Defining EIM and IAM

There is a lot of fresh conversation about “information as an asset.” This is a good thing. For many years, technology resources that were involved with information management (which includes the various related disciplines like data warehousing, business intelligence, data quality, data governance, etc.) always have claimed that we do not manage information like we manage other assets. Alas, this metaphor has not accomplished much in the way of buy-in or progress toward greater discipline.

The fact is, all organizations manage data and information. If you process a form, accept a purchase order, design a database, draw a data model or even write an email, you are an information manager. You bear some accountability for the data “asset.” Consider this “rule of thumb”: If your enterprise can be harmed by you mismanaging the data you deal with, you are an information manager.

However, this does not mean you do Enterprise Information Management (EIM). It does not mean you understand the intricacies of managing information as a formal asset. Briefly, Enterprise Information Management (EIM) is a program that treats data and all other types of enterprise information as assets. IAM represents the application of the fundamental asset management concepts and processes to manage an (any) asset – in this case, the asset of information versus cash, or a physical facility. 

The actual concepts of asset management for information are called out separately from the components of the EIM program. There are many reasons to split out the program from the concepts, and we will cover these in the next article.

This article will introduce the terms Enterprise Information Management (EIM) and Information Asset Management (IAM),  not in the context of an expansive metaphor, but in the context of acceptance of a formal business program for doing so.

Enterprise Information Management (EIM)

EIM is the acceptance of a formal philosophy and principle that information is an asset, and expresses the intent to make this philosophy formally accepted. This acceptance takes the form of an overarching program that manages and implements the various elements used by organizations to create, move and use data and content. This program contains the people, processes and technology that are applied to carry out the management of information as an asset. Many definitions around EIM focus intently on data quality or the nuts and bolts of data management from an IT context. This is not without reason. Data quality is usually the most likely manifestation of the need for EIM. But this falls short of an enterprise definition. Granted, a data quality program will get an enterprise a long way toward benefits. Data quality can account for enormous costs. But the definition also has to mention proper activity that applies the content toward the needs of the business. In other words, we also need to manage the use of data. That means it cannot cost too much for the benefit we obtain, and we need to ensure that the right content is delivered to the right people for the right reason – that’s all. Consequently, Enterprise Information Management / data strategy (or some combination thereof) can usually be defined along the following lines:

EIM is the program that manages enterprise information assets to support the business and improve value. EIM manages the plans, policies, principles, frameworks, technologies, organizations, people and processes in an enterprise toward the goal of maximizing the investment in data and content.

Information Asset Management (IAM)

The label Information Asset Management (IAM) separates the concepts for formal asset treatment of information from the EIM program. IAM represents the fundamental asset management concepts and processes to manage an (any) asset – for example, the asset of information versus cash, or a physical facility. 

If we contrast data to a “hard” asset., e.g. aluminum billet (a billet is a large chunk of metal that is reduced and processed into many products like doors, window frames, and the aluminum frames that go on the outside of buildings),  we see that data is also reduced, aggregated and processes used to create value as well (business decisions, documents, reports). The key to asset management of the non-fungible item (like data) is measuring its usage vs. value. Other than that, both accrue value to organization through usage, enhancement and consumption.

For a business person, the key concept here is “managing the asset.” Managing implies setting goals, planning, directing, governing, and supervising the execution of a plan. The act of managing the people, processes and technology that touch data then becomes easy to understand.  This is the mind-set we label as Information Asset Management (IAM):

IAM describes philosophies to ensure that data, information and content are all treated as assets in the true business and accounting sense,  avoiding increased risk and cost due to data and content misuse, poor handling, or exposure to regulatory scrutiny.

The definition here avoids the “asset” metaphor as a part of the definition. Lastly, IAM covers more than structured content. An enormous amount of money and effort has been poured into rows and columns content – aka information.  This investment has not been in vain; however, the amount of unstructured information in an organization is an order of magnitude larger than the structured information. In the 21st century, the difference between unstructured and structured data is blurred.

The TakeAway

Until data, information and content are managed as other assets are managed, neither information nor data nor content has a chance to fulfill its potential or its role within organizations. There can be billions more spent on “exploiting” data. Buying business intelligence tools and replicating data and content many times in many places just increases the costs with little perceptible gain. It is wasted money unless you know what to exploit, where it comes from, and what it is worth to your enterprise. If you are going to do business or operate any organization in the 21st century, the asset metaphor needs to become asset policy. 

Remember to move past the metaphor and make IAM “real.” The expression of this will vary from organization to organization. At the end of the day, we must get better at managing the material we spend billions on annually. We need to treat this so-called asset as an asset. That means examining other disciplines like accounting and supply chain management. It means acknowledging and implementing a new philosophy without disrupting day-to-day operations. This is not trivial, but it is mandatory for the 21st century.

Summary

The good news is there truly is genuine interest in Data Strategy/Information Management (IM) at the enterprise level. But that good news is being delivered in the form of reports and documentation of the cost of poor data and content quality. Part of the interest comes from the “new ROI.” As a client recently put it, R O I is the abbreviation for “Risk of Incarceration.”  In short, the legal and regulatory ramifications to the presentation and accuracy of data are beginning to materialize. 

The bad news is that those who are close to hands-on management of information still really stink (and I use that word with deliberation) at explaining what this means to business people. Even if the explanation of data value and the need for good data is presented well, we still need to make it real for the business.

The remainder of this series is not going to talk about managing information assets. It is going to talk about managing an asset called information. We will see there is a large difference in those two statements. Future articles will address topics such as:

  • The details of treating information as a formal asset – value, risk, return
  • The five core principles of EIM
  • An overview of assessing information value and the business case for EIM
  • Business alignment and EIM / IAM
  • A cross reference of the DMBOK to formal EIM /; EIM programs
  • Sustaining an IAM environment – how not to run out of gas
  • Standing up to data governance – building effective organizations

Some of this material will be basic and familiar, but with a twist. Some of it will be new. Hopefully, it will all be perceived as pragmatic. All of it is wrapped around a holistic approach to managing the various products of the digital age toward the goals of improving enterprise value or reducing enterprise risk.

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