The Ultimate Guide
How to measure soft skills in 2021
What are Soft Skills?
‘Soft skills’ is a bucket term that refers to a wide range of social-emotional competencies. In general, ‘soft’ skills are contrasted to ‘hard’ skills, which refer to technical skills related to technical tasks e.g. software coding proficiency, a flying qualification or plumbing accreditation. Increasingly the term human skills is being used instead of soft skills. Defining those uniquely human skills which won’t be replaced by machines is becoming more and more important. Bodies such as Pearson and the World Economic Forum argue that skills such as critical thinking, collaboration, leadership and social influence are amongst the most critical proficiencies for employees to develop, not least because such skills are most likely to prove irreplaceable in the face of increasing automation.
Categories of soft skills
Soft skills can be categorised in different ways. For example, ‘business soft skills’ are skills such as collaboration, team building, influencing, persuasion, leadership. ‘Emotional Intelligence’ is another model for soft skills popularised by Daniel Goleman’s definition of an emotional quotient, or EQ. Character is another way to think about soft skills which draws on the ancient language of ethics and moral behaviour. Character qualities are often described by social goods such as perseverance, patience, trust and worthiness which can be seen as a basis for soft skills. Finally, ‘social and situational agility’ is another key idea in soft skills.
Soft skills are also culturally constructed
Soft skills are not only dependent on the individual; they are also facilitated, or constrained, by the context. For example, it’s been shown that people are more patient and empathic having been unconsciously primed by images of the elderly and sick, whereas they are more dismissive and aggressive when primed with acquisitive cues of money. Organisational cultures may amplify soft skills or constrain and diminish them, depending on the embodied values and behaviours.
Measuring soft skills
In order to measure the soft skills in a workforce, you first need to define those skills you intend to assess, as no single approach will capture them all. Workplaces should identify which skills they regard as the most important drivers in business success. These are likely to be task and role related. For example, it is important that sales forces are effective at persuasion, but it is less important that they are skilled team builders. Managers must be effective at collaboration, whereas CEO’s need to be more effective as leaders.
Approaches to soft skill measurement
Surveys
Traditionally self-report surveys have been used as a low-cost method. The limitation of traditional surveys is that you collect more noise than signal. Research suggests that much of the data from self-surveys is unreliable; surveys are easy to fake and employees often wish to present themselves in a certain light.
That said, if the purpose of the survey is simply a bit of self-reflection as part of, say, some informal team building, then there is probably little harm in employees exaggerating their favourable qualities. It really depends on how serious the intended use of the data is.
If you are going to use a survey more widely, our advice would be to incentivise participants to be honest. Organisations with high trust cultures will be likely to obtain more useful survey data than those where employees fear their responses may be used against them. Our advice would be to determine whether your employees trust your intentions and potential use of the data before you start to collect any of it.
180/360 Feedback
180 or 360 feedback is likely to be of higher quality as it comes from a number of different perspectives. Once again, anonymity improves honesty, though it does not eliminate malicious, inaccurate and partial perspectives. 360 feedback is also relatively time consuming and as such may only be feasible as part of an annual or bi-annual appraisal.
Machine Learning and Monitoring Software
Recently, machine-learning driven monitoring software has entered as a market solution. These approaches harvest data on employee behaviours from varying sources: these may include textual and email semantic monitoring and analysis; facial analysis though device cams; website browsing and social media behaviour. These technologies work by feeding such data into machine learning algorithms and identifying patterns which correlate with other metrics - performance, productivity etc.
The advantages of such methods are that the flow and analysis of data is continuous, real time and automatic. Once set up, they are also potentially very low cost. However there are two main objections to such approaches: objectivity (or bias) and over-surveillance.
Objectivity or bias:
All algorithms are designed to search for certain types of data and are necessarily weighted; however, by definition, because they are self-learning, which data they pay attention to becomes obscured from the developers themselves.
If a client installed such technology and, for example, made employment or promotion judgements on the basis of behaviours the algorithms identified as business-favourable, the client would not know whether the analysis was fair. Was the algorithm skewed, for example, to look for certain facial expressions more prevalent in white men than women of colour? If it looked for smiling or nodding as a cue, would it bias against individuals from cultures in which stillness and inexpressiveness were social norms?
Over-surveillance:
Privacy campaigners have been concerned that such digital monitoring may amount to an infringement of privacy. Consent may be difficult to obtain. Beyond issues of legality, there is the psychological question of whether surveillance itself will change, and potentially impede, the quality of soft skill behaviours themselves. Some would argue that monitoring lowers trust in others, thus breeding a culture of suspicion and reducing collaboration, risk taking and teamwork.
Driving improvements in soft skills
Measuring soft skills should always be seen as part of a wider project to improve soft skills. Improving employee soft skills will always have intrinsic costs because, fundamentally, they are hard to acquire. Essentially, the cost of driving improvements to soft skills lies with the fact that the human mind is lazy and tends to take the easiest, lowest cost route to any solution, which isn’t necessarily the best. Companies need to both instruct and guide employees, but also incentivise and motivate them to develop better soft skill behaviours. Incentives can be cultural as much as promotional or financial. A good deal of human behaviour is based on mimicry; in a culture where poor soft skills are modelled from the top down, it will be very difficult to train better ones more widely.
LXPs and soft skill training
One of the key design principles in driving soft skill change is to make the individual the owner of their own developmental pathway. In business, gains can be achieved through programmes designed to give formative feedback to the employee as she progresses, and then empowering her toward the next step in her learning.
LXPs, or learning experience platforms have emerged as a major approach to giving individuals ownership of their learning pathway. A core advantage of an LXP is that the journey can be personalised rather than generic, adapting to the individual’s needs.
However, one caution: LXPs should not be used as learning ‘sat navs’, into which you simply plug employees and take them on a soft skill ride. LXPs are highly effective at presenting timely content to users; they are much worse at noticing, feeding back, supervising and incentivising the learner to really internalise their learning and change their behaviours as a result. Like a sat nav, an LXP might get an employee to the desired destination without them having noticed much along the way.
How USTEER drives next generation human skills
USTEER was developed out of our extensive experience of the challenges in measuring soft skill improvement. We set out to find the function of the mind that really regulates a person’s social-emotional interactions; we call this our cognitive steering. We found that cognitive steering wasn’t being effectively assessed by traditional surveys, so we designed a technology that could measure it. Our founder, Dr Simon Walker, also led the work which defined this as a uniquely human skill; thus, we call soft skills, human skills. We tested this technology rigorously in both business environments and in education, with more than 70,000 participants over 10 years, in order to build a platform that is both robust and intuitive. We launched USTEER when we were certain we had a solution that could really help businesses today.
If you’d like to know more about how USTEER might be able to help your business drive next generation human skills, please get in touch.
