• Nigel Dias
    September 12, 2019

    Starting and successfully growing an HR and People Analytics meetup community isn't easy, but maybe we can make it a bit easier. This guide will hopefully be a living document, growing as more meetup organisers around the world contribute to it. For now, it is based on the London HR and People Analytics group - here is our overview video, and here are some recordings from our sessions.

    The six steps below contains the steps we take when we run a meetup, and also contain the support that we - 3n Strategy, our university partners, and the HR Analytics ThinkTank community - can provide you with (for free).

    Before you start though, we recommend you take the following steps:
    1. Register your meetup here for regular updates and to be listed on the Global HR and People Analytics Meetup Map.
    2. Join the HR and People Analytics Meetup Organiser group on Linkedin.


    How to Run an HR and People Analytics Meetup


    Relevant Links:


    Relevant Links:
    • Need sponsorship? Maybe we can sponsor, or put you in touch with someone who can. Please email .
    • Need help finding a venue? Maybe we can help, or someone in our network can help. Please post in the Linkedin group or email .


    Relevant Links:
    • Can't find a speaker? Maybe someone in the Linkedin organiser group knows? Or we can check the global ThinkTank Community and put you in touch with someone if we can. Please post here, or in the group or message .
    • Can't think of a topic? Join the Organiser calls and brainstorm topics with other organisers. Also from October the ThinkTank will share (at least) one case study or report that organisers can share with their communities.


    Relevant Links:
    • List your event on the Forum's Global Meetup Calendar and we will include it on all our newsletters and on our social media feeds.


    Relevant Links:
    • Check the Meetup Resource Pages for support materials.
    • Ask the Linkedin organiser group for ideas on how to open and run your meetups.


    • Share your videos and content with the global community (and help us drive innovation in HR and People Analytics).
    • Post blogs and insights that we can share with academic researchers and with the global community.

    Think something is missing? Have any ideas? Want to write your own guide? We'd be happy to share it, so please get in touch.
  • Nigel Dias
    August 4, 2019

    Looking for a meetup near you? Check out this our meetup calendar and sign up to the newsletter for regular updates. You can also check out this Google map of meetups around the world (let us know if we missed yours).

    Want to start your own meetup? Want to speak with other HR and People Analytics organisers? Looking for some support? Please complete this form if you'd like to be included in our organisers community to share ideas and experiences.


    In a world increasingly saturated by conferences, webinars, podcasts, videos, articles and blogs, there is another event format becoming more popular throughout the HR and People analytics industry: The Meetup.

    I believe HR and People Analytics meetups have the potential to play a crucial role sharing HR analytics practice, and accelerating innovation in the space - but many people don't know what meetups are, or based on my inbox, how to start their own.

    In this blog I'd like to to do three things:

    1. Share the value of meetups (using our London meetups as a case study).
    2. Invite existing meetup organisers around the world to connect our local communities with a global network, and maybe grow a pool of awesome content.
    3. Inspire (and support) potential meetup organisers to found their own communities around the world.

    What is a meetup?
    Imagine a room filled with people from your city, using their spare time to discuss HR and people analytics. Then imagine they represent the widest diversity of thought: people from HR and people from not-HR; analytics professionals and non-analytics professionals; Veterans of the industry and rookies. Finally, imagine this grassroot network, given a loose structure as part of a safe community, sharing their day-to-day experiences and inspiring innovative new ideas.

    How has it worked in London?
    In pure numbers, over 2000 tickets have been "sold" (our events are all free), to a community that identifies itself as approximately 40% HR data professionals, 20% non-HR professionals, 30% HR and 10% Other. Average registrations have gone from about 20 to 150 during that time, to watch speakers of whom around 66% are advanced HR analytics practitioners, and 33% are non-HR data professionals, invited to inspire us with data stories from other industries.

    Since June 2018 we have been recording all the sessions, and they can be viewed by anyone for free. I've shared my favourite presentations below, but if you don't read that far, please click this link.


    Top Five Reasons to Attend and Run Meetups
    It is no surprise to anyone reading this, that cultures of openness and diverse thought result in greater engagement, learning and innovation. This is literally what meetup culture is.

    I've run hundreds of meetups, starting from my days in Croydon Tech City (meetups were the foundation of our strategy to grow the fastest growing tech cluster in the UK), to the London HR and People Analytics Meetup and #ThisIsHR, our HR tech startup community.

    Here are my top five reasons to attend HR and People Analytics meetups:

    • They are inclusive - Nearly every other event costs money (usually a lot) and requires time during the work day. These costs exclude anyone who can't afford a ticket, anyone who is curious to learn about this seismic industry change but can't justify the time off work (like an interested HRBP), and most importantly, non-HR data specialists who can inspire us with alternative and vital perspectives from other data industries.
    • They are innovative - How do you drive innovation? Get a talented, diverse group of people into a safe space and get them talking. We deliberately structure our talks to profile HR analytics trends, and to inspire new ways of thinking - whether by encouraging discussion in a room with a high diversity of thought (the best kind of diversity), or trying to spark innovation by profiling examples of data use from other industries.
    • They are local - We strongly believe that meetups should be owned locally, so even when we help other people run meetups in their cities, we insist that local people own it. We don't want meetups to feel like an event arriving in town for the day, and the local knowledge, enthusiasm and pride will help the community form.
    • You hear real stories about HR data use - How many times do you hear presentations that are either too polished, too high level, or just generally un-relatable? Whether it is because the presenters can be less senior, or because the meetup is a smaller, safer and more intimate space, it is common that you can hear more detailed stories. In the London group, we deliberately try and encourage more detailed technical talks, to develop better technical practices in the industry.
    • You hear the actual obstacles - Similar to above, the safe meetup environment means that often presentations can be less polished and tell easier truths. When presenters are giving 'their favourite data story' it is easier to understand what they did (or didn't) do and why.


    What types of talks might you see at Meetups? Watch our recordings...
    At our meetups, we usually ask our HR data speakers to 'tell their favourite data story', and I ask at least one speaker per session to 'try and blow people's minds' with technical complexity (they don't always listen) - we want to push boundaries and get HR data scientists thinking together, right?

    We've had a wide variety of talks, from hot topics (has anyone not predicted attrition?) to niche issues (absence) to technique specific (text analytics). Since June 2018, we have been recording our meetups so anyone in our community, or the world, can watch them for free. If you are a meetup organiser, and record your sessions and would like to share it with the ThinkTank community, please feel free to post it there too.

    Three talks to watch from the London meetup sessions:
    • @Andreas Kyprianou (ex-Head of EMEA Talent Practice at Bank of America) on Predicting Performance
    In this talk, Andreas gave an excellent (and quite funny) talk on analysing recruitment and talent data in the context of performance. Yes, it is quite technical, but I'd encourage everyone in the field to watch it if they have time. Click here for the video (you may need to create a free user account).


    • @Kevin Metherell (People Data Scientist at Experian) on Organisational Network Analysis
    Whilst I am personally a bit tired of Organisational Network Analysis (or ONA) talks, Kevin's is the first in a long time that made me stop and think. In particular, listen out for his example of ONA to identify not only who is talking to who, but when - and specifically how they try to analyse WHEN women are tagged into a decision-making process, rather than just 'if'. Please click here for the video (you may need to create a free user account).


    • Dr Stylianos "@Stelios" Kampakis (Sports and Social Media Data Scientist) on the relationship between Performance on the pitch and Social Media performance
    We may measure and analyse performance data all the time, but we aren't the only ones. Stylianos is a highly experienced data scientist, and gave us an interesting talk about sports and social media data science. This is a great example of a talk that might inspire HR and people analytics professionals to learn, apply or adapt techniques from the sports data industry. Please click here for the video (you may need to create a free user account).


    I would like for everyone in the HR and People Analytics profession to have the opportunity to attend meetups in their local areas - I can think of few better ways to both grow our industry and truly accelerate innovation. If you like the idea too, then maybe you can get involved. How? Read on.

    OPTION 1: How can I find my nearest Meetup?
    Lots of meetups already exist - In New York, Chicago, San Francisco, in Mumbai, in Sofia, and we think there are more - but they can be hard to find. We all use different platforms (Meetup.com, Linkedin, Facebook, Eventbrite) to host our sessions. How can you find the nearest one to you?

    1. Click here to view the global meetup map. These are all the Meetups that we are aware of, and that were happy for us to link to their homepages. Please note: The meetups listed are independent of us and we aren't responsible for their sessions.
    2. Click here to find all the dates and events of meetups shared by the organisers.
    3. Sign up to our newsletter, which now includes all upcoming meetup dates.

    Please click this link to open the interactive map of Meetups around the world.


    OPTION 2: I'd like to work with other meetup organisers around the world. How can I register my meetup on your map and site?
    1. If you would like us to include your meetups on the map, please message me here or email .

    2. If you would like us to share your meetup details on our site, our Twitter, our Linkedin and newsletter, please post it on the Calendar Page.

    3. If you would like to speak with other meetup runners, and maybe even align themes and sessions, please complete this form and we'll include you in our conversations.

    OPTION 3: How do I found a meetup chapter?
    If there isn't an HR and People Analytics meetup in your area, or if we can't find one, or if you want to start your own, maybe we can help.

    1. Please complete this form and we will invite you to our How to Run an HR and People Analytics meetup webinars.
    2. Keep an eye on the newsletter for our How to Run an HR and People Analytics Meetup Guide and Resources.
    3. If you can't find speakers, or need a bit of sponsorship, or help coming up with topics, or anything like that, perhaps we can help with that too. Don't feel shy to ask!


    Full list of meetup speakers (London and Leeds) available to view on the Forum. Please note: you may need to create a (free) user account to watch the videos.:
  • 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:


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