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Workforce diversity, in my view, is one of the more misunderstood and misquoted aspects within Human Resources practice. You’ll often find people, often very senior people within organisations, stating how top organisations have a diverse workforce, and so that is something that ‘we’ should replicate. This represents a fundamental misunderstanding of diversity and its relationship to high performing organisations.

Generally speaking, those top-performing organisations have a very simple approach, find the brightest people who have an interest in that work and employ them. As it happens intelligence is not determined by gender, sexuality, height, weight, age, or any of the numerous aspects that we seem to focus upon in mainstream media. Hence organisations that focus on hiring and retaining the best in their respective fields and/or career levels, very often end up with quite a diverse workforce. Which then leads to this incorrect belief that diversity drives performance, which is invariably followed by organisations almost laughably launching a diversity-focused program based on discrimination. How many of us have been in organisations and witnessed age or gender-focused programs as a means of building diversity? As it turns out both age and gender are terrible predictors of performance.

Focusing on extremely poor predictors of performance in their desire to be diverse, will lead to a diverse workforce within that organisation, in some cases however it will lead to that organisation being a low performer. Rather, focus on what does predict strong performance, focus on finding the brightest people that you can afford and recruit them. Focus on removing those aspects in your recruitment and selection processes that discriminate, leaving the way open to actually finding high performers who will be female, male, gender diverse, tall, short, native, and non-native speakers of the dominant language in your workplace.

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Brendan Lys
By Brendan Lys

Operating at the intersection of Human Resources and Data Science, I leverage extensive specialist experience within Human Resources, with the methodologies and approaches of Data Science. This focus on the discovery of actionable insights from data, has been applied to areas such as: remuneration & benefits, workforce planning, recruitment, health & safety, diversity, and training. But what does the application of data science to HR challenges and opportunities actually look like. Within an HR framework the data we work with typically comes directly from our HRMIS, an advantage of using data science methodologies is that we can bring in additional data either held within the organization or from external sources - data which is out of reach from a pure HR analytics approach. Consider for example position descriptions, these contain a wealth of data that we typically ignore as its not in a analysis ready format. A side project I'm working on currently (April 2019) is using text mining on job descriptions to provide insights into which job family the position may fit into. The insights of my work have been enjoyed by organizations across a diversity of sectors including: Government (Australia and New Zealand), ASX and NZX listed companies, utilities, not for profit and higher education.