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2 min read

HR Reporting – And Why HR Doesn’t Care

Brendan Lys
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Brendan Lys
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.

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I had somewhat of a revelation the other day, for quite some time I’ve wondered why the lack of interest in HR reporting from the wider HR team. This isn’t specific to a client or workplace, it’s been quite a universal experience. One example of this was informing my direct manager than a significant percentage […]

HR Reporting – And Why HR Doesn’t Care

I had somewhat of a revelation the other day, for quite some time I’ve wondered why the lack of interest in HR reporting from the wider HR team. This isn’t specific to a client or workplace, it’s been quite a universal experience. One example of this was informing my direct manager than a significant percentage of the organisations leave liability came from leave in excess of our yearly allowance. Simply put people were holding onto their annual leave, rather than taking it, this amounted to millions of dollars that we hadn’t budgeted for. I was pretty startled that this manager was really interested. In the end, word of my findings reached upper management and the executive asked for a report on it.

So, why is this the case? Why are HR practitioners not interested in HR reports? My realisation is that we’re not talking the same language, HR is still very much a one to one business. HR practitioners deal with one employee at a time, many HR practitioners simply aren’t interested in averages across a business, or trends, etc – unless it supports their own Key Performance Indicators (and then they’re interested in it maybe once a month). Because they work on individual cases, poor performers are individuals, high performers are individuals, groups, or divisions or people don’t register for the most part. While for the most part, the reporting that we do in HR is a whole of the organisation, or at the division level. From a reporting perspective, I don’t care what ‘Jane’ did, I care about what thousands of employees did.

This is the disconnect, HR reporting is about hundreds or thousands of employees, HR primarily is focused on individual employees. Outside of predictive analysis which can operate at a granular per employee level, I’m not quite sure how change my practice within HR reporting to engage the rest of HR. And potentially there isn’t a need to, it might simply be a case of actively promoting predictive analytics, and relegating HR reporting to simply being a support metric for predictive analytics.

I’d love to hear your perspective on this? As an HR practitioner are you interested in HR reporting? Or as a person involved in HR reporting, do you also see this disconnect within the HR function?

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.

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