Performance prediction

As the UK continues to languish in a productivity slump, the search for what makes us more productive has value. Researchers led by Dartmouth University believe that they can predict with some accuracy, which employees are high performing, and which are not. Based on a similar assessment focussing on students, the researchers analysed data feeds from a series of wearables and fixed sensors implanted in the workplace to test the performance of 750 employees over the course of a year. The study found that it could predict with 80% accuracy whether an individual was a low or a high performer, based on factors such as heart rate and resting time. In this case, higher performers typically used their phone less, had periods of day sleep and exercised more. Could this replace your year-end appraisal? There is of course a question of cause and effect and any appraisal of performance based on input metrics rather than outputs may unjustly reward those who artificially replicate these inputs and under-reward those that are just more efficient. Nevertheless, the idea of tracking people as they navigate places such as office and retail premises is still gaining traction. The real estate industry needs to consider its role in this. Operators such as WeWork see an opportunity in this space, using spatial analytics (e.g. Euclid, acquired this year) to drive productivity services. For more traditional landlords there remains the question of whether to deliver the sensor / data infrastructure as part of the core real estate offering or leave this for the tenant to resolve.