Hiring inefficiencies can lead to costly overstaffing, lost productivity, and unclear decision-making. GS, a payer-provider company, faced significant challenges in their role approval process, causing bottlenecks, unnecessary meetings, and a lack of transparency. KN Process partnered with GS to redesign, automate, and optimize their hiring review workflow using Mello, a process automation and execution tool.
Through AI-driven automation and structured process design, KN Process helped GS reduce hiring process costs by over $9,000 per month, achieving a 229% return on investment (ROI).
The Challenge: A Cumbersome and Inefficient Hiring Process
GS’s hiring process had no structured vetting system, leading to:
- Lost role requests – 20% of new-role submissions were missed in inboxes, chats, or meetings.
- Excessive meeting overhead – Pre-meetings and weekly review meetings were inefficient and time-consuming.
- Lack of visibility – Hiring managers had no insight into approvals, rejections, or necessary changes for denied roles.
With these inefficiencies compounding, GS turned to KN Process to streamline hiring approvals, enhance accountability, and introduce AI-powered automation.
The Solution: AI-Powered Workflow Automation
To address GS’s challenges, KN Process implemented a structured, automated hiring approval system using Mello, focusing on three core areas:
1. Process Standardization & Visibility
- Created a centralized, trackable request submission system accessible to all hiring managers.
- Eliminated outdated forms and manual tracking, replacing them with automated workflows in Mello.
2. Workflow Execution & Efficiency Gains
- Implemented decision nodes and feedback loops to ensure only complete, high-quality submissions reached the review panel.
- Introduced automated task assignments, reducing weekly meeting time by 50%.
- Added real-time notifications, eliminating the need for manual follow-ups.
3. AI-Powered Process Automation
- AI agents assessed whether roles were mission-critical (e.g., direct patient care) and automatically pre-approved them, reducing delays.
- Automated feedback delivery, providing instant explanations for denied or delayed roles.
- Integrated data-driven insights, allowing GS leadership to make faster, more strategic hiring decisions.
Key Benefits & Measurable Impact
| Improvement Area | Before KN Process & Mello | After KN Process Optimization |
|---|---|---|
| Role request tracking | 20% of requests lost | 100% visibility in a centralized workflow |
| Pre-meeting burden | Multiple unnecessary meetings | Eliminated via structured request form |
| Review meeting duration | Weekly meetings were inefficient | Time cut by 50% |
| Approval delays | No structured prioritization | AI pre-approvals for critical roles |
| Decision transparency | No feedback on denied roles | Automated, instant feedback |
Return on Investment (ROI)
Before KN Process optimized the workflow, GS’s hiring review process cost over $15,000 per month in meeting overhead and lost productivity. After redesigning the workflow with AI-powered automation:
- New process cost: $5,950/month (including Mello platform fees, AI automation, and process optimization).
- Savings: $9,050 per month.
- ROI: 229%, with full payback within 2 months.
| Metric | Pre-KN Process Cost | Post-KN Process Cost | Savings |
|---|---|---|---|
| Hiring review process | $15,000/month | $5,950/month | $9,050/month |
Implementation: How KN Process Delivered Results
The transformation at GS was driven by KN Process’s expertise in process automation and AI agent deployment. The implementation included:
1. Process Engineering & Training
- Mapped and redesigned GS’s hiring workflow to align with best practices.
- Provided comprehensive training for finance and HR teams to ensure smooth adoption.
2. Mello Integration & Customization
- Fully integrated Mello into Microsoft Teams for seamless workflow execution.
- Configured automated decision pathways to reduce manual approval workload.
3. AI Agent Deployment
- Introduced AI-driven role prioritization, fast-tracking critical hires.
- Developed an AI-based review mechanism that achieved 98% accuracy in task completion.
Conclusion: Smarter Hiring with AI-Powered Process Automation
Through KN Process’s expertise in AI-driven process optimization, GS transformed a cumbersome hiring workflow into an efficient, automated, and transparent system. By integrating Mello’s automation and AI capabilities, GS achieved:
✅ Significant cost savings
✅ Streamlined, AI-powered hiring decisions
✅ Greater efficiency and visibility in role approvals
This case study highlights the power of strategic process automation—demonstrating how KN Process helps enterprises eliminate inefficiencies, reduce costs, and scale smarter.
Looking to optimize your business processes with AI-driven automation? Contact KN Process today to see how we can help you streamline workflows and maximize efficiency.