Over the years, in dealing with hundreds of analytics-based projects, I have honed my internal definition of the term business analytics, or BA. BA is a process that refers to the use of skill sets, technologies, applications and practices for continuous, iterative exploration and investigation of past business performance. It is used to gain insight and drive business planning. The BA process makes extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling, and fact-based management to drive decision-making.
Several disciplines make up the BA process: analytics, performance management, business intelligence and data management. Each one of these disciplines furthers the goals of BA and provides its own unique, important capabilities to the overall BA process.
Analytics is the use of modern data mining, pattern matching, data visualization and predictive modeling tools to produce analyses and algorithms that help businesses make better decisions. With regard to topics such as customer management, pricing, supply chain, logistics and workforce analysis, analytics helps companies answer questions such as: "Why is this happening?" "What if trends continue?" "What will happen next?" "What is the best outcome?" Thus, analytics can provide foresight to what events may have the most impact on the enterprise as a whole.
Performance management is an umbrella term that describes the methodologies, metrics, processes and analytical applications used to monitor and manage business performance. Examples include budgeting, planning and forecasting; profitability modeling and optimization, scorecard applications and financial reporting and consolidation. Performance management can also provide insight into the future and better understanding of current activities and events.
BI is the use of querying, reporting, online analytical processing and alerts that help answer event-based questions such as: "What happened?" "How many?" "How often did it happen?" "Where exactly is the problem?" "What actions are needed to resolve it?" BI is best for gaining insight into current activities and events, as well as understanding what has happened and how those events have affected the business.
Finally, data management is the development and execution of architectures, policies, practices and procedures designed to help properly manage the collection, quality, standardization, integration, aggregation and governance of data across the enterprise. Data management primarily involves looking backward and figuring out how to learn from the past to improve the present and future.
There are multiple drivers of investments in BA technologies. First, companies collect vast amounts of information about their business activities and customers via transactions generated through customer relationship management, enterprise resource planning and online systems, among others. However, this discrete information doesn't provide an integrated view across the enterprise. The problem of data is literally growing out of control, and the lack of a holistic view will begin to cripple many companies in the not-too-distant future.
Compliance needs also drive the push for better BA capabilities. BI applications, reporting and analytics tools are key enablers to support regulatory requirements. Costly as it may be, most companies have no choice but to implement these tools in order to adhere to compliance measures and to monitor and mitigate risk.
Finally, increased performance and competitive demands are intense drivers of improved BA capabilities. The need to remain competitive compels companies to invest in BA tools that improve insight into business and market information, which in turn can enable more informed and proactive decisions. Most companies have also implemented comprehensive performance management systems to deliver information to decision-makers to improve insight and outcomes.
How do BA capabilities meet these needs? They can shift the paradigm. Over the last couple of decades, companies have been investing heavily in ERP systems to streamline their processes. This has resulted in a significant increase in organized data; however, the focus has shifted from simply organizing data more efficiently toward analyzing information to improve performance. Business analytics can help companies move from answering the question, "What do I need to do?" to answering the more complex, nuanced question of "What do I need to know?"
This paradigm shift is the wave of the future. Most companies know what they need to do. To stay ahead of the competition in the future, companies will need to slice and dice their data in myriad, increasingly complex ways in order to understand what they need to know about their business to improve its performance. One way to gain this knowledge is to leverage BA to gain foresight as well as insight. I believe that companies that are best able to leverage BA capabilities will certainly gain a leg up on their competition and better position themselves to thrive in an uncertain future. We'll see, won't we?
Deloitte is not, by means of this article, rendering business, financial, investment, or other professional advice or services. This article is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business.
Jane Griffin is a Deloitte Consulting LLP partner. Griffin has designed and built business intelligence solutions and data warehouses for clients in numerous industries. You can follow Jane on Twitter at @janegriffin. She may be reached via e-mail at janegriffin@deloitte.com.
Be the first to comment on this post using the section below.