Why enterprise information management is a key to analytics success

Why enterprise information management is a key to analytics success

Why enterprise information management is a key to analytics success
As the velocity of data increases—and the demand for and consumption of that data intensifies—many organizations find themselves struggling to manage all of that data effectively.

Increasingly, organizations find themselves unable to keep pace with volume, velocity and variety of all of this data. As a result, many organizations have created data coping mechanisms to try to keep up, but in the end, they just fall further behind.

In this article, we’ll examine how organizations can right the information ship, putting themselves, their employees and their customers on a course to information management excellence.

Several of these common reactions to the swell of data can be found in most organizations.

The creation of silos of data analysis. This is often a first step: Frustrated with the lack of responsiveness from IT, business users start to set up their own mini data infrastructures based on whatever data sources or extracts they can get their hands on and start building some of their own reports.

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Shadow IT. Still frustrated by the slow reaction time from IT and confronted with urgent customer needs, business divisions take IT control into their own hands and independently hire the required technical skills to get the job done. They often grow into shadow IT groups with dozens of people in informal organizational structures. This often results in shorter tenures of IT staff, because they do not see any long-term career opportunities in the dysfunctional business and its relationship.

Duplication. As the amount of data silos grows, a significant duplication of both data and analysis starts to occur across the organization. Duplicated data starts to get out of sync with source systems and repositories because of changes, enhancements, modernization efforts or deprecation. This results in manifold increases in the total cost to the enterprise for maintaining the same underlying information across several data assets.

Fractured or no data governance. As this is occurring, any pre-existing data governance starts to break down, and business users start to question what reports to trust, which one is up to date or who has implemented the correct calculation.

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There is little doubt that when business divisions take matters into their own hands, it can reduce time to value. However, doing so creates a new set of operational challenges that adds to an already long list of problems to be solved.

The way to facilitate solving this problem of uncontrolled data, while minimizing the creation of new problems, begins with an overriding philosophical approach to information as follows. Organizations that democratize generations of information and business intelligence have a major advantage over organizations where IT—or any other single group—has a monopoly over the creation and dissemination of information. Rather, IT should have a supporting role in information development and certainly not a monopoly.

This is a fundamental shift in thinking for most organizations. However, the concept of Enterprise Information Management (EIM) can provide a framework that can oversee and govern the use of information development and dissemination across the organization.

According to Gartner, EIM is an integrative discipline for structuring, describing and governing information assets across organizational and technological boundaries to improve efficiency, promote transparency and enable business insight.

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Before EIM implementation can start, it is important to gain cross-functional organizational support from senior management. It is best to adopt EIM as early as possible as a supportive measure to facilitate bringing data close the business, and at the same time as a preventive measure to keep the possible issues highlighted above, from becoming bigger problems.

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