Panda Doc in Pigment

Inside a Pigment Implementation: Metrics, Naming Standards, and Workforce Planning

A recent walkthrough of a completed Pigment implementation provides key insights into how this modern planning tool compares to legacy systems like Planning Analytics, and how it supports scalable, structured financial planning—particularly for workforce management.

Workforce Planning and Metric Structure

In Pigment, workforce planning is broken into several distinct but related metrics:

• Base Salary Metric: Captures the core salary, including merit increases.
• Bonus Metric: Separately tracks expected bonuses.
• Direct Compensation Metric: Combines base salary and bonus into one aggregated value.

This layered structure not only allows for flexibility in data visualization (e.g., showing intermediate calculations in tables), but also simplifies downstream use, such as tax calculations or cost modeling. While it’s technically possible to consolidate these calculations into fewer steps, maintaining modular metrics provides transparency and auditability.

Conditional Calculations and Formula Design

Pigment supports complex formulas with conditionals, and these can be used within a single metric or across multiple data sets. For example, a single metric might apply logic that changes calculation methods based on business rules or time periods. This conditional structure makes Pigment a powerful tool for dynamic modeling scenarios.

Naming Conventions and Organizational Standards

Naming consistency is vital when working with large models containing hundreds of metrics. To address this, a standard naming structure has been developed:

• Push and Pull Metrics: Metrics that move data between applications (e.g., workforce planning and reporting) use a suffix system. For instance:
  • metricName_push for outbound metrics
  • metricName_pull for inbound references

This makes it easier to understand data flow at a glance and supports maintainability across connected models.

Folder structure and capitalization standards are also employed to promote organization and usability. These were adapted from Pigment’s prebuilt assets, which are often overly complex, and streamlined for more practical day-to-day use.

Navigation and Efficiency

Pigment includes built-in tools to improve user navigation:

• Search Functionality: The platform allows for quick access to metrics using a global search bar or keyboard shortcuts (like Ctrl+K). Users can locate any metric by typing partial names, which becomes especially useful in models with extensive data.

This Pigment implementation showcases how thoughtful structuring of metrics, use of conditional logic, and naming conventions can create a scalable, transparent, and user-friendly financial planning environment. These best practices not only make the platform easier to use but also prepare it for long-term sustainability as models grow in complexity.