Few business decisions look as simple — and are as interconnected — as changing a price.
A 5% increase does not necessarily mean 5% more revenue. A 10% discount does not simply mean giving up 10% of one sale. Price changes behavior: volume, conversion, mix, frequency, retention, perceived value, commissions, margins and working-capital needs.
What economic behavior do we expect to produce — and how will we know whether our hypothesis was correct?
Before changing: build the economic model
Every meaningful change should begin with a baseline. Understand realized price, average discount, volume, contribution margin, product mix, variable cost, cost to serve, payment terms, customer concentration, churn, conversion and seasonality.
Without a reliable baseline, every comparison that follows is fragile.
Contribution margin changes the conversation
Unit contribution margin = net price − variable costs and expenses
Consider a product sold for R$100 with R$70 of total variable cost. Contribution margin is R$30. If price rises to R$110 while variable cost remains unchanged, contribution becomes R$40.
Approximate maximum volume loss = 1 − old margin / new margin = 1 − 30 / 40 = 25%
In this simplified scenario, volume could fall by approximately 25% before total contribution becomes lower than before. This is more useful than looking at the percentage price change alone.
Elasticity: price and volume do not move independently
Price elasticity of demand seeks to measure how much quantity reacts to a change in price.
Elasticity = percentage change in quantity / percentage change in price
Because price and demand often move in opposite directions, the coefficient is commonly negative; managerial analysis often focuses on its absolute magnitude. But a company rarely has one single elasticity. It may differ by segment, region, channel, product, customer size, contract or competitive context.
Simulation does not mean predicting the future perfectly
The purpose of simulation is to make assumptions explicit before capital is put at risk.
| Variable | Conservative | Base | Favorable |
|---|---|---|---|
| Price change | +5% | +8% | +10% |
| Volume | -8% | -4% | 0% |
| Average discount | Higher | Stable | Lower |
| Mix | Worse | Stable | Better |
| Margin / cash | Calculated | Calculated | Calculated |
The goal is to know the break point, the risk being accepted, what result justifies continuing and which condition should stop the change.
Six Sigma applied to economic decisions
Six Sigma is especially useful when the organization needs to distinguish perception from evidence. A pricing decision can be structured through DMAIC.
DEFINE
Define the problem and the outcome variable Y: recover margin, reduce discounts, improve profitability per customer or increase return on constrained capacity.
MEASURE
Create a reliable baseline for margin, realized price, conversion, volume, churn, mix and recurrence. Poor data can create very precise conclusions about a reality that does not exist.
ANALYZE
Investigate which X variables explain Y: price, discount, channel, salesperson, region, product, quantity or customer profile. Correlation, regression, segmentation, ANOVA and hypothesis tests help reduce the risk of attributing causality to the wrong factor.
IMPROVE
Instead of changing everything at once, run a controlled pilot by customer group, region, channel, product line or time window.
CONTROL
Continue measuring after implementation so discounts, mix changes, competitive responses or internal behavior do not silently erase the improvement.
Hypothesis testing: did the change actually work?
H₀: the change did not produce a meaningful economic improvement.
H₁: the change improved the defined economic indicator.
The indicator could be contribution per customer, contribution per order, margin per unit of capacity or net revenue per customer.
Statistical significance is not the same as economic relevance.
A good decision considers effect size, confidence interval, sample size, variability, financial impact and implementation risk together. Statistics does not replace executive judgment; it improves its quality.
After changing: measure what actually happened
Price realization
How much of the announced increase reached the actual net selling price after discounts and concessions?
Total contribution margin
Did percentage margin improve? Did absolute contribution improve? Both matter.
Volume and conversion
Is the decline within the expected range? Does behavior differ by segment?
Mix and retention
Did customers move to lower-margin products? Were lost customers strategically valuable or economically unattractive?
Economic information as a growth instrument
The same discipline can be applied to hiring, new units, products, geographic expansion, capacity, investments, automation, outsourcing or acquisitions.
Ask three questions: What is the economic hypothesis? How can we simulate it? What evidence will tell us to scale, adjust or stop?
Financial information should not only explain what happened. Mature organizations also use it to understand what can happen and what actually happened after a decision.
If your company changed price, discount, capacity or channel tomorrow, which indicators would allow you to prove — rather than merely believe — that the decision worked?