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This month, Talent Tech Solutions has teamed up with Sue Howse (CEO - The Human Collaborative) to take a look at how far Talent Analytics has come over the last 10 years.
Over ten years ago, Sue penned a paper stressing that Talent Analytics had the potential to transform the recruitment process by using data to identify the best candidates and reduce bias in decision-making. She also emphasised the importance of ethical considerations in Talent Analytics, particularly around data privacy and the potential for algorithmic bias.
Well, now we’re here in 2023, and just like those hoverboards and flying cars that Back to the Future promised us, it is a bit disappointing that many organisations still do not have any reporting at all or have basic operational reports. People are still talking about the same things in regards to algorithmic bias with the new wave of AI-led technologies only exacerbating the problem. When consulting with our clients, we’re regularly surprised at the low level of talent analytics being used - despite it consistently being a hot button topic at talent events.
Why are too many businesses still shying away from Talent Analytics? It boils down to the following two sentiments: “It’s too hard to get started,” and “It’s only for big businesses”.
The foundations are easy
In a recent HR Leader podcast, Arun Chidanbaram (People Analytics Leader at GE Healthcare) said that companies were turning their attention back to data governance and the data ecosystem - which are the very foundational elements of any analytics. If companies who have been investing in data analytics for years are relooking at their basics, the message we take away from this is setting some foundations is easy.
Small, medium, large
Most people think Talent Analytics is just for big businesses, but there are lots of benefits for businesses of all sizes, two of the benefits of time is that there are new platforms like seeHR from Talent Tech Solutions that offer off the shelf reporting/analytics capabilities that would have taken months to deliver in the past and that your company can draw upon the the experience of Sue and ZiChuan and leapfrog many of the challenges and stumbling blocks faced by early adopters..
Here are our three biggest reasons why Talent Analytics are important no matter what size of organisation.
1. So you can understand your baselines
“You can’t improve what you don’t measure” is the mantra of data analytics, and the same applies for Talent Analytics. Even if you don’t think you have a need for Talent Analytics right now, think about where your company will be in 6 months, 12 months, two years.
Let’s say right now you don’t have the budget or the justification to invest in improvements for your hiring process. Maybe you’re a small business, maybe there’s a hiring freeze, or maybe you haven’t yet convinced the higher ups of the value in investing in people. But what if in a year or so circumstances change and the company now has the funding to invest in its talent tech? If you haven’t established a baseline of Talent Analytics, you’re just going to be shooting in the dark to try and find out where inefficiencies lie.
Simply put, establishing a strong baseline now is going to solve plenty of headaches later.
2. So you can demonstrate your value as a Talent professional
This is a very self-serving justification but still an important one. What better way to demonstrate to the company how valuable you and your team are by being able to point to increasing metrics and say “we drove these outcomes”.
Measuring common HR metrics like time to hire and new hire attrition rates are a necessary first step. But over time, the organisation changes, the needs and maturity of the report recipients change and even the messages and stories that we need to highlight change too.
As one of our favourite people in the Australian People Analytics community Adam McKinnon says “So what? Now what?” A really in-depth Talent Analytics system can take common metrics such as time to hire and new hire attrition a step further and calculate the actual monetary gain to your company.
For example, if you know exactly how much it costs the company to have a vacant position, or how much it costs to have a bad hire that has to be re-recruited for, you can show how your team actively reduces these scenarios and exactly how much money you’ve saved the company.
On the flip side, it can also be used to identify any problem areas and address them accordingly. Let’s say your time to hire isn’t improving as much as you’d like to. Without proper Talent Analytics, you might simply blame the software, or the hiring managers. But if you have the data to show that these steps in the process are actually shortening, while the time it’s taking your recruiters to book people into interviews is lengthening, then you know where to take action.
3. So you can hire ethically and avoid algorithmic bias
We all have biases, and no amount of training and understanding is going to completely overcome them. We are human, after all, and similarity bias is one of the most human things for people to feel (people who are like me are better).As mentioned at the start of the post, discussions about AI driven algorithmic bias are a hot topic today.
In this situation, data is both the problem and the solution. When we feed biased data into the AI model, the model will learn from our biases instead of correcting them. But data is also the key to identifying potential areas where bias is occurring through the process. By using data to identify the areas where bias is occurring, we can potentially remedy the situation and stop the biases impacting hiring outcomes and the data which is eventually fed into the AI models.
Let’s say you are concerned that a particular ethnic group is being underrepresented in a certain area of your business. You might assume it’s because you’re not getting enough applicants from that group, and focus your efforts on outreach, while missing where the actual problem lies: hiring managers rejecting applicants from that group at a higher rate than usual. It’s a bias with your hiring managers that you need to correct for with proper training or policy.
Summary
It's been ten years since the potential of Talent Analytics was first highlighted, and we're still seeing too many businesses neglecting the benefits it can bring. We know that Talent Analytics is for everyone, not just big businesses, and we've outlined three of the biggest reasons why it's so important to invest in Talent Analytics now. So what’s next? The way we see it, there are two doorways open to you.
In doorway one, you have nothing. No analytics, no buy-in from the business, no value proposition. You’re at square one and worried you’re going to be behind the curve. That’s okay, and that’s exactly what software like seeHR is designed for.
Pro tip: seeHR is a managed service combining best-of-breed analytics technology and highly skilled data analytics experts to get you up and running quickly and at a fraction of the cost of doing it yourself.
In doorway two, you’ve got … data… but is anyone using it? Maybe you’ve got analytics software integrated in your Talent Tech Stack, and you’ve got dashboards and reports coming out of your ears. But people are not sure how to interpret it, or what to do with it.
We can help you turn this data into actionable items, and help you with the next step of your analytics journey. After all, passive and even proactive reporting can only tell you so much - a truly holistic analytics solution requires predictive analytics powered by machine learning to give you a real edge over your competitors.
Pro tip: Enabling your business to outperform and deliver against your strategic plan is what The Human Collaborative does. Specifically relating to Talent Analytics, The Human Collaborative works with clients and teams to ensure that a company’s talent strategy and operations align to the business goals through insights.
It's time for businesses to take advantage of the benefits it can bring and invest in it today!
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