{"id":38718,"date":"2021-07-07T10:45:56","date_gmt":"2021-07-07T05:15:56","guid":{"rendered":"https:\/\/www.mygreatlearning.com\/blog\/using-data-science-in-hr-to-understand-attrition-and-increase-retention\/"},"modified":"2024-09-03T08:48:50","modified_gmt":"2024-09-03T03:18:50","slug":"using-data-science-in-hr-to-understand-attrition-and-increase-retention","status":"publish","type":"post","link":"https:\/\/www.mygreatlearning.com\/blog\/using-data-science-in-hr-to-understand-attrition-and-increase-retention\/","title":{"rendered":"Using Data Science in HR to understand attrition and increase retention - Arfan Yusuf Shaikh, PGP DSBA"},"content":{"rendered":"<figure class=\"wp-block-image size-large td-caption-align-https:\/\/www.mygreatlearning.com\/blog\/wp-content\/uploads\/2021\/07\/Data-Science-Stories_Arfan-Yusuf.png zoomable\" data-full=\"https:\/\/www.mygreatlearning.com\/blog\/wp-content\/uploads\/2021\/07\/Data-Science-Stories_Arfan-Yusuf.png\"><img decoding=\"async\" width=\"1024\" height=\"717\" src=\"https:\/\/www.mygreatlearning.com\/blog\/wp-content\/uploads\/2021\/07\/Data-Science-Stories_Arfan-Yusuf-1024x717.png\" alt=\"ds at work\" class=\"wp-image-38723\" srcset=\"https:\/\/www.mygreatlearning.com\/blog\/wp-content\/uploads\/2021\/07\/Data-Science-Stories_Arfan-Yusuf-1024x717.png 1024w, https:\/\/www.mygreatlearning.com\/blog\/wp-content\/uploads\/2021\/07\/Data-Science-Stories_Arfan-Yusuf-300x210.png 300w, https:\/\/www.mygreatlearning.com\/blog\/wp-content\/uploads\/2021\/07\/Data-Science-Stories_Arfan-Yusuf-768x538.png 768w, https:\/\/www.mygreatlearning.com\/blog\/wp-content\/uploads\/2021\/07\/Data-Science-Stories_Arfan-Yusuf-696x487.png 696w, https:\/\/www.mygreatlearning.com\/blog\/wp-content\/uploads\/2021\/07\/Data-Science-Stories_Arfan-Yusuf-1068x748.png 1068w, https:\/\/www.mygreatlearning.com\/blog\/wp-content\/uploads\/2021\/07\/Data-Science-Stories_Arfan-Yusuf-600x420.png 600w, https:\/\/www.mygreatlearning.com\/blog\/wp-content\/uploads\/2021\/07\/Data-Science-Stories_Arfan-Yusuf-100x70.png 100w, https:\/\/www.mygreatlearning.com\/blog\/wp-content\/uploads\/2021\/07\/Data-Science-Stories_Arfan-Yusuf-150x105.png 150w, https:\/\/www.mygreatlearning.com\/blog\/wp-content\/uploads\/2021\/07\/Data-Science-Stories_Arfan-Yusuf.png 1500w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p><strong>Contributed by: <a rel=\"noreferrer noopener\" href=\"https:\/\/www.linkedin.com\/in\/arfanyusuf\" target=\"_blank\">Arfan Yusuf Shaikh<\/a><\/strong><\/p>\n\n\n\n<p>I am Arfan Yusuf. I graduated from Sydenham College of Commerce in Mumbai and later on joined my Family business of International Human Resource Consultancy. I started with the base as an HR\/Operations executive and then developed my skills with core experience in Human Resource Management, currently heading HR and Global Operations.<\/p>\n\n\n\n<p>I work as an HR in the organization, and one of the verticals where I decided to use <a href=\"https:\/\/www.mygreatlearning.com\/blog\/what-is-data-science\/\" target=\"_blank\" rel=\"noreferrer noopener\">data science<\/a> is understanding attrition and increasing retention. The dataset, apart from the attrition tag, contained attributes such as employee\u2019s age, marital status, travel time, total work experience, employee role, total tenure at the organization, total tenure at current role, clocking time, etc. I pre-processed the data retaining relevant variables, and performed exploratory data analysis using a box plot to understand the relationship of attributes with the attrition tag. I identified that employees who travel are more likely to leave than a desk job. Interestingly, unmarried people are more likely to leave than married people are. Over time employees are also more likely to leave.<\/p>\n\n\n\n<p>I developed a <a href=\"https:\/\/www.mygreatlearning.com\/blog\/logistic-regression-with-examples-in-python-and-r\/\" target=\"_blank\" rel=\"noreferrer noopener\">logistic regression<\/a> to predict the probability of attrition on a test dataset and identified it to have an accuracy of 77.3% and AUC of 82.5%. I am going to use my learning from this model to identify the employees who are most likely to leave. This will help me understand the root cause behind their attrition and develop strategies to retain the best talent. Ex- Career development programs and opportunities within the organization for employees who are in the same role\/ team for a long time. Strategies identified from the developed solution will definitely help my organization in reducing attrition, thereby reducing the cost of training new employees and increased productivity.<\/p>\n\n\n\n<p>An employee data management and retention solution are helping us to develop the productivity of employee performance. Now, as the performance has increased, our closings have increased, and we are able to close the targets with minimum turnaround time.<\/p>\n\n\n\n<p><em>Want to learn more of such data science concepts and work on real-world implementation? Join&nbsp;<a href=\"https:\/\/www.mygreatlearning.com\/pg-program-data-science-and-business-analytics-course\" target=\"_blank\" rel=\"noreferrer noopener\">Great Learning\u2019s PGP Data Science and Business Analytics Course<\/a>&nbsp;and upskill today!<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Contributed by: Arfan Yusuf Shaikh I am Arfan Yusuf. I graduated from Sydenham College of Commerce in Mumbai and later on joined my Family business of International Human Resource Consultancy. I started with the base as an HR\/Operations executive and then developed my skills with core experience in Human Resource Management, currently heading HR and [&hellip;]<\/p>\n","protected":false},"author":41,"featured_media":38723,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[5],"tags":[],"content_type":[],"class_list":["post-38718","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-success-stories"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.3 (Yoast SEO v27.3) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Using Data Science in HR to understand attrition and increase retention - Arfan Yusuf Shaikh, PGP DSBA<\/title>\n<meta name=\"robots\" content=\"noindex, follow\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Using Data Science in HR to understand attrition and increase retention - Arfan Yusuf Shaikh, PGP DSBA\" \/>\n<meta property=\"og:description\" content=\"Contributed by: Arfan Yusuf Shaikh I am Arfan Yusuf. 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