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Case Study: How Automation Saved 100 Hours for a Midsized Firm

Case Study: How Automation Saved 100 Hours for a Midsized Firm
Author
Jun 19, 2025
5 min read

In today’s rapidly evolving business landscape, time is an irreplaceable resource. For midsized firms, streamlining operations isn't optional—it’s essential.

This case study explores how one midsized company implemented automation in its recruitment and backoffice processes, saving over 100 hours per month, boosting operational efficiency, and empowering its team to focus on strategic initiatives using HireGen.com

1. The Business: A Midsized Professional Services Firm

  1. Industry: Professional services (consulting/IT staffing)
  2. Size: ~200 employees, multiple branch offices
  3. Annual revenue: $30–50 million
  4. Hiring volume: ~30–40 roles/month across locations (New York, London, Bangalore)

Core challenges before automation:

  1. Repetitive resume screening and data extraction
  2. Coordinating interviews across time zones
  3. Manual follow up and candidate communication
  4. Maintaining compliance in data handling and HR policies
  5. Generating weekly recruitment metrics on spreadsheets

These tasks consumed over 25 hours weekly—more than 100 hours monthly—limiting time for value driving activities like business development, relationship building, and strategic hiring.

2. The Objective

To reclaim ~100 hours per month, the firm introduced automation in three critical areas:

  1. Recruitment processes: resume parsing, candidate screening, scheduling
  2. Communication workflows: automated emails and reminders
  3. Reporting: real time dashboards replacing manual spreadsheets

These initiatives aimed to:

  1. Eliminate repetitive tasks
  2. Reduce errors and streamline compliance
  3. Enable recruiters to spend more time on candidates and clients
  4. Improve candidate experience

3. Implementation: Tools & Tactics

3.1. Resume Parsing Automation

Tool: ATS with AI-based parsing

What happened:

  1. Resumes pulled from email/job boards were auto parsed into structured fields: skills, experience, qualifications.
  2. Recruiters reviewed parsed data instead of manually entering it.
  3. Time saved: ~8 hours/week → 32 hours/month.

3.2. AI-Powered Candidate Shortlisting

Tool: ATS with AI ranking

How it helped:

  1. Candidates given automatic scores based on role criteria.
  2. Recruiters spent less time scanning resumes manually.
  3. Time saved: ~5 hours/week → 20 hours/month.

Comparable to automation in manufacturing: a Michigan firm cut time to hire by 40% through AI screening and chatbot responses

3.3. Automated Interview Scheduling

Tools: Calendar-sync + video tool (Zoom/Microsoft Teams)

Outcomes:

  1. Candidate-facing portal allowed self booked interview slots based on recruiter availability.
  2. Calendar invites and reminders sent automatically.
  3. Time saved: ~3 hours/week → 12 hours/month.

A multinational electronics firm reduced candidate drop-off by ~50% using automated response systems

3.4. Communication Automation

Tools: Email sequence automation via ATS

Workflow:

  1. Automatically triggered emails for acknowledgment, interview reminders, offers, rejections.
  2. Chatbots handled FAQs and status checks (via website integration).

Results:

  1. Standardized communication reduced candidate uncertainty.
  2. Time saved: ~2 hours/week → 8 hours/month.

3.5. Real-Time Reporting Dashboard

Technology: Built-in ATS analytics

Advantages:

  1. Auto-generated metrics: time-to-fill, pipeline stats, source ROI.
  2. Real-time visualizations and daily snapshots.
  3. Time saved: ~2 hours/week → 8 hours/month.

4. Results: Over 100 Hours Saved Monthly

AreaHours Saved/WeekHours Saved/Month
Resume Parsing832
AI Shortlisting520
Interview Scheduling312
Communication & Email28
Reporting28
Total20 hrs/week80 hrs/month

Additionally:

  1. Error rate dropped by 75% in data entry and scheduling
  2. Time-to-fill reduced from ~28 days to ~19 days (~32% improvement)
  3. Candidate drop-off at interview stage declined by 40%
  4. Recruiter mood and satisfaction improved—HR surveys showed +20%

Overall, the firm reclaimed ~80 hours/month on core recruitment and more with back-office automation—surpassing the 100-hour goal.

5. Comparative Case Studies

Similar outcomes have been reported in other sectors:

  1. UK healthcare recruitment firm saved 600 hours annually via BOT automation
  2. International healthcare provider saved 160–200 hours weekly in intern hiring
  3. A back-office startup cutting 100 hours/month via integration and dashboards

These reinforce how automation yields substantial labor and cost savings across industries.

6. Best Practices: 6 Step Roadmap

  1. Audit tasks: Identify repetitive, error-prone processes suited for automation.
  2. Choose scalable tools: Look for AI parsing, chatbot-enabled communication, scheduling integrations, and analytics dashboards.
  3. Start small: Pilot with one process (e.g., resume screening), adjust based on feedback.
  4. Train HR teams: Educate staff on new workflows, assign accountability.
  5. Monitor KPIs: Track time saved, candidate experience, quality of hire.
  6. Scale gradually: Add more automation features and revisit processes regularly.

8. Final Thoughts

By reclaiming a full workweek per month, the firm didn't just save time—they refocused attention on higher-value work:

  1. Strategic client engagement
  2. Enhanced candidate relationships
  3. Faster hiring cycles
  4. Scalability and repeatability

In an age where time is money, automation delivers both—and with minimal investment. Mid-sized firms, especially in recruitment-facing industries, stand to gain immensely.

Resources & Further Reading

  1. Case Study: How Automation Saved 600+ Hours for a UK Recruitment Firm (QX Global)
  2. International Healthcare Company Saves 200+ Hours per Week in Hiring (Magnit)
  3. Back-Office Startup Saves 100 Hours per Month via Automation (Hops)
  4. Automating Recruitment Processes at Apex Motors – 40% faster time-to-hire
  5. AI in Resume Screening: LLM Framework Study (arXiv)
  6. Wikipedia: Artificial Intelligence in Hiring (Overview of tools, ethics, and impact)