A Manifesto for Information Knowledge Management

With this manifesto for information knowledge management, data and business professionals will be able to determine for themselves whether or not EIM represents a valid concept.

This article originally appeared on the BeyeNETWORK

In my previous article, we discussed the problems inherent in the traditional understanding of data administration, and the need for a new paradigm, called enterprise information management (EIM). Yet it is by no means certain that data administrators will be willing to move away the old mode of working, with its confinement to the logical layer in opposition to the physical, and its emphasis on data modeling. After all, producing artifacts in the logical layer is necessary, and data modeling is extremely useful. Why should these be abandoned for some poorly defined “new” way of doing things? Data administration, it can be argued, has always been conceptually well understood, and its products can be of great benefit if enterprises choose to utilize them.

Without retracing the arguments put forward in the previous article regarding the issues with data administration, there is definitely an obligation to try to provide a detailed description of how EIM will look in some detail. If this can be articulated, then data and business professionals will be able to determine for themselves if EIM represents a valid concept or whether data administration should simply continue in its twilight state.

The vision for EIM is that it will be a horizontal business function, like human resources or facilities management, dedicated to managing an enterprise’s information assets. This does not mean turning away from data modeling or ignoring the logical layer. But it does require stepping up to a set of responsibilities oriented to the business, rather than aligned to data theory. One of these responsibilities is information knowledge management. To be fair, the “librarian” tendency within data administration has always recognized the need for information knowledge management, but it has typically been poorly articulated and rarely executed well. In my experience, it has always been subordinate to the ascendant imperative to produce logical data models, and has had little implementation support.

If information knowledge management is to be a part of EIM, then just what is it? The best way to begin is to articulate a set of principles that can be used to create an expectation of what EIM will need to provide in order to implement effective information knowledge management. Such a set of principles is subsequently provided in a Manifesto for Information Knowledge Management.

The Manifesto for Information Knowledge Management

It is the responsibility of the Enterprise Information Management function to ensure that any knowledge worker in the enterprise should be able to:

  • Know what data the enterprise manages
  • Know what the data means
    • Including calculations and derivations
  • Know where the data is stored
    • At a minimum, the Authoritative Source
  • Know who is allowed to access the data (security)
    • If they are allowed to know this
  • Know how to get the data
  • Know what can be done with the data (privacy, compliance)
  • Know what decisions have been made about the data
  • Know who has made decisions about the data
    • Governance
    • Stewardship
  • Know what quality issues exist with the data
  • Know who else is interested in the data
    • Stakeholder community
  • Know who to contact if there are issues with the data
    • Know what processes exist to resolve issues

With this knowledge, an enterprise knowledge worker will be able to:

  • Use the data they rely on to perform their assigned responsibilities
  • Ensure that the data can always be turned into information
  • Participate effectively in stewardship functions that assure the quality, privacy, security, and compliance requirements of the data

The enterprise as a whole will benefit as knowledge workers also:

  • Use the data to increase the efficiency of the enterprise’s operations
    • Including reengineering of business processes to take advantage of improved data understandability, availability, and quality
  • Use the data to meet the enterprise’s business goals
    • Including adaptation to changing market, regulatory, and other environments
    • And also agility in responding to new opportunities
  • Use the data to mitigate risk in the enterprise
    • Including reduction of operational risk inherent in the data itself as data quality improves

The Imperative for the Manifesto

Before beginning to examine the manifesto in detail, there are three key questions that should be asked about it in any enterprise.

  • Are any of the principles stated in the Manifesto for Information Knowledge Management irrelevant to the enterprise? If so, why is this?
  • Are any of the principles stated in the Manifesto for Information Knowledge Management not the responsibility of the enterprise information management function? If so, whose responsibility are they?
  • If any of the principles stated in the Manifesto for Information Knowledge Management are not currently being addressed, when are they scheduled to be addressed? If there is no plan to address them, why is this?

The Relevance of the Manifesto

The need for enterprise-wide information knowledge management has not been seen as relevant in the past for a two main reasons.

The first is that data administration has been part of IT and oriented to systems development activities. These have typically been projects in which knowledge about data was perhaps gathered in a systematic way, but certainly shared informally. With the members of the project totally focused on the data, and with time and budget constraints, it was seen as not relevant to worry about the “formalities” of information knowledge management.

Of course, this approach cannot work when projects have a large scale, or are very complex, or involve teams not in close geographical proximity, or involve timescales in which staff rotation occurs. Such details, of course, are usually ignored in the approach to project implementation that is nearly always adopted in practice. And, ignoring information knowledge management is a big problem post-implementation. Programmers are known to spend about half their time reverse-engineering artifacts to understand what systems actually do. From my personal experience, a good portion of this time is involved in trying to comprehend the data.

The second main reason why information knowledge management is not perceived as relevant has been the silo-based nature of applications. Why would enterprise information knowledge management ever be needed for a series of independent silos? The barons who own the silos employ CMM Level Zero Heroes to manually maintain them. The Heroes make it their business to acquire the knowledge that is needed to keep the silos running. Frequently working long hours, they actually become part of the applications they support, and typically jealously guard the knowledge they have garnered with so much effort.

Indeed there would be no need for enterprise information knowledge management if the data landscape were composed of independent silos. However, those days are over. We now live in a time when data sharing in data warehouses and marts, or data exchange between operational systems, is being demanded. This means that data integration has to be accomplished, and there may be any number of consumers for data that is initially produced in a silo. Both IT and the business suddenly need to know a whole lot about the data that they are dealing with.

What the Manifesto Means for EIM

Unfortunately, the new world of data exchange, sharing, and integration is not oriented to data. IT is still focused on tools and technology. For instance, it is possible to build a technically perfect data mart with the correct star schema designs, the latest business intelligence (BI) tools with capabilities to drill up, down and across, and all of it fed by a warehouse that collects and integrates data in real time. And the majority of these efforts will be failures. They spend all the effort on getting the plumbing right and pay no attention to the quality and meaning of the data that goes into it. IT simply does not get it, and may never get it. The business, however, is beginning to worry about data. That is part of what is feeding the current interest in master data management (MDM) – at least according to my surveys of the MDM vendors.

Sooner or later the business is going to begin to express the requirements described in the Manifesto for Information Knowledge Management. At first, business users are likely to have only a fuzzy and vague notion of the principles contained in it. However, when they get to the point where they can clearly articulate these principles, they are going to realize just how badly served they have been not just by IT in general, but data administration in particular. It will become glaringly obvious. The answer cannot be that the business did not take enough notice of the data models produced by data administration. What is required is an EIM function that can build infrastructure and services that will actually deliver real value to meet the requirements that lie behind the principles. Therefore, it is better to get out ahead of the business users now before they come to these conclusions on their own.

In future articles, the Manifesto, and other responsibilities of the EIM function, will be explored in greater detail. 

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