Machine Learning Approach for Intelligent Promotion Recommendation

Satadru Kundu

Promotion of employees is one of the most critical talent development functions of any organization. It helps employees to meet their career goals and ambitions, and on the other hand, organizations create future leaders, prepare succession planning, retain efficient employees and so on.

From the employee perspective, promotion is a career development process through which higher responsibilities and higher compensation is achieved. Promotion is not only a formal event but also will have a significant impact on both the employees and employers. It boosts productivity, loyalty and improves the overall engagement index of employees. Efficient and effective employee engagement helps to increase an organization's growth prospects.

Challenges with the Traditional Promotion System

Promotion is crucial to keep the employees motivated. It fuels healthy completion and develops competitive skills among employees. Generally, in most of the cases, promotion will be done on the system for junior-level employees, or by the recommendation of supervisors for senior-level employees. But sometimes, this manual recommendation might be biased or erroneous. This can adversely affect employee performance as well.

Attributes to Consider for Promotion Recommendations

For any organization, to identify whether an employee is eligible for promotion or not is a challenge and many times, employees raise questions about the process. Promotion of an employee implies higher pay scale, new grade, new role, new responsibilities, and new leadership. Thus, the decision to promote an employee should be taken after proper assessment with respect to skills, competencies, experience, leadership qualities, past performance and appraisals, company’s performance etc. Promoting junior-level employees is relatively easy, as this is mostly time-bound. But to promote senior-level employees, it is difficult to evaluate based on the aforementioned attributes, avoiding any biases. We can leverage the power of Artificial Intelligence based technique to identify whom to promote without human intervention.

Intelligent Promotion Recommendation with Artificial Intelligence (AI)

To reduce human bias and rule-based decision, artificial intelligence can be used to identify a candidate suitable for promotion. AI will learn from the historical promotion pattens within the organization based on different attributes and parameters, like employee appraisal history, highest qualification, experience, learning etc., and recommend the most eligible candidate for promotion. This can be considered as a supervised learning problem wherein all historical promotion cases can be used to train the models. We can use any tree-based classifier like random forests, extra trees, gradient boosting etc., to train this machine learning models. Later, this trained model will be used to predict the promotion recommendation scores for active employees. Along with the promotion recommendation score, the topmost influencing factor to get this promotion recommendation score can also be identified from this machine learning models. The influencing factors at the individual employee level will enable the management to assess the employee’s promotion eligibility, and eventually, facilitate their decision to initiate the promotion process.

Managers and talent development teams can use this AI-based, data-driven approach to initiate promotion for an employee. Key influencing factors with respect to promotion for any employee can be embedded into the employee profile along with the recommendation score. This will help to initiate promotion for any employee intelligently, and get rid of the traditional rule-based approach. This machine- and data-driven approach can reduce the time and effort in identifying eligible candidates for promotion without any human intervention. The model will also help the management by optimizing the choice of promoting the most suitable ones from a list of employees, keeping in mind the promotion budget in a given financial year.

Conclusion

Talent development is one of the important domains where we can leverage the power of AI to make more data-driven decisions than relying on a human-centric approach, which can be misleading in some cases. But AI also has some limitations. Before implementing AI-driven models, each and every attribute with respect to employee promotion needs to be checked carefully. The data shouldn’t be biased, and any bias can mislead AI models. So, data analysis becomes an important factor here.

Promotion is one of the key aspects of talent development which can affect both employees and the organization as well. An AI-based, data-driven approach can be used hand in hand with the rule-based, human-centric approach to get more intuitive results and better insights.

About the author

Satadru Kundu

Satadru Kundu is a Senior Developer with nine years of experience in the Innovation and Product Engineering (IPE) - Analytics group with the Platform Solutions unit at TCS. His area of expertise includes solution design, development and implementation of various AI and ML use cases for the homegrown products CHROMATM and TAPTM. He holds a bachelor’s degree in Electronics and Communication Engineering from Netaji Subhash Engineering College, Kolkata, India.

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Intelligent Promotion Recommendation for Eligible Employees

About the author

Satadru Kundu

TCS is here to make a difference through technology.

We’re in it for good, driving positive change for the benefit of all.

Extraordinary expertise leads to remarkable results.

Want to be a global change-maker? Join our team.

Find the latest news about TCS in our Newsroom

Recent Press releases

Recent News

Recent recognitions

TCS works hand in hand with world-leading investors.

About the author

Satadru Kundu

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