Enterprise information management (EIM) is a strategic business discipline that combines principles of enterprise integration, business intelligence, and content management to streamline and formalize data storage, access, and handling across an organization.
EIM leverages various disciplines like metadata management, data management, data governance, master data management, and process management to bring enterprise order, purpose, structure, efficiency, and performance to applications, processes, data, and technology from a holistic perspective.
Leveraging Digital Asset Management for Structured and Unstructured Data in Business Processes
Enterprise information management is one of the hottest topics in information technology (IT) today. Many organizations are expanding their focus beyond traditional metadata management in data warehousing/business intelligence to cover digital asset management for both structured and unstructured data across the entire enterprise.
This is essential for optimizing business processes in today’s competitive landscape. Effectively managing all forms of data helps these organizations gain a strategic advantage in the “Information Age,” allowing them to compete more efficiently and outperform their competition in the coming years.
Enterprise Information Management (EIM) is critical for large organizations seeking to optimize their day-to-day operations and drive digital transformation initiatives. EIM integrates various disciplines like metadata management, document management, data governance, and process management to manage business information effectively.
Key Components of EIM
EIM focuses on the systematic processes and governance procedures that span across applications, data, and technology to ensure improved data quality, enhanced data security, and optimal use of information management solutions. The primary objectives are to:
- Promote collaboration between users and teams
- Support decision-making processes with accurate, up-to-date information
- Ensure compliance with new regulations and data security policies
- Reduce costs by integrating separate applications into one EIM platform
Systematic and Holistic Approach
The term “systematic” is crucial to EIM because it ensures automation across processes and tools, avoiding reliance on spreadsheets or static documents. This leads to better management of information and enables businesses to stay competitive.
A holistic approach is equally important. EIM should not be a one-off solution but rather an evolving process built to scale. This ensures that EIM software can adapt to new technologies and enterprise-level needs, integrating various components of the business for better decision-making and reporting.
Benefits of EIM Software Solutions
Implementing an effective EIM platform provides significant benefits:
- Improved decision-making from access to consistent and reliable customer data and business information
- Centralized storage of data created from various sources in one location
- Enhanced control over access rights, ensuring compliance and data security
- Better reporting and analysis to support digital transformation and competitive advantage
In today’s digital transformation era, EIM is an essential part of how an organization faces the challenges of managing information across on-premise and cloud environments. By leveraging the combined power of EIM, businesses can streamline day-to-day operations, ensure the value of their information, and make better decisions that reduce costs and enhance performance.
In Enterprise Information Management (EIM), metadata, data, and information form the foundation of any successful effort. These elements are deeply interconnected and essential for managing enterprise content efficiently.
- Metadata: Metadata provides the context for data. For example, it defines that the “Customer_Name” field is 40 characters long and exists in multiple systems (A, B, and C). It also shows that our company has three systems containing customer master data. Enterprise content management uses metadata to organize and make sense of information across different systems.
- Data: Data refers to specific content within a system. An example of data would be a particular instance of “Customer_Name,” such as David Marco. Managing customer data is essential for promoting collaboration and ensuring services are optimized.
- Information: Information is data made meaningful to business users. When users understand and trust the data, they can use it to make informed decisions. In this way, information management solutions convert data into actionable insights.
The formula:
Information = Data + Metadata
(content + context) ensures that businesses can rely on their data to support operations, services, and decision-making processes effectively.
Data on its own has little to no value. I could give you some data “24”, “37” and “42”. OK are you ready to make some key decisions in your company? Of course not, because I only gave you data (content). What I didn’t give you was the metadata (context) relating to the data. If I provided you metadata that stated that these data values are annual net sales revenues, in millions of US dollars for your region over the last 3 years, now you can make decisions and actually utilize this data. Simply put, information is the merger of data (content) and metadata (context).
It is important to understand that most companies and large government agencies never planned their IT enterprise; rather, it “just grew” over time. As the IT environment grew as we built “stovepipe” solutions all over the enterprise, nobody (of authority) ever stopped and said, “Wait a minute – we need to optimize and tune this environment so that we can reuse that which we’ve already done.” As a result, our IT environments have grown like weeds that go untreated in a garden. After some time the flowers (applications) can’t grow or survive anymore and the weeds (redundancy and needless dependencies) are ruling the garden.
Most current IT environments are plagued by excessive levels of data redundancy, process redundancy, technology (software/hardware/middleware) redundancy, massive data quality problems, extended IT development life cycles, high project failure rates, and applications that are so convoluted that they are almost impossible to adapt to changing business needs.
Many IT environments have a budget in the billions of dollars annually. Yet these same companies just assume it will just take care of itself. Any quality information management professional knows that Data Does Not Manage Itself.
Consolidation vs. Integration
Many organizations confuse consolidation with integration when in reality these two concepts could not be more different. Consolidation endeavors to take ten tables, each with a million rows, and simply merge them into one table with ten million rows. If that ten-million-row table has 20% data redundancy and 15% data quality problems then that is acceptable, since consolidation does not address this problem. The integration looks to take the ten tables and integrate them into one table (maybe more) with 8 million unique rows and data quality problems at 0%.
Why Every Organization Needs EIM
Every organization, of any size, in every industry, needs to practice enterprise information management, so it can use the data and metadata, the processes and technologies it has invested in, to create information and knowledge that will enable effective operations, optimal decisions, and competitive advantages.
