Technology has turned HR into a data-driven game. This does not mean intuition is waning, but rather that a larger number of practitioners are likely to experience some shame or guilt if they admit that they are ‘playing it by ear’. The recent rebranding of talent management as ‘people analytics’ has arguably enhanced the status of HR.
The hope here is that HR can empower organisations with robust tech and data to turn the art of people management into a science: an objective, defensible and replicable process with a clear ROI.
That said, there is still room for improvement, as most technological innovations have yet to be rigorously scrutinised or effectively applied. The HR tech world is replete with shiny new objects, including some that warrant a considerable amount of optimism, even among cynics. However, at this stage there is no indication that these toys are more effective than applying well-established scientific principles. This is perhaps clearest in talent identification. Consider these salient examples:
Gamification. Although the application of game-like features to talent identification tools has enhanced user experience, enabling organisations to tap into a much wider candidate pool and turning recruitment upside down (from B2C to C2B), it is hard to get carried away. First, most assessment games look like 1980s arcade games.
If you look at what goes on in the real gaming industry, where it is increasingly hard to see the difference between a game and a 3D movie, gamified assessments seem to belong to a prehistoric era.
Second, most gamified assessments are either good-looking IQ tests or glorified situational judgment tests. However, they are less valid than traditional (non-gamified) tests of the same type. Third, the cost of gamified assessments is much higher than traditional ones, so you end up spending more on less accurate tools.
A more hopeful path may be to mine data from existing gamers – who play real videogames – to assess their job-related potential. There are now more gamers in China than people in the US, and hardcore gamers spend an average of 20 hours a week playing. Imagine a future in which companies send avatars to recruit Grand Theft Auto players as heads of sales because of their kick-ass aggression.
Big Data. There is now so much data available on people that we probably don’t need to gather any more. Internal company data, such as email content or metadata, can be used to monitor people’s performance, engagement, and identify their potential. The opportunities are even bigger online where our digital exhaust is as vast as it is underexploited. If only algorithms could access people’s browser history, Amazon purchases, Spotify playlists, Facebook and Twitter feeds (as in programmatic marketing), we would probably ‘know’ them better than the average manager does. However, there is no evidence this approach can predict work-related behaviours better than established selection methods, which also represent more ethical (and legal) alternatives. There is big a difference between what we could and should know about people.
Digital interviewing. A final area of technological disruption is in interviews, which are still the most widely used selection tool in the world. Today it is possible to interview anyone, and analyse their answers and behaviours, without the need for human intervention. Questions can be asked by avatars, and speech- and video-mining algorithms can translate interviewees’ behaviours into valid predictors of future performance, eliminating unconscious biases while reducing time and cost.
The problem, however, is most interviewers can’t ignore their intuition. It’s like having self-driving cars; people still put their hands on the steering wheels because they have more faith in themselves than in technology.
In short, when measured against intuition HR tech is making the industry smarter. But it has yet to reach the level of rigour of scientifically defensible methods.
This article was originally published by HR Magazine on January 10, 2017 and is authored by Tomas Chamorro-Premuzic.