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How to Manage Your Company’s Data Portfolio Using Data Rationalization

  Article published in DM Direct Special Report
March 11, 2003 Issue
  By Robert A. Liebke

There are some key things you need to know about IT trends in financial markets. As revenue and margin pressures increase, IT strategy needs to focus on increasing IT efficiency with server, application and data consolidation. "Duplicated, low or no value data" has become an inherent reality that companies cannot ignore with the inevitable decline of custom applications, cheaper servers combined with the accumulation of data through mergers and acquisitions, technology changes and new business requirements. Additionally, with the advances of data analytics and aggregation functions in today's database management systems combined with the sophistication of business intelligent tools, managing your company's information portfolio correctly is the best way to get the most business value out of this data.

Figure 1: Best Business Benefits Realized with Data Rationalization

Server consolidation and application rationalization will generate cost and IT efficiencies during the current economic squeeze. However, the best business benefit will be gained through data rationalization:

  • Strategic data alignment - The ability of information to support the company's business strategy, future direction and required pace of change and to provide useful strategic information for decision making.
  • Technical value - The ability to lower the total cost of ownership by focusing on core data-centric methodologies, tools and technologies.
  • Functional value - The ability to support the company's revenue and profit goals, to protect against financial loss or to meet mandatory regulatory requirements.
  • Operational impact - The ability to lower ongoing operational costs, meet functionality and usability metrics, improve business process metrics and provide useful operational information for decision making.
  • Data quality - An assessment of the quality of the information to determine singularity, accuracy and timeliness.
  • Ease of use - End user must know what the data means, how is it calculated and who is responsible for its content.

What is Data Rationalization?

Data rationalization is basically the use of meta data to determine the optimum collection of objects that will provide the greatest business benefit to the end users (much like a stockbroker selecting the mutual funds). Data rationalization is essential for a company that desires a sound approach to driving down operating costs and maintaining the most efficient technology. Many companies continue to sustain data that remains outdated or has declined in quality. Continuing to maintain this data is a drain on business performance as its value significantly decreases and works against corporate cost-cutting strategies and IT objectives.

Data rationalization is an approach for addressing low value or (zero value) data within a business context by:

  • Determining assessment criteria and weightings - Based on criteria such as business benefit, maintenance cost, data quality, technology platform, age and user satisfaction.
  • Quantifying the value of each data element within the company's data portfolio.
  • Eliminating underperforming, redundant and end-of-life data elements.
  • Eliminating disparate and incompatible data - Data portfolios commonly accumulate isolated and incompatible data structures that require costly special skills and hardware/software requirements.
  • Eliminating all non-core functions - Remnants of non-essential data (or applications) that support de-emphasized corporate strategies are prevalent throughout organizations.
  • Eliminating non-core technologies - Expensive and outdated data items within your portfolios on non-core technologies.
  • Develop an action plan to facilitate implementation.

Recommendations to help manage your data portfolio:

  • Implement quick hits - Eliminate data that has no relevant business function or value, identify opportunities for savings and higher value in current hardware and software licensing agreements and explore the need for user-centric improvements in data value, such as training and data transformation
  • Eliminate redundant data - Identify instances of overlapping and redundant functionality and select the strongest system to support them, merging functionality and migrating data when necessary before eliminating the unnecessary applications
  • Retire end-of-life database - Retire databases whose operation and support costs exceed business value, sometimes replacing them with new, less costly applications.

As a data warehousing practice manager, people have often asked me what the value of meta data is. I am now able to give both the business community as well as the technology community a simple concise answer: It is the key essential area that helps me manage my corporation's data portfolio and helps us achieve bottom line results.

Managing your IT portfolio through data rationalization will provide the following benefits:

  • Reduction in overall IT expenditures - will reduce costs by eliminating underutilized data, lower the support costs of retained data and enable the consolidation of IT platforms.
  • Freeing up valuable resources - The ability to free up IT resources that were traditionally responsible for supporting the retired set of applications will eliminate the support requirements for the inefficient and low business value data. A corporation will be able to redeploy its IT resources to more strategic IT initiatives.
  • Enhanced IT flexibility - Reducing of the number of non- business critical databases and integrating more scalable architectures into the data portfolio will enable the corporation to efficiently respond to changing business requirements and economically integrate new data into the environment.
  • Extension of the life of value-generating system - By extending and optimizing the life cycle of business-critical systems, the corporation will be able enable to obtain a greater return on its investment
  • Empower the end user to create the own data portfolios (scorecards) based upon their department's overall needs and objectives.

Figure 2: Optimizing your ROI through Data Rationalization

Business intelligence tools and data warehousing methodologies make it possible to segregate data from its underlying application and to create and maintain an information portfolio that increases (not decreases) the value of data over time (see Figure 2). Data rationalization is a process that focuses on life cycle activities that will increase the ROI of your data.


1. White Paper: "Applications Rationalization: Reducing the High Cost of Low-Value Applications." Keane, Inc. 
2. White Paper: "Application Lifecycle Optimization: Maximizing the Value of IT Investments." Keane, Inc.


For more information on related topics visit the following related portals...
Data Management and Strategic Intelligence.

Robert A. Liebke is a data warehouse practice manager for Keane Inc. He can be reached at rliebke@keane.com.

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