Date: Friday 06 October
Location: Spui 25, 1012 XA Amsterdam, Netherlands (https://www.google.com/maps/place/Academisch-cultureel+centrum+SPUI25email@example.com,4.8874992,17z/data=!4m13!1m7!3m6!1s0x47c609c1967d88e3:0x13311cda8817c633!2sSpui+25,+1012+WX+Amsterdam,+Netherlands!3b1!8m2!3d52.3685931!4d4.8896879!3m4!1s0x47c609c18df64475:0xc44a9e6e9913c8cb!8m2!3d52.3685931!4d4.8896879)
ADS Coffee & Data offers the opportunity for researchers and business to share their knowledge and give insight on a central theme, specifically on Friday 06 October this will be on HR Analytics. There is also a chance to network with a cup of coffee.
Introduction & Chair: Sandjai Bhulai (http://www.math.vu.nl/~sbhulai/)(Full Professor of Business Analytics Vrije Universiteit Amsterdam)
09:10-09:35: Vladimer Kobayashi (http://www.uva.nl/profiel/k/o/v.kobayashi/v.kobayashi.html) (Marie Curie Fellow, Data Scientist, PhD: Eduworks, Amsterdam Business School, UvA)
Traditional job analysis (JA) strategies are not able to keep up with, let alone account for, the dynamic nature of work. Additionally, potential and existing data sources that may be useful for JA are materializing at a rapid rate. One data source is online. An example of online data that may be relevant for JA are job advertisements or job vacancies and job seekers’ resumes. Thousands of job vacancies and resumes are uploaded online daily and they potentially contain up-to-date information about the job as well as about the job seeker. Researchers are presented with an opportunity to make use of these data to augment JA and enhance the recruitment process. However, the sheer size and high velocity of these data sometimes hinder their full utilization. On the other hand, we are witnessing ever increasing capability for collecting, managing, and analyzing data. A subfield of data mining called text mining may be used to perform automatic extraction of non-trivial patterns from (huge) text data. Thus, one strategy is to use text mining techniques in JA. In this way, we augment traditional JA with text mining techniques so that we can efficiently analyze massive text data.
Our research explores the potential of using state-of-the-art methods from text mining to analyze data relevant for JA. We specifically apply text mining methods to handle free text in job vacancies. Vacancies consist of information pertaining to job title, job location, workers requirements and job activities among others. The most challenging data to disentangle are perhaps work activities and worker requirements since they are embedded within the text without distinctive identifiers (also called tags). Therefore, our work lies in automatizing the extraction of these job information types. The extracted job information can be used to forecast skill demand, to identify skill overlap across job professions, and to provide novel ways to classify jobs. In summary, this presentation will focus on text mining techniques and how they may be used in job analysis through vacancy mining. We demonstrate our approach by analyzing a huge database of vacancies generously provided by Eduworks’ industry partners. Lastly, we are going to showcase some of the applications of our text mining results.
09:35-10:00: Dirk Jonker (https://www.linkedin.com/in/crunchr/) (Leader People Analytics & Technology, Founder Crunchr / Focus Orange)
How companies become better employers by analyzing employee data
Skilled managers have never been more critical to the success of companies than they are today. Not because they need to manage employees, but because they need develop talent. The problem is that very few managers are also good people managers. So imagine if data science could predict when talent is leaving the company? Or help companies understand what people want so they can provide personalized career planning? A machine that scans the workforce continuously flagging risks and identifying opportunities.
In this ADS talk, we’ll explore how people analytics can help employers to make better decisions on the workforce – and become a better employer. Dirk Jonker, founder of people analytics solution Crunchr, will share what is already possible today and how he sees this field rapidly evolving.
About Dirk: Dirk Jonker is the founder and managing director of the Workforce Reporting & People Analytics platform Crunchr (SaaS). For over 10 years, he advises companies to translate operating models into people strategies and generate competitive advantage, using predictive people analytics. Prior to Crunchr, he worked as a consulting actuary at Towers Perrin in New York and Amsterdam.
He combines a unique background of actuarial sciences, five years of corporate restructuring experience, six sigma process optimization and data governance, to make People Analytics accessible and actionable. His areas of interest are workforce planning and top potential identification. Currently he is conducting research in using artificial intelligence to predict talent attrition and to find new ways of visualizing data.
IT research and advisory company Gartner named Crunchr ‘cool vendor in Human Capital Management 2015’ and Randstad Innovation Fund made a seed investment of € 2 mio. In 2016, Dirk was named Dutch entrepreneurial top talent by the Dutch Financial Times. In 2017, he was awarded as Actuary of the Year. He regularly speaks at international conferences and is covered in newspapers with expert opinion. In 2017 he will be featured in The CEO Magazine.
10:00-10:25: Maaike van Beijnen (https://www.linkedin.com/in/maaike-van-beijnen-8b05878/?ppe=1) (Manager HR Analytics at AkzoNobel)
Levers for successful implementation of HR analytics in organisations
Research in the field of HR analytics is getting more advanced and organisations struggle to keep up with the increasing complexity. What are the success factors to implement HR analytics in an organization and what are the differences between (academic) research and business implementation of HR analytics?
10:25-10:30: Further questions and wrap-up
10:30-11:00 Coffee & Networking
Registration is free but please do so in advance through Meet-up
The event will be in English and is open to all
Amsterdam Data Science (ADS) accelerates data science research by connecting, sharing and showcasing world-class technology, expertise and talent from Amsterdam on a regional, national and international level. Our research enables business and society to better gather, store, analyse and present data in order to gain valuable insights and make informed decisions.
Find out more about ADS at http://amsterdamdatascience.nl