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Michael E. Reed

Chairman of the Board, CEO, and President at GCI
Board
Since November 2013
Age
57 years
Tenure
Joined in November 2013 as a member of the board and as CEO and President, later promoted to Chairman in May 2019.

Also at GCI

CG
Cindy Gallagher
Controller, Chief Accounting Officer, and Principal Accounting Officer
DEH
Douglas E. Horne
Chief Financial Officer and Principal Financial Officer

About

Michael E. Reed has over 25 years of experience in the newspaper and publishing industries, beginning his career with senior roles, which provided him a strong foundation in media before joining GCI.

He joined Gannett Co., Inc. in November 2013 as a member of the board and as the Chief Executive Officer and President, assuming significant responsibilities for shaping strategy and operations.

In May 2019, he was elevated to the position of Chairman of the Board while retaining his roles as CEO and President, reflecting his long-standing leadership and deep industry expertise. His previous experience as CEO of GateHouse Media and his involvement with several prominent boards underscores his commitment to driving success across the organizations he serves.

$GCI Performance Under Michael E. Reed

Past Roles

Organization Role Date Range Details
Minneapolis Star Tribune Board Member 2009 - 2014 Served as board member
GateHouse Media, Inc. Chief Executive Officer January 2006 - November 2013 Filed for Chapter 11 bankruptcy in September 2013
GateHouse Media, Inc. Board Member Started October 2006 Served on the board of directors prior to merger
Newspaper Association of America Board Member and Chairman (1 year) N/A Represented the newspaper industry on the board
Associated Press Director and Chairman of the Audit Committee N/A Served on the board and chaired the Audit Committee

External Roles

Organization Role Date Range Details
TouchCare Holdings LLC Board Member Current Currently serves as a board member outside of GCI

Fixed Compensation

Data from  FY 2023
Component NameAmountPayment ScheduleAdditional Details
Base Salary $900,000 Annual Reflects the salary rate after the voluntary reduction in late 2022 due to company expense initiatives

Performance Compensation

Data from  FY 2023

Cash Performance Units (CPUs) 2023

Metric (Unit & Scale)ThresholdTargetMaximumPerformance Result
Adjusted EBITDA (Million $)$240.0M $300.0M $330.0M $267.7M
Digital Revenues (Million $)$903.0M $1,129.2M $1,242.1M $1,050.4M
  • Performance Weighting: Each metric contributes 50% to the overall CPUs performance assessment.
  • Vesting Schedule: The CPUs have a three-year performance period (2023–2025) with vesting occurring three years from the grant date of March 24, 2023.
  • Vesting Outcome: Based on 2023 performance, 77.8% of the target CPUs vest, corresponding to a value of $389,050.
  • Grant Details: CPUs are cash-based awards with a grant date fair value provided; no grant date stock price since they are not equity awards.

Annual Bonus Plan (ABP) 2023

Performance ComponentMetric/GoalThresholdTargetMaximumActual Performance
Adjusted EBITDA Component Adjusted EBITDA (50% weight)$240.0M $300.0M $360.0M $267.7M
Media Segment – Total Digital Revenue Total Digital Revenue$541.7M $677.1M $812.8M $641.7M
Media Segment – Digital + Print Circulation Revenue Digital + Print Circulation Revenue$700.6M $875.8M $1,051.0M $854.5M
Media Segment – Local YOY Profitability Trend Profitability Trend (ppt)8.40 10.50 12.60 9.90
Digital Marketing Solutions (DMS) – Revenue DMS Revenue$410.3M $512.9M $615.5M $477.9M
DMS – Adjusted EBITDA DMS Adjusted EBITDA$53.4M $66.7M $80.1M $53.2M
  • Performance Weighting: Company financial goals account for 75% of the ABP with the remaining 25% tied to individual performance goals.
  • Bonus Payout: Michael E. Reed achieved 77.8% of his target bonus level, resulting in an award of $875,559.
  • Plan Characteristics:
    • The ABP is a cash-based incentive with performance evaluated annually for the fiscal year.
    • There is no vesting schedule for the annual bonus as it is not equity-based.
    • Payouts are scaled linearly between the threshold, target, and maximum levels for each metric.