3 Mistakes To Avoid When Starting an HR Analytics Function
HR leaders recognize that they should be using analytics to support decision making. However, how to do so is often a bit of a mystery.
Since many HR leaders don’t have a good sense of how to get value from analytics, they move it off their plate by passing it to the HR reporting team or to some newly hired data scientist. Not surprisingly, HR leaders are not familiar with the role the average HR professional plays in analytics so they don’t involve them at all.
Here are why these mistakes are detrimental to analytics success:
Mistake 1: Asking HR Reporting to do analytics without sufficient resources
When organizations are unsure how best to approach analytics, the accountability for analytics is put on the people already handling data — the HR reporting team. It might make sense to combine analytics and reporting; however, the reality is that most HR reporting teams don’t have the mandate, tools, or skill set to do analytics. Hoping that a team already up to their necks in producing routine reports can suddenly start doing sophisticated analytics, such as predicting turnover or using machine learning, is unrealistic.
Recommended Read: Why Great HR Strategy Shouldn’t Be About Making HR Better
Mistake 2: Hiring data scientists and asking them to “do people analytics”
Some organizations are willing to invest in analytics, but don’t have a clear idea how analytics are supposed to impact business decisions. They presume that people with Ph.D’s in data science will know what to do so they hire them and ask them to start analyzing.
The problem with this approach is that while data scientists understand data, they do not understand the business problems that data is meant to address.
Data scientists will be happy to work with the IT team on integrating data sets and playing around with a data warehouse in the hope they’ll bump into something interesting. This kind of wandering around in data is both expensive and unlikely to yield helpful results.
Analytics needs to be closely tied to business issues. This means the people leading analytics must be business people who understand the goals and key performance indicators of the organization – rather than just analytics wizards. In fact, it makes sense to have analytics as part of the HR strategy group because this ensures it focuses on the most important issues.
Mistake 3: Overlooking the role of the average HR professional
Even companies with effective analytics teams and effective HR reporting teams sometimes make slow progress because these groups are not closely connected to the average HR professional.
The analytics team can only do so much and they’ll quickly be overwhelmed if the average HR professional cannot handle everyday analytics on their own. Similarly, the HR reporting team may produce crisp reports and clean data, but if the average HR professional doesn’t know how to use data then those reports will sit in a drawer unread.
Recommended Read: How Merck KGaA Uses People Analytics to Win in the New World of Work
If you are serious about analytics then you need to recognize that the average HR professional plays a critical role in making the whole department “analytics savvy.”
The Main Takeaway
These problems are to be expected; analytics is relatively new for HR and is often presented as being something rather mysterious. HR leaders have not been given much help in understanding the way forward.
A successful analytics function starts with a core group of HR professionals who can see how the better use of data helps with business decision-making. This group must then be supported by an effective HR reporting team to get them basic data and a small HR analytics team that can advise them and help with problems requiring more sophisticated analytics. From there, analytics could be extended to other business leaders, enabling them to get insights for the questions that matter to meeting organizational objectives.
Here’s an example of what successful HR analytics looks like:
- The head of talent acquisition recognizes that sales in Asia are falling short of targets because it’s taking too long to hire new sales reps. She realizes that if she had better data on each step in the talent acquisition pipeline then she’d be able to reduce the time it takes to fill vacancies. She works with the HR reporting team to get the data she needs. Notice that there is no statistics involved; she knows exactly what data she needs and how she’s going to use that data. The HR reporting people know how to create processes to get clean data and how to pull it out of the system in the form she needs.
- A senior HR business partner for a retailer believes that store performance depends on having the right mix of staff. He has several hunches about what factors cause some teams to be successful and others to fail. He calls on the workforce analytics team to do the math that will determine which of his hunches are correct and which are not. Armed with the analysis, he’ll then work with store managers to adjust how they handle schedules so they get the right mix of skills in the store for each shift. Notice that this case involved more advanced analytical skills, but it was driven by a business-savvy HR professional who had a clear goal in mind.
Analytics should be woven into everything HR does and that’s why it can’t simply be farmed out to HR reporting or farmed off to data scientists. Analytics it not a side project, it should be part of the broader shift of the HR function to becoming a more business-focused and data-savvy operation.