Research analyst at a KPO: company profiles, sources and deadlines

What lands in the queue

Requests arrive from bankers, consultants, sales teams or strategy groups, usually through a request system with a deadline and a template. Typical work types:

• Company profile — business overview, segments, financials, management, recent developments.
• Industry primer — size, structure, key players, drivers, regulation.
• Comparable companies — a table of peers with financial and valuation metrics.
• Target screening — a long list of companies matching criteria, then a short list.
• News and event monitoring — daily or weekly digests on a set of companies or topics.
• Market sizing — a top-down or bottom-up estimate with stated assumptions.

A request might read: "Two-page profile of a mid-sized European packaging company, focus on India operations, by 9 AM London time." That deadline means late evening in India, which shapes the working day.

The artefact: a source log with quality grades

Every profile or primer should be backed by a source log that a reviewer can check quickly. The grades below are a common house convention, not an industry standard, and the entries are hypothetical.

The grading makes decisions easy. Grade A and B claims go in as fact with a citation. Grade C claims go in with attribution language ("reported to be") and a flag. Grade D is noted and left out. Row 6 is as important as row 1: it shows the reviewer that a tempting number was seen and rejected.

Two habits prevent the most common errors. Always record the period and currency next to a figure, since mixing a calendar-year number with a financial-year one is easy when parent and subsidiary report differently. And record the page or slide, because a reviewer who cannot find your number in thirty seconds will doubt the rest.

A sample day on a UK-facing team

• 11:00 — log in; read overnight client messages and prioritise the queue.
• 11:30 — finish the comparable companies table started yesterday; update share prices at the agreed cut-off.
• 14:00 — start the packaging company profile; build the source log as you go, not at the end.
• 17:30 — team lead review of the comps table; two peers questioned and replaced.
• 19:30 — overlap with London begins; clarify the scope of the India section with the requester.
• 21:30 — submit the profile after a checker's review; update the time sheet against the request.

Errors caught in review and deadlines met abroad

• Accuracy, usually measured by errors found in quality checks or by clients.
• On-time delivery against the stated deadline.
• Turnaround time for standard requests.
• Client feedback scores on requests.
• Utilisation — billable or productive hours against available hours, in many firms.

Team leads, reviewers and requesters overseas

Analysts report to a team lead or delivery manager, and above that an engagement manager who owns the client relationship. Work is checked by a senior analyst or reviewer. You interact with requesters abroad, database and information specialists, and sometimes graphics teams.

Confused with equity research analyst and data analyst

A sell-side or buy-side equity research analyst makes investment recommendations under a regulatory framework; a KPO research analyst usually supports someone else's recommendation or decision. A data analyst works with an organisation's own datasets, typically in SQL and BI tools; KPO research work is mostly secondary research and financial analysis in Excel and databases. The paths do cross: the source discipline carries over well, and the MIS executive guide shows another entry route into data work.

Secondary research, comps and UK-shift signals

• "Secondary research, company profiling" — the core work described here.
• "Financial spreading, comps, precedent transactions" — investment banking support.
• "Capital IQ, Bloomberg, Factiva, PitchBook" — named database experience valued.
• "UK/US shift" — late or early hours; ask about the exact schedule.
• "Primary research, expert calls" — you may interview people, not just read.

Templates first, then end-to-end requests

Month one: learn templates and pass review on standard profiles. Month two: take on primers and screening. Month three: handle a request end to end, including scoping calls. Next roles include senior analyst, team lead, delivery manager, or moves into strategy, corporate development or data analyst roles. The Data Analyst programme adds SQL, Power BI and statistical analysis on top of the source discipline research work already builds.