Nikita Raj
Supply Chain Consultant
Pricing is a powerful lever for profitable growth. A mere 3% price adjustment, when managed precisely, can improve operating margins by over 10%. However, the risk of customer shifts or supply chain disruptions often makes leaders cautious. This is precisely where Price Simulation within Integrated Business Planning (IBP) makes a difference. By running rapid, verifiable "what-if" scenarios, teams can accurately foresee how changes to pricing or promotions affect demand, revenue, profit, and supply chain capacity before committing execution.
For instance, a 5% price adjustment in a high-value market might reduce expected demand by a minimal 2%, significantly increasing revenue. Yet, applying the same adjustment in a price-sensitive market could cut demand by 6%, causing profit erosion. Simulation allows companies to identify these details and optimize prices at a specific level.
The Challenge with Standard Planning Tools
Standard IBP systems align planning functions but are not built for complex pricing decisions. Their reliance on historical averages and static assumptions ignores the non-linear, time-dependent nature of customer behavior. Furthermore, older architectures, separate from core data sets, result in slow, fragmented processes. This methodology often leads to flaws: temporary sales improvements from discounts that damage long-term profitability, excessive forecasting that leads to excess inventory, and separated views that cause disagreements between Sales, Operations, and Finance teams
CT Plan Apps: Planning with Price as a Variable
Celebal Technologies solves this with IBP by CT Plan Apps,, for superior processing and featuring an intuitive, Databricks for superior processing and featuring an intuitive, spreadsheet-style interface (Sigma), this system places advanced planning directly onto a single, governed data source.. This ensures that every department operates with the same information and targets.
Our platform embeds a mathematical optimization engine directly within the IBP framework. It combines AI-based time-series forecasting with operations research. Critically, it uses Pricing as a core input for AI demand models, providing visibility into every expected financial and operational impact.
Core Components for Pricing Strategy
- AI Demand Prediction: The system estimates specific changes in customer demand based on prices. It accounts for product relationships, providing accurate, unbiased forecasts.
- Scenario Testing: Planners can quickly test unlimited pricing concepts to assess the combined impact on revenue, margin, and constraints like manufacturing capacity.
- Continuous Improvement: As actual outcomes are recorded, the self-adjusting AI models improve future pricing recommendations.
Confident, Profitable Decisions
IBP by CT Plan Apps moves pricing from a subjective guess to an objective optimization challenge, giving leaders the certainty needed to make the correct move.
- Quantify Trade-offs: See exactly how a 2% discount aids demand but stresses capacity, or how a 5% regional adjustment improves the margin with minimal customer loss.
- Find Best Prices: Use optimization to locate the ideal price across numerous items, channels, and regions simultaneously.
- Align Functions: Sales, Operations, and Finance share a single dashboard showing the same modeled results, unifying their approach.
Stop making pricing decisions based on assumptions and start planning with confidence!
Request a personalized demo to see how IBP by CT Plan Apps can integrate precision pricing into your planning cycles.
