Welcome to this fall edition of our ‘Most Trending Articles’ of 2018! Here at Analytics in HR, we’re definitely noticing the weather changes. We hope that you’re all sitting warm, with a fresh cup of coffee beside you. Enjoy the following top articles in the HR Analytics space of October 2018!
#5: 3 common mistakes that can derail your team’s predictive analytics efforts
Starting off this month, we have a great article by Eric Siegel on predictive analytics. Who better than the author of the book “Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die” to talk about this topic?
In his article, Eric mentions how many organizations work to ramp up their existing staff’s analytics skills, including predictive analytics. But organizations need to proceed with caution, as predictive analytics is especially easy to get wrong. The most common things that go wrong are:
- Falling for buzzwords
- Leading with software selection
- Immediately jumping to number crunching
How to solve these common mistakes? Read the rest of his article here!
#4: A Different Kind of Dashboard
As HR professionals, especially in the analytics space, we’re accustomed to working with dashboards. But what is the secret behind a good HR dashboard? The right metrics? Clean data? David Creelman answers this question in his article that comes in at our #4 spot.
In his article, he focuses on the idea that HR professionals shouldn’t put the data first, but instead, they should concentrate on asking the right questions. If you start with the data, you can easily end up in the land of “So what?” The best type of dashboards, which focus on answers rather than data, can avoid that fate.
It’s an interesting read, so I highly recommend you to read his article on a different kind of dashboard.
#3: Amazon scraps secret AI recruiting tool that showed bias against women
At our #3 spot, we have an article about Amazon’s AI recruiting tool which made headlines all over the world this month. Unfortunately, not in a good way. Amazon’s recruiting team had built an AI tool that would help them with recruitment, but it unfortunately showed a bias against women.
Due to the AI’s learning algorithm, it taught itself that male candidates were preferable over women. It was trained to observe patterns in resumes submitted to the company over a 10-year period. Most resumes came from men, due to the male dominance across the tech industry. Therefore, it penalized resumes that included the word “women’s”, as in “women’s chess club captain”.
Upon discovery, Amazon’s recruiting team quickly updated the tool to make it neutral to these particular terms. But, that was no guarantee it wouldn’t find another way to discriminate against certain candidates.
Amazon’s experiment offers a case study in the limitations of machine learning. Josh Jersin, Vice President of LinkedIn Talent Solutions, said: “I certainly would not trust any AI system today to make a hiring decision on its own. The technology is just not ready yet”.
If you’d like to learn more, you can read an excellent article by Reuters here: Click here.
#2: How to develop a data-savvy HR department
Most of you who are reading this are very much aware of the need for an analytical mindset in HR. However, many of you may still be wondering how to develop a data-savvy HR department. That’s what this article is all about, taking the #2 spot of this month’s trending articles.
- First of all, you need to understand your current levels of HR Analytics expertise. Most HR professional can be broadly categorized in one of three groups: Analytically savvy, analytically willing, and analytically resistant.
- Next, you need to hire for analytical capability. It’s important to distinguish between analytically-savvy workers, who will be your number crunchers, and analytically-willing workers, who are your HR business partners.
- Third, you need to develop the analytical capability to grow your workers at all levels of expertise.
- Finally, personalize your learning and deliver it at scale.
The article is a great read! You can find it here.
#1: Employee Engagement 3.0: Humu Launches Nudge Engine
Josh Bersin is no stranger to our monthly list, but it’s been a while since he took the #1 spot. This time, he won us over with his excellent article on employee engagement.
In his article, he goes over the history of the employee engagement market, where you can see certain trends:
- Employee Engagement 1.0: Annual Engagement or Climate Survey. In the beginning, this was a market of annual surveys, benchmarks, and year to year comparisons. Most of these surveys were done by hand and on an annual basis, which made the results interesting, but not very actionable.
- Employee Engagement 2.0: Pulse Surveys with Intelligent Action Plans. When the internet came and surveys could be put online, engagement surveys could be done much more quickly. It made employee feedback more actionable, with greater insights all around.
- Employee Engagement 3.0: Even more data, intelligent nudge engines for everyone. So what comes next? This is where the power of AI comes into play. AI can turn feedback and ONA data into prescribed organizational change, using nudges suggestions to make work better.
In Josh Bersin’s style, he goes much deeper than this and goes into great detail what he thinks the future of employee engagement will be. You can read the rest of his article here.