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Enterprise Information Management (EIM) Part 2 – A Vendor’s Perspective

by Lyndsay Wise, President, WiseAnalyticsWednesday, November 26, 2008

Part 1 of this article gave an overview of information management, its importance in relation to other initiatives across the organization, and its continued growth in the market.  Part 2 complements Part 1 by looking at how Business Objects/SAP views and delivers enterprise information management (EIM), EIM’s overall importance, and how it adds value to organizations.  This article is based on an interview with Philip On, Director of Product Marketing for EIM at Business Objects.

The Historical Role Of Information Management And Its Challenges

Until recently, organizations have used business intelligence and data management initiatives to solve tactical requests from the various business units requiring large amounts of data.  An example could be building a data mart to look at revenue and sales for reporting and pulling this information from various operational systems to help different business units access the right information such as sales and marketing, manufacturing, etc. Many of these initiatives start from a tactical or departmental perspective and require leveraging the same information – customer, order, product being purchased and delivered – but in different ways.

As organizations start to look at the information that is coming out of these initiatives, they begin to realize that it is difficult to get an enterprise-wide view of the information because the initiatives focus on departmental or business unit views.  This means that similar data sets are being used for different initiatives, creating silos of information across the organization. Unfortunately, unless information is looked at from an organization-wide perspective, the operational information being used as part of these initiatives will only offer visibility into a particular department or business unit without giving the organization a single view of what is occurring within the organization as a whole. 

In addition, many organizations are faced with a data explosion caused by acquisitions and consolidations.  The test for IT becomes how to integrate this data from various data sources and rationalize it.  The challenge exists because of data volumes and the addition of data sources, not to mention how to integrate disparate systems that might not easily interoperate. Consequently, rationalizing data is no easy task.  The integration of sales revenues for all companies or suppliers and their accounts payable becomes a challenge for organizations lacking a single view of the organization, or coherent definitions of data and the categories they fall into. 

Creating a single view of data extends beyond data integration. Business users need to be able to see the company and how it works on an enterprise-wide scale versus how independent business units work.  The challenge to this view is that data integration alone does not help organizations create a single view.  For this to occur, it becomes essential to develop single definitions of data, identify relationships that exist between data sources and types of information, such as customer, product, or supplier, and complement this with a data quality initiative to ensure accurate data across the organization.  The result is trusted, accurate, traceable, data that is critical for audits, meeting compliance, etc.

The Importance Of Data Integration, Data Quality, And Master Data Management And The Role Of Data Governance

Now that the data integration market has matured and many organizations have implemented data integration practices within their organizations, the adoption of data quality initiatives has increased.  In addition, organizations are recognizing a significant need to reconcile data definitions and to understand how data interrelates across their organization.  Standardized definitions become important because disparate systems may have different ways of defining entities (such as customer, supplier, product, etc), taxonomy, or hierarchy, creating a difficult situation when it is time to roll up and look at information from an enterprise perspective. 

Data governance is also an important component within an EIM initiative. EIM is about developing a strategy to leverage data and strategic assets.  In order to do that people, processes, and technology are required to develop the closed-loop processes to have the right stakeholders to develop guidelines and policies and carry them out. Managing these processes by using a data governance strategy can help organizations maintain levels of collaboration and cohesion among various business units.

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