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Case Study

How a Global Leader in Motion and Control Technologies Uses the Incentive Plan Analytics Calculator (IPAC)


Incentive Plan Analytics Calculator (IPAC)


Challenge

The Company’s compensation team is tasked with analyzing long- and short-term incentive design, including documenting plan metrics, payment vehicles, vesting information, and more for peer companies and companies associated with its board of directors. This information is available in proxy statements, but searching through individual companies’ filings to find the necessary information—without the benefit of comparison across customized peer groups—is time intensive and inefficient.

Solution

IPAC has been a helpful starting point for researching plan design elements for peer companies. I could see the tool becoming very useful and time-saving.

Senior Compensation Professional, Motion and Control Company ($23.5B Market Capitalization)

The Company has primarily used IPAC to source metric prevalence as a reference for the CHRO and the compensation team. The tool has been a helpful starting point for researching plan design elements for peer companies, which can be analyzed down to the individual executive level. The Company has also used the metric research tool, uncovering an instance where a peer company had an ESG metric, which are not common in incentive plans but are being widely considered across industries.

Without IPAC, these key insights might never be uncovered, or at the very least require valuable time and resources when the same research could be achieved with the click of a button.

Results

In one scenario, new directors joined the compensation committee, so the team sought to understand compensation practices and plan designs at their other companies for insight into the perspective they would bring and questions they may have. In another scenario, they looked at peers to find the prevalence of a payout modifier component being considered for a short-term incentive plan. In each case, IPAC’s quick reference tools provided data-based analysis to support decisions.