Part I: Mastering the Measurement of Incentives, Rewards, and Recognition

• Fear of outcomes – Many program leaders avoid measurement out of fear that ROI studies will reveal poor results.
• Short-term mindset – Executives too often look for immediate returns rather than long-term stakeholder impact.
• Activity metrics instead of impact metrics – Companies focus on vanity data (likes, attendance, clicks) rather than business outcomes (productivity, retention, sales growth.)
• CEO blind spots – As Patti Phillips points out, many CEOs don’t ask the right questions because they have little training on how to think of human capital as measurable assets.

Recommendations for Measuring Anything

• Start by shifting the conversation from a focus on engagement and experience to performance improvement and ROI.
• Demonstrate that engagement programs are not just about experiences but about measurable business outcomes.
• This reframes internal advocates and solution providers from being seen as rewards/travel/event vendors or advocates to strategic business partners and solutions.

• State clearly and specifically what your proposed engaged effort is designed to accomplish, increase sales, improve productivity, cut costs, enhance safety, foster alignment, etc.
• This includes the purpose of the effort.  Steer clear of vague generalities such as increase engagement and focus on specific benefits aligned with organizational priorities and values.
• Instead of increase morale, a purpose could be to increase retention, reduce turnover, improve internal or external customer satisfaction, improve productivity and quality, reduce accidents, generate cost-savings suggestions, successfully participate in training programs, engage in communications, etc.

• Establish the specific data needed to correlate results versus process measures.  This is in effect a data availability audit. Generally, measurement requires access to financial data, including revenues, gross profit, net profit, margins; program costs (human resources, technology, marketing, training, rewards, incentive travel, communications, gifting, etc.); number of employees and customers; customer and survey engagement data; voluntary turnover rates; lost days due to accidents; employee referrals and project cycle time compliance; suggestions and the value of suggestions; participation in training or communications programs, etc.  From these numbers, a trained analyst can employ simple calculations to determine changes in productivity, quality, retention, referral and other performance metrics to guide enhanced program design.
• Contextualize data selected by stakeholder group. What demographic and other characteristics generally define sales and non-sales employees, channel partners, customers, supply chain partners, volunteers, or other stakeholders in terms of their needs, levels of education, skills or other capabilities required.
• Look for unaccounted for inter-dependencies. Consider that people in other departments may have a direct impact on your own group’s goals and objectives. Look to access data on related departments and better collaborate when possible to make sure one group doesn’t undermine your own efforts.
• Data creates “stickiness.” Once management or clients trust your team or solution provide with sensitive business data, the data becomes an asset and helps enhance the perceived value of the investment.
• Security. If management is concerned about having an incentive, recognition, loyalty or other tactical solution provider hold its data, consider having it managed by a qualified third party not involved with the implementation of your programs.

• Use standard spreadsheets to manage data with appropriate security procedures and gated access as appropriate.
• When possible, place all available data on a single spreadsheet with tabs for each stakeholder group including pre-populated formulas when possible. Based on the data, set up quarterly and annual totals, as well as formulas to automatically determine metrics such as human capital ROI and value add of marketing, sales or the ROI of other activities; sales and profits per customers, employees, channel partners; number and dollar value of referrals or suggestions; cost of lost hours due to accidents, etc.
• For the purposes of eventually benchmarking metrics, whenever possible, refer to international standards such as ISO 30414, the 2025 version of which is now available, so that the final metrics formulas selected can potentially be benchmarked with other companies over time. Your company does not have to become ISO certified to benefit from its carefully thought-out metrics and formulas. The standards can be purchased online for about $250.
• In addition to creating dashboards in Excel or other program with the most relevant data, program your spreadsheet or use other tools to graphically represent your results and process data to identify correlations you might otherwise miss. You wish to easily graphically compare all the metrics either together or in isolation to identify potential correlations between results and actions to help determine the best ways to help the targeted audience improve performance.
• In addition, use common AI tools to further enhance the ability to seek overlooked correlations between actions taken and outcomes by who.
• Reports should be configurable by time period (quarterly, annually, multi-year) and tailored to internal or client priorities.

5. Overcome the Data Barrier with Education and Templates  

• The biggest challenge is getting data from the organization or clients. Show senior management what’s possible with even limited data to motivate them to encourage sharing. As part of this series,the EEA is creating case studies to demonstrate the process as well as standardized templates set up for ease of customization.
• Provide clear templates so clients/the organization can easily contribute the right data.
• Start with what they already track (sales numbers, training completions, email opens, etc.) and expand over time.

• Feed structured data into analytics platforms (Excel, AI tools, Darwin’s correlation engine, or similar), or the EEA’s PVIC platform.
• Examine correlations between participation (training, co-op marketing, communications engagement) and outcomes (revenues, profits, distributor activity).
• Highlight cause-and-effect possibilities: e.g., co-op program participation strongly correlated with revenue increases.
• Leverage AI (including ChatGPT or other AI analysis) for quick insights, then validate when possible with deeper, customized prescriptive analytics and expert human analysis.

Enterprise Engagement Alliance Services