How Does Business Analytics Provide a Competitive Edge?

Gary Cokins' takes a look at how business analytics is narrowing the margins of error


Business analytics is becoming a competitive edge for organizations. Once being a “nice-to-have”, applying business analytics, especially its subset predictive business analytics, is now becoming mission-critical. The use of business analytics is a skill that is gaining mainstream value due to the increasingly thinner margin for decision error. There is a requirement to gain insights, foresight and inferences from the treasure chest of raw transactional data (both internal and external) that many organizations now store (and will continue to store) in a digital format.

Business intelligence versus business analytics and decisions

Here is a useful way to differentiate business intelligence (BI) from business analytics and decisions. Analytics simplify data to amplify its value. The power of analytics is to turn huge volumes of data into a much smaller amount of information and insight. BI mainly summarizes historical data typically in table reports and graphs as a means for queries and drill downs. But reports do not simplify data nor amplify its value. They simply package up the data so it can be consumed.

In contrast to BI, decisions provide context for what to analyze. Work backwards with the end decision in mind. Identify the decisions that matter most to your organization and model what leads to making those decisions. By understanding the type of decision needed, then the type of analysis and its required source data can be defined.

To clarify, BI consumes stored information. Analytics produces new information. Predictive business analytics leverages data within an organizational function focused on analytics and possessing the mandate, skills, and competencies to drive better, faster, decisions and achieve targeted performance.

Queries using BI tools simply answer basic questions. Business analytics creates questions. Further, analytics then stimulate more questions, more complex questions, and more interesting questions. More importantly, business analytics also has the power to answer the questions. Finally predictive business analytics can display the probability of outcomes based on the assumptions of variables.

The application of analytics was once the domain of “quants” and statistical geeks developing models in their cubicles. However, today it is becoming widely adopted for organizations with the conviction that senior executives will realize and utilize its potential value.

An imperative to apply business analytics

Today many businesspeople do not really know what predictive modeling, forecasting, design of experiments or mathematical optimization mean or do. However, over the next ten years the use of these powerful techniques will become standard. This is no different from applying financial analysis and computers for businesses that want to thrive and survive in a highly competitive and regulated marketplace. Executives, managers and employee teams who do not understand, interpret and leverage these assets will be challenged to survive.

In my co-authored book with Larry Maisel, Predictive Business Analytics, this topic is addressed with case studies, core principles, and inspiration.

Case studies, including some in this book, demonstrate that for a company to use predictive business analytics effectively it must commit to a sustained and rigorous process in order to achieve meaningful results. This includes the ability to establish a team of individuals with complementary skills and competencies; a repeatable set of practices, functional data and tools; and a management process to review its results and forge its decision making by leveraging these results and insights. Together, these are used to continuously analyze the right business and cost drivers and measures that have strong cause-and-effect relationships to gain insight to better manage the business and to improve decision making.

One can make the case that increasingly the primary source of attaining a competitive advantage will be an organization’s competence in mastering all flavors of analyt ics. If your management team is analytics-impaired, then your organization is at risk. Predictive business analytics is arguably the next wave for organizations to successfully compete. This will result not only from being able to predict outcomes but also to reach higher to optimize the use of their resources, assets and trading partners. It may be that the ultimate sustainable business strategy is to foster analytical competency and eventually mastery of analytics among an organization’s work force. 


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