Requisition Approval Bottleneck and Offer Decline
Cobalt Logistics has 3,200 employees, 40 open requisitions, six recruiters, and five hiring managers. The requisition approval chain has five sequential levels: hiring manager, director, HR business partner, finance, and compensation. Average approval time is 12 business days, and time-to-fill is 52 days against a 35-day target. Offer decline is 18%, concentrated in three markets where compensation bands have not been refreshed in 18 months. Recruiters report that candidates accept competing offers while Cobalt is still waiting for internal approval. The compensation team says offers above the 75th percentile require a fifth approval, but managers routinely request the 90th percentile because they believe the band is wrong. The CHRO wants a dashboard, faster approvals, and a lower decline rate before the next hiring wave.
1. How should the talent team diagnose whether the problem is approval speed, compensation competitiveness, or both?
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Separate the funnel into stage-conversion and cycle-time measures. For each requisition, measure days in each approval step, days from approval to first interview, days from final interview to offer, and offer acceptance. If approval time is 12 days but candidate decline occurs after offer, approval speed is not the primary driver. If decline is concentrated in the three stale-band markets and offers cluster at the 90th percentile, the issue is band credibility and manager behavior, not only routing. Compare offer acceptance by market, job family, grade, and compa-ratio at offer. Also measure requisition aging by recruiter and hiring manager; a few managers may be the constraint. The conclusion should be evidence-based: a faster approval chain will not fix a noncompetitive offer, and a band refresh will not fix a 12-day approval delay. The dashboard should show both, segmented by market and stage.
2. What configuration and governance changes would you recommend, and in what sequence?
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Sequence matters because compensation changes require finance and HR partnership. First, implement conditional requisition routing: auto-approve against an approved headcount plan, route by job family and grade, and add an SLA escalation after two business days. Remove compensation from routine approvals when the offer is within band. Second, separate offer approval from requisition approval so the recruiter can move a candidate while the requisition is being finalized, if policy allows. Third, refresh the three stale bands using market data and document the effective date. Fourth, introduce a manager guide and a compa-ratio-based offer matrix so 90th-percentile requests require a written exception, not a habit. Fifth, publish weekly metrics: approval cycle time, offer acceptance, exception rate, and time-to-fill. Governance should include a monthly review with HR, finance, and compensation. Do not simply reduce approval levels without a control for headcount and budget; replace sequential control with pre-approved guardrails.
3. Which metrics should the CHRO dashboard show to prove improvement without encouraging bad behavior?
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Use a balanced set that measures speed, quality, and cost. Speed: requisition approval cycle time, time-to-fill, and time-to-offer. Quality: offer acceptance rate, first-year attrition for new hires, hiring manager satisfaction, and quality-of-hire where available. Process: percentage of requisitions auto-approved, exception rate above band, and aging by stage. Market: acceptance rate by market and compa-ratio at offer. Cost: cost per hire and agency spend. Add a guardrail metric for offer competitiveness, such as percentage of offers below market median, and a fairness metric by demographic group where data is available. Avoid using time-to-fill alone; it can encourage premature offers or pipeline stuffing. Report trends over at least two quarters and compare against a baseline. The dashboard should allow drill-down by market, job family, recruiter, and hiring manager so the CHRO can see whether improvement is systemic or isolated.