METHODS AND APPARATUS FOR ANALYSIS OF EMPLOYEE ENGAGEMENT AND CONTRIBUTION IN AN ORGANIZATION
Methods and apparatus for modeling, using a data science approach, the propensity of employee turn-over and the level of engagement of employees. Both unstructured and structured data from internal and external sources are included in the analysis to determine the level of satisfaction and contribution by employees. What-if analysis permits assessment of the impact on satisfaction, contribution and/or budget for various what-if scenarios, permitting management to take the most effective action to drive retention and/or employee contribution goals.
1 . A computer-implemented method for obtaining employee insights from aggregated data pertaining to an organization, said aggregated data including at least unstructured data, comprising:
processing said aggregated data using natural language processing to generate a set of attributes, said set of attributes being associated with at least one of satisfaction and contribution;
processing said aggregated data using natural language processing to generate a set of contributors, said set of contributors being related to said set of attributes; and
analyzing, using said of attributes and said set of contributors, to generate a set of insights, said set of insights including at least one of a satisfaction level and a contribution level associated with an evaluation target entity (ETE) of said organization, said ETE being one or more employees of said organization.
2 . The computer-implemented method of claim 1 wherein said natural language processing includes topic analysis and said set of attributes includes said set of topics.
3 . The computer-implemented method of claim 1 wherein said natural language processing includes sentiment analysis and said set of attributes includes said set of sentiments.
4 . The computer-implemented method of claim 1 wherein said natural language processing includes emotion analysis and said set of attributes includes said set of emotions.
5 . The computer-implemented method of claim 1 wherein said analyzing also employs employee evaluation data for employees of said organization.
6 . The computer-implemented method of claim 1 wherein said analyzing also employs financial data of said organization.
7 . The computer-implemented method of claim 1 wherein said aggregated data comes from multiple data sources.
8 . The computer-implemented method of claim 1 wherein said aggregated data includes structured data.
9 . The computer-implemented method of claim 1 wherein said unstructured data includes social media data.
10 . The computer-implemented method of claim 1 wherein said unstructured data includes blog data.
11 . The computer-implemented method of claim 1 wherein said unstructured data includes narrative data obtained from sources internal to said organization.
12 . The computer-implemented method of claim 1 wherein said set of contributors are associated with weights prior to said analyzing.
13 . The computer-implemented method of claim 1 further including analyzing what-if scenarios to assess budget impact against change in at least one of a contribution level and a satisfaction level associated with said ETE.
14 . A computer-implemented method for analyzing contribution and satisfaction data pertaining to employees of an organization, said analyzing being responsive to a query, comprising:
aggregating unstructured data from various data sources to form aggregated data;
processing said aggregated data using natural language processing to generate a set of attributes, said set of attributes represent at least one of a set of topics, a set of sentiments, and a set of emotions; and
processing said set of attributes to generate a set of insights, said set of insights representing at least one of a level of satisfaction and a level of contribution associated with an evaluation target entity (ETE) of said organization, said ETE being one or more employees of said organization.
15 . The computer-implemented method of claim 14 wherein said natural language processing includes topic analysis and said set of attributes includes said set of topics.
16 . The computer-implemented method of claim 14 wherein said natural language processing includes sentiment analysis and said set of attributes includes said set of sentiments.
17 . The computer-implemented method of claim 14 wherein said natural language processing includes emotion analysis and said set of attributes includes said set of emotions.
18 . The computer-implemented method of claim 14 wherein said aggregating includes aggregating structured data to form said aggregated data.
19 . The computer-implemented method of claim 14 wherein said unstructured data includes social media data.
20 . The computer-implemented method of claim 14 further including analyzing what-if scenarios to assess budget impact against change in at least one of a contribution level and a satisfaction level associated with said ETE.