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21st Century Information Architectures

  Article published in DM Review Magazine
December 2001 Issue
  By John Ladley

After almost 20 years of information management theory, movements and gurus, why isn't anything any better? Critical success factors continue to be elusive; perhaps the most frustrating has been meta data and information management. Corporations recognize information as an asset, but still can't treat information as an asset. The vendor community continues to provide lip service to standards while producing targeted, product-specific solutions. At the root of all of this seeming failure of information management is that many of our previous and treasured concepts of information management may not address the current reality of information technology. No one has done anything wrong. Technology, application taxonomies and the explosive increase in business user reliance on information and collaborative intelligence have modified the rules.1 In this environment, the current mind-sets of information management will never work. Corporations cannot exploit the information asset without new processes and perspectives on information.

There is tremendous emphasis placed on meta data standards, repositories, stewardship and alignment. Some of these are still good ideas. Others will be placed into a new perspective. The bottom line is simple - information as it is known is evolving outside of its traditional role, and the inadequate tools and philosophies of the past are even less adequate now. IT departments must overcome several barriers to effective use of information.


The first barrier to change is the mind-set of information managers toward meta data and information management (IM). The good news is that meta data management has proven to be vital to project success.2 Use of information models and repository layers increases utility and relevance of applications. SAP's architecture is a splendid example of this, but there is a trap lurking under these supposed examples of current IM thought.

The first mind-set to toss aside is the relevance of a comprehensive global repository for an enterprise. Meta data has created successful data warehouses, data marts, etc., but less than a handful of organizations have implemented an enterprise repository product with any hint of success. Few, if any, of these implementations are based on a global repository. Those companies using repositories for impact analysis and management of operational applications rarely tie use of the repository into decision support. This is not saying there haven't been some successes. The track record is too disappointing to call the current instantiations of repositories a success.

History aside, the real reason to avoid pursuit of the classic repository is simple - the idea they represent is irrelevant to most businesses. Corporations will acquire their operational application "meta layers" via an integrated package such as SAP, PeopleSoft or Oracle. Or they will choose to purchase disparate applications that are functionally adequate. Within the confines of a product such as SAP, all is semantically consistent. Outside the tool, traditional information chaos reigns. The reason for this is few organizations have 100 percent implementations of Oracle, SAP or PeopleSoft. Many have some of all three, plus a few supply chain products thrown in. This means, by default, the organizations must use different definitions and business rules within subject areas. The relevance of a repository is diminished in the face of practicality.

The next mind-set to scrutinize is "information as an asset." Information (and knowledge) is an asset, but the current treatment is out of date. Currently, the repository should function as the overseer, with stewards and owners acting to implement and enforce rules and standards. Through this process, great universal changes can be made to applications, and the organization knows at a glance the relevance of a piece of data.

Unfortunately, this view ignores reality. The successful uses of meta data tools do not track this path. Successful uses of meta data are usually navigational and knowledge-based, i.e., the user knows where to get information, and why and how it got there.3 Modern repositories barely have any capability in navigation. Current repositories are acceptable at the administration of data and contain some level of definitions (but poor semantics and synonym management).

Another mind-set is that information has to be in rows and columns to be useful to be real business intelligence. However, we all realize that a great deal of the actions and decisions in a business are based on unstructured information as well. In fact, the types of content available in the 21st century up the ante on any meta data strategy.

There are different categories of information, knowledge and data. Therefore, the blanket stewardship/ownership of a piece of information is subject to the context within which the information exists. Stewardship and ownership are dynamic within the enterprise. Rules may be put in place to make stewards and owners accountable, but where is the business measure of accountability? An asset has value. Many authors (e.g., Karl Sveiby) are working on valuation of information and knowledge. As such, tools and process will have to treat information with the rigor assigned to money and labor. Again, the concept of the universal semantic repository cannot do this.

The usage and context of a particular piece of information determine who is to be the caretaker and definer of that information, not a global concept of steward and owner. This simplified example shows how one simple element can be viewed and treated across an organization.

Without a business goal and business context, stewards and owners are not accountable and interest wanes rapidly. In addition, structured information has received all of the attention of the tool and rules-makers. However, most of the powerful content in an organization is unstructured. No tools to date deal effectively with structured and unstructured information (unstructured data includes digital media, text and documents).

Finally, to demonstrate that the IT organization is not alone in mind-set changing, business users must acknowledge the quality of the actual data is as important as the so- called management of the semantics. Only recently has attention been paid to this area. To doggedly pursue standard definitions, repositories and extensible markup language (XML) when the business processes corrupt data as a matter of course is a futile exercise and laughs in the face of treating information as an asset.

Taxonomy of 21st Century IM

The new IM mind-set needs to be this: There will never be a universal set of definitions used by all applications in an organization unless there is a compelling business need. As long as the disparate applications do their jobs and there is hope in some interoperability processes, such as data warehouse (DW) or enterprise application integration (EAI) software, the business will not perceive that need. Information managers must address the new issues. It is time to engineer an IM environment that moves the business forward.

All actions and decisions within a business take place by executing along a knowledge continuum. That is, every time a manager makes a decision, he uses data, information, and tacit and explicit knowledge, and takes action. The extent to which an organization manages information as an asset determines where on the continuum the enterprise shifts from automated support to manual support. The meta data of the future must support an organization's evolution from one end of the spectrum to the other.

There are eight parts to the 21st century IM taxonomy. Some of them are familiar, while others reflect new requirements:

  • Semantic management: This manages what the information means to the specific user and process. Different context will ascribe different meaning. However, some information that is represented in organization-wide metrics will be centrally and universally defined.
  • Portal: Content discovery and navigation is accomplished and measurements are taken as to how users of various skill sets and roles use the information. The portal is used to present all types of content, launch queries and monitor workflow.
  • Administration: This determines how the semantics and relationships are managed. Public and private information communities are reated and maintained as well.
  • Content: Structured and unstructured information content is indexed dynamically and stored.
  • Context: This is where meaning is ascribed and rules for usages, access, maintenance and filtering are kept.
  • Information-gathering and movement tools: This part of the taxonomy contains the logistics workers, the tools that move data and meta ata around. Messaging, aggregations, replication and transformation are xecuted via these tools.
  • Collaboration Engine: This works with the portal layer to permit collaboration and knowledge sharing. At a minimum, it will contain instant essaging, chats, an e-mail interface and a knowledge-base interface.
  • Business Processes: The meta data of the future will actually manage processes as well as document them. This is the only way that the alue delivered by information management will be tied to business value.
  • Governance: Successful meta data and IM will require information principles, policies and accountability. The taxonomy must define who reates policies and enforces the information architecture.

Granted, no tools exist to do all of this, but the pieces are in place. The federalist mind- set will implement the preceding taxonomy with the following principles in place:

  • Only the absolute universally recognized measures and attributes of a company are globally standardized. Everything else is fair game and "local." Standards are enforced for metrics at first; other federal items are identified over time.
  • The meta data must support interoperability between applications, an inventory of metrics in use and an accounting of the relevance of information scattered throughout the organization.
  • Information and knowledge policies may not appear on the balance sheet for many years; however, organizations should track information usage and processes. Information usage can then be tied directly to business processes.
  • Business personnel will be held accountable for business goals, but the context and content of the goals will be reflected in the use of information to achieve these goals.

The mind-set of information as an asset should be this - even intangible assets are measurable. Therefore, information management must adhere to a business mind- set and answer these questions:

  1. How is information used in a company?
  2. How is it governed?
  3. How are the processes and rules that use information managed?

Final Recommendations

It is easy to see why repositories as we know them are doomed - few have accomplished their old charters, none can accomplish the new one. It is also understandable why most successful meta data and repository efforts are characterized by being in-house developed or by repository product owners implementing extensive extensions to the acquired tools. Because no tool exists for this taxonomy, a series of evolutionary steps can be achieved to begin the migration toward effective IM.

  1. Develop a global conceptual data model, based on global measures and metrics. This achieves alignment of meta data with business goals.
  2. Apply the global conceptual model to business functions and IM to project- level management. This reinforces the business alignment.
  3. Implement enterprise information visibility of business measures via a useful BI architecture, or balanced scorecard. The facility must be driven by the meta data layers.
  4. Initiate enterprise information management and IM architecture via documenting IM processes and bottom-up models. This includes identifying information supply chain processes.
  5. Add enterprise context: business processes and unstructured information architectures. This step folds in the truly rich content that will be required.
  6. Add collaborative information - navigation standardized, IM and business communities defined. Lay the foundation for knowledge.
  7. Add a knowledge framework. Identify IM behavior, measure with business results and identify key reserves of human capital. Use the collaborative layer and the portal to track how people work.
  8. Identify information managers in the business ranks. Build information accountability into management by objectives (MBOs).
  9. Recognize information assets on balance sheets.

As an organization moves along a maturity cycle, information managers will become, or be recruited from, business areas. To truly exploit information, corporations must permit and recognize information managers and accountants. They must acknowledge the broad spectrum of content that is information; and finally, they must incorporate the new information management principles into all business efforts. Businesses must terminate the "we and they" mentality when combining information processes with business processes. Meta data must evolve from a documentation mind-set to an active mind-set. Only then will IM become an effective component of the business landscape.


1. Collaborative Intelligence - The combination of business intelligence based measures with measures of business processes and human behavior.
2. META Group, Research Delta 825, "Metadata Maelstrom Sinks Standards and Repositories," 2/4/2000.
3. META Group, BPM report, 2001 pending.


For more information on related topics visit the following related portals...
DW Design, Methodology, Enterprise Application Integration (EAI) and Enterprise Information Management.

John Ladley is a director for Navigant Consulting, a management consulting firm specializing in knowledge and information asset management and strategic business intelligence planning and delivery. Ladley is an internationally recognized speaker and, more importantly, a hands-on practitioner of information and knowledge management solutions. He can be reached at jladley@navigantconsulting.com. Comments, ideas, questions and corroborating or contradictory examples are welcomed.

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