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A Balanced Scorecard for Maximizing Data Performance.

Elizabeth Pierce1

  • 1Department of Information Science, University of Arkansas at Little Rock, Little Rock, AR, United States.

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Summary
This summary is machine-generated.

Organizations need strategic performance indicators to measure data capabilities effectively. A balanced scorecard approach helps select meaningful metrics to maximize data asset value, despite implementation challenges.

Keywords:
data governancedata literacymetricsmonetizationscorecard

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Area of Science:

  • Data Science
  • Information Systems Management

Background:

  • Effective performance monitoring is vital for assessing data capability evolution.
  • Comprehensive performance measurement systems are resource-intensive, requiring significant investment in time, personnel, and finances.
  • Organizations must strategically select performance indicators to evaluate the value generated by data initiatives.

Purpose of the Study:

  • To propose a balanced scorecard approach for designing effective data performance metrics.
  • To assist organizations in creating coordinated and meaningful metrics for data asset optimization.
  • To address the challenges associated with implementing such performance monitoring systems.

Main Methods:

  • The study proposes a balanced scorecard framework.
  • It outlines a strategic approach to selecting a portfolio of performance indicators.
  • Discussion includes implementation considerations and future research directions.

Main Results:

  • The balanced scorecard approach offers a structured method for metric selection.
  • It facilitates the design of coordinated metrics aligned with organizational goals.
  • Identifies key challenges in implementing performance monitoring systems for data initiatives.

Conclusions:

  • A strategic, balanced scorecard approach is recommended for developing robust data performance monitoring.
  • Effective metric selection is crucial for maximizing the value derived from organizational data assets.
  • Further research is needed to address implementation complexities and refine methodologies.