Foresight’s multidimensional modeling engine provides a new foundation for the future of revenue performance
TORONTO, ON — September 29, 2026 — Varicent, a leader in Sales Performance Management, today introduced a new architecture for revenue performance. The new architecture is specifically designed for the complexity and interdependence of today’s go-to-market. It allows revenue teams to model decisions in greater depth, understand the impact of those decisions across the organization, and continuously improve how they plan and operate.
At the center of the new architecture is Foresight, a multidimensional modeling engine and environment built specifically for revenue planning. Foresight brings capacity, territories, quotas, incentives, market opportunity, and other planning variables into an integrated model, giving teams a clearer view of how decisions interact before they reach the field.
Revenue planning requires teams to work across many interdependent variables at once. A change to a territory can affect capacity, quota attainment, account coverage, and incentive costs. A shift in market opportunity can change where resources should be deployed.
Multidimensional modeling has been used in enterprise FP&A and other forms of operational planning for years. But until now revenue planners have had to adapt general-purpose planning engines to the specifics of the revenue org. Foresight, in contrast, was designed from the beginning around the way revenue organizations actually operate. It’s purpose-built to handle these complex relationships dynamically, allowing teams to change assumptions, recalculate the plan, and understand the effects across the organization without rebuilding the model from scratch, preserving historical context.
“Revenue performance is not one problem,” said Marc Altshuller, CEO of Varicent. “It’s the result of hundreds or thousands of interdependent decisions about where growth will come from, where resources should be deployed, how territories and quotas should be set, and how people should be motivated. Foresight delivers what many customers have been asking about for years: a fundamentally better way to model those decisions together and understand how they affect performance.”
Foresight also marks an important evolution in the architecture of the Varicent platform.
Because of its inherent complexity, revenue performance demands different types of calculations for different problems. Enterprise incentive compensation, for example, requires processing massive volumes of transactions accurately through complex rules. Territory and capacity planning, in contrast, require teams to rapidly model alternatives, recalculate assumptions, and compare different views of the business.
Varicent’s platform is evolving to leverage multiple calculation engines, each built for a specific revenue need but all operating within the same integrated platform. This allows Varicent to use the right engine for each problem without breaking revenue performance into separate applications.
Foresight adds a multidimensional modeling engine for revenue planning, expanding the problems Varicent can solve while keeping planning and performance together in one platform. Foresight operates alongside the platform’s existing transaction engine, which will continue to support enterprise incentive compensation.
“The idea is straightforward: use the right engine for the problem while preserving the context and relationships across the platform,” said Neil Whitney, Chief Product and Innovation Officer at Varicent. “That lets us solve very different revenue problems without turning the platform into a collection of disconnected applications.”
Foresight gives revenue teams a unified model of the decisions that shape performance, including how those decisions change over time. Varicent can then relate those planning decisions to the performance signals that follow.
This matters because many apparent sales execution problems are actually the logical consequences of decisions made during planning. Because Varicent connects these performance signals to the planning decisions that shaped them, practitioners can see which planning assumptions should be changed to produce a better outcome.
That same connection gives Varicent’s AI the context it needs not just to flag underperformance, but to understand which planning decisions contributed to it and what should change in the next cycle.
“The real opportunity with AI is not simply to explain performance after the fact,” said Altshuller. “It’s to take what teams learn from each cycle and turn it into better decisions and better actions in the next.”
Foresight is the first major expression of Varicent’s new architecture for revenue performance, and a foundational step in the broader evolution of the platform. New modeling, intelligence, and AI capabilities will continue to expand that architecture throughout the coming year.