Designing human-centric incentive plans

ZS wrote the book on incentive compensation. Now we’re unleashing motivation for a digital world—starting with human-centered design built to perform.

Incentive plans can be catalysts for excellence. They drive employee motivation, performance and engagement. Smart incentives align individual and organizational goals and foster a focused, productive workforce. As technology reshapes industries and workplace expectations shift, well-designed incentive strategies can help companies adapt and succeed.

But what if designing these plans requires more than the data-focused approach we use today? What if communication needs to do more than just inform participants about the plan? In today’s rapidly evolving business landscape, successful life sciences organizations must think differently about how they approach motivation and performance.

ZS has reimagined the incentive design process to create engaging, human-centered programs that reflect how people are truly motivated. Powered by AI and behavioral insights, these fair and adaptive structures drive the right behaviors and align with business and field goals.

Research indicates that well-designed sales incentive programs can significantly boost revenue. For example, McKinsey reports that companies could achieve up to a 50% higher impact on sales from adjusting their compensation models compared to increasing advertising investments​. The Incentive Research Foundation found that sales incentive programs led to a net sales gain of approximately 7.5% in some cases.​​ Additionally, a study highlighted by Harvard Business Review suggests that incentive programs aligned with profitability rather than just sales volume can further optimize financial outcomes.

For many years, designing fair and fiscally responsible incentives using data has been the holy grail of incentive design. The focus has always been on getting quotas as accurate as possible and designing payout curves and commission rates that get the plan payouts as close to the budget as possible. PowerPoint presentations and PDF one-pagers are considered sufficient plan dissemination to participants, and emails are still the most common mode of communication. A recent ZS study found that 70% of respondents do not allow any form of customization in their incentives, with an increase in complexity cited as a key reason.

As we design incentive programs for the workforce of the future, we need to ask questions such as:

• What is our organization’s total rewards philosophy—and how do our incentive plans support it?
• What do we know about the sales force as individuals and what truly drives them to perform better?
• What new data and methodologies are now available to us that can make design analytics even more insightful and holistic?
• What other tools and techniques can help us elevate our communication process and enable us to “speak the same language” as the plan participants?

The figure shows what an updated approach might look like.

The first step to designing incentives that motivate employees is to understand what drives the organization forward. A great place to start is to develop a robust understanding of the company’s mission, vision and core values to grasp the broader context of the culture and business objectives. In-depth interviews with senior leadership are critical for developing a robust understanding—they also help getting leadership buy-in from the start.

Understanding the organization’s talent acquisition, development and retention strategies, as well as internal mobility practices, leadership development programs and recognition systems can provide additional flavor to the assessment. It is also crucial to evaluate the competitive landscape, benchmarking against industry peers to understand where the company stands in terms of salary scales and talent management practices. 

Before delving into the mechanics of an incentive plan, a comprehensive understanding of the workforce’s demographics, attitudes and behaviors is crucial. It lays the foundation for designing incentives that resonate with employees and drive desired outcomes. Workforce analytics and surveys are powerful tools to gain these insights. Workforce analytics and surveys are powerful tools to gain these insights.

Workforce analytics teams collect and analyze data on employee demographics, skills, performance and turnover. This data can be derived from HR information systems, performance management platforms and other enterprise tools. Analytics help identify trends and patterns that inform incentive design.

Analytics can also help in understanding the generational makeup of the workforce, which can influence the types of incentives that resonate with different groups. For example, a Society for Human Resource Management study revealed that Generation Z and millennials value recognition in the workplace and are more likely to stay in their roles even when given small rewards.

One-on-one interviews, focus groups and surveys provide qualitative insights into employee attitudes and preferences. These methods reveal what motivates employees and make them feel included in the design process. Anonymous surveys allow employees to voice their opinions on current incentive programs, workplace culture and overall job satisfaction. They also offer a platform for employees to suggest improvements and highlight areas where incentives can make a real difference. Analysis of these insights reveals how employees in different groups view incentive plans and what they’re willing to exchange for better rewards.

Designing effective surveys involves asking the right questions. Consider including questions about employees’ perceptions of fairness, work-life balance, career development and recognition. You can also ask employees to rank different types of incentives, such as cash bonuses, flexible work arrangements, additional time off or professional development opportunities. These responses can guide you in crafting a plan that aligns with employee expectations and preferences.

Products and markets are more complex than ever. Deep understanding of brand objectives, the target audience and the marketing team’s approach to customer behavior shapes product success. Simultaneously, in life sciences, particularly in pharma organizations, the role of the rep has also evolved, necessitating redesigned incentives to drive different behaviors. 

The evolution of the role of the sales rep means that now companies can bring together tech and analytics to lead customers through personalized journeys, using digital tools to break down barriers and connect to customers where they are. With ZS’s proficiency in analytics and data science, we can turn data into insights to help companies understand the emotional and functional sparks that motivate customers to act and overcome the barriers that prevent them from acting. Human sales reps, empowered by AI, can act as mainstays, not mere messengers, by focusing on solving customer problems. In medtech as well, the role of the rep has changed, due to complex regulatory environments and evolving healthcare needs. This evolution requires a thoughtful redesign of incentive models to motivate medtech reps to embrace novel sales strategies, educate on intricate device functionalities and navigate the competitive landscape effectively. 

Research indicates that misalignment between sales and marketing is a common challenge. For example, a 2019 study by LinkedIn found that 93% of sales and marketing professionals believe that poorly aligned teams negatively affect business growth, yet only 23% of respondents reported strong alignment between sales and marketing in their organizations. Additionally, 40% of survey respondents say sales and marketing goals are being measured by different metrics.

Including the marketing team early in the incentive design process can help ensure that the plan is designed to meet brand objectives and the KPIs tracked by marketing can be valuable inputs into the plan components themselves. Conversely, the marketing team should include the incentive design specialists in their processes and conversations to ensure an appropriate understanding of the brand priorities and that incentives are not misaligned. For example, for many organizations, limited customer strategy and planning prevent many organizations from benefiting fully from coordinated, multichannel outreach.

This part of the incentive design journey may feel familiar to most, since it is where the bulk of the effort is focused. Design teams typically use historical performance data and the latest customer universe to make adjustments to goals, payout curves and commission rates to design the plan for the upcoming year.

Although this a relatively mature process, there are opportunities to accelerate using AI. Traditionally, most analytics have been limited to the basics (for example, retro testing, correlation charts); we can evaluate multiple parameters in goal-setting, conduct analyses using natural language models and reduce the overall time and effort required for plan modeling.

We can combine the power of AI with the insights from brand imperatives, organization philosophy and workforce analytics to design incentives faster and in a more customized manner. Some ways in which AI can increase the impact of the incentive compensation design process are:

• Data-driven analysis: AI can analyze large volumes of historical data to identify trends and patterns in employee performance, engagement and retention. This allows companies to understand what incentive structures have been most effective in the past and to use these insights to inform future plans.
• Predictive modeling: Machine learning algorithms can be used to predict employee behavior based on different incentive scenarios. By simulating various compensation models, AI can help identify which plans are likely to yield the highest motivation, productivity and retention rates.
• Continuous learning and improvement: AI systems can continuously learn from new performance and incentive payout data, allowing organizations to adapt their incentive plans near-instantaneously. This ensures that the incentive plans are always modeled based on the latest data and that financial modeling is always up to date, reducing the lag between data and decisions.

Using AI tools, we can reduce the time required to model incentive plans, design innovative plans that are customized to individual needs and uncover hidden patterns in performance that would have otherwise been missed in the design process.

Effective communication is a crucial component of an effective incentive program—but it is often overlooked or thought of as the final step. Communication should be planned up front; regular messaging of incentive priorities can help get increased engagement from the sales team and leaders. It is not sufficient to just communicate often; personalizing communication is essential to ensure that employees understand the plan and feel valued as individuals. A generic email blast won’t suffice.

Here are some key considerations for a personalized communication strategy:

• Innovative communication: Life sciences companies should use storytelling techniques to illustrate the benefits of the incentive plan and share success stories from within the organization. Similarly, medtech companies can demonstrate the impact of their medical technologies on patient care and healthcare outcomes. With new AI-based tools, creating engaging animated videos is easier than ever. These tools can be the difference between an exciting, engaging incentive plan and just another company video about how to make a paycheck.
• Multimodal engagement channels: People consume information differently, so it’s important to use multiple communication channels. Given the diverse environments life sciences employees operate in, from offices to hospitals and clinics, it’s crucial to adopt a variety of communication methods. Leverage a combination of email, video, intranet posts and in-person meetings to reach all employees. Some employees may not regularly check email, while others in the field cannot attend office hours. “Change champions”—members of the field team who have been involved in the design process—can help propagate this information more broadly and support adoption.
• Feedback and interaction: In this industry, where products and regulations are complex, it’s vital to encourage feedback and interaction throughout the communication process. Create opportunities for employees to ask questions, provide suggestions and discuss the incentive plan. This two-way communication helps address concerns, build trust and ensure that employees feel heard. This dialogue can uncover unique insights into how the plan affects life sciences field operations and, ultimately, patient outcomes.
• Role of leadership: Leaders play a crucial role in reinforcing the incentive plan’s importance. Senior leaders should actively participate in communication efforts, emphasizing their commitment to the plan’s success. Leaders can also share their own experiences with incentive programs, highlighting the positive impact on performance and career growth. Further, drawing connections between employee performance and its direct impact on advancing healthcare solutions can be motivational. When leaders share personal stories about the power of incentive plans, it underscores their value beyond financial gains, highlighting contributions to career growth and the broader mission of improving patient health.

Designing an effective incentive plan is a multistep process that goes beyond traditional fairness testing and performance distribution evaluations. It begins with a deep understanding of the organization, the workforce and the brand objectives through in-depth interviews, workforce analytics and surveys and pulls through with innovative communication techniques that grab the salesperson’s attention.

Incentive compensation is more than just payouts—it’s a strategic lever for motivating the workforce, enabling effective sales execution and achieving better business outcomes. Without an innovative approach toward incentives, organizations will find that their sales teams are not adequately challenged or rewarded, resulting in lost revenue, decreased engagement and increased attrition. An AI-powered, human-centered approach creates adaptive, fair incentives that align with business strategy and motivate teams for a digital world.