Proof & Results
The model was run end to end as a measured deployment — not a pilot with a favourable write-up.
Case study
Two weeks of pre-arrival HR hiring, one week of environment setup, then eight weeks of live pipeline. The base unit was deliberately simple — one HR recruiter processing fifty applications a day — so that every downstream rate could be measured against a known input and the model could be scaled by multiplying recruiters rather than guessing.
What the deployment established was not a single headline number but a set of conversion rates: application to complete, complete to interview, interview to training, training to activation. Those rates are what a scaling formula needs, and they are what we bring to the next engagement.
MEASURED THROUGHOUT
Applications received per campaign day
Applicants finishing all six forms
Booked interviews actually attended
Candidates completing and passing coursework
Certified agents reaching the field
Agents still producing after three months
Because the base unit is one recruiter at fifty applications a day, capacity scales by adding recruiters rather than by reworking the process. The conversion rates hold; the input multiplies. That is the whole argument for building the pipeline as a system instead of a team.
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