ENCHANCING EMPLOYEE COMPETENCE USING BEST FITTED TALENT RECOMMMENDATION ALGORITHM

PROFESSIONAL PRACTICES LAB

Submitted by

RAMAKRISHNAN R

(2016658006)

MASTER OF ENGINEERING

in

COMPUTER SCIENCE AND ENGINEERING

MADRAS INSTITUTE OF TECHNOLOGY

ANNA UNIVERSITY: CHENNAI 600 025

1

TABLE OF CONTENTS

CHAPTER NO.

TITLE PAGE NO.

1 AIM 32 OBJECTIVE3 LITERATURE SURVEY REVIEW 34 SYSTEM STUDY

4.1 EXISTING SYSTEM 4.2 PROPOSED SYSTEM

77

5 SYSTEM ARCHITETURE 86 ALGORITHM USED 97 UML DIAGRAM

7.1 Use Case Diagram 7.2 Class Diagram 7.3 Sequence Diagram 7.4 Collaboration Diagram7.5 Data Flow Diagram

1011121213

8 SYSTEM SPECIFICATION

8.1 HARDWARE CONFIGURATION

8.2 SOFTWARE CONFIGURATION

14

14

9 CONCLUSION 1510 REFERENCES 15

2

1. AIM

To provide and ensure the employee with high utilization of learning metrics along with their inspirational trends both in technology and management skills by providing best fitted competency using adoptive dynamic algorithm.

2. OBJECTIVE

Talent allocation, as a vital part of talent strategies, plays an important role in improving the utilization of talents.

In this mechanism, the concepts of talent-post match degree and talent utilization rate are introduced as evaluation criteria of talent optimal allocation.

Best way to predict and ensure the best competency match with standard accuracy.

3. LITERATURE SURVEY

1. TITLE OF THE PAPER : Researches on the best-fitted talents recommendation algorithm

JOURNAL : 2015 IEEE 27th Chinese control and Decision Conference- 4247-4252

SYSTEM DESIGN : Based on the talent demand and the number of talents predicted by time sequence model, a dynamic planning algorithm is adopted after formula derivation to recommend best-fitted talents list.Experimental results show that this best-fitted talent recommendation mechanism possesses higher utilization and is of use to the government department in talent management.

HIGHLIGHTS : Possess highest talent utilization ratio and talent-post match degreeTalent-post match degree and talent utilization ratio are introduced as evaluation criterion of talent optimal allocation

CHALLENGES :Time sequence model is applied to explore the distribution law of talents and predict number of talents

ALGORITHM / PERFORMANCE : Dynamic programming algorithm

3

2. TITLE OF THE PAPER : Information Retrieval, Fusion, Completion, and Clustering for Employee Expertise Estimation

JOURNAL : 2016 IEEE International Conference on Big Data (Big Data)- 1385 -1393

SYSTEM DESIGN : Using a novel big data workflow with components of information retrieval and search, data fusion, matrix completion, and ordinal regression clustering.

Find evidence of expertise and determine appropriate evidence weights for different queries and data sources that we merge and present in a manner consumable by businesspeople.

HIGHLIGHTS :Specialization, and collective intelligence are accelerated when organizations and even society-at-large has a proper inventory of the expertise of all individuals because information and communication technologies can then be used to allocate human capital

CHALLENGES : The current output depths of expertise (very deep, deep, moderate, some, limited) are only valid within the data set. The labels have no external calibration, which could certainly have different data sources than the internal data

ALGORITHM / PERFORMANCE : Interior-point algorithms or accelerated proximal gradient Machine learning algorithms (supervised learning, support vector)

3. TITLE OF THE PAPER : Big data analysis on the relationship between the organizational career management and knowledge workers’ work involved

JOURNAL : 2016 IEEE TrustComBigDataSE-ISPA- 2251-2256

SYSTEM DESIGN : The big data analysis technological constructs the organizational career management of knowledge type staff involved in the theoretical model of mechanism. Fair promotion, career information, pay attention to training, vocational self-cognitive and the employee's work involved in a positive correlation relationship, puts forward the corresponding organizational career management countermeasures.

4

HIGHLIGHTS : There has significant positive correlation between provide profession information anon knowledge staffwork involved.There has significant positive correlation on knowledge staff work involved attention to training and knowledge staff work involved.There has significant positive correlation between professional identify and knowledge staff involved.

CHALLENGES :Dedicatedly drives and will focus on specific attributes

ALGORITHM / PERFORMANCE : OCM(Organization Career Management) methodology.

4. TITLE OF THE PAPER : Competence Management as a Dynamic Capability: A Strategic Enterprise System for a Knowledge-Intensive Project Organization

JOURNAL : 2016 49th Hawaii International Conference on System Sciences – 4252-4260

SYSTEM DESIGN : Competence typology and Level 5 Leadership concepts fit well in guiding competence management in dynamic service economy markets. Competence management should aim towards customer demand and employee interests rather than only focusing on current strengths

HIGHLIGHTS :Suggest that strategic Competence management should aim towards customer demand and employee interests rather than focusing on current strengths

CHALLENGES :Better integration and visualization of customer demand in competence management context

ALGORITHM / PERFORMANCE : Research Approach(Case description, Data collection, Data analysis), Dynamic Competence Capability Lindgren’s competence typology and Collins’ hedgehog concept

5

5. TITLE OF THE PAPER : The Influence of Knowledge Management Tools Utilization Towards Knowledge Management Readiness

6. JOURNAL : 2016 International Conference on Information Technology

Systems and Innovation (ICITSI) -ISBN: 978-1-5090-2449-0

SYSTEM DESIGN :Analyzes factors related to knowledge management tools utilization within the organization as antecedents towards knowledge management implementationreadiness.

HIGHLIGHTS :The variable Portal for Client and Service providers as well as Internal KM Repository Tool were classified as having strong variance, while the variable KM readiness was classified as one with weak variance

CHALLENGES :The use of Internal Collaboration Tool did not carry a significant influence on the use of Internal KM Repository Tool. Additionally, the prior did not have a significant effect on the use of Portal for Client and Service Provider as well.

ALGORITHM / PERFORMANCE : Partial Least Square Structural Equation Modelling (PLS-SEM)

6

4. SYSTEM STUDY

4.1 EXISTING SYSTEM

Based on the talent demand and the number of talents predicted by time sequence model, a dynamic planning algorithm is adopted after formula derivation to recommend best-fitted talents list.

Not focus on an overall mechanism of talent education, recruit, and allocation in the project

4.2 PROPOSED SYSTEM

Effectively adopted within the project and also for the future requirement and prediction in current market trends.

Useful to adopt in Recruitment, talent education in Organization both in technical and non-technical demands.

Enhance the best-fitted competency to employee to achieve their career goal along with their passion towards work.

Organization investing (return in investment index) in talent development will be optimized in cost.

Satisfaction index for the employee will drastically increase.

7

5. ARCHITECTURE OF THE PROPOSED SYSTEM

8

Data collecting

Talents Distribution

Collect data from website

Intelligent index

Talent info structuring

SOA Architecture

Classification Analysis

Data Visualiza

tion

Best-fiitted talent

recommendation

Data Vis

ualizationNN

Modeling

Model Building

Recommend-ation

Search List

6. ALGORITHM USED

9

Begin

GetDemandByCompetencyID

ClassifyTalentByEmployeeskill

Group k <NumofGroup

p

AttainAllTalentByModel

ApplyGrownModel

Demand j =totaldemand

Differ=1

Differ=Tltt-Dmd j

Store (t,j)

Demand i =totaldemand

Differ>Tltt-Dmd j

End

Y

YY

N

Y

N

N

7. UML DIAGRAM

7.1 Use Case Diagram

10

7.2 Class Diagram

11

7.3 Sequence Diagram

12

7.4 Collaboration Diagram

7.5 Data Flow Diagram

13

8. SYSTEM SPECIFICATION

8.1 HARDWARE REQUIREMENT

Dual-core 64-bit processor

8 GB of memory

Up to 24 GB of internal storage (Kony Visualizer: 4GB, Android SDK: 2GB, Windows SDK: 4GB, BlackBerry NDK: 4GB, plus ample space for multiple complex projects)

Network interface card

8.2 SOFTWARE REQUIREMENT

14

Name Software

Operating System Windows 10, Windows 8.1 Update, Windows 8, and Windows 7.

Front End ASP MVC 5 .NET Framework, Microsoft Visual Studio 2016

Back End Microsoft SQL Server 2012

9. CONCLUSION

Effectively adopted within the project and also for the future requirement and prediction in current market trends.

Useful to adopt in Recruitment, talent education in Organization both in technical and non-technical demands.

Enhance the best-fitted competency to employee to achieve their career goal along with their passion towards work.

Organization investing(return in investment index) in talent development will be optimized in cost.

Satisfaction index for the employee will drastically increase.

10. REFERENCES

William A. Schiemann, et al, From talent management to talent optimization, Journal of World Business, No.49, 281–288, 2014.

Sanne Nijs, et al, A multidisciplinary review into the definition, operationalization, and measurement of talent, Journal of World Business, No.49, 180-191, 2014.

Gutteridge T G. “ Organizational career development systems˖The state of the practice” ,San Francisco: Jossey-Bass Publishers,1986.50-95.

R. L. Martin, “The rise (and likely fall) of the talent economy,” Harvard Bus. Rev., Oct. 2014.

K. R. Varshney, V. Chenthamarakshan, S. W. Fancher, J. Wang, D. Fang, and A. Mojsilovic, “Predicting employee ´ expertise for talent management in the enterprise,” in KDD, 2014, pp. 1729–1738.

Herriot, P, Gibbons, P, Pemberton, C, Jackson, P. R.. “An Em-pirical Model of Managerial Careers in Organizations”. BritishJournal of Management, 1994, (5): 113-121.

Crabtree MJ. “Employees Perception of Career Management Practices: The Development of a New Measure”Journal of Career Assessment,1999. [4] SalehSD, Hosek J. “Job involvement: concepts and measurements”.Academy of Management Journal,1976,19:213-224.

15