ContentClient Context

A Fortune 100 BFSI organisation was setting up its first Knowledge Management (KM) team in India to support high-stakes, regulated, global proposal workflows.

Their definition of “Knowledge Management” had two distinct parts:

1. Industry-specific proposal writing
   Creating proposals tailored to a specific industry segment (often referred to as portfolios in enterprise BFSI environments).
   
2. A living proposal knowledge system
   Managing a structured repository where proposals, bid decks, and reusable content blocks could be stored, searched, and adapted for future bids—without recreating material from scratch.
   

The Real Business Need

This team served two outcomes:

1) A shared internal knowledge engine

A knowledge backbone used across multiple departments, kept current in near real-time, so teams weren’t working off outdated content.

2) Direct revenue enablement

Even though the business operates in BFSI, the core motion is still sales.
The KM team was designed as a sales acceleration function focused on improving speed, consistency, and quality of proposals tied to revenue.

The Challenge

The initial JD was authored outside India and didn’t map cleanly to Indian market titles or recognisable talent pools.

Then we discovered a more critical gap:

Candidates from sectors like SaaS and Healthcare often looked perfect on paper for proposal + content management work.

But the regulatory and compliance scrutiny in those environments was typically lower than what this BFSI organisation operated under.

That meant: even with strong writing and process skills, many candidates lacked the behavioural muscle needed to succeed in a regulated enterprise proposal system (governance discipline, precision, stakeholder rigor, audit-ready thinking).

And getting it wrong wasn’t a minor miss, it risked early attrition, and reputational exposure for the India delivery lead with global stakeholders.

What We Did

Step 1: Calibrated what “KM” truly meant in their system

We ran deep alignment with the hiring team to map:

• What the KM function does day-to-day
• How it connects to revenue and proposals
• Which teams it supports cross-functionally
• The non-negotiable behaviours required to thrive

Step 2: Localised the designation for Indian market reality

We translated the role into titles and language that Indian candidates would immediately understand without diluting scope. This improved relevance and reduced mismatch conversations early.

Step 3: Ran cross-sector discovery before narrowing the search

We spoke to professionals across proposal writing + knowledge-system roles across sectors to stress-test fit. This helped eliminate pipelining people who matched the JD, but not the regulated enterprise operating style.

Step 4: Tightened the target profile (and accepted a smaller pool)

We narrowed the target to:

BFSI proposal writing profiles

• knowledge management exposure
• preference for international stakeholder experience

Yes, this shrank the pool significantly but it improved funnel quality.

Step 5: Switched from cold calling to structured nurturing

Because the pool was smaller and higher-value, we switched the approach:

• relationship-led outreach (not spray-and-pray)
• consistent feedback loops
• acting as a career sounding board, not just a recruiter

That gave us a stronger signal of intent and fit and ensured only the best candidates were presented.

The Tool That Made It Scalable: The Hiring Canvas

We documented the entire role system into a Hiring Canvas first to align with the hiring team, then to transfer the same clarity to our recruiters.This reduced rework, shortened calibration loops, and kept sourcing consistent across the team.

Outcome

With sharper alignment, localised role framing, and a nurture-led search motion:

• Sourcing-to-offer cycle reduced from ~8 weeks to ~2 weeks
  (dependent on interviewer availability and stakeholder turnaround)
  

More importantly, the hiring was driven by environment fit + behaviours, not just JD a match, thereby reducing early attrition risk in a high-visibility setup.

What This Proved

For roles at the intersection of revenue + compliance + knowledge systems, the hiring challenge is rarely “finding writers.”

It’s finding professionals who can operate inside:

• regulated expectations
• governance-heavy workflows
• cross-functional stakeholder ecosystems
• bid-driven timelines
• reusable knowledge discipline

That’s not a skills gap. That’s an operating environment + behavioural fit gap.