Features
Feature
Extend
Your Reach
A decision framework is crucial to expanding BI benefits.
by Colin White
Organizations have been building and deploying business intelligence (BI) solutions for years, and at first sight it would appear that this marketplace is mature. Further investigation, however, reveals that although the use of BI for strategic and tactical decision making has matured, many enterprises are looking to leverage existing investments by expanding their scope and reach to address a broader range of business problems and a wider user audience.
This growth frequently entails evolving information technologies that are far from mature. Enlarging the scope and reach of BI effectively requires a decision framework that shows how to incorporate new technologies into an existing BI environment.
Broader Application Scope
One important area where enterprises are looking to advance the scope of BI is enabling the organization to be more responsive to the constantly changing business climate. The solution is operational BI, which involves the use of business analytics to support intra-day and, in some cases, near real-time decision making.
Operational BI reduces latency—the time it takes to gather and analyze operational data and to deliver analytics to business users. This can be done by updating and analyzing data warehouse information more frequently, but in situations where near real-time decisions are required (fraud detection, for example), events may need to be analyzed as they flow through enterprise systems. Most organizations are likely to employ a combination of these data-warehouse-driven (data analytics) and event-driven (event analytics) approaches.
To improve the return on investment (ROI) of BI solutions, companies must improve not only the application scope of BI but also its user reach.
Organizations are also extending the scope of BI by gathering data from a wider range of sources and by producing richer analytics. Many are capturing unstructured information, such as Web and social media data, and converting it for use in a data warehouse. In other cases, content analytics is being developed directly from the unstructured data.
Richer analytics can be created using sophisticated mining models and predictive data models. These enable corporate leadership to react to business needs and problems before rather than after they occur.
Efforts to enlarge the scope of BI often lead to the need to manage and analyze large data volumes. Good scalability and price/performance are important considerations when it comes to supporting big data and big analytics. Technology areas of interest include data management appliances, cloud computing and software as a service (SaaS), and in-database processing where the analytical processing is performed in parallel by the database engine.
Greater Business User Reach
While the main application of BI, at present, is for strategic and tactical decision making, even in this context, user access is often restricted. Typically, it’s limited to power users, such as business analysts, who have the expertise to employ sophisticated BI tools and understand the data and analytics handled by these tools. To improve the return on investment (ROI) of BI solutions, companies must improve not only the application scope of BI but also its user reach.
Vendors and IT groups often conclude that growing the audience for BI simply involves making the technology easier to operate. While improvements such as connections to office products and rich Web interfaces help, they are insufficient by themselves to have a dramatic impact on growing the user audience. Instead, more emphasis is needed on making the information produced by BI tools more easily consumable.
Vendors have progressed in making information more easily leveraged by adding features such as business glossaries, data lineage tracking, BI search and basic collaboration capabilities. They have also made BI more actionable through performance management features such as scorecards and alerts.
Perhaps the area that offers the greatest potential for making information more easily consumable is advanced collaboration capabilities such as faceted search, blogging, tagging, feedback features (ratings, surveys, annotations, etc.), information usage tracking, decision workflows based on best practices, and communities of interest. These collaborative capabilities allow more experienced business users to take advantage of their expertise and opinions to enhance the value and knowledge content of business analytics and associated decision-making information. This added value makes the information more functional for less-experienced users.
Connect the Pieces
It’s clear then that expanding the scope and reach of BI can involve many new components and technologies, and it’s important that enterprises build a flexible decision-making framework that can incorporate these techniques. (See figure.)
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With the traditional BI and data warehousing environment at its center, the decision framework enables events to be analyzed by embedding BI processing in operational applications or by storing raw or filtered events in a data warehouse. At the same time, unstructured business content can be analyzed in place or stored and converted in the data warehouse. Analytics is delivered to the collaborative environment where it can be shared and enhanced by business users.
The traditional environment addresses only a small fraction of the applications and user audience that could exploit the business value of BI. New and evolving technologies allow organizations to increase both the scope and reach of BI and leverage their investments in this area. The key to success is a decision framework that allows these technologies to be incorporated into the existing BI environment in a cohesive, but flexible, fashion.
Colin White is the founder and president of BI Research.