The examples below are illustrative scenarios, not client case studies or claims of measured results. They show how we connect a business question to data, a usable solution, and an agreed way to evaluate it.
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Business question: Which products, branches, or customer groups need attention?
Starting point: Sales and cost records spread across spreadsheets or business systems.
Solution approach: Agree on revenue and margin definitions, prepare the data, and build a dashboard with filters and drill-down views.
Example outputs: Sales and margin trends, a shared KPI reference, refresh rules, and a guide for business users.
How to evaluate: Reconcile figures with the agreed source, check refresh reliability, and observe whether users can answer their priority questions.
Business question: Why do some branches run out of stock while others have excess inventory?
C — Corporate: Align product and location identifiers, define available stock, identify data owners, and check lead times, permissions, and freshness.
B — Business Intelligence: Build a shared view of stock aging, slow-moving items, stock-out risk, and branch differences.
A — Artificial Intelligence: Use the same definitions and business rules to explain a risk and prepare a transfer recommendation for a responsible person to review.
How to evaluate: Check source reconciliation, recommendation validity, required approvals, and confirmed outcomes. This is a demonstration scenario, not a completed client project.
Business question: How can employees find an approved procedure or policy without searching many documents?
Starting point: Internal documents with different owners, versions, and access rules.
Solution approach: Select approved sources, define access boundaries, and pilot an assistant that references its sources and hands uncertain questions to a person.
Example outputs: A limited assistant pilot, a source register, access rules, and an evaluation set.
How to evaluate: Check answers against source documents, test permissions and uncertain questions, and collect feedback from intended users.
Business question: Can a repetitive internal request move through the process with less manual coordination?
Starting point: Requests arriving in messages or forms and being copied between systems.
Solution approach: Map the process, use AI where useful to structure the request, validate required information, and keep approval with the responsible person before an action changes records.
Example outputs: A workflow pilot, an approval checkpoint, a status view, and an activity record.
How to evaluate: Measure confirmed task completion, review effort, failure handling, and duplicate-action prevention against the current process.
Your data, systems, and operating rules determine the final design. We agree on a scope and success measures before implementation.
Data Story serves organizations across Thailand.
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