Hold onto talented people by better understanding the needs of highly responsive employees whose productivity is affected by certain personality traits says Bhavini Shrivastava from Workplace Talent Development at the National Centre for High Sensitivity.

Our sensory processing sensitivity (SPS) research identified a specific group of IT workers affected by a type of temperament at work. The research can help IT companies to see who is getting stressed, and by what type of stress, so preventative rather than reactionary actions can be taken.

Temperament is so important because it affects work performance and how productive people are at work (Rust & Golombok, 2008). The general impact of employee well being on organisational performance is of concern.

According to Sainsbury’s centre for mental health statistics the cost of absenteeism per average employee is £335 and the total cost to UK employers is £8.4 billion.

The costs are £605 and £15.1 billion for presenteeism. Presenteeism is the lost cost associated with the loss of productivity when employees turn up to work with illness even though they should be at home.

HRP positives

It is not just that they are a vulnerable group in the negative sense and need more attention to work environment characteristics and leadership style / impact. HRP were rated as better performers by their managers despite having greater sources of stress in their lives and as a result lower levels of well-being.

Despite the negative effect of the work environment, there are obviously other factors at play that enable HSP to perform well as rated by their managers. The findings lend support to HRP’s unique contribution as talented, conscientious and creative employees, as managers perceive HRP as better performers despite their lower levels of overall well-being resulting from the sensory processing sensitivity (SPS) trait.

So what is sensory processing sensitivity? And what does it mean for IT professionals? IT professionals are highly responsive in that they form about 15-20 per cent of the population born with the SPS trait. This means they have inherited a more alert nervous system and thus are more affected by stress.

One in five IT professionals will be affected by the trait meaning their senses absorb more information, which is processed at a deeper level and thus events are more likely to be felt strongly and can overstimulate.

SPS is not due to a greater volume of sensory input but a greater attenuation to subtleties and complexities in the information entering the senses (Aron & Aron, 1997).

The research to date shows that people high in SPS benefit more from a particularly good environment than people without SPS (Aron et al., 2005; Belsky & Pluess, 2009; Ellis, Jackson & Boyce, 2006). This means they will have a differential susceptibility to predictors of work performance such as work environment characteristics or situational factors and the leadership style of first line managers.


Consistent with previous research on SPS in general, highly responsive IT professionals are older people with a mean age of 42 (r= .5) who have greater sources of stress in their lives (r= .2) and thus lower well being (r= .3).

The research has captured the positive end of highly responsive IT workers as despite having lower well-being than non highly responsive people, managers reported highly responsive IT workers as better performers overall (r=.3).

The strength of the relationship is strong as observed by the effect sizes reported above. Highly responsive IT workers are highlighted as a potentially vulnerable group with respect to stress; as such they may need more consideration in the workplace to reduce stress.

The results did not show a moderating effect by HRP status, therefore it is not that this group needs a different type of consideration or any qualitative adjustments to the working environment, but rather they need ‘more of the same’.

They need the same considerations in the workplace as IT workers unaffected by the sensory processing sensitivity trait but more in terms of quantity. This is due to the fact that they are more likely to perceive the work environment as stressful.

Practical implications

When it comes to talent management and retention, it would appear that many great IT professionals with the SPS trait may have left companies and perhaps could have been retained with effective adjustments to reduce their sense of stress.

A battery of assessments is recommended for coaching and training purposes to ensure as complete a picture as possible is achieved of an employee’s current level of functioning. This could include measures of stress such as the Perceived Stress Scale (PSS) (Cohen, Kamarck & Mermelstein, 1983).

For IT workers with high SPS, there are obvious recommendations, such as pointing out the normalcy of their reactions to stimulation, as well as teaching them to take their predicament into regard in their different life domains.

Another strategy is teaching highly responsive people how to find some quiet pursuits, for example, in muscular relaxation, meditation, yoga, sports or other artistic and musical pursuits.

Main lessons

An effective intervention or workplace adjustment would allow HRP to perceive their work as more comprehensible, manageable and meaningful, so that they can effectively influence it, commit to it and connect with it.

This would not only be advantageous to the HRP involved, who would feel better and be more effective, but it would give all other persons the opportunity to enjoy the results of all the delicate reflections that highly responsive persons are able to produce (Aron & Aron, 1997).

Key design strengths of the research

Total sample size of 435 majority IT professionals after checks and a response rate of 8%.

A matched sample was achieved of 96 matched pairs of responses from employee and manager. By collecting objective manager ratings alongside self-reported productivity ratings common method variance bias was reduced.

A cross sectional survey design for a large cross-organisational population - an IT company in Mumbai, India.

Statistical analyses

Factor analysis. Multiple regression analyses. T-Tests.