LESSON - New Enterprise Information Management Requirements Demand Better Solutions
By Dennis McLaughlin, VP of Sales, iWay Software
and JT Taylor, CTO, iWay Software
Enterprise information management (EIM) has emerged as an effective way for companies to better control and leverage the explosive volumes of information they generate and maintain. When an organization plans and executes an EIM strategy properly, it can significantly enhance the value of its corporate data, creating a “single version of the truth” for all who access and utilize information, company wide.
However, many organizations embarking on an EIM initiative have a narrow view of what it really is and often have selected and deployed solutions that address only one piece of the puzzle. Their plans—and the technologies they have acquired to support them—have gaps that make the achievement of true, enterprise-scale information management an elusive goal.
Every Piece of Information Counts
Many companies build data warehouses and marts to serve as the foundation of their EIM strategies—but do little else to facilitate the efficient creation, maintenance, and use of corporate data. This approach has been proven ineffective because these sources have been populated with only historical data from back-end systems.
What the approach ignores is the critical data that constantly flows across various points during the course of business activities (e.g., information generated during automated workflow execution or consolidated data available for decision support). It also fails to consider the data that enters and moves throughout the business via electronic means, such as EDI and other business-to-business (B2B) transactions.
Additionally, EIM must not only address structured information stored in databases, transactional systems, marts, and warehouses, but also information contained in spreadsheets, EDI documents such as sales orders, and other semi-structured data. In order for EIM to have maximum impact, all data must be managed from end to end, regardless of its point of origin, source, format, or location.
Quality Management Must Be Proactive
Any EIM strategy that focuses solely on the collection, consolidation, and centralization of data will be only partially successful and deliver moderate returns at best. Data must be more than just accessible. It must be consistent, accurate, and relevant—requirements have become increasingly urgent as reporting and information disclosure guidelines continue to grow more rigid. Companies must also guarantee that corporate data is always correct, complete, and most important, auditable.
But as information passes through a larger number of touch points (e.g., as it moves among more systems or more people interact with it daily), optimum integrity and consistency become much harder to achieve and maintain.
What many companies don’t realize is that once corrupted, outdated, or invalid information enters their environment, the potential damage may have already been done. For example, bad information may have been used to make a critical business decision. It may have resulted in a missed opportunity, or even worse, it may have been shared with regulatory agencies, hindering compliance and putting the company in jeopardy of receiving fines or penalties.
Data must be managed proactively, not reactively. This means bad data must be identified and corrected before it finds its way into an infrastructure.
Additionally, the majority of data quality solutions are applied only to the information contained within warehouses and other sources designed for end-user access and decision-making support. But information contained in back-end systems also plays a crucial role in core business operations. Therefore, data quality must be managed at the point of origin—not just the point of access.
“Real Time” Is Critical
Many people associate data warehouses and marts with historical information. While this may work for some needs, there are many scenarios in which information needs to be managed in a true real-time fashion. For example, information derived from certain B2B transactions, such as sales orders, may need to be dynamically pushed to suppliers or pulled by production automation systems the moment transmission takes place.
Since information contained in warehouses is rarely this current, the additional burden is placed on back-end systems, negatively impacting their performance. However, when an EIM strategy supports real-time information capture and handling, data is instantly available to facilitate core operations, and the strain on back-end databases and data warehouses is eased, freeing them up for their primary purposes—transaction processing and decision support, respectively.
What You Need in an EIM Framework
Because traditional EIM requirements are changing drastically, the solutions employed to satisfy them must be improved and more comprehensive. To address these new needs, today’s EIM suites must provide such advanced functionality as: Unlimited Information Access
Companies own countless types of information assets, including packaged applications, databases, files and documents, electronic messages such as SWIFT and HIPAA, and automated transactions. An EIM framework can only deliver significant results if it can handle all the types of data that exist across a business, regardless of who generated the data, where it’s stored, or whether or not it’s in a standardized format. Support for Multiple Levels of Information Latency
A world-class EIM suite will be highly flexible, allowing companies to manage all data and its quality via a variety of methods: online as users are generating it or interacting with it, in real time as it is created during automated processes, or in batch as it is pushed or pulled across various sources at timed intervals. Proactive Data Quality Management
A variety of data quality techniques, such as profiling, automatic cleansing, and dynamic merging and matching must be utilized to not only locate and remove bad data from the environment, but also to prevent it from entering in the first place. Only this kind of truly proactive quality management will ensure optimum integrity of enterprise information.
Additionally, an EIM framework should provide the ability to enrich and enhance information. For example, it should allow for the extension of existing corporate data with additional relevant information derived from third-party sources. Master Data Management
An EIM suite must enable the creation of a single system of record—whether it’s a central physical master data instance or a “virtual” repository—that can feed complete, consistent, and correct data back to applications across the company. This is particularly important in certain key functions, such as customer relationship management, financial management, or inventory management, where numerous disparate systems, maintained by different departments, may contain multiple versions of the truth that can negatively impact related business operations. Flexibility and Reusability
EIM is a dynamic concept and its requirements continue to change drastically. What EIM means today will likely be radically different from the EIM of the future. Therefore, any EIM suite implemented to support current needs must be powerful and agile enough to address new needs as they emerge. Additionally, an EIM suite that is built on reusable components will deliver the greatest current value and maximize long-term return on investment.
In order to achieve EIM success, the strategy—and the technologies that support it—must account for all types of information, all levels of data latency, and all middleware paradigms. Additionally, to effectively create, administer, and use information on an enterprise scale, both data quality and master data must be thoroughly managed from end to end. Only by addressing these needs will an organization realize true information consistency, accuracy, and accessibility across their entire business.
For a free white paper on this topic, click here and choose the title “Enterprise Information Management (EIM): The Hidden Secret to Peak Business Performance.”