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Using Big Data to Enhance
the Value of Compensation
Programs
Lance A. Berger
Managing Partner, Lance A. Berger & Associate...
Introduction
Organizations collect, connect, analyze, use, and store
large quantities of data pertinent to their business ...
Five Elements of Big
Data
Foundational knowledge
Levels of big data
Competencies of big data practitioners
Value-creating ...
Foundational Knowledge
Definition: Big
Big compensation data involves the integration of data
elements from different disc...
Foundational Knowledge
Six Criteria for Big Data
Outcomes. Before embarking on big data, practitioners should clearly
defi...
Foundational Knowledge
Six Criteria for Big Data
Timeliness. After relevant data are identified and their quality ensured,...
Levels of Big Data
A foundational understanding of big data enables an organization to
classify its current and potential ...
Big Data Practitioners’ Competencies
Analysis and creativity
Organization focus
Communications (oral)
Communications (writ...
Value Creating Outcomes
The transformative power of big data for compensation
practitioners lies in identifying and managi...
Value Creating Outcomes
Examples
Business. Do incentive plan payouts vary directly with
competitive business performance?
...
Big Data Blueprint
Organizational strategies encompassing long-term plans for maximizing
value based on the institution’s ...
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A Guide to Realizing the Value of Big Data

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How "Big Data" helps compensation decisions better, more efficient, faster , and cheaper.

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A Guide to Realizing the Value of Big Data

  1. 1. Using Big Data to Enhance the Value of Compensation Programs Lance A. Berger Managing Partner, Lance A. Berger & Associates, Ltd. Based on Chapter 46 of sixth edition of the Compensation Handbook Copyright © 2015 by McGraw-Hill Education
  2. 2. Introduction Organizations collect, connect, analyze, use, and store large quantities of data pertinent to their business and employees. This gives them a foundation for integrating multiple data elements into a smaller set of cogent decision points. These decisions pertain to the design, implementation, and audit of the effectiveness of compensation strategies. Technology makes this process more accurate, easier, faster, and cheaper than ever before. This technological phenomenon has been titled big data.
  3. 3. Five Elements of Big Data Foundational knowledge Levels of big data Competencies of big data practitioners Value-creating outcomes Big data blueprint
  4. 4. Foundational Knowledge Definition: Big Big compensation data involves the integration of data elements from different disciplines using a variety of analytical tools and technologies to identify and address important human resources issues.
  5. 5. Foundational Knowledge Six Criteria for Big Data Outcomes. Before embarking on big data, practitioners should clearly define the issues they seek to address. Collectively, these issues seek to answer the question, “Does the organization’s compensation strategy align with its business strategy, culture, and talent-management strategies? Types of Data. Once outcomes are defined, the data necessary to address them must be identified. The data required typically will come from documented business strategies and performance, compensation strategies and practices, talent-management strategies and practices, and culture surveys Quality. Once big data sources are identified, their accuracy, consistency, and comprehensives for identifying and/or solving targeted compensation issues and solutions such as just listed are determined.
  6. 6. Foundational Knowledge Six Criteria for Big Data Timeliness. After relevant data are identified and their quality ensured, they are harvested and made available in the time frame necessary for identifying and/or solving active and future issues. Time frames range from periodic to real time. Worth. After determining whether their data meet the criteria listed earlier, practitioners must determine whether engaging in a big data process is worth its cost and time of implementation or whether simpler processes could be used by the organization to address compensation issues. Credibility. In order to implement solutions based on big data, an organization must ensure that its employees trust and believe in its capabilities for addressing compensation issues. This means that an organization must have a formalized and timely employee communications program that honestly presents the role of data in its compensation decisions.
  7. 7. Levels of Big Data A foundational understanding of big data enables an organization to classify its current and potential level of implementation. Descriptive. Descriptive big data involves the systematic approach to identifying, collecting, organizing, and analyzing high-quality business and compensation data to unearth valuable insights that help to guide compensation decisions and actions. Analytical. Analytic big data involves the blending and integration of business, compensation, and talent-management data into cogent and useful pieces of information that can be used to make valid compensation decisions. Predictive. Predictive big data is used to make more effective compensation decisions through the extensive mining of all relevant data to create paradigms that provide a clear understanding of the relationship between organization strategies and practices and current and future outcomes. Prescriptive. Prescriptive big data is complex and sophisticated. It draws on historically valid paradigms. It enables the organization to make highly accurate decisions involving specific actions necessary to achieve desired short and long outcomes.
  8. 8. Big Data Practitioners’ Competencies Analysis and creativity Organization focus Communications (oral) Communications (written) Fact finding Industry knowledge Leadership Project results Technical knowledge Value added
  9. 9. Value Creating Outcomes The transformative power of big data for compensation practitioners lies in identifying and managing the relationship between pay and three basic key activities and value-creating outcomes: Business Culture Talent Management
  10. 10. Value Creating Outcomes Examples Business. Do incentive plan payouts vary directly with competitive business performance? Culture. Do the employees’ perception of the compensation fairness and organization value align with actual practice; that is, does it reinforce a success culture of innovation, creativity, engagement, leadership, motivation, and equity? Talent management. Does the compensation system support the talent-management strategy?
  11. 11. Big Data Blueprint Organizational strategies encompassing long-term plans for maximizing value based on the institution’s vision, philosophy, values, mission, goals, and priorities. It includes success measures for each strategy. Organization values that guide institutional behaviors in implementing strategies toward stakeholders, including customers, employees, vendors, government, and media. Values typically include ethics, beliefs, institutional competencies, and behaviors. Talent-management strategies that describe the types of the people in whom the organization will invest based on their values and current and potential contribution to organizational success. High achievement, replacements for key positions, high potentials, and critical-competency employees are usually those receiving the highest compensation package. Compensation strategies that indicate how an organization will allocate employee pay based on its business and talent-management strategy.

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