To many people matching algorithms and people analytics sound like topics that are only relevant to experts in deep tech or AI. What they don’t know is that they constantly get in contact with them while using the internet.
Algorithms influence our behavior by recommending us who we should be friends with on social media, which movies we should watch, or what product we should buy. These lines of code are even used by companies to decide who to employ or who to give loans.
Did you ever wonder what data about you is collected on the internet and what it’s used for? This article will highlight some examples of what impact people analytics have on our daily life and what they are capable of right now. It is based on an episode of our interactive web show Gymtalk with Benjamin Pieck. He is the founder of the HR-tech startup matchingbox, speaker, and expert for people analytics.
So how are modern algorithms working? They work like a cooking recipe:
First, we need instructions. In the case of algorithms, the method is a framework or scientific model. Then we need to put in the right ingredients like chocolate and flour. For algorithms, this means we need to feed the framework with the right data. This is then processed with the right resources and equipment like an oven or a timer. For algorithms, it’s the right technology.
What is people analytics? In people analytics, there are 3 types of data:
- Sociodemographic data e.g. the Information from your ID or passport.
- Psychometric data e.g. personality traits, value systems, skills which are then analyzed and assessed by online assessment instruments.
- Behavioral data e.g. how you are browsing through a website, what you are clicking on, and how much time you spend on which page.
How is this data already used in our daily life by companies and platforms?
Behavioral data is for example used by the peer to peer loan platform aux money. They want to know if you are capable of paying the money back. In Germany, loan companies normally use Schufa. It only works with sociodemographic data which has an influence on your credit rating. Aux money, in contrast, assesses the behavioral data of your user journey on their website: How much time do you spend on which pages and sections? How fast do you go through the process? Did you read and download the terms and conditions? Another example is Google that is continuously making predictions by assessing your behavioral data in real-time.
Psychometric data has been used for the presidential elections in 2016 in the US. Cambridge Analytica combined different data sets and included psychometric data. Based on that data they created different profiles on a state level and individual level. With this data, they created a psychometric targeting: They made online advertisements to manipulate the reader's emotions, personality, and feelings to change the electoral behavior from voting Hillary Clinton to Donald Trump.
What you can do with people analytics?
The HR-tech startup matchingbox for instance wants to fit candidates and companies and find the right candidates for the right company culture. The key metric being used is the tendency to quit the job and the goal is to decrease this tendency. They want to ensure the best job satisfaction. For this, they use four matching layers: person-job fit, person-organization fit, person-team fit, person-supervisor fit.
There is a big shift from job-related data (work experience, education, location, etc.) to potential-based data (value system, personality traits, soft skills). The job-related data is a mirror of the past and the potential-based data is trying to predict the future.
The company culture should be assessed at the team level: What does the team culture look like? Which values are important to the team? Are they more performance-driven or have strong social bonds?
Outlook into the future: Companies will make job ads based on collected people's data and attract talents that are really fitting to their corporate culture.
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https://www.pewresearch.org/internet/2017/02/08/code-dependent-pros-and-cons-of-the-algorithm-age/
https://medium.com/@orge/algorithms-tell-us-how-to-think-and-this-is-affecting-us-eec7fb215dfa
