
LEAP trainees are expected to think commercially even in an entry role. This tests structured problem-solving, data use, and customer empathy.
Show a logical flow: data gathering (internal sales reports, store visits, competitor checks), diagnosis, and a specific, costed recommendation. Mention engaging the team and tracking results. Keep it simple and actionable.
Start by anchoring your first week in data and ground truth, not assumptions. Pull the last quarter's sales records, route plans, and inventory movement per outlet, then segment the drop by area, product line, and customer type to see if the decline is concentrated or across the board. In the same week, get out to at least ten stores in the worst-affected zones and talk to sari-sari store owners and wholesalers directly, asking open questions about pricing, stockouts, and what they hear from their own customers. By week two, compare your findings against competitor activity, new product launches, or any policy shifts that might have changed buying behavior, and check if the drop aligns with a seasonal pattern or a one-off event. Then propose a recovery plan that ranks actions by cost and impact, for example, renegotiating display space, adjusting promo mechanics, or retraining the sales reps on the territory, and put a simple tracking sheet in place with weekly check-ins. Say plainly that you would validate the plan with your supervisor and the field team before rolling it out, and frame it as a test-and-learn approach so you can adjust quickly. Keep your tone direct and confident, and avoid filler phrases like "more or less" or "parang," because the interviewer is watching for clarity and ownership.
Many fresh grads panic and say "Mag-coconduct po muna ako ng survey" without specifying methodology or action. Others get lost in jargon without offering a concrete sequence. Avoid vague Taglish like "Titingnan ko po yung figures, tapos ayusin yung problema" which shows no analytical framework.
Situation
During my internship at a local dairy distributor, our key account in the NCR+ region reported a 20% volume drop versus the previous year, and the regional manager asked me to investigate.
Task
I was to produce a root cause analysis and a one-page proposal within two weeks, using available sales data and store visits.
Action
I pulled three months of SKU-level sell-out data from the company's system, created a simple trend chart in Excel, and flagged that two top-selling SKUs had frequent stockouts. I visited 10 high-volume sari-sari stores and learned from owners that a competitor had introduced a similar product at a 10% lower price and gave free display racks. I cross-checked with the pricing team and found our trade margins hadn't changed. I recommended a time-bound "buy 2 get 1" promo on the affected SKUs, reallocation of delivery schedules, and training for store staff on upselling.
Result
The manager approved the promo; within 30 days, sales rebounded by 13%, and the store owners appreciated the direct engagement. The competitor's share returned to previous levels.
Data tells you what is happening; talking to customers tells you why. Combining both creates practical solutions.
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