UNIQUE DATA-DRIVEN SOLUTION
OFFER A UNIQUE PERSPECTIVE
67% of employers see a candidate’s cultural fit as ‘very important’ in the hiring process (HR Magazine, 2017)
67% of employers see a candidate’s cultural fit as ‘very important’ in the hiring process (HR Magazine, 2017)
Teamscope combines big data with scientific testing to analyse the existing team. Based on that, our algorithm suggests what characteristics to look for in a candidate and evaluates how well each candidate fits the role and the team. Finally, the platform provides a detailed candidate profile and a personalised interview guide for each candidate to help the hiring manager choose the best person for their team.
BECOME A PARTNER
Join our partnership network to get early access to Teamscope
Differentiate from the competition
Make your firm stand out to prospective clients and candidates with an innovative solution.
Close the good candidates
Teamscope makes it easier to convince the highly sought after candidates to take the role because the right fit means they are likely to be successful at his company.
Offer value-added services
Better understand the challenges of the organization to create a long-term partnership with the hiring manager.
SOM STATISTICS
We are driven by data
Every team that we analyse makes our algorithm smarter
Finished projects
Teams analyzed
Profiles created
Data points collected
Strong science combined with groundbreaking technology
Teamscope combines decades of academic research on human personality and organisational behaviour with modern big data analytics to deliver unique talent insights.
We rely on the Big5 framework for analyzing personality and the Schwartz model of universal human values to understand what really motivates people and how they normally interact with others.
We utilize the groundbreaking technology developed by IBM Watson and the My Personality project to get a better understanding of people’s character based on their virtual footprint.
Every team that we analyze gives us additional data points that help further refine our data model and increase the predictive validity of our algorithm.
