Robust evidence is vital for making good decisions, particularly when the decisions impact people’s careers and business success. The growing focus on Evidence-Based Practice (EBP) is refreshing, but also intriguing - evidence isn’t a new concept for psychologists, so why is EBP so firmly in the spotlight? Have people not been using evidence? Is there a disconnect between research and practice?
For me, this is partially explained by the influence that technology is having across the talent sector. Disruptive yes, but not always positively. Whilst digitisation brings transformational workplace change at a rapid pace, my worry is where new technologies are seen as shiny new solutions in their own right, disconnected from results and to the detriment of evidence-based practice and future impacts. It seems to be a question of time – having enough of it to critically review evidence behind technology before ‘solutioning’ and getting excited by new features. I spotted this Tech vs Time conflict at the 2018 Division of Occupational Psychology conference. There were two main themes;
Firstly, the importance of evidence-based practice and a clear message about how long it takes to ‘do good research’ (it’s a long time).
Then, completely separately, the second main theme was for the unavoidable reality of rapid change affecting businesses and talent.
These themes were not explicitly linked but feel in conflict with each other. I wondered ‘how can we do good research quickly enough to support the rapid changes at work today?’ If we can’t achieve this, we risk the speed of technological advancement overshadowing the importance of in-depth research because that takes too long. We’d then live in a world where it’s just easier to scrap the old and bring in the new without a second thought. Technology can be misused and ultimately its need to add value.
With this in mind, I’ve captured blockers and enablers of EBP as I’ve seen them. It’s not exhaustive list and I’m keen to create a dialogue about it:
Time – We’re under pressure to take action now, but are we rushing data capture, analysis and problem scoping?
Getting evidence – It’s hard to identify useful metrics. It’s even harder to capture this data, but do we explore how to capture relevant data upfront?
Technology – Technology should be deployed to add value and tackle known challenges, but are we critical enough of the inner workings of new ‘innovations’?
‘Out with the old, in with the new’ – A good example is the humble ability test, which remain the most robust single measure of general job performance, but are all fairly similar in format with limited change. But, rather than chuck ability tests for good, how can we build upon decades of research to make them more relevant today?
Buzzwords & Fads – These are new terms for old things and fads based on limited research. One example is ‘Experience Days’ replacing ‘Assessment Centres’. Another could be Machine Learning and how different this really is to the algorithms powering established psychometrics.
An Evidence Mindset - When Cubiks wins industry awards for talent solutions, it is always with long standing clients. The awards are not for patience, but reflect research over time that drives informed changes. In every single award case, it’s the analysis that has created the cutting-edge solutions, with technology simply the enabler of psychology.
Technology – There is no better example at the moment of technology enabling psychology than in People Analytics. These teams build infrastructure to make data collection, anonymisation and analysis quicker than ever before. This is the key to making evidence more agile – we are getting data faster, considering it upfront and exploring evidence in real time.
Critique the Buzz - If something says it’s ‘proven by science’, chances are it’s not. Human behaviour is too complex, particularly in assessment. We can observe and measure, but that’s not 100% accurate, let alone future projections of performance. Ask to see the ‘proof’ and critique it.
Collaborate – This one might be impossible in the world of GDPR and the War for Talent, but imagine if practioners and businesses collaborated to share data on talent challenges. It does happen, but all too rarely. Many hands make light work.
Past evidence of results should be the biggest factor in shaping future talent solutions, not technology alone and certainly not buzzwords. Most innovations are not the work of genius, but the evolution of something that is already well established. Rather than technology facilitating an empty buzz, the best outcomes are where technology enhances established solutions and speeds up our analysis. This sharpens our knowledge over time, narrowing our focus and increasing the ability to predict future outcomes. That’s genuinely exciting because it adds value and it’s data-driven, to coin a buzz-phrase.