Overview

Project recommendations in Talent Management (TM) are an intelligent system designed to connect employees with internal projects that align with their individual skills, growth goals, and business needs. This AI-driven solution goes beyond simple keyword matching. It uses a deep, skill-based analysis to find the best people for projects and the most important projects for an employee to grow. The core objective is to drive internal mobility, facilitate skill development, and maximize talent deployment.

How it works

The project recommendation engine operates through a multi-phase process:

• Identifying relevant opportunities (Search and filtering)
  
• The system only considers active and available projects that are currently posted and have a future end date. Completed or draft projects are excluded.
• It focuses strictly on new growth opportunities, omitting projects the employee has already joined or created.
• Projects that match employees' development goals are given priority. This directly helps them achieve their career goals.
• Projects are filtered based on the employee's stated work location preferences to ensure practicality.
• Determining the best fit (Matching and ranking)
  

• Success in projects is primarily determined by technical and functional capabilities; the matching engine gives 100% of its weighting to skill alignment.
• The system performs a thorough skill analysis, examining an employee's full profile, including past projects and work experience, and can assess up to 50 skills.
• Intelligent skill augmentation occurs when project owners provide ‘ideal candidate profiles’. The system mines and blends skills from these reference profiles into the project's required-skill list, enriching the project's requirements for more precise matching.
• Employees' expressed skill interests are also evaluated in addition to their current profile skills.
• Ensuring recommendation quality (Scoring and thresholds)
  

• Each project is assigned a Match Score, presented as a 1-to-5-star rating, which quantifies the strength of the match based on skill alignment.
• Organizations can configure a minimum match score threshold (For example, showing only projects with 3+ stars) to control recommendation quality and prevent overwhelming employees with less relevant opportunities.
• User experience and dynamic updates
  

• Employees see a personalized, continually updated ‘Recommended Projects’ feed. The feed is sorted to show the most recently matched projects first to keep the experience fresh.
• Recommendations refresh in real time as projects or employee profiles change.
• Only employees with the right access and eligibility (as set by administrators) are shown project recommendations. This is done in both the user interface and backend services.
• Data Integrity
  

• For compliance and review, the platform stores project match scores at the time of assignment or application. This enables organizations to retroactively validate why an employee was recommended or chosen for a project, ensuring transparent decision-making.
• Project completeness nudges
  

• To improve recommendation quality, project managers are prompted to enter key details (For example, minimum three skills, ideal candidate profile, detailed descriptions). A ‘project completion score’ provides real-time feedback, nudging managers to improve project postings, which leads to better matches.

Key benefits

Implementing a project recommendation system offers significant advantages:

• Optimal talent deployment: Matches employees to internal projects to use the most talent in the company.
• Accelerated skill development: Focuses on projects that match skill development goals and interests. This helps people grow physically and improve their skills.
• Improved internal mobility: Drives movement within the organization by presenting new avenues for growth and experience.
• Increased employee engagement: Gives employees personalized, relevant chances. This helps them take control of their career paths and stay engaged.
• Match scores are stored for easy access, so you can see why employees were recommended or chosen for projects.
• Continuous improvement: Recommendations change as projects or employees change, so they're still relevant.