Business Intelligence and Business Analytics

Business Analytics tools help organizations to automate the decision making and to optimize business processes. They are crucial tools for companies in leveraging data for competitive advantage. BA is generally used for exploring data to find new patterns and relationships (data mining), statistical and quantitative analysis, experimenting previous decisions, and forecasting future results (predictive modeling, predictive analytics).

Business intelligence and business analytics terms are often used interchangeably but there are some major differences. BI usually provides information through querying, reporting, online analytical processing (OLAP) or other straightforward analysis tools. On the other hand, BA is more focused on statistical and quantitative data for explanatory and predictive modeling. According to Steve Cranford, a managing director and practice leader at PricewaterhouseCoopers, BI typically involves the mechanics of turning data into information and then using dashboards and scorecards to disseminate it. BA, in contrast, centers on solutions-oriented capabilities that create value and transform information into knowledge.

Hallmark is one of the companies that successfully deployed BI and BA initiative to better understand buying patterns at more than 3,000 Hallmark Gold Crown stores across the United States. In order to foster its relationship with its frequent buyers and to determine effective marketing methods to serve different consumer segments during holidays and special occasions, company used predictive modeling. By simplifying and improving analytics process, Hallmark has managed to increase sales.

As more companies try to capture the benefits of BI and BA tools in guiding decisions and strategies for areas in marketing, credit, R&D, customer care, and inventory management, they also discover the challenges in navigating these tools effectively. BI and BA generally require strong infrastructures, effective data collection tools, and well-designed software for mining and analytics.

One of the challenges often disrupt the effective deployments of these tools is