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    The authors of this post are: Yanitsa Ilieva (SuccessFactors Recruiting Practice Manager at Global IT Division in Atos and the founder of the HR & People Analytics Sofia Chapter) and the speaker of MeetUp #2 Martin Boudikianov: an independent consultant delivering Digital HR transformations with SuccessFactors and SAP Cloud Platform. We opened the session with a brief introduction of the chapter, our objectives and commitment to play a crucial role sharing HR analytics practice, and accelerating innovation in the space. 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.

    How to Build an HR/People Analytics Practice with Martin Boudikianov
    In the presentation of the evening, Martin Boudikianov (an independent consultant with 15 years of experience delivering Digital HR transformation in 13 countries for companies like Deutsche Bank, Coca Cola, Deutsche Telekom, ABB, Allianz ) took us through the major steps of preparing an organisation for starting a People Analytics practice and a practical Machine Learning example for predicting an employee leave. The audience was very curious and the lecture quickly transformed into a nice discussion.

    The main focus aspects covered were of course the ones that would guarantee a good foundation setting, proper expectations, timing and what not to secure the business results expected:
    • Motivation and pitching the stakeholders (all of us in the audience agreed that this can be your fast track guarantee and securing the needed resources, support, communication and engagement)
    • How to build the team (what is a project without a team so we dived into the profile types needed and how we can find those people to join the HR/People Analytics practice and learn how to collaborate with the others involved. The main identified groups: data engineer, data translator and data scientist.
    • Data Quality Framework (Here we made sure that it is clearly impossible to get the required results if we do not invest time in securing data quality as a solid foundation to build upon. How to do that: plan enough time, focus on accuracy, breadth, consistency and depth)
    • Data Logistics (System integrations, Storage , Usage, Retention, Data Provenance and GDPR compliance)
    • The Process of Analytics (It was time for us to see the end to end process in simplified steps starting with defining the business objective, translating it into a data project, collecting and obtaining the necessary data, explore it, transform it, clean it and get to the point of conducting the data analysis. Next step is to translate the data insights into action and last but not least, assess the outcomes. )
    • Where Analytics should not be used (Like anything else in life there are cases where a solution is not fit for every problem, so it was important to share with our audience that there are cases when analytics will not work: when trying something novel and we do not have historical data, when the salient event is rare and we cannot train the models sufficiently or when we try to confirm what one already believes to be true but we are confirming a bias)
    • Demo: (Seeing is believing they say, so our lecturer delivered a demo on 2 use cases)

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    We had our next speaker Daniela Piryova in the audience who had the chance to announce the next event topic: “HR Analytics & Talent Optimization” on November 13th, 2019 herself in person. Keep an eye on the Global Meetup Calendar to sign up.
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