Imagine you are asked to prepare a financial forecast for a new business initiative at Ayala, but you have very limited historical data. How would you approach this?
RoleBusiness Analyst
DifficultyDifficult
TopicTechnical
Asked at
Why This Is Asked
The holding company constantly evaluates new ventures across industries. This question tests your ability to think structurally under uncertainty, a skill needed when supporting the Head of Corporate Planning.
General Approach
Acknowledge the limitation, then break down the problem: identify what you do know, find external proxies, consult internal experts, use scenario analysis, and be explicit about the confidence level of each assumption. This shows sound judgment.
General Answer
Start by explicitly separating what you know from what you're assuming: list the known inputs, such as market size estimates, comparable unit economics, and cost structures from similar businesses, and flag every assumption you have to make in place of missing data. Where the new initiative resembles an existing business, either within the group or in the broader market, use it as an analog: apply its unit economics, margins, or growth curve as a starting reference point rather than guessing from scratch. Consult people closer to the ground, operations or business development leads who have informal market intel, to sanity-check your assumptions before they go into the model. Build the forecast with a base, upside, and downside case rather than a single number, and be explicit in the presentation about which line items are high-confidence, such as known costs or contracted terms, versus low-confidence, such as market adoption rate or pricing elasticity. This transparency lets decision-makers see exactly where the real risk in the forecast sits, rather than treating a single point estimate as more certain than it is.
PH Interview Gotcha
Kung walang data, mage-estimate na lang ako ng katulad na product, tapos ilalagay ko sa Excel. Okay na yan, basta may maipakita.
Sample STAR Answer▾
S
Situation
During my internship at a local consumer goods company, the finance team wanted to estimate the first-year revenue of a new product line that had no sales history.
T
Task
I was responsible for creating a preliminary forecast model that could support a go/no-go decision, despite the lack of internal benchmarks.
A
Action
I researched market reports for similar products, identified the key demand drivers like population demographics and competitor pricing, and built a simple model with best-case, base, and worst-case scenarios. I also interviewed the product manager to validate my demand assumptions and understand the planned distribution channels. I clearly documented every assumption in the model.
R
Result
The forecast gave the management team a range of outcomes and highlighted the sensitivity to price changes. They used it as a starting point for further refinement, and my manager appreciated that I did not pretend the numbers were exact.
Key Takeaway
When data is scarce, transparency about assumptions and scenario planning is more valuable than a single, misleading point estimate.
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