Portfolio decisions are expensive to reverse. Therefore, they need to be tested before implementation . Scenario analysis shows how the portfolio will shape up under different budget, capacity, and market assumptions. In enterprise applications, this is achieved through simulation environments that run on a copy of the existing portfolio.
Typical scenario questions
If the R&D budget is cut by 20%, which projects will survive and how will this affect revenue three years from now?
If we add two more people to a key engineering team, how many months will each launch be brought forward?
If our main competitor enters the market with a new product, which of our product lines will be at risk?
If the price of a raw material increases by 40%, how many products in the portfolio will move into the loss zone?
If we remove 120 low-volume SKUs from the portfolio, how will the balance between revenue, margin, and customer loss be affected?
If a new customs duty or regulation is introduced, which of our products in which markets will be affected?
The requirements for scenario analysis to work.
Scenario analysis is only meaningful when based on a single database . If sales data is in one system, cost data in another, and capacity data in a spreadsheet, running the scenario will take days, and the results will become outdated.
In an integrated system, the scenario can be set up within minutes on a copy of the existing data and discussed live within the decision-making meeting.
Benefit to the customer
Decisions are made not by intuition, but by anticipating the consequences.
During times of crisis, decisions to cut costs are made with full awareness of their impact, not blindly.
Alternatives can be presented to the board of directors together.
The response time to market shocks decreases from weeks to hours.