Investigation on how people analytics have the potential to improve managerial and business decision making processes during the COVID pandemic era and beyond, wherein teleworking is a common practice
organizational performance management | people analytics | data-driven performance insights | data-driven performance management system | people analytics in QlikView
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List of Tables
Table 1 Phases of organizational performance and their Key Parameters (Author’s own research). 25
Table 2 Main elements of People Analytics concept (Author’s own research). 49
Table 3 Attributes associated with each employee and their explanation and values 64
Table 4 KPIs associated with each employee and their explanation and values 64
Table 5 Historical Overview of Organizational Performance Management. (Author’s own research). 81
List of Figures
Figure 1 Goal and sub-goals of this Thesis (Author’s own research) 13
Figure 2 Literature Review Process (https://libguides.reading.ac.uk/food-research-project/literature-review). 15
Figure 3 HR Management, People Analytics and Digital Transformation. (Author’s own research) 18
Figure 4 Evolution of Performance Management. Image taken from (Shrestha, 2020) 20
Figure 5 Performance Management as a process and external forces (Author’s own research). 23
Figure 6 Performance Management Cycle (Author’s own research). 24
Figure 7 Relationship between Performance Management and Performance Appraisal (Author’s own research. 29
Figure 8 Interaction between Digital, Technology and Human Learning (Author’s own research). 30
Figure 9 Digital Transformation at the intersection of four pillars (Author’s own research). 31
Figure 10 Typical strategy framework for the digital transformation of a modern organization (David Snowden, 2022). 32
Figure 11 Role of Digital Performance (Author’s own research). 33
Figure 12 Research Methods (Author’s own research). 38
Figure 13 Research design vs development. Image taken from research design funny – Bing images. 42
Figure 14 Jim Ollhoff’s quote on literature review. From Quotestats.com 44
Figure 15 Adkins’ quote on basic research. From https://www.azquotes.com/ 46
Figure 16 The process of People Analytics (Author’s own research). 50
Figure 17 People Analytics: Maturity phases (Author’s own research). 51
Figure 18 The seven (7) pillars of People Analytics success (Author’s own research). 52
Figure 19 Usefulness of People Analytics to HRM (Author’s own research). 53
Figure 20 Correlation between HR Management and People Analytics (Author’s own research). 54
Figure 21 A typical workflow in the R programming framework - Source: https://r.analyticflow.com/en . 56
Figure 22 Main Pros and Cons of R. (Author’s own research). 57
Figure 23 Process Flow of Power BI -Source [https://data-flair.training/blogs/power-bi-tutorials-home/] 57
Figure 24 Pros and Cons of Power BI (Author’s own research). 58
Figure 25 Pros and Cons of SPSS (Author’s own research). 59
Figure 26 Pros and Cons of QlikView (Author’s own research). 60
Figure 27 Workplaces’ intelligence – Source: Francis,2021. Available at https://contentandcloud.com/microsoft-workplace-analytics-a-guide-for-hr-professionals/ 61
Figure 28 Analysis of Customer Satisfaction Level per Division 66
Figure 29 Analysis of Customer Satisfaction Level per Unit 67
Figure 30 Analysis of Customer Satisfaction Level per Section 68
Figure 31 Attributes and their values for all employees of the top performing section 1.2.2 69
Figure 32 Analysis of Manager Satisfaction Level per Division 70
Figure 33 Analysis of Manager Satisfaction Level per Unit 70
Figure 34 Analysis of Manager Satisfaction Level per Section 70
Figure 35 Attributes and their values for all employees of the top performing section 1.1.2 71
Figure 36 Analysis of Team Members Satisfaction Level per Division 72
Figure 37 Analysis of Team Members Satisfaction Level per Unit 72
Figure 38 Analysis of Team Members Satisfaction Level per Section 72
Figure 39 Attributes and their values for all employees of the top performing section 2.3.1 in respect to KPI 3 73
Figure 40 Analysis of Own Satisfaction Level per Division 75
Figure 41 Analysis of Own Satisfaction Level per Unit 75
Figure 42 Analysis of Own Satisfaction Level per Section 75
Figure 43 Attributes and their values for all employees of the top performing section 2.1.14 in respect to KPI 4 75
Figure 44 Attributes and their values for all employees of the 2nd top performing section 4.8.1 in respect to KPI 4 76
Figure 45 Analysis of KPI 5 per Division 77
Figure 46 Analysis KPI 5 per Unit 77
Figure 47 Analysis KPI 5 per Section 77
Figure 48 Attributes and their values for all employees of the top performing section 1.1.1 in respect to the average of all KPIs 78
Figure 49 Organizational Performance, Organizational Appraisals and Digital Transformation Strategy. (Author’s own research). 83
Figure 50 Performance Management System in the Digital Era. (Author’s own research). 84
Figure 51 The evolution of Industrial Revolution. Source: (Genovese, 2022). Available at: https://www.huawei.com/en/technology-insights/publications/winwin/29/accelerating-success-in-the-4th-industrial-revolution. 85
Οι οργανισμοί οι οποίοι διανύουν την διαδικασία ψηφιακού μετασχηματισμού έχουν επενδύσει σε μεθόδους και εργαλεία για εξόρυξη δεδομένων για να υποβοηθήσουν τους λήπτες αποφάσεων με διαισθητικά συμπεράσματα που προκύπτουν από μεθόδους εξόρυξης δεδομένων και που επιπλέον ελαχιστοποιούν υποκειμενικές εκτιμήσεις. Η σημερινή ψηφιακή και βασισμένη σε δεδομένα διάσταση της διαχείρισης απόδοσης οργανισμών αποτελεί την κεντρική έννοια της ανάλυσης ανθρώπινου δυναμικού η οποία και αποτελεί την προσέγγιση την οποία η παρούσα διατριβή θα αναλύσει εις βάθος και θα επιδείξει τους τρόπους με τους οποίους δύναται να επιφέρει πραγματικό αντίκτυπο στους οργανισμούς εκείνους που χρησιμοποιούν την ανάλυση ανθρώπινου δυναμικού στο χαρτοφυλάκιό των.
Δεδομένου ότι δεν υπάρχει δημόσια διαθέσιμο λογισμικό Ανάλυσης Ανθρώπινου Δυναμικού καθώς και ότι οι εταιρίες αντιμετωπίζουν τις υλοποιήσεις τους ως ιδιόκτητα αγαθά για να ξεπεράσουν τον ανταγωνισμό, η παρούσα διατριβή παρουσιάζει τη δική μας υλοποίηση ανοιχτού κώδικα (https://github.com/leonidas-afk/PeopleAnalytics-Demo) ενός εξειδικευμένου λογισμικού Ανάλυσης Ανθρώπινου Δυναμικού, χρησιμοποιώντας ένα ευρέως διαδεδομένο εργαλείου.
Χρησιμοποιούμε την υλοποίησή μας με σκοπό να παράγουμε διαισθητικά συμπεράσματα για ένα οργανισμό που προσομοιώνουμε και τελικά προτείνουμε κατευθύνσεις για την βελτίωση του επιλεγμένου εργαλείου λογισμικού καθώς και την βελτίωση παρόμοιων εργαλείων λογισμικού που συχνά χρησιμοποιούνται για την διαχείρισης απόδοσης οργανισμών.
Organizations undergoing digital transformation have invested on data analytics methods and tools to assist leaders to undertake data-driven decisions, while also decreasing bias. This digital and data-driven side of organizational performance management is the core concept of People Analytics, which constitutes the approach that this thesis shall analyze in depth and shall demonstrate how it can derive real impact to decision-makers within an organization using People Analytics in their portfolio.
Given that there does not exist any publicly available People Analytics software implementation in any Information Technology tool because companies treat their People Analytics implementations as proprietary and as precious assets to overcome competition, in this thesis we present an own open source (https://github.com/leonidas-afk/PeopleAnalytics-Demo) released implementation of a custom People analytics software using a selected widely used tool for Performance Management. We use our implementation to provide data-driven people analytics insights for an emulated organization and finally we provide an account of directions for improvement of the selected tool as well as for the improvement of similar tools commonly used for organizational performance management.
Investigation on how people analytics have the potential to improve managerial and business decision making processes during the COVID pandemic era and beyond, wherein teleworking is a common practice Περιγραφή: std111374-ΛΥΜΠΕΡΟΠΟΥΛΟΣ-ΛΕΩΝΙΔΑΣ.pdf (pdf)
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Investigation on how people analytics have the potential to improve managerial and business decision making processes during the COVID pandemic era and beyond, wherein teleworking is a common practice - Identifier: 172094
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Investigation on how people analytics have the potential to improve managerial and business decision making processes during the COVID pandemic era and beyond, wherein teleworking is a common practice