I was talking with someone the other day about why there is an increased emphasis around Enterprise Information Management (EIM) -- if there isn't there should be.
An organization’s successful use of a variety of home grown and COTS applications across the breadth of its business has caused many different representations of business entities (e.g.: customer, invoice), over time. In a way, we’re a victim of our own success as we grow, pulling more of our spending into maintaining this fragile environment. This redundant, unaligned data causes organizations unnecessary cost and confusion. Enterprise Information Management (EIM) is a technique that weaves an information fabric throughout the enterprise, developing a common understanding underpinning the Process, Application, and Business view. EIM is key to creating a single view of truth and integration for the new agile enterprise, improving communications, reducing costs and increasing flexibility.
When I looked for EIM inside Wikipedia, about the closest definition I could find was Enterprise Data Management. As we move into having a more service based approach to the IT environment though it will require more than just common data. We need more commonality of data, process and service.
The IT industry has tried to tackle a common view of data before. In the 1960s and early 1970s, the answer was database management systems (DBMSs), in the late 1970s and early 1980s, it was 4GLs, spreadsheets. In the 1990s, it was ERP, OLAP and data warehousing. Each of these approaches has solved part of the information access problem, but getting at the right information across the enterprise is still a problem.
Enterprise Information Management looks at both the data and the processes, enabling agility within the enterprise by incorporating principles of model-driven reusability of standard data, information, intelligence, knowledge, and wisdom throughout the organization. We’ve taken a multi-tiered approach to EIM within our processes:
- The Data Resource Infrastructure (DRI) tier represents a new layer of data for the agile enterprise created from 100%-reusable data structures that are based on industry best practice data models. For most organizations at least 80% of their data and process model is not unique. These data assets create the IT foundation for enabling data management (sometimes called metadata management or master data management) for any business or industry.
- The Enterprise Information Architecture (EIA) tier represents a new layer of information and intelligence for the agile enterprise that enables the single point of truth and integration for clients and EDS. These client-specific or industry-specific assets are intended to create the foundation for information architecture. This seems to where many master data management efforts focus.
- The final tier Strategic Information Architecture (SIA) enables the client-specific or industry-specific business system to be modeled and the implicit knowledge and practice (wisdom) to be modeled explicitly to graphically reveal the business system of performance (that is, to show companies what makes them succeed or fail based on their goals and initiatives).
Having this more holistic approach enables greater consistency and value in a way that can be validated.