The overwhelming amounts of data organizations face today is not limited to what resides in their collective data centers; it also includes external and largely unstructured data found in e-mails, blogs, and more—much of it generated by third parties.

Turning that wealth of data into usable benchmarks for sound business decisions is a real challenge. Part of the problem is that many organizations are struggling to manage information that extends far beyond the structured data in their data centers. Despite major investments in business intelligence (BI) tools over the last decade, many organizations still make decisions in ad hoc ways and struggle to master analytics.

Rock-solid analytical foundations
So what does it take to develop and support a cohesive, concrete approach to analytics? Analytics done right isn’t only about using the most sophisticated software. It also means building very robust foundations in information management and business intelligence.

For some organizations, the ultimate goal is to have a true analytical enterprise—demonstrating the highest level of analytics capabilities. Accenture refers to this as the “analytics-enabled decision making” level—seen in high-performing organizations that have embraced an analytics mindset and can act on insights at scale. By taking the steps necessary to become more analytical, organizations can make substantial gains in efficiency and cost-effectiveness. A company that already has solid data-architecture underpinnings can often do more to shore up its analytics governance models in order to better manage data and content.

Excelling at managing information
Regardless of where organizations are on their analytics journeys, leading organizations ensure that they excel along two vectors: consolidating and streamlining their information “infrastructure”—the physical layer—and refining their logical views of the data. To begin with, they place a premium on sound data architecture in order to source, store and secure their data. They also are good at factoring in the aggregation of data through the services that buy and bundle data from all kinds of data providers.

Whereas traditional databases are designed to keep track of where the data is stored and how it can and should be accessed, data platforms will provide a layer of abstraction that hides the data’s location, and is not concerned with the form in which the data is stored or how its consistency is maintained. So in effect, the data representation architecture will be decoupled from the application.

Establishing optimum BI practice
The rising tide of capable BI tools has lifted all organizational boats—meaning that core BI capabilities are rapidly becoming commoditized. Although BI software has indeed helped improve the generation of data-rich reports, it is debatable whether those reports have done much to improve decision making.

To some extent, such reports may be of use only to a handful of users for a specific project or a finite period of time. The new frontier for productivity is found in mobile BI. Reflecting the reality of globally dispersed and more mobile management teams, mobile BI can significantly enhance the availability and usability of data.

Today, executives must be able to turn information into insights, then convert insights into actions, and be sure those actions produce positive outcomes. To make sure they have everything needed to make more of the right decisions at the right time, it’s time for all organizations to identify where they are on their analytics journeys.

Please download our thought leadership paper for more information on Excelling at Analytics: http://www.accenture.com/us-en/Pages/insight-decisions-outcomes-analytics.aspx