Interview: Development of Candidate Experience During the First Half of 2019
A summer interview with the founder of Trustcruit, Simon Werner-Zankl
First half of 2019 has passed and I took the time to sit down with our CEO and co-founder Simon Werner-Zankl to have a chat about things learned about candidate experience during this period, challenges about working with data and people analytics, Simons view on the evolution of data, how Artificial Intelligence (AI) could be used in human resources as well as Trustcruit’s challenges and vision. Last but not least, Simon told me about his pro tips for maximizing the summer vacay ☀️
Great to catch you before summertime and vacay starts here in Sweden! From all the interesting discussions and topics I overhear at the office, I think that the things that you will share in this interview will be valuable for people interested in people analytics and data in general.
Perfect reading between sunbathing and ice creams 🍦
— Well, first of all, thanks for this initiative! It has sure been a fun first half of 2019 at Trustcruit! Concerning the topics for this summer’s interview, I feel that these are areas where I personally have gained a lot of experience and knowledge. So, I will be happy to share my thoughts and knowledge.
I would like to start the interview by hearing about your thoughts about challenges that are faced when working with data both in general and specifically in human resources.
What are the challenges when working with data, in general, and within candidate experience?
— Data is a go-to source for decision making. Whether it comes to choosing what types of apples to buy at the grocery store, booking a flight or improving your candidate experience, you will base your decisions and choices on data. Are these apples produced in my own country? Are prices lower for this flight when a go to one of the other online flight booking sites? What do my candidates think that I need to change/improve?
I think I get it. You are stating that we use data every day for decision making.
Is it fair to compare buying apples and improving the candidate experience?
— Of course not. But this brings us back to your question about the challenges when working with data. And this is valid not only for Trustcruit. I would impose for every organization that wants to use data to drive change. I find it quite simple, when you buy apples, you know what to look for and the grocery store presents the data you need. Are these apples produced in my own country? Are these apples to pricey? Are these apples the kind that I like?
– Based on those things I think 9 out of 10 knows what apples they will buy. Moving over to using data improving the candidate experience, I would impose that the challenge here is to know what data we need to present and how to communicate it so that it leads to changes and improvements that we seek!
— A big general challenge with working with data is to use the data in a way that engages those that need to take action. For HR and for us at Trustcruit I would say that our challenge is the same as in general but to bear in mind. Human resources is compared to other parts of the organization not used to working with data. Therefore when working with data in HR, you need to bring it down some notches and understand that compared to IT and Sales, for example, communication using data needs to be on a very easy to digest level.
Please tell us more related to how you do this at Trustcruit.
How do you present data in an easy way so it leads to actions and improvements from the organization and the people working in HR and candidate experience?
— To start with, I’ll be dead honest here. I don’t think we present and communicate data so it is easily digested enough so that it leads to actions to an extent that makes me satisfied. Looking at the upcoming second half of 2019 this will be our head focus. I know our clients take actions based on our data. But I want to see more of that!
Okay. I see Simon. How will you, more in-depth, go about to do this?
— Looking at the evolution of data, I think we are in the middle of a shift. If we move 10-15 years back in time, everybody was talking about Business Intelligence (BI or also referred to as descriptive data). Business intelligence in my world is structuring and visualizing data. This is not enough anymore. The shift I am talking about is to go from business intelligence to working with prescriptive and predictive data.
I think a lot of the readers never heard of prescriptive and predictive data before.
What is prescriptive and predictive data?— While business intelligence is looking at historical data, prescriptive and predictive data presents what will come in the future, when looking at historical data. If used right, this is the power to involve and help users in your organization to take correct actions. Examples in a Trustcruit case would be:
Just to make clear, this is what you will focus on more when entering the second half of 2019?
— Yes. Trustcruit’s mission is to help our customers to improve their candidate experience. Today I am satisfied with Trustcruit to the extent that we empower our “superusers” to do so. In the coming months, recruiters and managers involved in recruiting will see changes that will help them take action too. Changes that also will help them improve in their recruiting and turn more candidates into promoters.
Interesting thoughts! Let us take a step back and look at a topic often and widely discussed, AI.
How do you think AI will be used in HR/recruitment and specifically when measuring the candidate experience?
— Oh, boy! I have so much to say here! We need to split the term here and talk about AI but foremost about machine learning which will be what we will see first in the HR area. Machine learning is to set up rules that you learn to mine out the data you have. What area will be first here are the areas that recruiters spend most of their day doing? Reading resumes for example. Here I think more and more ATS:s will build machine learning support to compare qualifications in the job ad with applicants and recommend what candidate would have been picked, only looking at online data.
– Don’t expect any “hocus pocus” things coming the HR and recruitment way, since I know many already think that machine learning and AI is hocus pocus. It will get down to the basics, as it has in many other areas. Spotify uses AI to help you listen to songs you like. Amazon uses artificial intelligence to help you buy the stuff you want to buy there. Recruiters’ main purpose is to pick and attract the right candidates.
— Looking more specific at candidate experience data and artificial intelligence I would say that test analysis will be first out. Many candidates write comments but it is hard to get the whole picture about written comments. Sentiment analysis to help filter positive/negative comments and keyword analysis is something we ourselves have been looking at. This will be launched when we feel that this will help our clients improve their candidate experience.
I think I get it. Don’t do the hocus pocus, focus on the core parts close to the purpose of using that tool.
I think this will get us closer to the end of this summer interview. Last but not least, what are your best vacay tips for people working in HR/recruitment?
— If you look at different people in a company, recruiters and people involved in recruitment are the ones that have the most external contacts. For one role having 20 applicants is normal and if you have multiple roles at the same time then there are a lot of people outside your company who want to get in contact with you. Recruiters’ phones and inboxes are under heavy pressure. Try to get away from that. Not in a bad way, but just to give your mind and soul the best possibilities to relax.
Thank you very much for your interesting answers to the questions and I hope that you will have a great summer!
I hope that Simon’s answers can both inspire and help you to work with data-driven decision making and that it gave you some new knowledge of the evolution of data and how Trustcruit uses data to turn your candidates into promoters.
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