4 ways leading pharma teams are rethinking IC

A formulary shift changes the opportunity in several territories. A competitor gains ground faster than expected. A new indication launches, but adoption is uneven. A direct-to-patient channel starts influencing demand in ways the field team cannot easily see.

Something we hear from clients is that any one of these can create the same chain reaction:

• Reps question whether their goals are still fair.
• Managers ask how payouts will be affected.
• The incentive compensation (IC) team is left trying to implement changes while the cycle is already underway.

By the time the plan catches up, the field may have already lost confidence in it.

That is why leading pharma teams are taking a fresh look at IC to build a process that can move faster, explain decisions more clearly, adapt when conditions change, and maintain trust in how people are paid.

IC was built for a simpler commercialization model

IC is where commercial strategy becomes personal for the field. If teams cannot explain goals, adapt to market change, and pay accurately, the field loses trust, even when the plan design is sound.

Commercialization no longer follows a straightforward rep-to-prescriber model. Field teams now operate across hybrid channels, patient-support models, digital engagement, payer and government-driven access dynamics, complex account structures, and growing direct-to-patient activity.

At the same time, the shift toward specialty, rare disease, and orphan drugs has made patient populations smaller, territories more nuanced, and performance harder to evaluate through traditional activity or volume metrics alone.

The rep role is changing. Reps are being asked to understand access barriers, coordinate with patient support and medical teams, interpret digital and omnichannel signals, and play a broader role in moving the right patients toward therapy.

That means IC is no longer just about calculating payout against a plan. It is part of a larger orchestration challenge: bringing together the right data, context, rules, and performance signals so teams can understand what happened, what it means, and what to do next.

Organizations are managing more data than ever: sales, claims, affiliations, targets, territories, patient density, product performance, digital touchpoints, and plan performance signals. Often, this complexity makes IC harder to administer, validate, and explain. However, when that data becomes “IC-grade,” it helps make IC more precise and streamlines orchestration.

Where today’s IC is falling short

Many programs still depend on manual work across the entire lifecycle: plan creation, goal setting, data validation, market change assessment, plan updates, payout processing, exception handling, audit, reconciliation, and rep inquiry management.

That manual work creates a fragile process prone to delays, errors, and confusion that directly affect the field.

The table below shows how those operational breakdowns often appear in the field and why they matter.

These challenges are especially difficult because IC is rarely one-size-fits-all. Different rules might be required by role, brand, market, territory, product maturity, or business objective.

However, every variation adds operational burden, and building a system flexible enough to manage that complexity is difficult. Standardized tools can be too rigid; fully bespoke approaches can be slow, expensive, and difficult to scale.

4 things leading teams are doing differently

For IC teams, the challenge is no longer just designing the right plan. It is creating a process that can administer, explain, and adjust compensation as conditions change.

Because IC directly affects how people are paid, how reps prioritize their time, and how much confidence the field has in leadership, modernization has to be both ambitious and controlled. Leading teams are looking for ways to move faster, reduce manual work, improve transparency, and adapt to market change without sacrificing accuracy, governance, or trust.

This is where leading teams are focusing their efforts:

1. Automating more of the IC lifecycle

The shift:

One-off handoffs are being replaced with configurable workflows, reusable plan logic, automated validation, locked plan versions, time-bound data snapshots, and clearer approval paths.

That creates a more controlled way to manage complexity, so changes can move faster without sacrificing accuracy, auditability, or trust in the final payout.

What it enables:

• Faster plan launches
• Quicker response to market changes
• Fewer payout delays and errors
• Better governance and auditability
• Less time spent chasing issues manually
• More capacity for strategic IC decisions

2. Reducing goal-setting friction

The shift:

Leading teams are putting more structure around goal-setting and review, especially in markets where access, patient opportunity, territory dynamics, and historical performance vary widely. The focus is less on reinventing goals and more on making the process faster, more consistent, and easier to explain when reps or managers ask why a goal was set.

What it enables:

• Earlier visibility into goals that may need a second look
• Fewer avoidable disputes after goals are released
• Clearer explanations for goal decisions
• More confidence from reps and managers
• A better foundation for future fairness checks, scenario modeling, or AI-assisted validation

3. Giving reps clearer visibility into performance and pay

The shift:

As commercial execution becomes more coordinated, reps need a clearer view of how their activities, account progress, access dynamics, and other performance drivers collectively translate into compensation. Greater transparency helps build trust in the process and gives reps a better understanding of the behaviors and actions that will influence future performance and payout.

To support this, teams are giving reps and managers clearer visibility into performance, payout calculations, and the drivers behind changes. That can include field-facing scorecards, payout calculators, explainable reporting, and structured ways to handle payout questions, goal disputes, data issues, and exceptions. The goal is not just to answer questions faster but also to make IC feel less like a black box.

What it enables:

• Fewer payout escalations
• Faster answers to rep questions
• Better tracking of disputes and exceptions
• Clearer visibility into recurring data or plan issues
• More trust in the IC process
• Less manual burden on managers and IC teams

4. Building more flexibility into plan changes

The shift:

Teams are creating a more controlled way to evaluate and implement changes when business conditions warrant it. With clearer governance, configurable plan logic, controlled approvals, localized rules, and scenario views, they can understand the impact of a change before it reaches the field and act quickly, accurately, and transparently.

What it enables:

• Controlled mid-period adjustments
• Faster response to access, competitive, or launch changes
• Localized plan variation without one-off workarounds
• Better visibility into the impact of proposed changes
• Stronger governance and auditability
• Better alignment between IC and market reality

Keeping up with market change and evolving field roles

As market conditions shift faster and field roles become more coordinated, IC teams need better ways to see what is changing, understand the impact, and adjust without creating confusion or mistrust.

• “There is a lot of interest from clients to use AI for incentive compensation, especially around areas like territory balancing, goal setting, and identifying potential bias or gaps in the data. But there’s still uncertainty about how to use it effectively.
• The opportunity lies in bringing the right framework, the right data, the right prompts, and the right expertise to the process. That is where AI can start to become useful in IC: helping teams move faster from data to estimated payouts, flag data or payout anomalies, compare scenarios before making changes, and make plan administration more nimble and transparent.”
• -Melissa McDevitt, Partner, Beghou

That near-term opportunity is mostly operational: helping IC teams move faster, reduce manual work, and build more confidence in the numbers. It also points to a larger shift. As commercialization models become more coordinated, IC teams will need better ways to understand not only what happened but also what contributed to performance and how different roles influenced the outcome.

Those capabilities may also matter as field roles continue to evolve. As Beghou Partner Rohit Gupta describes, the "rep of the future" may look more like a data-enabled connection point, someone who works with field, digital engagement, access, patient support, analytics, and medical stakeholders to improve account and patient outcomes. In that model, AI could help teams not only work faster but also see where to focus, how to coordinate, and what actions may influence future performance.

As this model evolves, companies may need new ways to define, measure, and reward contribution across the team. That could mean increased adoption of indicators such as patient starts, adherence, time to therapy, account progress, or other measures of coordinated impact, not as a replacement for sound IC design but as part of a broader effort to connect field activity, commercial orchestration, and incentive outcomes.

A stronger foundation for modern IC

By improving speed, transparency, accuracy, and flexibility, leading teams can give reps more confidence in their plans, managers clearer answers, and commercial leaders an IC approach built for how commercialization works today.

Just as importantly, they can create a foundation for continuous improvement and AI enhancements, where IC is easier to test, refine, and adapt as field models, market dynamics, data needs, and commercial orchestration become more complex.