November was an interesting month for people analytics. I noticed that the number of likes and shares this month was lower than usual. However, the quality of articles is even better and this month’s list is therefore very exciting! I listed the articles in reverse order: from the 5th most shared article, all the way to the most shared article. Enjoy!
In his post, David Creelman reviews Wharton’s people analytics program, a quite popular course which we also mention in our HR analytics courses overview. David reflects on the course by making a number of observations. I think his observations are spot-on, for example that the Wharton talks a lot about specific analytics techniques.
Despite the difficulty of analytics – and the difficulty of teaching analytics to a not-so-technical audience – Wharton does a good job challenging people to think differently about data. I do agree with David that for any organization a little analytics is already better than no analytics. However, I also think the Wharton course absolutely triggers people to think about how to play around with data and it opens people’s views to what is possible.
An interesting and thought-provoking article which you can read here.
No, this post is not written by Visier. Brian Sommer dotted down his thoughts about Visier’s Talent Acquisition solution. According to Brian, Visier’s solution provides a number of great Talent Acquisition metrics, like the average amount of time to get a job offer, time to fill the job, and recruitment drop-off points. All these metrics are very relevant. For example, the average time to get a job offer is a reason for applicants to drop out, either because they have become disinterested or because they already accepted another offer.
Is Visier really doing (predictive) HR analytics, or is it still focusing on the slice-and-dice applications? The latter focusses more on descriptive instead of predictive analytics (also called ‘visual analytics’). This question is relevant, as it confuses a lot of people (read our recent post titled: Where’s the analytics in HR analytics tools?).
To read the article and to see some great visuals, click here. This is the second time Brian is featured in our top 5!
Related: 21 Employee Performance Metrics
We already featured Neelie Verlinden’s blog last week and now it made it to our monthly top 5! Neelie mentions that HR is miles behind on other fields like marketing and finance. This should change. She then explains what predictive analytics are and how these analytics apply to key areas in HR, like recruitment, retention, and learning & development.
An interesting and short post for those of you who are interested in what predictive analytics are. You can read it here!
Andrew Marritt is known for his nuanced articles, like the one we featured before about why companies should focus on expected loss/value in attrition analytics. In his newest post he lists five of his favorite books for the aspiring people analyst.
The difficulty of learning people analytics is that it involves different areas of expertise. This is reflected in Marritt’s list. He mentions Lazlo Bock’s very practical Work Roles, but also tips a book on statistics, data visualization, and a book that provides more specific domain knowledge.
I haven’t read all the books he lists, but I would sure love to. Check Marritt’s list here.
Our e-book on The Basic Principles of People analytics was not yet released when Marritt made his list, or it would surely have been on it (wink wink, nudge nudge). Check it out here. Also, did we mention David Green loved the book so much that he wrote a foreword for it?
In this week’s no. 1 most trending article on people analytics, Steffen Maier, co-founder of Impraise, explains how Google uses people analytics to create a great workplace. Using two different case studies from Google’s re:Work, he explores the factors that lead to higher team effectiveness and performance, and what other companies can learn from Google.
These lessons are important, especially because of the growing resistance to engagement surveys. Filling in surveys with the goal of filling in surveys makes no one happy. Make sure to use the data and the opportunity to survey employees to gain insight into business problems that go beyond the organization.
The article is an interesting summary of two of Google’s projects and of Steffen’s view on how engagement and feedback should happen. Read it here.
Also, check out our overview of the best online HR analytics courses!