Case study # 1: Automating Resume Screening for a Recruiting Company

Objective:
To streamline and automate the resume screening process, reducing manual effort and improving efficiency in identifying qualified candidates based on predefined criteria.

Background:
A recruiting company relied on manual resume screening to identify candidates based on specific keywords, such as top MBA schools or consulting firm experience. Recruiters had to manually search for names of institutions (e.g., Harvard, Stanford) or companies (e.g., McKinsey, Bain, Deloitte) in each resume, which was time-consuming and inefficient.

Challenge:
The key challenges in this process were:

• High manual effort required to review each resume.
• Time-consuming searches for relevant keywords.
• Inefficiencies in filtering candidates based on predefined criteria.
• The need for a faster, automated solution without disrupting the existing workflow.

Solution Implemented:
To overcome these challenges, I developed and implemented an automated resume screening solution with the following features:

• OCR-Based Resume Processing: The system automatically extracted text from resumes as soon as a candidate’s application was received.
• Keyword-Based Filtering: Recruiters could search for candidates by simply typing relevant keywords.
• Predefined Filters: The system allowed recruiters to set predefined keyword-based filters for instant shortlisting or rejection.
• Automated Matching: The solution automatically flagged resumes that matched the set criteria, reducing manual screening time.
• Seamless Integration: Designed to work smoothly with the existing recruitment system without requiring major workflow changes.

Outcome:
The implementation of this automated resume screening tool resulted in:

• A significant reduction in manual effort required for candidate screening.
• Faster identification of qualified candidates based on predefined criteria.
• Increased efficiency in the recruitment process, allowing recruiters to focus on higher-value tasks.
• A more scalable and systematic approach to resume screening, ensuring consistency in candidate evaluation.

Case study # 2: Document Management System

Objective: Develop an automated system to manage and store project submissions efficiently in a structured Google Drive setup, thereby reducing manual workload and improving organizational efficiency.

Background: The client operated a business model requiring talent to submit project examples and past work documents. Initially, these documents were manually uploaded by staff to respective candidate and category-specific folders in Google Drive, a process that was time-intensive and prone to human error.

Challenge: The key challenge was to automate the uploading and sorting of documents into the correct hierarchical folder structure in Google Drive to save time and reduce manual handling errors.

Solution Implemented: An automated integration was developed between the client’s applicant tracking system and Google Drive, utilizing automation scripts and APIs to streamline document handling. When candidates submitted project files, the system automatically identified the candidate and project category, then uploaded and sorted each file into the correct hierarchical folder structure within Google Drive. The automation dynamically created new folders and subfolders as needed for new candidates or categories, ensuring files were always organized and accessible. This eliminated manual uploading and sorting, reduced human error, and enabled scalable, efficient management of project submissions.

Document Handling:

• Integration with Applicant Tracking System: The solution interfaces directly with the client’s existing applicant tracking system where project submissions are initially uploaded by candidates.
• Sorting and Storage: The automation tool identifies the submitting candidate, categorizes the submission, and automatically uploads the document to the appropriate category folder under the candidate’s name in Google Drive.
• Folder Management: The tool dynamically manages the creation of new folders and subfolders if a new candidate or category is introduced, ensuring that the folder structure remains organized and scalable.
• Technology Stack: The system utilizes advanced automation scripts and APIs to interact between the applicant tracking system and Google Drive, ensuring seamless data transfer and accurate file placement.

Outcome

• Time Savings: The automation reduced the time required for file management, which previously involved multiple steps and manual intervention.
• Error Reduction: Automating the sorting and uploading process minimized human errors, ensuring that documents are always placed in the correct folders.

Scalability: The client can easily scale operations without additional manual overhead, as the system automatically adjusts to new submissions and categories.