Top 18 HR Analytics Articles (first half year 2015)
Once again we are bringing you a selection of our favorite articles on HR analytics, this time for the first half of 2015. Having gone through hundreds of articles by some of the most recognized experts and thought leaders, narrowing it down to the top 18 was not an easy task. From the do’s and don’ts in implementation, to dismantling common myths and to exploring the evolution of HR analytics, this selection guarantees that you will be up to speed with the major trends, shifts and pitfalls in the, often times complex yet vital for HR, world of analytics.
So, as you settle in your office chair sipping on a cup of morning coffee looking in disbelief at your to-do list for today, take the next 30 minutes to skim through the articles we selected for you. We promise, they are worth the read.
Josh Bersin delivers an insightful article on the changing landscape of analytics in HR as well as the type of professionals working in this field. The article walks the reader through the history of HR Analytics, which in the past 10 years has evolved from a simple tool to clean up HR’s messy, often inaccurate people data to the first steps towards “People Analytics.” Yet, HR teams are just starting to get good at analytics. As a result of this lack of experience an interesting trend has emerged – statisticians, mathematicians, and engineers have entered the people analytics space. These data scientists are not looking at HR data alone. They look at the real-world business issues: sales productivity, turnover, retention, accidents, fraud, and even the people-issues that drive customer retention and customer satisfaction.
A practitioner’s view on HR analytics – Patrick Coolen and Auke IJsselstein (twitter @PatrickCoolen and @AukeIJsselstein)
Patrick Coolen and Auke IJsselstein answer the question on the type of capabilities a team needs to successfully start with HR analytics based on their experience as practitioners. The answer is: “Only those organizations that manage to create and maintain a balanced blend of different relevant capabilities will be successful in HR analytics.” Patrick and Auke introduce the HR analytics capability wheel, which groups the relevant capabilities in 6 different perspectives – business, HR, consulting, data science, IT architecture and software management.
The Race Is On: Winning Analytics Fitness – Rebecca Atamian and Travis Klavohn for Workforce blog (twitter @workforcenews)
Business competitiveness is rooted in achieving the right level of analytics fitness in the right areas as part of an enterprise analytics strategy. Most organizations invest in analytics capabilities piecemeal where they see potential for the highest impact on business outcomes. Given current global workforce dynamics and the inordinate cost of labor, organizations should consider their workforce one of the most critical areas in which they should be analytically “fit” right now. Four key elements contribute to workforce analytics fitness: a workforce analytics strategy; workforce priorities based on business objectives; workforce analytics tools; and workforce intelligence advisers.
Predictive analytics and algorithms: the future of recruiting? – David Green for HR Tech World blog (twitter @david_green_uk, @HRTechWorld)
Recruiting is the perfect shop window for analytics as not only is hiring great people of utmost importance for all organisations, but hiring is high-volume, comprised of repeatable processes and for too long has been primarily based on intuition and unconscious bias. This lethal combination of gut instinct – surely tantamount to guesswork, and the focus on metrics such as time to hire and cost per hire over quality of hire is potentially dangerous. David Green explores the alternatives, which includes implementing a strategy based on predictive analytics. The options for predictive analytics in recruiting are potentially limitless, providing that organisations are able to effectively utilise the plethora of recruiting data it already has
Separating reporting and analytics is (usually) a bad idea – Andrew Marritt (twitter @AndrewMarritt)
One of the common things that HR does when building an organization to deliver analytics is to separate reporting and analytics. In many instances this is a bad idea. Some of the problems include the differences in the skill sets and backgrounds on analysts and reporting teams as well as in the approaches to data analysis and its end goal. As a result, multi-disciplinary teams are the way forward. Experience has shown that all these people – statisticians, graphic designers/data visualization specialists and technologists – need to be engaged at the beginning as recommendations and work of one will impact the work of the others. It’s hard to do that if you separate reporting and analytics.
How to Fail at HR Analytics – Lessons from a Leading Loser – Mark Berry (twitter @s_markberry)
Mark Berry, a recognized thought leader in the area of HR analytics, takes a look back at his experience and the pitfalls he had on the way. The article highlights the “don’ts” of HR analytics, which include positioning your program as “strategic,” investing a high percentage of your resources into technology (rather than using technology as an enabler), deluding yourself into believing that others value what you are doing as much as you do, and a number of others. Mark suggests that his readers learn from the mistakes of others in order to maximize the probability of success.
12 Reasons why outsourcing HR analytics is good for HR – iNostix blog (twitter @iNostix)
There are numerous reasons why companies turn to outsourcing, depending on their vision and purpose. It’s a hotly debated topic of course, with pros and cons. iNostix summarizes their top 12 reasons to outsource based on the feedback of client companies. Top 3 reasons: speed of analysis, building analytical capabilities takes a long time and the challenge of managing analytical people. For the full list make sure to read the article. Make sure not to forget that outsourcing analytical execution is one thing, but taking internal ownership of outcomes and the optimization or change management process thereafter will be the key to HR success.
Dear HR: Stop Hiring Data Scientists Until You Are Ready For Data Science – Greta Roberts (twitter @gretaroberts)
The pressure on HR to begin using an analytical approach has led them to hire data scientists, but when it comes to actually using this approach it’s too foreign, or scary or “not what we’ve done before”. HR needs to learn from these brilliant people they’re bringing into their domain or stop hiring them to begin with. HR Data Scientists can help move HR from being tactical to strategic, using an analytics approach to highlight never seen before patterns, make decisions based on data and the like. Greta provides tips on letting that brilliant HR Data Scientist you hired be one of your most brilliant hires.
Talent Analytics: Old Wine In New Bottles? – Edward E. Lawler III
Most of the discussion of analytics emphasizes how much can be gained by better talent utilization and the ability of analytics and big data to improve overall organizational performance. It is hard to disagree with this, but it is also important to point out that talent analytics is not a new area by any means. There is a bit of an “old wine in new bottles” about it. The major reason for the greater attention being paid to talent analytics is the growing importance of talent. However, organizations need the “right culture” and leadership approaches—ones that value evidence-based decision making – to make a great difference in how they manage their talent.
5 Golden HR Analytics Bullets for Geeks to Secure Early Wins!!! – Manoj Kumar (twitter @reach2manoj)
Following up on one of his earlier articles, in which Manoj recommended a collective, inclusive and collaborative approach for data geeks to secure early buy-in for HR Analytics adoption, he now presents 5 proof of concepts (POCs), which he suggests geeks to consider when they are empowered to make a change. These POCs are focused to address not only Attract, Develop & Retain but also demonstrate analytical capabilities to solve operational, HR and business problems touching end to end employee life cycle. Manoj urges to remember that simplification, redeployment and speed to market is key.
Janine Milne presents a summary of IBM’s recent report Starting the workforce analytics journey: the first 100 days, co-authored by Dr Nigel Guenole, a researcher at the IBM Smarter Workforce Institute and a lecturer at Goldsmiths, University of London. The report focuses on the organizational development and change management required for HR to establish an enduring workforce analytics program and addresses the issues in phases. The first phase is all about establishing a clear vision of what you want to achieve. The second phase is about being smart with data quality and smart with technology, such as using the cloud. Phase three is about growing analytics capabilities.
iNostix asks two of Benelux’ most advanced HR analytics practitioners – Esther Bongenaar, HR Analytics Manager at Shell and Patrick Coolen, HR Analytics Manager at ABN-AMRO Bank – for their opinion on 5 common myths about predictive analytics. Read the interview as they confirm or dismantle such myths as “HR has not matured enough to do predictive analytics,” “HR doesn’t capture enough data to do predictive modelling,” “HR will need to make big investments in data technology to do predictive HR analytics,” “HR can simply buy a predictive-modeling capability by investing in advanced HR business-intelligence solutions,” and, finally, “HR will need to hire a group of statisticians before we can do predictive modelling.”
OrgVue has put together its top trends for HR analytics in 2015 for you to look out for and look forward to! There is a lot for HR to continue to be excited about for 2015 surrounding HR analytics. Not only will HR analytics become more user friendly, interactive and fun to play with, but increasingly more value will be realised by HR and the business as technology progresses and HR professionals develop the skills to make the most of the analytical tools available. The emphasis is now on vendors to deliver usable, effective solutions, and HR to continue to embrace data and analytics to deliver lasting results.
Data analytics can be a powerful tool for the HR profession. It can be used to highlight talent or leadership shortages in a global firm or boost employee engagement. But many global firms believe that analytics is one of the areas where organizations face a significant capability gap. Karen Higginbottom explores what skills are required of a data analyst to work with the HR profession.
HR Is Shifting To A Data-Drive, High Business Impact Approach, So Don’t Be Left Behind – Dr John Sullivan for ATC Hub (twitter @DrJohnSullivan, @ATCevent)
The largest shift in the history of HR is underway and you simply cannot afford to be left behind. This shift is from a historical reliance on intuitive or “off the top of my head” decision-making among HR professionals and supervisors/managers to a more businesslike data-driven approach. This soon to be dominant approach can also be called “data-supported”, “data-based” or “evidence-based” HR decision-making, because data or evidence support are the foundation of all major HR decisions that result in direct business impacts. HR leaders don’t get “a vote” on this shift, because it is being driven by corporate executives and a faster moving more competitive business world. Unfortunately, HR currently ranks at the bottom in analytics and data-driven decision-making, despite the fact that the opportunities presented to it by data-driven approaches are numerous.
Analytics is becoming a regular aspect of all of the roles in Dave Ulrich’s HR model – HR Business Partner, Change Agent, Employee Advocate, and Administrative expert. What we once viewed as a technological skill is now becoming part of each of these jobs. The tasks are still specialized although the skills can span multiple roles. HR professionals don’t all have to become Data Scientists to understand how to do analytics because vendors have made that aspect much simpler by guiding users with appropriate questions and actions that HR people would ask or take.
Google’s Scientific Approach to Work-Life Balance (and Much More) – Laszlo Bock for Harvard Business Review (twitter @LaszloBock2718, @HarvardBiz)
Laszlo Bock, Google’s SVP of People Operations, introduces the audience to gDNA, Google’s first major long-term study aimed at understanding work. This isn’t your typical employee survey. Since we know that the way each employee experiences work is determined by innate characteristics (nature) and his or her surroundings (nurture), the gDNA survey collects information about both. Acknowledging the resources Google possesses to conduct a study of this scale and depth, Laszlo Bock gives tips to organizations that want to start their own exploration and move from hunches to science.
This article was prepared in response to the many questions Luk Smeyers and his company iNostix receive on a daily basis with regards to the ways in which to add value with HR Analytics. The HR Analytics Pyramid presented in the article consists of four levels: classical reporting, HR effectiveness measures, people optimization and business optimization. While there are many analytics maturity models in the market, this particular one approaches the subject from the perspective of the ideal focus for HR when it comes to data, reporting in general and (predictive) HR Analytics, in particular.
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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: [email protected] 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!