Adp, Inc.

Xiaojing Wang

Marc Rind

Sachin V Havaldar

Min Xiao

Dmitry Alexandrovich Tolstonogov

Lei Xia

James R Haas

Nitin Kumar Tammewar

Vikas Saini

Eric Zitaner

Chandradeep Kanakamedala

Samir Khanal

Anshuman Gaur

Manoj Oleti

Michael Ratcliff

Uday Kovur

Faseeha Khan

Slawomir Krysiak

Linxuan Jiang

Fang Yuan

Kishore Bangali

Hafeez Raji

Dong Meng

John Robert Catino, Jr

Surekha Avasarala

Manish Karanjavkar

Managing and applying human resources data comprising aggregating employee transaction data for an organization. A number of human resources-related attributes are evaluated across heterogeneous transaction data. The employee transaction data is classified via statistical machine learning into a number of normalized codes according to the human resources-related attributes, a user interface is presented to adjust a number of organizational operating procedures according to the normalized codes.

Earning code classification

A method and system for analyzing employee retention across an enterprise based on commuter modeling is disclosed. The method can be implemented in a computer system which includes: mapping longitudinal and latitudinal coordinates of address information of a plurality of employees and a work location onto a map, which shows a predefined geographic location encompassing the work location surrounded by the longitudinal and latitudinal coordinates of the address information; obtaining calculated analytics data of employee turnover rate for the plurality of employees based on a commute distance from the work location to each of the longitudinal and latitudinal coordinates of the plurality of employees; and graphically overlaying the analytics data of the turnover rate for the plurality of employees onto the map to show employee turnover rate for different segments of the map.

Systems and methods for commute analysis and modeling

A method, computer system, and computer program product for determining job levels of an employee within an organization. A computer system identifies employee data for the employee. The computer system determines whether the employee is a manager or a non-manager based on the employee data for the employee. The computer system applies a manager employee level model to determine a manager job level of the employee in response to determining that the employee is a manager. The computer system applies a non-manager employee level model to determine a non-manager job level of the employee in response to determining that the employee is a non-manager.

Job level prediction

A method and apparatus for normalizing data. A computer system receives category data for a first code from a first client of a plurality of clients. The computer system also generates a category rule based on the category data. The computer system also assigns a category to a second code of a second client of the plurality of clients using the category rule. The category data is generated using input from the first client. Assigning the category to the second code of the second client comprises selecting the category rule to use to assign the category to the second code from a plurality of category rules.

Data normalizing system

Display screen or portion thereof with animated graphical user interface

Display screen or portion thereof with graphical user interface

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Warren, NJ, United States of America

Xiaojing Wang