Overview — Academic Manuscripts

This table gives an overview of the most important People Analytics academic manuscripts. The table contains the available information about the manuscripts. Further, the table offers the function to toggle columns individually. You can filter for a certain attribute by simply typing in your filter term in the field below. Additionally, you can order the table according the different features in the table heads. Hovering over the table head will show you a short explanation about the property in this column. Please note: if you have a small display, it might be possible that not all columns are visible without scrolling.

Details
Dummy
Term
Purpose/ Statement
Genre/ Research Methods
Concept
IT
Data
(Research) Methods
Stakeholders
/Drivers Outcomes/Goals Contributions
Theoretical Warrant(s)
Level of analysis
Side effects
Theoretical instanciation/ link function
Comparison with our model
Comment
Bodie et al (2017) - The Law and Policy of People Analytics. University of Colorado Law Review 88. discipline Law People Analytics Review ethics and bias in algorithmic recruiting Review (Legal) [argument based on history, definition of people analytics & taylorism] Thus, while the term people analytics can cover a variety of approaches to HR management, they, as a group, generally follow a particular pattern: (1) the search for new pools of quantitative data that are correlated with business and employment success, and (2) the use of such data to make workplace decisions and to replace subjective decision making by managers. Computer Science "more data" Quantitative & statistical analysis & knowledge discovery & data mining & predictive analytics & NHST & Correlations HR department Management (Workplace) Decision making scientific management & taylorism Individual Group Ethics & Legal & Bias Not addressed wider focus, takes into account all sources of data, looking to improve any people related organisational outcomes jh: legal perspective, history of and definition of PA, more details on definition of PA
Cheng (2017). Causal modeling in HR Analytics: a practical guide to models, pitfalls, and suggestions. Academy of Management Annual Meeting Proceedings, 1. discipline HR/management HR Analytics Review (technical) modeling and quasi-expermential designs Review (technical) & Methodology a tool that encompasses statistical models to add strategic influence in human resource management PA as Tool IT provides Big Data Big Data Quantitative & statistical analysis & predictive analytics & regression & longitudinal multivariate models & quasi-experimental HR department Improve HR Decisions & Strategic Influence not discussed & implied positivist Individual Statistical Errors & Robustness of Models Not addressed nucleus is HR function, which if moving beyond boundaries can provide strategic influence & different focus than us jh: review of 8 papers on HR Analytics, provides info on pitfalls or current implementation, e.g. lack of academic rigour, pracititioners not sharing details & good for motivation & goal is providing overview and recommendations for modeling & only chose peerreviewed articles
Marler, J. H., and Boudreau, J. W. (2017). An evidence-based review of HR Analytics. International Journal of Human Resource Management, 28(1), 3–26. HR Analytics Review Review A HR practice enabled by information technology that uses descriptive, visual, and statistical analyses of data related to HR processes, human capital, organizational performance, and external economic benchmarks to establish business impact and enable data-driven decision-making IT as Enabler HR Data Performance Data External Market Data Quantitative & Descriptive & Visualisation & Statistical Analysis HR department (Data-driven) Decision making RBV & HR Scorecard & Agency Theory Individual Group Not addressed evidence-based integrative synthesis sjacome: jh: main goal is review of HRA articles & how & why it works
Shrivastava, S. et.al (2018) Redefining HR using people analytics: the case of Google discipline HR/commercial People Analytics & HR Analytics Overview & Best Practices Business case study People analytics or human resource (HR) analytics refers to the use of analytical techniques such as data mining, predictive analytics and contextual analytics to enable managers to take better decisions related to their workforce not mentioned Performance Data Quantitative & Predictive analytics & data mining & contextual analytics Management Decision making & Hiring & Retention & Collaboration & Performance not discussed & implied positivist Individual Group Not addressed Not addressed wider focus jh: pracitioner view, sales pitch for PA at google
Singer, et al (2017) People Analytics in Software Development. Intl Summer School on Generative and Transformational Techniques in Software Engineering discipline tech People Analytics Present PA Tool für Software development Design Science the use of data, quantitative and qualitative analysis methods, and domain knowledge to discover insights about how people work together with the goal of improving collaboration. IT as Enabler Big Data Quantitative and Qualitative Developers Collaboration they discuss gaming the system, presentation of metrics more important than actual numbers Individual Privacy & Surveillance & Impression Management Not addressed focus on developer logs, fits to our model jh: case study of software engerineering gamified dashboard, provides weak definition of PA, mostly focuses on their experiment & goal inquire how PA can improve software dev collaboration
Tursunbayeva et al. (2018), People analytics - A scoping review of conceptual boundaries and value propositions People Analytics Review Review People Analytics is an area of HRM practice, research and innovation concerned with the use of information technologies, descriptive and predictive data analytics and visualisation tools for generating actionable insights about workforce dynamics, human capital, and individual and team performance that can be used strategically to optimise organisational effectiveness, efficiency and outcomes, and improve employee experience IT as enabler not mentioned Quantitative & Descriptive & Visualisation & Predictive Analytics HR department Performance & Employee Experience Not mentioned Individual Group Not addressed Not addressed sjacome: They adopt a broad approach to examine the PA topic, that according to them is poorely understood. sjacome: jh: overview of terms, provides integrated definition, weak method, mostly based on frequency of words, no critical discussion
Sprague (2015) - Welcome to the Machine Privacy and WorkplaceImplications of Predictive Analytics. Richmond Journal of Law and Technology discipline Law Workplace Analytics Review privacy concerns Review (Legal) Predictive Analytics use a method known as data mining to identify trends, patterns, or relationships among data, which can then be used to develop a predictive model & in many cases attempting to predict behavior." IT as enabler "more data" log data Quantitative & Data mining & Predictive Analytics Data scientists Improve Management & Predict Behaviour Taylorism Individual Group Privacy & Surveillance & Discrimination too broad sjacome: complemented. Jh: legal perspective, negative stance, provides analogy to taylorism, argues from big data analytics to PA, makes a point that employers must prove causation over mere correlation.
HR and analytics: why HR is set to fail the big data challenge [Angrave, David et al, 2016] HR Analytics Critique academic opinion-piece HR analytics involves complex multistage projects requiring question formulation, research design, data organisation, and statistical and econometric modelling of differing levels of complexity and rigour based on big data enables data driven decision making to improve performance of people-related processes HRIS dashboards HRIS big data longitudinal data (un)structured data surveys Quantitative & Visualisation & Statistical analysis & Experiments, quasi-experiments & predictive analytics multivariate longitudinal analysis HR department Strategic value & Performance & Decision making RBV & positivist & organizational psychology & critical realism Organizational lack of analytical capability & strategic impact & reduced wellbeing & privacy & ethics & data quality & does it work? Not addressed Mix the concepts of HR and data analytics jh: critical perspective of HR developments by Angrave, opinion piece
Optigrow: People Analytics for Job Transfers [Wei. D, 2015] People Analytics Propose big data approach for Job Transfers Design Science & Methodology No concept or definition used Custom Algorithm expertise assessments curricula vitae project tracking data and HR information Quantitative & Custom Scoring Algorithm HR department Internal Hiring & Job Transfer Not mentioned Individual Sponsorship Not addressed jh: case study at IBM, optigrow for re-hiring from internal employees & mathematical feasibility and organisational recommendations, e.g. stakeholder, management buy-in & no mention of PA, taylorism, pitfalls, etc. no definition & no causality or theory
The best practices to excel at people analytics, [Green. David, 2017] People Analytics Best practices Practitioner's whitepaper No concept or definition used not mentioned not mentioned Anectodal references HR department CHRO Business Value Not mentioned Not clear Sponsorship Not addressed not comparable jh: no scientific rigour, lacks method, selection bias, only looks at top cases, no arguments for the points & may be useful for some anectodal references and further inquiry into the mentioned cases sjacome: the practices are described according to the expertise of the author.
Smart HR 4.0 – how industry 4.0 is disrupting HR(Review) [Sivathanu, B. et. al, 2018] Smart Human Resources Best practices business case study SHR is characterized by innovations in digital technologies such as Internet of-Things, Big Data Analytics, and artificial intelligence (AI) and fast data networks such as 4G and 5G for the effective management of next-generation employees IT as Enabler Internet of-Things fast data networks such as 4G and 5G Big Data Quantitative & Artificial Intelligence & Big Data Analytics HR department Improve Management & Hiring & Onboarding & Offboarding & Retention & Learning & Development Not mentioned Individual Culture Conceptual framework for talent on boarding jh: some nice ideas, introduction no substance, and not related to specifics of PA & hypotheses are interesting, but not theoretically derived, i.e. arbitrary & 1 case study referenced (capgemini) & goal is conceptual framework, which depicts basic ideas on how big data can influence HR
Implicit bias in predictive data profiling within recruitments [Persson A, 2016] People Analytics Review ethics and bias in algorithmic recruiting academic opinion-piece Companies use data mining:machine learning with algorithms and statistical learning. This if often referredto as using “Big Data”, or “People Analytics” & i.e. using large datasets to identify parameters that represents the best candidates for various positions. The motivation for companies is often the claim to become more objective in their assessment. They can also be claimed to want to become more certain in their decision making for hiring. not mentioned Big Data Quantitative & Statistical analysis & machine learning & Data mining HR department Recruiters Decision making Not mentioned Individual Discrimination & Bias & Data Quality & Does it work? & Complexity of algorithms & Privacy & GDPR Not addressed jh: not very well theorized, development of argument is lacking warrants and evidence & repeats some ideas that are covered elsewhere & note it is IFIP pre conf paper by a phd student it is not clear where this paper is positioned and from what arguments it draws from & weak sources & goal is to analyse potential pitfalls and provide ideas how to deal with them in terms of big people data analytics
People Analytics: an organizational psychology perspective on data-oriented leadership [Reindl, 2016] People Analytics Overview Review People Analytics bezeichnen die systematische Analyse von Daten aus dem Personalwesen in Verbindung mit Daten aus anderen Unternehmensbereichen mit dem Ziel, Faktoren der Zusammenarbeit von Mitarbeitern und der Wettbewerbsfähigkeit von Unternehmen besser zu verstehen und gezielt zu fördern IT as Enabler "more data" HRIS employee count churn rates sick people personnel costs revenue curricula vitae longitudinal data sociometric badges Quantitative & Clusteranalysis & Trend analysis & Regression analysis & SEM & SNA & predictive analytics Management hiring & retention & workforce planning & employee experience & competitive advantage & leadership & decision making & strategic alignment organisational psychology Individual Legal & Ethics & Privacy & Change Management (Actionable Insights) Sozial-, Emotions- und Motivationspsychologie sowie aus den Praxisbereichen Business Intelligence und Big Data. jh: introduction to people analytics incl. definition, common methods, potential applications of PA & pitfalls and challenges & article is a call for more PA & overview is supported by selected sources, but lacking some sources & definitely useful article
Book: Human resources strategy and change: Essentials of workforce planning and controlling [Weiss, C., 2016] Workforce Planning and Controlling Best Practices Practitioner's handbook Workforce planning and controlling is the process of HR that ensures in a structured way that an organization always has the right number of people with the right competencies at the right moment at the right location and with the right costs. It analyzes the workforce demand, determines the workforce supply, and generates the insights to enable the relevant stakeholders to match demand with supply, allocate and schedule resources, identify workforce gaps, and develop action plans to fill or reduce the gaps. Specialized workforce planning systems workforce metrics skills employee count GPS costs KPIs Quantitative & Descriptive & Predictive Analytics HR department Improve management & Performance not mentioned & Positivist (controlling) Individual Compliance & Transparency & Data Quality & Effort & Adoption & Change resistance Not addressed jh: quickly touches workforce analytics as going beyond KPIs and reporting into predictive analytics & that's it & it is a practitioner's handbook, not research article
Is Your Company Ready for HR Analytics? [Baesens, Bart & De Winne, Sophie & Sels, Luc, 2017] HR Analytics Best practices opinion-piece HR analytics is “the new kid on the block” in busi-ness analytics applications, therefore practitioners can substantially benefit from lessons learned in applying an-alytics to customer-focused areas — and thus avoid many rookie mistakes and expensive beginner traps. IT as Enabler Big Data public data social network data eg. Emails project data location skills Quantitative & Statistical analysis & Social network analysis & Regression models HR department performance & hiring & retention & decision making Not mentioned Individual Lack of analytical capability & actionable insights & privacy & ethics & diversity Not addressed benefit from lessons learned in applying analytics to customer-focused areas jh: mitsloan & provides advice for practitioners on how to use predictive models & extrapolated from experience in customer predictive models & look at business, safeguard privacy, constantly evaluate models, considers SNA/networks
HR analytics and performance appraisal system: A conceptual framework for employee performance improvement [Sharma and Sharma, 2017] HR Analytics Research employees willingness to improve under performance appraisal systems Conceptual HR analytics is more than just metrics and/or scorecards. It consists of various modeling tools such as behavioral modeling, predictive modeling, impact analysis, cost–benefit analysis and ROI analysis required for strategic HR decision-making IT as Enabler not mentioned Quantitative & Behavioral modeling & Predictive analytics & Impact analysis & cost–benefit analysis & ROI analysis HR department performance & (objective) decision making not mentioned Individual Bias & (perceived) Fairness & Discrimination Not addressed jh: posits that HRA is objective and can improve employees perception of appraisal system, coz "objective" & uses HRA as a blackbox term and does not address it any further & basically just "objective" theoretical development seems okay-ish, so probably a legit paper & quality is mediocre & paper name is wrong in column B
The rise (and fall?) of HR analytics A study into the future application, value, structure, and system support [van den Heuvel, Sjoerd, 2017] HR Analytics & People Analytics Explore future of HR Analytics academic research paper (20 interviews) the systematic identification and quantification of the people drivers of business outcomes, with the purpose to make better decisions "a tool for HR" digital personnel management IT as an Enabler "more data" internal and external integration from multiple sources Quantitative & statistical analysis & descriptive & correlations & predictive analytics & visualisation Any department HR department Management absenteeism & diversity & evidence-based decision making & performance & efficiency & costs & leadership & hiring & succession planning & workforce planning & retention & learning & development & wellbeing & compensation & engagement not addressed Individual legal & privacy & trust & strategic impact & sponsorship Not addressed "The label workforce analytics is actually detached from the HR function, but may have an exploitative association. Still, some leading software vendors such as Workday and SAP’s SuccessFactors use the term workforce analytics for their products. People analytics may the most neutral and employee friendly label, and is for example consistently used by Google, who in general avoids the term human resources and therefore named the HR department ‘People Operations’. Usage of any specific label will therefore mostly be a matter of consistency in specific product or business language and/or philosophy. The present study adopts the label HR Analytics, since the study was conducted in a Dutch context, where the dominant label is HR Analytics."p5 jh: defines PA and has 20 survey/interview as sample on what defines PA & too long for me to read in detail, but seemed interesting enough & clear motivation (i.e. lack of academic articles on HRA) & needs more attention
Learning from practice: how HR analytics avoids being a management fad [Rasmussen, Thomas, 2015] HR Analytics Critique academic opinion-piece Evidence-based decision making for HR function Analytics Qualitative and Quantitative Quantitative & Multivariate Statistics Organizations / HR Professionals HR Decision making Not mentioned Organizational Not addressed Not addressed "So far the published evidence supporting the alleged value of HR analytics is actually quite slim it is currently based more on belief than evidence, and most often published by consultants with a commercial interest in the HR analytics market" negative: Lack of analytics about analytics It is not about data,but about data for informed decision-making Academic mindset in a business setting HR analytics run from an HR Center-of-Expertise(CoE) Hr analytics can be misused to maintain the status quo and drive a certain agenda jh: it maersk oil article & opinion piece with practical guidance & no scientific rigour & does provide interesting take on all our columns though & needs more attention
"Personal social dashboard": A tool for measuring your social engagement effectiveness in the enterprise [Kremer-Davidson, S. et al , 2017] Social Analytics Present PA Tool for social analytics design-science Personal feedback on social activities via Dashboard Dashboard CACS Logs Quantitative & Social Network Analysis & Activity Ranking Employees Employee engagement & Employee empowerment & Employee retention not addressed Individual Privacy Not addressed Only employees themselves have access to their scores and even their managers cannot see them. This is crucial for protecting the privacy of employees and verifying that these scores cannot be used against them in any way. Interestingly, we see many employees sharing their scores through screen captures in the enterprise social network. Some employees mentioned they would like their managers to see their score improvement towards their yearly performance assessment jh: design science, social analytis, self-service & users improve engagement & does not consider wider discussion of social analytics & is relevant though & they do not argue why their tool is better than others & tool itself not evaluated
Raising your eminence inside the enterprise social network [Kremer-Davidson, S. et al , 2016] Social Analytics Overview design-science No definition provided Tool interview company's bloggers social behavioral patterns Quantitative and Qualitative Employees Employee engagement Graph Theory (?) individual Not addressed Not addressed jh: includes some descriptives on what makes high contributors sjacome: not relevant (?)
Inferring employee engagement from social media [Shami et al, 2015] Social Analytics Present Algorithm design-science Social Analytics using natural language processing for predicting social metrics such as employee engagement. IT as Enabler Dashboard CACS Logs Quantitative & Natural Language Processing & Multivariate Statistics Not addressed Employee engagement not discussed & implied positivist Individual Not addressed Macey and Schneider model of employee engagement Employee Engagement (employee willingness to apply discretionary effort towards organizational goals), state vs. trait jh: measures employee engagement, discusses that data traces can be me realtime than annual surveys, addresses trust, gaming the system & as such considers PA a little bit more broadly
Understanding employee social media chatter with enterprise social pulse [Shami et al, 2014] Social Analytics Present PA Tool design-science Social Analytics using natural language processing for predicting social metrics such as employee engagement. Dashboard CACS Logs Quantitative & Natural Language Processing & Multivariate Statistics Not addressed Employee engagement not discussed & implied positivist Individual Lack of managerial support & Privacy Not addressed We believe that ESP will be beneficial for companies with an active social media footprint and the business need to understand employee chatter. Technological challenges such as the limitations of sentiment analysis, and cultural barriers such as self-censorship and the lack of relevant social media content remain jh: text mining and computational linguistic analysis, evaluated results wiht survey & real-time automated analysis is beneficial for dynamic phenomena that are subject to frequent change & employees can compare themselves to the average & typically such an analysis requires activity in the given software & needs trust by employees, possibility of gaming the system & & Note from IBM research team
Finger on the pulse: The value of the activity stream in the enterprise [Guy, I., 2013] Social Analytics Present PA Tool design-science Social Analytics using natural language processing for predicting social metrics such as awareness Dashboard CACS Logs Quantitative & Natural Language Processing HR department Management IT Awareness not addressed Individual Organizational Not addressed Not addressed jh: social analytics, topic identification, sentiment analytics & evaluated with interviews & in particular HR is intested in slicing the data by characteristics & design science & IBM product dev
Using workforce analytics to improve strategy execution [Levenson, Alec, 2018] Workforce Analytics Introduce Workforce Analytics & Best Practices & Critique Conceptual & Academic Case Study Workforce analytics is using scientific means, i.e. data collection and rigorous analysis, for improving HR processes, strategy exectuion, and organizational effectiveness in general. not mentioned anonymized aggregate data interviews surveys internal IT systems HRIS Qualitative & Quantitative & Multivariate Statistics & Multilevel modeling & Social Network Analysis HR department Management organizational management & strategic execution & organizational effectiveness & competitive advantage & recruiting & training & workforce planning & performance & engagement & compensation & learning & development Systems approach & Social science Individual Group Organizational Lack of managerial support & senior sponsorship referring to social scientists regarding importance "In this article I argue that we need a different orientation to how workforce analytics is defined and conducted in organizations: a much greater emphasis on systems thinking and diagnostics, The approach I recommend is to start with the business strategy and the overarching objectives senior leaders aim to accomplish in the marketplace" jh: focus on competitive advantage and analysis on higher level e.g. org/group level. quantitivate not (always) needed there, instead qualitative analysis & addresses some nice ideas for analysis & provides depiction of approach & part of special issue
Workforce analytics: A case study of scholar-practitioner collaboration [Simon, Cristina & Ferreiro, Eva, 2018] Workforce Analytics Illustrate exchange between academic and practitioners in workforce analytics projects academic case study Workforce analytics is an effort that goes beyond applying statistical techniques to resolve practical managerial issues through the use of inferences and the development and testing of hypotheses based on workforce data. Question what role the workforce plays in supporting business optimize the contribution human capital makes to corporate performance IT an Enabler Dashboard "more data" Big Data Demographic Data Performance Data Multivariate Statistics & Cluster Analysis & Regression & Correlation Analysis HR department Performance Following the guidelines of the six-stage model of Talent Analytics development by Davenport, Harris, and Shapiro (2010), it could be stated that the company had shared definitions for their basic key indicators and had therefore reached the level of “Analytical HR” (Stage 2) capabilities, but did not have the expertise in making complex inferences or predictions about the contribution of their workforce to store performance. Individual Group Organizational Lack of managerial support & Lack of analytical capability & Change management Not addressed relationship between practitioners and academics A successful Workforceanalytics infrastructure requires specific sets of knowledge on busi-ness research methods and rigorous analytical skills, as well as thedevelopment of a“questioning mind-set”that drives the design, col-lection, analysis, and further interpretation of the data (Angrave,Charlwood, Kirkpatrick, Lawrence, & Stuart, 2016) jh: case study on workforce analytics at inditex, quite interesting & addresses different methods and challenges when implementing such projects & storytelling & focus on competitive analytics & same group as Lawler, Boudreau, Levenson
A strategic approach to workforce analytics: Integrating science and agility [ McIver, Derrick, et al., 2018] Workforce Analytics Introduce Workforce Analytics & Best Practices Conceptual Process to collect, manipulate, analyse HR related data and test hypotheses in a scientific manner. Data is integrated from different internal and external sources towards evidence-based decisions, not only for HR, but business in general. IT as Enabler dashboard platform structured unstructured CACS Logs Big Data internal external Quantitative & Predictive Analytics & Statistics & Machine Learning HR department Management decision making & organizational outcomes & strategic value mix of inductive/deductive & theory- and data-driven Individual group organizational Ethical & political issues & stakeholder support & change management & analytical capability Not addressed agile workforce analytics process: (1) prioritizing issues, (2) integrating deductive and inductive approaches, (3) preparing and validating data, (4) applying multiple methods in concert to support decisions, and (5) transforming insight into action to improve business outcomes jh: weak article & proposes concept of agile+PA as a process & provides understanding and methods of PA & can be well used.
Workforce assessment method for an urban police department Using analytics to estimate patrol staffing [Srinivasan, Sudharshana, et al., 2013] Workforce Analytics Propose Simulation Model Simulation Study improve business effectiveness by evidence-based decision making using qualitative and quantitative analysis of empirical big data to compare multiple solutions to a problem before the actual implementation of the proposed solution. IT an Enabler "more data" Big Data Quantitative & Predictive Analytics & discrete-event simulation model Not addressed performance & staffing & business decisions evidence-based decision making Individual Group Change resistance Not addressed police agencies in the US This research provides mathematical evidence to support the size of the patrol workforce needed to meet the RPD’s performance benchmarks jh: more data by tech innovations & analytics enables better decisions & but requires overcoming stakeholder resistance (and costs) & evidence based decision making is hype & very specialised context.
Book chapter: HR metrics and workforce analytics [KD Carlson, MJ Kavanagh, 2011] Workforce Analytics & Predictive Analysis & HR metrics Best practices book chapter measurement of human capital and the impact of people on organization processes to improve effectiveness & evidence-based management & workforce analytics is a system IT as an Enabler HRIS dashboard HRIS Big Data Quantitative & realtime & metrics & benchmarking & predictive analytics & experiments (A/B testing) & balanced scorecard HR department Management decision-making & organizational effectiveness & recruiting & retention & promotions & succession planning & compensationb & employee engagement & performance & compliance & learning & development & workforce planning & strategc value Scientific management (Taylorism) & Industrial & Organizational Psychology Individual Group Organizational Stakeholder Support & Change Management Not addressed As a result, organizations that make investments in internal human capital assessment resulting in useful HR metrics and workforce analytics will become less willing to share their knowledge with other organizations in their industry
Book: Handbook of Service Science: Workforce analytics for the services economy [Aleksandra Mojsilovi?Daniel Connors, 2010] Workforce Analytics Review research paper workforce optimization through improved planning, scheduling, deployment and resource management to yield greater business value and profits IT as an Enabler HRIS data ERP data Quantitative & multivariate statistics, machine learning & clustering & simulations & social network analysis HR department manage skills & workforce planning & staffing & demand forecasting & talent management & recruiting & retention & knowledge management & promotion & learning & development & strategic value & innovation & not addressed Individual Group Organizational Not addressed Not addressed IBM
Transforming HR in the digital era: Workforce analytics can move people specialists to the center of decision-making [Prerna Lal, 2015] Workforce Analytics Review opinion-piece Evidence-based decision making, informed by visualization and analysis of workforce data, to provide actionable and deep insights for driving workforce-related activities in the HR function and processes throughout the organization. dashboard HRIS data Predictive Analytics & Descriptive Analytics & Visualization & forecast and scenario models HR department performance & evidence-based decision making & talent management & recruiting & employee retention & succession planning & learning & development & workforce planning & staffing & compensation & strategic value Not mentioned Individual Data Integration Not addressed jh: opinion piece, weak arguments & but okay journal
Achieving Human Capital Management: Building the Workforce Analytics Infrastructure [J Barrete, 2004] Workforce Analytics Technical Overview of Data Warehouse opinion-piece From metrics to Analytics: Date Warehousing using internal and external HR and other function's data to improve people-related business functions Data Warehouse OLAP cubes external data internal data HRIS surveys public data sets Quantitative & Data Warehousing & ETL & OLAP & descriptive analytics & what-if analysis HR department Analysts Talent Management & succession planning & employment satisfaction & workforce optimization not addressed Individual Legal & Data Integration & Costs Not addressed jh: opinion piece & non academic & technical focus
Quantile Regression for Workforce Analytics [KN Ramamurthy, KR Varshney, 2013] Workforce Analytics & Workforce Behaviour Propose Algorithm Methodological Workforce analytics is a broad area comprising many scientific techniques that help in understanding and predicting the behavior of the workforce in a business using available data not mentioned HRIS data Quantitative & Quantile Regression Not addressed Performance implied positivist Individual Not addressed Not addressed develop frameworks based on quantile regression jh: technical paper & IBM
Latent Ability Model: A Generative Probabilistic Learning Framework for Workforce Analytics [Z Luo, L Liu, J Yin, Y Li, Z Wu, 2018] Workforce Analytics Propose Algorithm Methodological Workforce analytics is a data-driven statistical learning methodology that employs statistical models and machine learn-ing algorithms to worker-related activity data logs, enabling enterprise organizations to optimize their talent pools and transform human resource management IT as an Enabler CACS Logs Quantitative & Machine Learning & Latent ability Model & Gradient Descent HR department Analysts Employee management & performance & improve HR processes implied positivist Individual Not addressed Not addressed jh: technical paper, which estimates 3 latent parameters (performance, ability, matchup) for employees given their activity-event-log & rich dataset &
Adopting Analytics to Effectively Manage Workforce Needs [R Isherwood, M Seale, 2014] Workforce Analytics Review Descriptive Report quantitative rigour to effectively manage workforce (e.g. recruiting, retention, development) with internal & external data. apply marcoeconomic data to inform sound decision making Workforce analytics offer a fact-based approach to addressing workforce-related issues can reveal risks for employee segments and also the reasons IT as an Enabler Internal External Quantitative & Predictive Analytics HR department recruiting & retention & learning & development & workforce planning & staffing & employee satisfaction & employee engagement & talent management & strategic alignment implied positivist Individual Group Organizational Lack of analytical capability Not addressed Oil Companies