technical expertise are generally considered to be barriers to adoption. Organizations can start by targeting easily implementable analytics solutions like inventory classification using basic tools like spreadsheets and enjoy significant returns. 
 
Further, investing in employee training or forming partnerships with academic institutions can help reduce these entry barriers. It is essential to foster a data-driven information culture within organizations, beginning at the top levels of management.
 
Business Analytics Programs at UNCW
 
Cameron School of Business at UNCW offers undergraduate and graduate programs in business analytics. The programs are housed in the Congdon School of Supply Chain, Business Analytics, and Information Systems. The students in the program learn the tools and techniques that equip them with the skills to transform data into information and help make strategic and operational business decisions. 
 
The capstone course in the master’s program is conducted in partnership with the Small Business and Technology Development Center (SBTDC) and Wilmington-based firms that provide data and problem statements to the students. This association benefits not only the students, who get valuable hands-on and real-world business analytics project experience, but also the organizations that benefit from Business Analytics solutions provided by the students. 
 
Business Analytics is accessible to everyone. For beginners, there is no need for expensive tools or a team of data analysts or scientists to start the journey from “data rich” to “information rich” world. Regardless of the business size, embracing analytics can bring success and give businesses a competitive advantage.