Case Study: Executive Search and Recruiting

Building the operating backbone: from chaos to AI-powered efficiency

Five months after launch, a two-person executive search firm was still running its entire business out of overloaded inboxes. Within months of bringing in a Vannin [now the Chief of Staff Association] chief of staff, it had a connected tech stack, a proprietary data asset, and a financial model shaping its first fundraising conversations.

Challenges

The firm launched in May 2024 as a small, founder-led executive search and recruiting business. By the time Kevin joined as interim chief of staff in December, the company was five months into operation and still running on the barest of foundations: a shared Google Suite and an Applicant Tracking System (ATS). Beyond that, practically no systems, processes or infrastructure existed to support business growth.The gaps were already creating strain. The ATS wasn't capturing contacts automatically, so every update was manual. With no Customer Relationship Management (CRM) in place, candidate and client communications lived in the co-founders' personal inboxes, which were overloaded and increasingly unmanageable. The co-founders were overwhelmed, and the firm's outbound sourcing and business development efforts fell short of what the business needed in order to grow. Left unaddressed, the costs were clear: missed or delayed revenue, mounting internal chaos, and burnout risk for founders trying to manage a high-volume, relationship-driven business without support. The environment was also greenfield. A dual-executive engagement, the co-founders were aligned on the company's vision but not always with how to implement systems or navigate complex data decisions. This added time and complexity to the early weeks of the engagement.

Solution

Vannin [now the Chief of Staff Association] matched the firm with Kevin, one of our chiefs of staff. In his first two to three weeks, Kevin ran an onsite with both co-founders and their one existing hire to align the team on business strategy, mission, purpose, tone and ideal client profile (ICP). Kevin later wondered if he over indexed on this step, but one founder told him that the alignment work was more valuable than Kevin realised. From there, Kevin took on three critical areas of responsibility:

Systems and data infrastructure (owned):
Kevin rebuild the firm's operating foundation from the ground up. He optimised the firm's existing ATS, then ran a full evaluation of ATS and CRM alternatives before implementing Revo, an AI-based CRM. He rolled out Zoom and an AI note-taker and implemented Claude as the firm's core AI assistant, then connected every system – ATS, CRM, Zoom, and Claude – through a mis of native integrations and custom Model Content Protocol (MCP) connectors he built himself. He also stood up a recurring operating cadence: a weekly Monday pipeline meeting, a weekly (later bi-weekly) Thursday project meeting, and weekly one-on-ones with each co-founder.
Executive leverage and proprietary data (owned):
Kevin led the hiring of an executive assistant, who ultimately took over the founders' inboxes and calendars, and sourced and managed a two-of-three-month engagement with a third-party agentic workflow firm to centralise and enrich the firm's data. This lay the foundation for a proprietary database of targets and candidates and the firm's first intellectual property.
Financial modelling and strategy (owned, with influence on messaging):
Kevin built a five-year financial forecast model projecting income and hiring needs for the recruiting business: complex enough to capture the nuance of the business, user-friendly enough for one of the co-founders to run it on his own. The model became a key input to fundraising conversations. Kevin also influenced, without directly owning, the firm's outbound messaging and go-to-market strategy.

Results

Kevin's work gave the firm's founders leverage. Taking over their inboxes and calendars freed up significant founder time, early on. As systems came online and were connected end-to-end, that leverage compounded: the founders could direct Claude to update their own systems or surface intelligence on targets that would previously have taken hours to compile by hand. Key outcomes included:

Faster, smarter decision making: Before, when the firm needed to work on an event contact list, a founder would ask Kevin to perform manual review and recommend outreach. By the end of the engagement, with every system (including the enrichment provider's market intelligence) connected to Claude, the founders could upload a contact list and receive a top ten rank by ICP fit, relevant market context, and personalised outbound messaging.
Nothing falls through the cracks: Kevin built lightweight AI skills that proactively flagged contacts who hadn't responded or hadn't been responded to over a set period. This protected the pipeline from silent drop-offs.
A path to fundraising: The five-year financial model Kevin built gave the founders a credible self-service tool for the hiring and revenue conversations that came with raising capital. Fundraising discussions were already underway before Kevin's engagement wrapped.
The beginning of IP: By centralising and enriching the firm's target and candidate data, Kevin helped it move beyond ad hoc sourcing to building a proprietary database.

Without this role, much of the work would have gotten done eventually, but far more slowly and disjointedly, and it would have been difficult for the firm to find another operator able to both design and personally build the level of system connectivity that Kevin delivered. An executive assistant would only have scratched the surface of what the engagement covered. Ultimately, Kevin took the firm from, in his words, 'not even crawling to basically jogging' in its data, intelligence and operational efficiency. He did this by drawing on deep expertise in systems and data, revenue operations strategy, and finance.

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