Staff Performance Assessment Solution of a Healthcare Firm

Client is a U.S. Healthcare provider which specializes in hospital services, mental health services, women’s health services, specialty services, and substance abuse work in the community to deliver a healthcare experience designed around individual needs.

Client:

Services:

Year:

They were looking to revolutionize their performance evaluation system and build a solution that could analyze employee data, predict employee performance and offer unbiased decision-making capabilities & recommendations to improve employee performance.

Key Challenges

The healthcare client wanted to overcome issues found in their current evaluation system as it was dealt with by humans
Humans default to their emotions, biases, prejudices, etc., which could negatively impact the organization’s growth and lead to inefficient decisions
Additionally, managing and analyzing vast quantities of HR data manually is time-consuming and prone to errors
The client needed a solution to help them eliminate inefficiencies that lower employee morale with a relatively easy-to-employ framework

Table of Contents

Key Challenges
Solution
Benefits

Solution

Sparity developed and implemented predictive models for performance evaluation using machine learning algorithms
Employed Hybrid techniques and developed and trained two predictive models, Data clustering and Decision Tree Classifier algorithms
Applied data clustering for evaluating the employee’s performance and decision-making process and imported python libraries — NumPy and pandas
The predictive model considered different performance evaluation factors like personality, punctuality, tact, oral expression, Quality of Work, perseverance, public relations, observance of security measures, capacity to guide & train subordinates, attitude towards superiors, moral integrity, and more to provide actionable insights and predict and evaluate the performance of the employees
Used the Label encoder utility class from scikit-learn and transformed those diverse categorical values into numerical
Leveraged Decision tree classifier to help visualize and analyze the situation better and evaluate the employee’s performance as well as in the decision-making process

Benefits

Attained maximum productivity by reducing manual workload by more than 35%
Empowered client to identify over and underutilized resources and design relevant training courses for a specific period of time
Minimized the bias that’s inherited in the old-school method of performance management
Predicts the employees’ performance for the following year and enabled easy advancement and promotion determinations

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