Top 20 HR Analytics Articles (second half year 2015)
Once again we are bringing you a selection of our favorite articles on HR analytics, this time for the second half of 2015. The second half of this year has provided us with so many insightful articles in the world of analytics that even narrowing the list down to 20 was a painful task. We hope that you can find some time to stop, unwind, and catch up on your reading.
The articles we selected for you cover everything from getting started with analytics in recruitment to making sure your analytics journey proceeds in an ethical way as well as double-checking that you are on par with the trends of the year we are about to wave goodbye to. So ignore the rest of your incoming emails for the next few hours and enjoy the read. Happy Holidays!
1. Developing Advanced Talent Analytics: Why It Matters to CFOs – CFO Journal (twitter @CFOJournal)
In Deloitte’s latest article in the WSJ’s CFO Journal, Josh Bersin discusses how advanced talent analytics is helping achieve better talent outcomes in terms of leadership pipelines, talent cost reductions, efficiency gains and talent mobility. In this interview Bersin explains how CFOs can help their companies develop a mature talent analytics capability and benefit along the way.
2. HR Analytics – Correlation of People Data with Business – Vishal Nagda (twitter @vicnagda)
While we are all talking about HR Analytics and all claiming to be using it, Vishal Nagda explains in one of his latest articles, the reality is that most companies are still stuck with basic Operational Reporting only. The author walks the readers through the first steps of getting started with analytics: using software solutions to facilitate the process and defining HR metrics, analytics and dashboards based on business goals.
3. Why Risk Scoring in HR Analytics is the New Black for CHRO’s – iNostix (twitter @iNostix)
In this interview, Luk Smeyers, HR Analytics Expert, raises the subject of Risk Scoring in HR Analytics as the next step in the development of a strategic relationship between senior management and HR departments. This type of predictive analytics can go very far: blind spots in the organisation that deserve attention, risks in terms of staff turnover, absenteeism and accidents, as well as dysfunctional leadership.
4. 6 Steps To Getting Started With Analytics In Recruiting – David Green for ERE Media (twitter @david_green_uk, @ERE_net)
Recruiting is arguably the perfect shop window in the HR function for analytics as not only should hiring great people be of utmost importance for all organizations, but hiring is high-volume, comprised of repeatable processes, and for too long has been primarily based on intuition and unconscious bias. For an aspiring analytically minded talent acquisition leader to start, David outlines the six steps that — if carefully adopted — should at least help recruiting functions start the journey.
5. 5 Important Differences About Google People Analytics – Mike West (twitter @mikecwest)
Mike West discusses what companies with high success rates in People Analytics do differently from those with low or modest rates. He uses Google as an example of a company that utilizes People Analytics to a high degree of success. 1) People Analytics is not another thing they do in HR, it is how they do what they do in HR. Make sure to read the rest of the article for more interesting insights.
6. Wake up, recruiters! – Luk Smeyers for HR Tech World blog (twitter @iNostix, @HRTechWorld)
While with a bit of good will and some study, it’s possible these days to use predictive algorithms and advanced analysis to predict the career chances of applicants with reasonable success, 99% of recruiters keep putting their time into meaningless metrics from the 1980s. As long as we gather high quality data, predictive possibilities are endless. This article is a call to all recruiting professionals: instead of trusting your feelings or intuition, let us take our emotions out of the recruitment process when we hire new employees and replace them with an approach steered by data!
7. How to Fix a Flawed Retention Program by Climbing the Analytics Ladder – Ian Cook for Visier blog (twitter @VisierAnalytics)
Ian highlights the trap many HR teams fall into: They’ve bootstrapped their people metrics to the point where they can answer a few basic questions about their workforce — such as the resignation rate for a given team — but they discover that a limited set of descriptive analytics isn’t enough. What they need is a way not just to see what happened, but to understand why it happened, what will happen next, and how to adapt their workforce strategy to align with company objectives.
8. How to Balance the Five Analytic Dimensions – Damian Mingle for SmartData Collective (twitter @DamianMingle, @SmartDataCo)
So many data scientists select an analytic technique in hopes of achieving a magical solution, but in the end, the solution simply may not even be possible due to other limiting factors. It is important for organizations working with analytic capabilities to understand the various constraints of implementation most real-world applications will encounter. When developing a solution one has to consider: data complexity, speed, analytic complexity, accuracy & precision, and data size.
9. Why Talent Analytics is HR’s Number 1 Priority for 2016 – InsideHR (twitter @insidehreditor)
The article presents a very useful summary of the report titled What’s Next for HR in 2016? 11 Trends from HR Leaders, which surveyed 350 heads of HR globally to assess their priorities and expected challenges in 2016. Despite the enormous promise of increased data availability, according to the report, increased analytics availability doesn’t necessarily equate to effective analytics use.
10. The Ethics of Analytics: A Look into the Dark Side – Tracey Smith (twitter @NInsights)
This article is dedicated to the darker side of analytics and the ethical decisions associated with it. As companies build their HR Analytics (HRA) functions, a few HRA leaders have been asked to use their data to prove that a certain leader’s programs are successful rather than “letting the data drive the decisions” through impartial analysis. These are companies that don’t wish to hear the truth of what’s working and what isn’t inside HR. For the ethical HRA leader, this is a difficult spot in which to be.
11. A Dozen Key Facts about Predictive Workforce Analytics – Greta Roberts for International Institute for Analytics (twitter @gretaroberts)
Whether you’re new to the concept of Predictive Workforce Analytics, or just brushing up, Greta Roberts prepared 12 essential rules to help Human Resources derive the most value from analytics. For example, HR needs to avoid the “Wikipedia Approach” to predictive analytics. When exploring HR data (or any data) without a question, what you’ll find are factoids that will be “interesting but not actionable”. Read the article for more helpful tips.
12. Three “Laws” of Workforce Analytics – Amit Mohindra (twitter @TheNelsonTouch)
Amit Mohindra has distilled what he has learnt as the head of Workforce Intelligence at McKesson for the last three years into three principles: (1) The demand for workforce analytics grows exponentially; (2) The consumption of workforce analytics requires effort; (3) Workforce analytics trumps workforce planning – in most circumstances. Make sure to read the article for further insight.
13. People Analytics Takes Off: Ten Things We’ve Learned – Josh Bersin (twitter @Josh_Bersin)
Josh Bersin summarizes his recent presentation at a major People Analytics conference, which covered the “State of the Market” for People Analytics. Some of these findings include: (1) People Analytics will grow exponentially, but we are in the early days; (2) Most companies still don’t really know what People Analytics really is; (3) Data Management remains the biggest barrier. Check out the rest of the “Top 10” list in the full article.
14. Seven Deadly Sins To Avoid with HR Analytics Initiatives – Mark Berry (twitter @s_markberry)
The wrong HR leader can help to kill a talent analytics initiative before its first breath. With the best of intentions, a misguided leader will – intentionally or not – engage in behaviors that virtually guarantee the failure (or significantly impeded the traction) of future workforce analytics initiatives. If you – as a HR leader – want to really support your organization’s HR analytics efforts, there are specific behaviors – “sins”, if you will – you should seek to avoid.
15. The 10 golden rules of HR analytics (revisited) – Patrick Coolen (twitter @PatrickCoolen)
Not even a year after Patrick first posted the 10 golden rules of HR analytics he feels it is already time to update most of the lessons learned. One of the most asked questions we hear when talking about HR analytics is: “What different type of capabilities does my team need to successfully start with HR analytics?” Patrick answers this and many other questions in his latest article.
16. 4 Approaches Everyone In HR Analytics Should Be Using – iNostix (twitter @iNostix)
iNostix presents a short overview of the 4 most common approaches or methodologies used in predictive HR analytics projects. These 4 approaches have differences in emphasis and use different techniques in the background, but they generally repeat two key features: 1) all projects combine data from multiple sources (people and business/organization) and 2) they start with a pressing people/business/organization issue that need to be solved (or better understood).
17. HR Ranks At The Bottom — Reasons To Adopt Metrics And Predictive Analytics – John Sullivan for ERE Media (twitter @DrJohnSullivan, @ERE_net)
When you survey the most frequent users of analytics and metrics in the corporate world, not surprisingly you find that HR ranks at the very bottom. Compared to finance, which is ranked No. 1, HR compares poorly with only half of its functions being classified as advanced users and three times more HR functions are classified as non-users. The article presents a list of credible reasons that resonate with most HR audiences as to why your corporate talent function should embrace metrics and a data-based decision model.
18. Think Like a Writer to Tell Your Analytics Story – Evan Sinar for DDI Blog (twitter @EvanSinar, @DDIworld)
New writers are taught to consider 6 key elements before composing a story: Characters, Conflict, Setting, Plot, Point of View, and Theme. The best stories share these elements to keep you turning pages until the end, but this doesn’t happen by accident—the authors have taken the time in advance to make sure that all these elements are in place. Similarly, if you want an audience to sit up and your message to soak in when you’re presenting the outcomes of your latest round of business analytics, you need to think and plan more like a novelist and less like a scientist.
19. Is your Analytics Predictive and Prescriptive? – Thomas Hedegaard Rasmussen
Analytics is about inferring causality by using scientific methods and statistics – i.e. identifying what works, what drives outcomes, how big is the effect? The ‘Predictive’ or ‘Prescriptive’ part is about applying common sense and actually acting on the knowledge derived by Analytics – it is not about more sophisticated statistics or additional analytics. So if someone gives you a pitch on the difference between analytics, predictive analytics, and prescriptive analytics, odds are that they either are trying to sell you something you don’t need, or do not know what they are talking about.
20. Helpful tips on how to start an HR Analytics project – Hendrik Feddersen and Lyndon Sundmark (twitter @h_feddersen)
Lyndon Sundmark and Hendrik Feddersen, both long-standing HR professionals and absolutely passionate about HR Analytics, offer some helpful tips written for HR data scientists and their HR counterparts to get an HR Analytics project started. For example, it is important to concentrate your attention on a very limited number of metrics. Reading will help you to develop a conceptual framework, which can encourage in developing a starting point of where you want to head. It will help to answer the question of ‘What’ needs to be done. For more useful tips, make sure to go through the article.
Interested in getting started with HR Analytics?
Interested in using predictive HR analytics as a key component in your HR strategy? Get in touch with CEO and co-founder Luk Smeyers for more information: firstname.lastname@example.org or via Google+. Or follow iNostix on Twitter and/or Facebook for exciting international articles on HR analytics. And don’t forget to register for this blog!