Big Data

Report Analytics: Complementing Business Intelligence for Data-Driven Business Decisions

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With the explosion of available data at an organization’s disposal, and despite the overwhelming offerings available to harness these assets, companies of all sizes continue to grapple with capturing and presenting the information they need in an engaging and understandable format. In an effort to make more informed business decisions, many departments and individual line-of-business users have turned to Business Intelligence (BI) solutions as a way to mine data for both reporting and forecasting purposes and to address increasing business issues.

Unfortunately, BI alone is not always the answer. Failure rates hover between 50-70 percent according to some studies, and business users continually look for new tools to help them easily get at the data they need.

It’s well known that BI software can provide advanced reporting and predictive analysis. But for many day-to-day reporting tasks, its sophisticated functionality is overly complex. For tasks like these, business users and self-service “data consumers” may find the technical challenges of BI a deterrent; as a result, they often rely on the IT department to generate custom reports. This not only creates more work for an already over-taxed IT group but also introduces delays and frustration for the users who require accurate and timely information in order to perform their job effectively.

The underlying issue is that business users often have all the information they need – but that information resides in existing reports and business documents scattered throughout the organization. Since they have no easy way to dynamically organize, integrate and analyze the intelligence trapped in these static documents, they are often left with less than ideal options.

For instance, business users can rely on predefined BI reports from a data warehouse or enlist the expertise of the IT department to program custom reports.

According to a recent Computing poll of more than 250 people who use or rely on data derived from BI reporting software, BI complexity is an ongoing problem (see Is Business Intelligence software always the right tool for the job?). Cost was cited as the most important factor in the BI software selection process (29 percent) followed closely by ease of use (25 percent).

The fact that cost and ease of use are the most important drivers of software selection underscores the challenges that complex BI solutions present to the people who consume the intelligence for making data-based decisions. These challenges are driving the emergence of a new category of solutions within the BI market, which industry analysts refer to as Report Analytics.

From ERP-generated reports to even mainframe reports, organizations of nearly all sizes generate thousands of reports monthly. But those reports are largely unusable without investing time and money into burdensome processes. Report Analytics software leverages an organization’s existing reports and reporting processes and provides consumers with a self-service environment. This allows them to extract the relevant intelligence from any combination of these existing documents themselves and transform that information into dynamic, interactive reports for easy analysis and visualization.

Whether the reports or business documents originate inside an enterprise or from external sources like customers or suppliers, Report Analytics allows business users to create, distribute and publish these reports without time delays or involving IT. And let’s face it: with increasing cost pressures and decreasing revenues, anything that bolsters productivity is critical in today’s real-time business environment.

Harnessing business assets

In most organizations, the volume of data is enormous, creating a challenge that lies not in amassing more data, but rather in integrating and using the meaningful data that already exists. Let’s face it: data exists in various static reports, transaction systems, data stores, and formats, which forces professionals to spend valuable time aggregating information from various sources. And that’s not all. Once they have access, they still need to manipulate the data in familiar programs like Excel in order to present the information in the right format and the right people instead of focusing on the more value-added activity of analyzing and acting on the data itself.

This creates an issue for many businesses according to a recent Ventana Research study, which found that “leveraging reports from BI systems is important to 57 percent of organizations, and getting to the data from source ERP, CRM and other applications is important to 71 percent of respondents” (see “Spreadsheets Undermine Governance, Risk Management and Compliance”).

To complicate matters, existing reports and business documents come from a variety of sources: internal transaction systems that generate “canned” ERP, HR or CRM reports, external customer or supplier systems and personal productivity tools such as Excel or BI systems. And these reports come in multiple formats: mainframe green bar, text, ASCII, PDF, HTML, spreadsheet, log files and semi-structured documents that are stored in content-management systems. All of these sources and formats of existing reports create a major challenge for business users that need to make timely, informed business decisions based on available data.

Making data meaningful

Today, the enormous amount of data has made it difficult to parse and analyze it, which means that the resulting reports are sub-optimal at best. The format of the report also comes with its own set of unique problems. ERP, HR and CRM systems deliver static reports, oftentimes in text or PDF format, which are inflexible and cannot be integrated with data from other reports. This does little to foster understanding, analysis or decision making and often does not include the unstructured, semi-structured or externally sourced data that is required to make information meaningful.

As a result, most organizations spend a great deal of money and time consolidating and mapping this data into a data warehouse, data mart or other operational data store. Or worse, an organization simply abandons the idea of leveraging that data and operates by intuition rather than hard data.

Report Analytics began to take root as a way to address this longstanding business challenge. Report Analytics tools model, aggregate and transform information from any number of existing reports and business documents throughout the organization, making it easy for users to access, extract and analyze data without having to invest in new reporting solutions.

Functioning as the “missing link” in the broader BI reporting arena, Report Analytics captures structured and semi‐structured data from virtually any existing document. It also enables faster and deeper visibility into the business and better, more informed business decisions.

Report Analytics and BI – not an either/or proposition

For many, Report Analytics sounds like it overlaps with business analytics or business intelligence. In all actuality they are complementary; yet key differences between the two exist. For instance, in BI deployments a few staff members, largely from IT, are charged with managing the data and creating both content and reports for business users. So while BI systems are an invaluable asset for many – allowing them to discern patterns in customer behavior and align the business behind a common goal – it may not always be the best, or only, tool for generating reports.

Of the IT staff questioned in the Computing study, 31 percent said their department was required to produce up to 100 reports a month while 16 percent generated up to 500. Even worse, four percent estimated that they were required to produce more than 1,000 reports every month. The time that IT staff spent on producing these reports varied, with half taking a day or more and 10 percent estimating an average time of weeks or months.

With such a limited group responsible for developing reports for the entire organization, backlogs undoubtedly will occur. In other words, it requires a lot of IT support to make information usable.

And, often, while IT is off programming the custom reports, the business requirements change – meaning the data that consumers receive in their custom report is once again incapable of helping them solve their particular business problem.This leads data consumers to the ever-popular BI “workaround” – Excel. All too often, business users dump the data they need into Excel, import additional information from transactional systems or other sources that are not in the data warehouse, and then perform analytics from there.

This cumbersome manual process, while painful, is necessary as there is often little analytic value otherwise because of the missing and incomplete data. And while it solves the business user’s immediate need – getting the data they need to answer specific questions – it is fraught with peril.

On a tactical level, moving data from a trusted system to the unsecure environment of Excel also introduces the possibility of compromising data accuracy due to simple human error. On a much more strategic level, this process completely undermines the integrity of the data. Once data is put into Excel, the business user is violating most data governance policies. The data is no longer trusted.

The Computing study demonstrated just how pervasive this problem can be. According to the financial decision makers questioned, 52 percent felt that less than half of the information needed to run the business effectively could be pulled from existing documents and in the correct format without having to rely on IT.

The fact that users struggle to get a grip with BI software is perhaps reinforced by the fact that for two out of three of those polled, it is not the more tech-savvy members of the IT department who are using it. More than half (54 percent) said responsibility for producing BI reports was with individual business departments such as finance and sales. Worse, only 11 percent of these individual executives or business managers said they run reports themselves – meaning they had to submit a request to the IT department to perform these tasks on their behalf.

Report Analytics is a smart approach in today’s economy. It is an easy self-service solution that enables business users and data consumers to get the data they need out of existing reports. Not only does this approach leverage an organization’s significant investments in enterprise applications, but it also avoids the costly route of creating a data warehouse, or worse – programming one’s way to an acceptable solution.

Michael Morrison is President and Chief Executive Officer at Datawatch Corporation, a provider of report analytics products and services. For more information contact Michael at Michael_Morrison@Datawatch.com or visit www.datawatch.com.

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