The trusted information payoff: productivity, performance, and profits.

• Author: Sidi, Karim N.

Building an information framework to ensure effective data management produces information that is true, has integrity, and can be trusted. This leads to a continuous improvement culture that can increase employee productivity, improve operational performance, and grow profitability.

Large organizations, especially those that have grown through consolidation, mergers, and acquisitions, are often fraught with incompatible systems and data sources that are costly and difficult to manage. The systems usually do not avail efficient extraction, aggregation, and sharing of data within or across the boundaries of the business process.

To address this problem, organizations can turn to an information management framework that facilitates managing raw data to create useful information that can be shared across the organization.

The IM Framework

An effective IM framework treats data as an asset, applying the same methodologies as for any other intellectual asset. As shown in Figure 1, the IM framework needs to address the following elements of data:

* Truth--It must maintain the consistency of meaning and common understanding throughout the organization. In data management, this is about ensuring through business processes and IT applications that the data element's meaning, consistency, and understanding do not change even though its format and storage topology may change to standardize and centralize the access.

* Integrity--The IM framework must enforce the truth through standards and governance.

* Trust--Trust is about consistency, reliability, and quality, which result from defined rules for standardization that are enforced through active governance.

* Evolution--The IM framework must have a process of continuous improvement to increase the value of the information. These elements are described further below.

Truth: Data Standards Required

The holy graft of data management is to identify the single version of the truth. This could be defined as it was in the 2008 Oracle Thought Leadership White Paper "The Myth of One Version of Truth" as "a single set of reports and definitions for all business terms, a way, in short, to make sure every manager has a common understanding of accurate corporate information."

It is a great challenge for distributed systems in an IT architecture to find a common meaning and data type definition for common data elements. For example, as John Schmidt wrote in the June 12, 2012, Informatica blog "Perspectives," "Multiple versions of the truth are often a result of the same information being captured and stored in slightly different ways by different systems."

Because data type definitions determine how a database stores information, there will be problems if the date on one application is defined as an integer (e.g., 20130414) while on another application it is defined as a string of...