• Mike Ulrich
    July 9, 2019

    The author of this post is Professor Mike Ulrich from Utah State University, ThinkTank Academic Lead and author of Victory Through Organization. To find out more about the types of work that the ThinkTank is undertaking, please click here. To take part in the research, please complete this form.

    HR analytics is not just about analytics - you can improve your analytical abilities without become a data expert.

    I once worked on an HR analytics project with a team of highly trained statisticians and HR professors. Our goal was to comb through hundreds of thousands of observations to predict what health insurance plan an employee would choose. At the start of our second weekly meeting, a statistician colleague mentioned in passing that her machine learning algorithm found a variable that explained over 95% of the variance in turnover. This was incredible–in just two weeks she accidentally figured out the leading cause of turnover, something companies and researchers spent decades trying to decipher.

    My other HR colleague and I immediately started dreaming about the publications and consulting opportunities that would result from such a significant finding. That is until she told us that whether a company offered pet insurance was the magical variable, which led us to question how much our statistician friend really knew about people and HR. Alas, after a little more exploration, pet insurance wasn’t the panacea we hoped.

    This story highlights an important principal of HR analytics that often goes overlooked: analytics is not about analyzing data or modern computational techniques; analytics is about using data to gain insights that enable better decision making and performance. Analytics without a structured decision-making process is like trying to bake a cake without sugar–it may look okay on the outside but ultimately leaves you wanting more.

    If I had an hour to solve a problem, I’d spend 55 minutes thinking about the problem and 5 minutes thinking about solutions — Albert Einstein

    How can you improve your evidence-based decision-making mindset?
    Regardless of your formal role, an analytics mindset can improve your performance and decision-making. Becoming an analytically-minded HR professional won’t happen overnight, and you likely will never be an expert in every part of analytics, but with deliberate effort and training you can begin to incorporate analytical and evidence-based skills into your day-to-day activities.

    While each analytics project is different, there are principals that research suggests produce better results.
    • Remember that analytics should be geared towards collecting and assessing evidence to make decisions with real business implications. Evidence-based management may not be trendy but it produces better results.
    • Spend time at the start of a project 1) identifying the right questions to ask; 2) understanding, reframing, and defining the problems the project hopes to solve; 3) how the project’s results could be implemented; 4) getting buy in from decision makers
    • Understand the limitations of data and statistics. Bad data may produce interesting results but fail to improve the business. For example, subjective data (e.g., engagement, net-promoter score) are far less valuable than objective data.
    • Bias is inherent in all science but don’t let that stop you from listening to people whose biases are different than yours. We lose perspective and limit opportunities for creativity when we only listen to people who agree with our existing opinions.
    • Not everyone on the team needs to be good at data science or statistics. Just because someone failed Introduction to Statistics or Research Methods for Dummies in college doesn’t mean they can’t add value to an analytics project. One of my most useful colleagues doesn’t know the difference between a mean and an eggplant but has an incredible ability to ask questions and reframe problems.
    • Finding amazing results doesn’t matter if you can’t tell a story around the data. Data doesn’t change minds without an accompanying story.

    These are just a few of the many ways you can start building better individual competency and business capabilities for HR analytics.

    The HR Analytics Forum hopes to shed greater light on these topics and other ways you can use analytics to make real business impact.
  • Nigel Dias
    June 21, 2019

    On Tuesday, we launched the latest HR Analytics ThinkTank report, Predictive Analytics and Data Science: A Guide for HR Analytics Leaders. Download instructions below.

    As part of this, the ThinkTank's Professor @Andy Charlwood (Professor of HRM) and Dr Danat Valizade (Senior Lecturer on Quantitative Methods) from University of Leeds took us through their ThinkTank paper, focusing on the use of real predictive analytics techniques used to connect HR factors to business outcomes in the care industry (nursing homes).

    Thank you to everyone who left some positive feedback. If you would like to watch it again, or if you missed the webinar, we are delighted to share the webinar with everyone, below:

    A few people have commented that the webinar was both quite "advanced" and quite "technical". As most of our community will know, our research and content (all for free) spans the spectrum of HR analytics content, from strategy topics to the advanced techniques to exploring change management. We believe that in order to develop the practice of HR analytics, we need to innovate and profile thought at each end of the spectrum. Even if you aren't a data scientist yourself, we hope you find the session useful, and will contribute your thoughts for how these techniques might help your organisation's decision making.

    Download the Report
    If you're a ThinkTank participant, you can login and download the report, Predictive Analytics and Data Science: A Guide for HR Analytics Leaders, from the Forum. If you can't reach the report, please email and we'll help you get access.


    Related Links
    ThinkTank Overview: Please click here
    Report Announcement: Please click here
    Meetup Recording: Please click here

    Please note you may need to log in to access some content.
  • Andrea Schirru
    June 16, 2019

    The author of this post is an Organisation and People Data Analyst at GSK, and a speaker from a previous meetup. To watch @Andrea Schirru give a talk on Survivor Analyses, please click here. To be kept up to date HR and People analytics meetups around the world, please sign up to the ThinkTank newsletter by clicking here or keep an eye on our Meetup Listings Page here.

    Predicting Healthcare Outcomes Using People Data Science with Professor Charlwood
    In the first presentation of the evening, @Andy Charlwood (Professor of HRM at Leeds University and HR Analytics ThinkTank Academic Lead) took us though a data science example within the healthcare industry. There is currently a global shortage of nurses at the moment, but there are massive challenges to invest in the industry being a low margin business.

    To develop a casual model, he considered outcome indicators related to quality, people resourcing and contextual variables. Regression analyses allowed him to view changes over time within individual homes as well as within home differences but was not very informative to take decisions. Random forest provided more immediate insight than traditional regression analysis approach. Creating a partial dependent plot in Python he could see more clearly that having a more experienced and skilled workforce will likely improve quality in nurses homes.

    However, the magnitude of the quality improvements is unlikely to make this a cost effective intervention. Professor Charlwood suggested that if we wanted to learn more from observational data, we would need to use it as a basis for experimental and quasi-experimental analysis.

    On 18 June, @Andy Charlwood and Dr Danat Valizade will be hosting a free webinar, talking attendees through the use of Data Science in HR, highlighting the techniques used in their talk. To register please click here.


    Seagulls and Bombs: Predicting Performance in the Workplace with Andreas Kyprianou
    In his presentation, @Andreas Kyprianou, Head of Talent, shared how at Bank of America they optimise assessment selection to predict if someone is going to be a good employee. Starting from Schmidt & Hunter’s key concept (1998) of predictive validity of assessment methods, that throughout more than 30 years proved that only GMA (general mental ability) & structured interviews work in practice, he focused on task performance (what) and contextual performance (how). He used ROC (Receiving Operating Characteristics) to predict whether someone is going to be a high performer taking all the test scores (the higher on top of the curve the better the prediction power of the test) and then created a binary variable (>50 high performers, all others). This way he proved that 66% of the time the numerical test would be right (‘what’) and, going a step further, tested the interrelationships between the tests through a Chi-Square and Regression Analysis. He found out that if the 3 variables numerical testing, AC-grouping exercise & 1st stage interview are all present the likelihood of predicting high performers is 75%, if one of 3 is missing it drastically falls down. There is a high degree of interrelations between those variables.

    However, with this approach, it was not possible to predict well the contextual performance. Therefore, as a result, for the task performance he requested improved versions of numerical testing, group exercise and 1st stage interview. He focused on training interviews and group assessors to identify impression management techniques and implemented a cut-off point of 80% at numerical testing to improve sifting prior to assessment centre. Within the contextual performance, because it was not predicted by anything, he introduced situation judgement testing and are now looking at different things, e.g. behavioural assessments, gamification tools and personality assessment testing.

    To watch the video (for free) please click here.


    To join us a the London meetup, or to find HR and People Analytics meetups near you around the world, please sign up to the ThinkTank newsletter by clicking here or keep an eye on our Meetup Listings Page here.

  • Andy Charlwood
    May 24, 2019

    On 18 June, we will host @Andy Charlwood (Professor of HRM and ThinkTank Academic Lead) and Danat Valizade as they talk us through data science in HR, giving real examples based on their recent work for the National Institute for Health Research.

    To sign up, please click here. If you have participated in the ThinkTank research, you will be sent a copy of the report after the Launch webinar. If you would like to take part in the research, please register here.

    There is a huge amount of hype about the potential of predictive analytics and data science to make HR more data driven and evidence based. At the same time, a range of evidence suggests that the use of predictive analytics in HR is quite limited. Although many organisations are now using predictive analytics to understand which employees are more likely to quit I haven’t come across many other interesting examples of predictive analytics in action. I have talked to a number of HR analytics leaders who have experimented with predictive analytics in projects but found the results underwhelming because the actionable insight from the analysis was limited.


    Does having more and more highly skilled care staff result in better quality care? — Andy Charlwood

    Over the last year, my colleague Danat Valizade and I have been working on a research project (funded by the National Institute for Health Research) with a care home operator to try to understand the relationship between care home staffing and indicators of the quality of care. Broadly, we have been asking the question, does having more and more highly skilled care staff result in better quality care? This is an important question, because the care home sector expected to provide high quality care for residents despite low levels of funding from the UK government (if we contrast the UK with countries like the Netherlands, UK funding is much lower). The care home operator provided us with data from their administrative systems detailing staffing levels for different job grades (care assistant, senior care assistant and registered nurse) week-by-week along with data on the characteristics of the care homes and their residents. This project has allowed us to experiment with predictive analytics techniques, comparing and contrasting these with more traditional forms of statistical analysis.


    Danat and I are going to be sharing the provisional results of this project in a webinar on Tuesday 18th June. The exciting thing about this is that it will give us the opportunity to share what we have learnt about applying predictive analytics to real world people management problems. We’ll be talking about the importance of thinking hard about causality before starting any analysis, how traditional regression results compare to machine learning techniques and the strengths and limitations of different machine learning methods for addressing people management problems. If you are interested in finding out more about how to apply predictive analytics in HR, or if you have yourself used predictive analytics and want to tell us about your experiences and how they compare with ours, we hope you can join us for the webinar.

    To register for the webinar on 18th June please register here.
  • Nigel Dias
    April 3, 2019

    On the 18 March, our London HR and People Analytics community held its second meetup of the year. During this event our HR speakers, Dr Keith McNulty from McKinsey and Jared Valdron from Github, shared their experiences being technical leaders within the field. In our search for inspiration from other data industries, Dr @Merve Alanyali, Data Scientist at LV=, presented on her PhD using neural networks to predict wealth in London and New York using Instagram photos.

    Exploring the Edge of the People Analytics Universe with Keith McNulty
    Many people will recognise Keith McNulty (Global Head of People Measurement and Analytics @ McKinsey) as one of the thought leaders pushing the technical boundaries of the HR analytics space. In his talk, delivered with a Star Wars theme, he talked us through structural equation modelling and text analyses to pull out the themes of what characters talk about. He also added to the conversation that Kevin Metherell from Experian started in the January meetup by talking more about the uses of ONA in HR decision making.

    To watch the recording of Keith's presentation please click the image below or click here.


    People Analytics Through Organizational Change with Jared Valdron
    There is a temptation to assume that when you are the People Analytics lead for companies like McKinsey or Github, that you have an advantage because your audience is already data driven. In his talk, Jared took us through a variety of themes, from understanding and identifying variables to use in our modelling and why they the pros and cons of working in a data-driven organisation, telling stories about his experiences using (or not using) model and the actions they might drive.

    My favourite part of the talk was Jared's third talking point where he highlights that sometimes analysts can become attached to their models - but a good analyst will know when it is working, when it should be changed, and when it should be scrapped.

    To watch the recording of Jared's talk please click the image below or click here.


    Estimating Income Using Instagram Pictures
    Dr @Merve Alanyali joined us as our non-HR speaker, giving our predominantly HR data audience a glimpse of what other industries are doing in their analytics practices. During her PhD, Merve used a series of deep learning tools to parse millions of Instragram images.

    To watch the recording of Merve's presentation please click the image below or click here.


    Don't forget, you can still take part in the HR Analytics ThinkTank Research in 2019
    If you would like to help us and our university partners analyse HR and People analytics, joining our community as it searches and shares free insights around building functions, skills, careers, technology and more, please click here to read more, or please register to take part in the research by completing this form.

  • Nigel Dias
    February 25, 2019

    The following is a blog from the London HR and People Analytics Meetup on 16 January 2019. If you are based in London and want to join the mailing list for these events, please click here. If you are looking for a meetup in your area, or want to share your community details, please click here for our Global Meetup Directory.

    On the 16 January 2019, the London HR and People Analytics meetup community met at Runway East to eat pizza, have a drink and a chat - but also to hear from three speakers: @Kevin Metherell (People Analytics Innovation Lead @ Experian), @Andrea Schirru (People Analyst @ GSK) and Dr Stylianos Kampakis (@Stelios) (Sports and Social Media Data Scientist @ Brandtix).

    The aim of our meetups is simple: to bring together a community diverse data experts (HR and non-HR alike), to share and inspire innovation from the grassroots HR and People analytics community in London. All recordings are available for free on the HR Analytics ThinkTank platform.

    What is ONA? Practical examples of Organisational Network Analyses at Experian
    ONA has been a hot topic for a while now, and everyone is familiar with the pretty visuals associated with it. In this presentation, we asked @Kevin Metherell to give a short and practical talk on ONA, sharing how Experian are really using it to make decisions, and (at least from my Q&A) to articulate what the data sets really look like.

    Some of the key highlights:
    • Diversity - They are able to use ONA to explore unconscious bias in different job paths and business areas
    • Talent Management - They are able to combine ONA and talent data to 'crowdsource' untapped pockets of potential in the workforce
    • Org Design and Social Capital - They were able to identify what capabilities and connections successful new teams need
    • Well Being - Kevin gave some slightly expected uses of ONA in identifying who people "turn to for emotional support" to help train Mental Health First Aiders

    To watch Kevin's whole presentation, please click here. Kevin is a long-term supporter of the HR Analytics ThinkTank too, presenting at the first meetup in 2016 and recording this webinar on predictive attrition modeling in 2017 (exclusive access for research participants).


    Launching the HR Analytics ThinkTank research for 2019
    We took the January meetup as an opportunity to launch the 2019 HR Analytics ThinkTank. For more information on the research, please click here but if you would like to help us analyse HR analytics, please register to take part in the research by completing this form.


    What is a survivor analysis? The basics with GSK
    After the networking break, @Andrea Schirru from GSK took us through his examples of conducting survivor analyses at GSK.

    Some of the highlights:
    • Andrea talked us through some of the basic principles of survivor analyses, how they were originally used by life-insurers, and help us to calculate the probability of if/when a state of change will occur across time. In this case, if/when an employee will leave the organisation.
    • Basic survivor analyses are great to summarize time-to-event data (e.g. voluntary termination data), very common in HR, and can be applied also to small samples.
    • By converting the metric to elapsed time (from calendar start/end dates), they were able to study if employees were likely to leave by certain work anniversaries across multiple cohorts within an early talent development programme (1st example) and compare cumulative retention rates across different groups (e.g. countries versus high-low performers) within a specific business unit (2nd example).
    • They could use this to make better decisions about many aspects of the employee lifecycle, from training to retention.

    To watch Andrea's presentation, please click here. Andrea is also a long-time member of the meetup community, so you can probably speak to him at one of the next sessions if you wish.


    Measuring Potential, Performance and Social Media Commercial Success for Sports Stars
    The final speaker of the evening was Dr Stylianos "@Stelios" Kampakis, a specialist in Sports and Social Media data science. We asked Stylianos to share some stories from his industry, in case it inspired us to think about HR analytics differently.

    Stylianos gave an engaging and detailed talk, but for me, here were a few of the highlights:
    • Performance measurement - Stylianos talked using shorter term discrete changes in performance to see how players get relatively better or worse, and how consistent they play
    • Potential - Related to the above, he talked about combining off-and-on pitch data (sports and social media) to identify "good [commercial] bargains" which might be interesting in HR
    • Employee Brand Value - His examples of using player social media brand measurements to determine commercial successes has some obvious links to how we measure the power of employer brands in attracting talent

    To watch the full recording, please click here.


    Want to find a meetup near you? Check out our meetup directory for existing groups or you can also join the the ThinkTank mailing list for general ThinkTank updates.

    Check out these photos from the event:

  • Nigel Dias
    January 18, 2019

    This week at the first London HR and People Analytics meetup of 2019 we launched the fourth year of HR Analytics ThinkTank research. Over one hundred HR analytics leaders have bought into our vision of analysing HR and people analytics practice, helping us to generate insights to answer practical questions about HR analytics strategy, and improve the decisions we make when building functions. As its founder and chair, it fills me with a sense of excitement and pride to talk about the research taking place over the next year. By reading the below, hopefully you'll be excited too.

    Four years researching HR and people analytics practices
    Firstly, simply put, it is the fourth year of research! That's a fourth year of supporting industry growth by sharing free, quality research conducted on every type of HR analytics function that exists - many of whom we've tracked year on year, as their story and value has evolved. Leveraging our global community of HR analytics practitioners, our historic data sets (qualitative and quantitative), how can we build on our insights in 2019? What types of decisions are leaders making over time that result in different types of business/people impact - and how can we replicate or even accelerate that impact in other organisations?

    What are some example insights have we found so far?

    Who is the HR Analytics ThinkTank Research Team?
    I'm almost more excited about working with our researchers than I am the topics being covered. In 2017, the HR Analytics ThinkTank partnered with @Andy Charlwood and the University of Leeds, bringing a level of academic quality to our approach, and producing our annual How do organisations build HR analytics functions? industry report.

    This year we are happy to renew our partnership with Leeds, and also add two more academic leaders to the team: @Sharna Wiblen, Assistant Professor at Sydney Business School at the University of Wollongong, and @Mike Ulrich, Assistant Professor at the Jon M Huntsman School of Business at Utah State University.


    What topics will be researched?
    Combining such an experienced and thought-diverse academic team with our rich databases of historic case studies and interviews, there are many different aspects of HR and people analytics strategy we could analyse. For example: how to better engage stakeholders, how to better serve evidence (insights) to HR and business, what skills, structures and governance make better analytics teams, what technologies to use, data to capture and metrics to view. Whilst these will all be covered in blogs, the core research this year will focus on:
    • The annual industry trend report How are organisations building HR analytics functions in 2019?
    • How do HR professionals make decisions, and how can analytics teams better provide the evidence they need? What do HR managers need to even know about data science?
    • What does an HR analytics career look like, and what do the best leaders and practitioners have in common?

    Why would you join the HR Analytics ThinkTank global community?
    Whilst everything we research is made available for free, in exchange for your time and contribution to our research, we delighted to offer some exclusive content too:
    • Research participants get first access to any new content produced by the ThinkTank, and access to existing content
    • HR analytics leaders can request free industry benchmarks ('How does my function compare with other 2 year old functions?') or specific case studies ('How far away is my function from being able to deliver value from predictive attrition modelling?')
    • Want to talk to other HR analytics practitioners? Want to see real examples of HR analytics in practice? Anyone can join the HR Analytics ThinkTank online forum, and watch video recordings our our grassroots meetups and meetup partners from around the world.
    • HR analytics leaders who take part in the research can also join our monthly sharing webinars, featuring other HR analytics leaders from around the world - and watch all the previous ones on the forum too.

    Want to take part? What does it require?
    We are looking for HR analytics leaders (do you run the function?) and HR data practitioners (do you work with data or share the results?) who are willing to take part in the research - most participants will be asked to complete a short survey (10min), and may then be invited to take an interview with a professor (1 hour) between now and the end of March.

    I hope this is an interesting and exciting to you as it is to us. If you would like to take part, please register your interest here.
  • Nigel Dias
    December 13, 2018

    Whilst the HR Analytics ThinkTank research has been running since 2015, one of the most exciting developments took place last year when we signed an official research partnership with Professor Andy Charlwood and the University of Leeds. By combining our frameworks and data, tracking the growth and impact of HR/people analytics functions over the years, we have been able to upgrade the quality of our research and reports to a an academic level.

    It therefore gives me great pleasure to announce that Dr Sharna Wiblen, Assistant Professor at Sydney Business School at the University of Wollongong, Australia, is also joining the research team.

    Sharna brings another new perspective to the research and analysis of the HR and people analytics industry, and we look forward to her contributions to our reports and ThinkTank content over the course of 2019.

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