How to Develop an Information Management Lifecycle Methodology

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Editor's note: This is the first in a series of articles focusing on key information management disciplines. Read Part 2 here, Part 3 here and Part 4 here.

In recent years, a greater reliance has been placed on information to support corporate decision-making. This has resulted in a shift in focus away from the mere storage and maintenance of data to the practice of information management. Efficient information management is increasingly becoming a key activity and an area of focus not just for IT, but also for industry executives and leaders. This activity is now identified as a critical factor to the success and continued growth of organizations.

There are several factors contributing to and driving this thought process. Some of the key drivers include:

  • Timely identification and management of risk,
  • Regulatory and compliance requirements,
  • Identification of opportunities for growth, and
  • Identification of issue/problem areas.

Historically, we have seen several instances of organizations experiencing sudden and drastic failure, loss of market share or a gradual decline in growth, thus rendering them irrelevant in the marketplace. As most of these occurrences can be attributed to the strategic nature of business decision-making, a lot of the tactical information required for such decision-making lacks good information management and best practices around it.
As a result, the information being delivered lacks the quality, integrity and timeliness required for effective decision-making. The results of poor information management practices manifest upstream in the form of systemic weaknesses, or worse, organizational failures. The good news is that there is a greater awareness today of the importance of developing best practices around the management, delivery and analytics of corporate information.  As a result, the information management discipline has matured greatly.

A good approach to implementing best practices is the development and adoption of a framework to manage information, and as a first step, the various relevant components of the framework need to be identified. Some of the essential components of an information management strategy are:

  • Canonical models and design strategy,
  • Metadata, master/reference data strategy,
  • Data quality,
  • Integration strategy,
  • Analytics (BI), and
  • Physical data management.

Once the various components are identified, the strategy can be implemented.
At a higher level, the strategy can be broken down further based on data flow and movement across the organization. The various components of the framework can then be built into the process outlined below, which provides more control over the components from a functional perspective. ADAM – analyze, design, acquire and manage – is a new concept that aligns with the development lifecycle methodology.


The first step to any new initiative is the analysis phase, where requirements, sources and systems are closely examined. The business requirements that drive the initiative need to be thoroughly analyzed and understood. The scope of the undertaking needs to be established and agreed upon by all parties involved. The current state of the system needs to determined with the gaps identified and documented. A roadmap needs to be established to determine how to get from the current state to the target state. The task may be as simple as accessing a data feed or it may require building a more complex system that traverses numerous functional areas. The deliverables at this component of the strategy are various requirements documents and specifications.


The design accounts for the all requirements, applying them from both a business and system perspective. Some key considerations at this step  are the translation of requirements to logical and physical structures, the ability to seamlessly accommodate new and changed information, consideration of the frequency of the information and historical needs, and planning for volume, growth and performance. The deliverables at this step include design documents, canonical models, and conceptual, logical and physical models.


The acquisition of information is the next step in the logical progression or flow of information into the organization. Special attention needs to be paid to determining the characteristics of the information. Deliverables at this step include data quality and integration strategies. Answers to the following questions will impact the acquisition of information and, therefore, should be addressed at the analyze phase:

  • What is the information being sourced?
  • What is the nature of the content?
  • How is it being made available?
  • What is the technology of transfer?
  • What is the frequency of the information?
  • What is the volume of the information?
  • Is it a delta or a complete refresh?


Once the information is sourced and stored within the system, it needs to be efficiently managed. How often does the information change? What is the frequency of the information required by the business? Transformations or enrichments based on business needs require some predetermined parameters; a determination of the storage medium needs to be made, capacity will be determined based on current and historical needs. Is the information going to be shared? What are the systems that have a need for the information? What is the frequency of the information feed? Is any of this information of a sensitive nature? If so, are there any special security needs to be taken into consideration? The deliverables at this stage include the analytics and meta/master/reference data strategy. The components need to be considered and implemented as appropriate. This often leads us back to the requirements.

The final step in managing information requires that the information be appropriately archived or destroyed. How much of the information needs to be retained and for what purposes? Certain regulatory requirements mandate that the information be retained for specific periods of time. In certain cases, organizations do not dispose of the data, but instead archive data on tape or disk, often outsourcing this function to third-party storage specialists. The volume of data impacts performance, so it is imperative that data is archived or moved to other online sources in order to improve performance. These are two different concepts – one is the archiving of data and the other is the destruction of data after a predetermined period of time.

How is the information being used? Is it a simple read operation, is the information being replicated? At this stage, the system of record  - the authoritative source of a particular piece of information - will need to be determined . This determination will ensure conformity in the usage of information across the organization. This is a critical factor in ensuring the quality and integrity of information across an enterprise. The characteristics of usage of the information are determined at this stage of the lifecycle.

While this methodology examines key components of information management, it is the organizations’ prerogative to decide on how and to what extent the methodology will be implemented. Each organization differs in its structure, mode of operation, adoption and execution of business functions and processes. As a result, the components of the overall strategy will need to be implemented based on the needs of each organization.

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