I can confirm I am a professional working in the talent and assessment space interested in learning more about changing talent assessment for good.
Are you currently a Sova Assessment Client?
What are your areas of expertise?
What are your areas of interest?
Hi Alan, thank you for taking the time to answer our questions. I wondered with the sudden increase in hiring, what are some of the key considerations organisations should take to ensure assessment is done right, so we don't miss out on top talent?
Hi Kate, thank you for your question - I think there is mixed picture here for many organisations around managing the quantity of applicants for some roles, with a desire to fill roles quickly where the intent is to quickly ramp up and the market has become more competitive for employers.
There is an opportunity I think to square that circle by using assessment very efficiently to filter the candidates that really best fit what the organisation needs, whilst doing so at speed so the need for agility in making hires at pace isn't compromised either. My view is there isn't a need to compromise here, as the solutions we are regularly putting in place focus heavily on rapid time to hire whilst making sure the right candidates get hired.
So using an integrated approach that ensures assessment can be done well and at speed is vital, so the best talent can be hired but without making too many mistakes along the way - as making the wrong hire also has a very significant cost in lost productivity and turnover down the track.
Where does the concept of changing assessment for good come from? What are the core values at the centre of that?
Our core focus is around ensuring assessment decisions, whether external or internal, are as objective and fair as possible.
Historically assessment has often been applied in quite a narrow, piecemeal way and often the follow through to delivering outcomes has been lacking. Instead, we aim to do so with an unrelenting focus on fairness, objectivity and prediction.
So in terms of changing assessment for good, we mean two things - firstly, changing it for the better in terms of much greater objectivity and fairness so implicit bias is driven out and the best decisions get made to ensure diversity and inclusivity.
Secondly, the goal is to change the world of assessment for good, so we raise the bar from the old school approach and focused on a much more integrated, innovative way forward that uses technology very purposefully to help organisations be fairer and better.
How do you measure the effectiveness of your assessment process?
I probably gave a bit of a sense of this in the thread above, I think the things that really matter here are:
Is it predictive of business outcomes?
Is it fair?
Is it a positive experience for users (candidate, hiring managers, talent functions)?
Is it cost and time efficient, and seamless compared to alternatives?
There are other psychometric elements like how reliable a process is, and how clearly candidates can be differentiated, which all feed into prediction.
However these would be the big 4 things that really matter most.
Hi Alan, Love that you're doing this! I wanted to know what your take is on the role technology plays in keeping assessment fair? How can we make sure that assessment technology remains unbiased?
This is a really important and current question, the bottom line here I think is what criteria we use to define success in how we apply any form of assessment, including machine learning and AI techniques in how results are calculated.
At a basic level, assessment is underpinned by 5 aspects - the comparability of results between people; the reliability of the information; the experience for those undergoing the process; whether it predicts meaningful outcomes; and whether it is fair.
Fundamentally, the last two - prediction and fairness - are both critical for the application of any assessment, be it no more than one person interviewing another, or the application of new technology.
A parallel example would be driverless cars - they need to get us from A to B, and do so safely. If the driverless car can't meet our safety criteria, it shouldn't be on the road. The same applies to assessment.
So ensuring assessment technology is unbiased should be a cornerstone of what success looks like, and baked in to how we run assessment programmes alongside ensuring they are predictive of business outcomes.
Alan, what drew you to working in the field of assessment in the first place and what innovation are you most excited about for the future?
Like many psychologists I've always been fascinated by what makes people tick, and also had a strong interest in what makes a difference in groups and organisations. Assessment as a field gives a unique lens into this which continues to provide fascination.
In terms of innovation for the future, the opportunity to bring together different aspects of assessment and data about people, and use this in ways which really drives fair outcomes is where the big opportunity lies. Rather than traditional products in silos, this will be holistic in nature and the exciting action will be where different data meets and can be used to make a difference.
Why did you create Sova and what does the name 'Sova' actually mean?!
When I started Sova I wanted a name that related to what we do. Sova in Czech and a number of other languages means 'Owl', an animal which is known for it's ability to see what others find difficult to see, and it's wisdom. In the Sova platform we are seeking to provide users with a much greater level of insight into people, hence the choice of name.