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Business analytics: helping you put an informed foot forward

Most companies today have plenty of data. Creating intelligence and gleaning real insight from this data is what continues to elude organizations. Despite years of talk about scorecards and metrics, gut feelings and experience are often still the guides for making important, sometimes critical decisions, even though current research reveals a clear link between business performance and the use of business analytics.

So what exactly is business analytics and how can it help? Business analytics is, simply put, the application of analytical techniques to resolve business issues. It provides organizations with a framework for decision making, helping organizations solve complex business problems, improve performance, drive sustainable growth through innovation, anticipate and plan for change while managing and balancing risk.

It sounds like a lot, but if you break it down it’s all about enabling effective decision making. Organizations make decisions every day, and these sit on a continuum from frequent, up to millions per day to transformative, which occur less frequently but greatly impact organizational strategy. The need for agile decision making has never been greater but unfortunately, IT infrastructure, people and processes are lagging behind.

Why BI is not enough

Business intelligence provides historical, metric-driven decision making – and answers questions like, how many units did we sell, what did customers buy and for how much? BI is characterized by the creation of simple rules and alerts and the distribution of known facts to systems and people. These decisions have a low transformational impact on the business.

BI is still a highly valuable part of your overall business analytics environment, however, offering an excellent general purpose backbone for ad hoc analysis and basic operational reporting.

For example, BI can alert management on how many credit card transactions were completed on a given day. It can also develop a simple rule for automatic reporting, like reporting on transactions greater than $10,000 to the regulators.

From a more strategic decision perspective, business analytics can help answer questions such as what new products should we offer and in what markets? Or relative to the example, which credit card transactions are likely to be fraudulent? Business analytics can predict this with certainty and automatically deny transactions – while reporting activities in real time.

Business analytics allows organizations to “face forward,” bringing insight to transformative decisions. It benefits all aspects of an organization’s value chain, including:

  • Inbound logistics: receiving, storing, inventory control and transportation scheduling.
  • Operations: including factors such as packaging, equipment maintenance, testing and all activities that add value from the raw material to final product.
  • Outbound logistics: the activities required to get the finished products to market, including warehousing and distribution management.
  • Marketing and sales: activities that lead a buyer to purchase the product, including channel selection, advertising, promotion, selling, pricing, retail management and shelf space optimization.
  • Service: activities that maintain a product’s value, including customer support, repairs, installation, training, spare parts management and more.

In this way, business analytics drives innovation and improves an organization’s speed of response to market and environmental changes. In the credit card scenario, business analytics can not only discover the causal factors of fraud, but also forecast accurately when it will occur again. The company can then change business processes accordingly.

A step toward business analytics

Effective decision making requires a business analytics framework that incorporates the people, processes, technology and culture of an organization. This common framework provides flexibility across the entire range of analytical decision-making types from highly managed operational analytics (such as a setting a simple credit limit) to discovery-based analytics (such as credit fraud scenarios or setting dynamic credit limits).

A business analytics framework is not a monolithic and costly approach, but rather provides for incremental growth to achieve strategic goals at any given stage of an organization’s value chain. It offers business-ready analytical applications with underlying technologies for key services like data management and quality, reporting and advanced analytics.

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