Just as people analytics doesn’t need to be sophisticated to unlock value, nor do findings necessarily need to be a great leap forward to be useful. Indeed, as Adam Grant writes in this excellent piece for MIT SMR, quantifying obvious insights through people analytics can help gain trust and overcome three obstacles to change. These are: resistance to data (“But that’s not what my experience has shown”), resistance to change (“But that’s the way we’ve always done it”) and organisational uniqueness bias (“That will never work here”).
Findings don’t have to be earth-shattering to be useful. In fact, I’ve come to believe that in many workplaces, obvious insights are the most powerful forces for change
In this article, which previews his white paper collaboration with ServiceNow of the same name, Josh Bersin describes the emergence of the Employee Experience Platform (EXP). He defines an EXP as a user-centric software layer that gives workers a single point of access for a range of services, thus shielding them from heterogeneous back-end systems. When implemented well, Josh explains that the EXP platform should also enable AI, nudges, mobile apps, and cognitive interfaces to help drive personalisation, productivity and engagement.
Ian Bailie builds on Josh’s article, some of the other latest thinking on Employee Experience and his own experience at Cisco, advocating that HR should aim higher than just service-based excellence and efficiency. Instead, Ian implores HR to design people-centric platforms that create a great experience for the entire workforce (not just employees) that they actually want to use. In what is truly a coruscating piece, Ian also urges that EX initiatives need to be linked to business value as well as being focused on fixing the key touch points that matter in the employee journey. Finally, Ian tackles the thorny issue of data ownership, concluding that HR should lead the charge for workers to own their own data, so they can take it with them when they leave and build intrinsic value for managing their careers and promote lifelong employability.
Most importantly of all, this should be a tool where the user owns their data and can take it with them when they leave their current company
Set a challenge by ING CHRO, Hein Knaapen, to explain the business value of Employee Experience (EX), Volker Jacobs pulls it off with aplomb in this terrific article. The model he describes (see ), shows the ‘What’ of TI-people‘s EX methodology on the right-hand side, which he connects to business value in the ‘Why’ part of the model. The two features Volker highlights is how the approach creates i) an engaging experience at ‘moments of truth’, and ii) an effortless experience of HR. He goes on to reveal that one company TI-people is working with has designed their EX initiative around the premise of ” Giving 1 million hours back to employees and managers each year “.
If there is one thing I learned as a CHRO, it is that everything HR does has to have a clear line of sight to business results
Giving people their own data to help them learn and develop is one of the conclusions drawn from Reb Rebele‘s excellent analysis on the pros and cons of psychometric tests. Reb describes why personality testing and other ways of analysing potential present some significant challenges. He explains that not all assessments pass the sniff test, and people’s personalities vary from moment to moment, often depending on the challenge at hand. Instead, Reb argues, we need a finer-grained understanding of human potential including a better consideration of context and measures designed with variability in mind. Reb’s and Adam Grant’s articles are both taken from a MIT SMR series on People Analytics. Check out the other articles by Angela Duckworth and Matthew Bidwell & Federica De Stefano too.
Learning is the raison d’être for people analytics… Give people their own data in ways that would help them (learn and) develop
TOM DAVENPORT – AI And HR: A match made in many companies
Tom Davenport has been referred to as ‘the father of analytics’, so when he writes that HR’s use of advanced analytics is 14% higher than in Finance (see ), one sits up and takes notice. Tom’s article, based on research he conducted in unison with Oracle, goes further in presenting evidence that HR is not just employing analytics but also AI in significant numbers. The research uncovered that just over half of HR organisations in the global survey now say they can perform advanced (predictive and prescriptive) analytics, with only 6% of HR respondents admitting they are “novices” at analytics. Perhaps even more surprising is the fact that 31% made AI the first choice of analytics they are using.
HR is employing not just analytics, but also AI, in significant numbers
This in-depth case study describes in detail how IBM reimagined its performance management system (see ) by co-creating a model with employees that promoted speed, innovation, promoted feedback over assessment and strove to cultivate a high-performance culture. Insights are offered throughout by IBM’s CHRO Diane Gherson and VP Global Talent Joanna Daly with supporting commentary from Anna Tavis. The MIT SMR article also describes how IBM overhauled and personalised learning to reflect that ” in today’s world, skills are actually more important than jobs. ” This platform uses data to infer which skills employees have and connects them with learning to build those skills that are increasingly in demand. If that wasn’t enough, the case study also outlines how IBM uses people analytics to predict and prevent attrition, as well as how the company has deployed chatbots and virtual assistants to improve the employee experience. A must-read.
(The purpose of HR is) to create competitive advantage with your talent and improve the employee experience
In this article, Dave Ulrich cuts through the hype and distils what the digital revolution means for HR. He describes a four phased approach to evolve HR into a digital function. These are: i) Efficiency “using technology to streamline administrative and repetitive work”, ii) Innovation (see ) “using technology and apps to innovate HR practice”, iii) Information “using technology, data and analytics to support better decision making”, and; iv) Connection “using technology to create connections and enhance the employee experience to drive individual and organisational productivity.”
TRENDS IN PEOPLE ANALYTICS
As highlighted earlier, the PAFOW conference in San Francisco was the biggest and most successful yet in the show’s thirteen-year history, as this highlights video shows. Over the two days, some of the crème de la crème of the people analytics cognoscenti spoke, which meant I was able to create and organise my key takeaways around a manifesto of four strategic imperatives for the field. The article features insights from the likes of: Josh Bersin, Dawn Klinghoffer, Brad Hubbard, RJ Milnor, Heather Whiteman, Misael Cerpas, David White, Piyush Mathur, Jeff Higgins, Richard Rosenow, Jonathan Ferrar, Stacia Garr, Manish Goel and Amit Mohindra. It all augers well for PAFOW London on 24/25 April and PAFOW Philadelphia on 11/12 September. See you there!
I am often asked how to set up and focus people analytics in a small to medium enterprise, and it is true that the vast majority of case studies, articles conference speeches and research focuses on people analytics in large organisations. However, if you look carefully enough there are a several examples of smaller companies having significant success with people analytics. In this revealing piece, Littal Shemer Haim interviews Michal Shoval on her journey at GIA – ‘the motives, the obstacles, the quick win, the team participation, and more’.
Even an organisation of a few dozen or hundreds of employees can and should use People Analytics
Three must-read articles for those leading or working in people analytics teams. First the inimitable Keith McNulty walks through the first question one should ask before building a model – namely is it intended to be explanatory (created to help understand why something is happening) or predictive (created to make predictions as accurately as possible regarding what will happen). The second article looks at the critical role of translators in analytics, providing guidance on hiring and developing translators, imbuing translator skills into the wider employee population and growing organisational ability to deliver analytics use cases. The third article, whilst focused on marketing, also highlights the need for a translator as well as seven other steps to take when conducting an experiment. As the authors state, experimentation promises the power of the scientific method to help reduce uncertainty.
Translators define business problems that analytics can help solve, guide technical teams in the creation of analytics-driven solutions to these problems, and embed solutions into business operations
ORGANISATIONAL NETWORK ANALYSIS
Learning to navigate and manage the intense rise of collaborative demands in today’s workplace is, as Rob Cross writes in his article, a skill that is necessary to survive and thrive in today’s world. Rob’s article then describes seven habits of highly inefficient collaborators including ‘time vampires’, ‘black holes’, ‘calendar killers’ and ‘fear creators.’ Ian Cook draws on further research from Rob in his article examining the business impact of collaborative overload such as burnout and ‘turnover contagion.’ Ian then explains how ONA can be deployed in conjunction with people analytics to reduce the risk of burnout by identifying influencers, uncovering turnover trends and quantifying the cost of the problem.
Without it (ONA), the people who truly deserve to be recognised within an organisation can be overlooked
One of the emerging use cases for ONA is in measuring the effectiveness of diversity and inclusion initiatives through a social capital lens. This is the focus of Greg Newman‘s terrific article. Citing research from Boris Groysberg, Greg describes how female and male employees tend to build stronger external and internal networks respectively and the impact this has when they move job. Greg also provides insights from some of TrustSphere ‘s clients on how networks can affect promotability, trust and collaboration. One example (see ) includes an organisation where if an employee had more than ten years tenure, they had virtually no strong working relationships with anyone with less than five years tenure. It doesn’t take a rocket scientist to see the negative impact this will likely have on innovation, problem-solving and ultimately business performance.
Last month’s collection featured a landmark study by Accenture on trust, data and unlocking value in the digital workplace. This article looks at how companies can use workplace data in an effective, responsible, and ethical way. The authors present a framework of three key actions responsible leaders can take: i) Give employees more control, ii) Create a system of checks and balances, iii) Use Data to Elevate People, Not Penalise Them. Examples from the likes of Schlumberger, JP Morgan Chase and AXA are provided respectively to highlight each step of the framework. Interestingly and similar to the earlier articles by Ian Bailie and Reb Rebele, the study advocates that people data should be co-owned with employees so they can take it with them when they move jobs.
Data can unlock people’s potential and boost business performance, but these aren’t prizes worth having if they diminish fairness and trust
As technology and workforce expectations evolve along with the shift from roles to skills, lifelong learning has become the expected norm. This has moved the goalposts with regards to learning and development and has prompted a revolution in the space and the increased use of data, analytics and personalisation. These three articles together provide a comprehensive view of this shift. Josh Bersin and Marc-Zao Sanders describe a new paradigm of ‘learning in the flow of work.’ The second article from McKinsey describe ‘lifelong employability’ and how this allows companies to get ahead of the skills challenge while in parallel making a better workplace for everyone. Finally, the Deloitte article provides an excellent primer on the what, why and how of learning analytics.
By changing how they think about L&D, senior executives can get ahead of the challenge and start making a better workplace for everyone
Paul van der Laken may well have produced with this list the best curation of books for the forward-thinking data-driven (or data-curious) HR professional in existence. Indeed, it almost deserves a Nobel Prize. Paul was inspired by a post by Jared Valdron ‘s call for book recommendations on people analytics on LinkedIn, which drew nearly 60 responses. Paul decided to merge these overviews and voila, the community now has a monumental resource to draw from.
DIVERSITY & INCLUSION SPECIAL
With the staggering but yet not surprising revelation from the World Economic Forum that it will take 202 years to close the global gender pay gap, it seems entirely appropriate to highlight some of the best D&I themed articles that were published in February. First, Steven Huang provides a practical step-by-step guide on how to answer the question: “Is there a systematic bias in how Men vs. Women employees are paid?”. Next, Ellen Taaffe provides a number of tips for firms to turn good intentions around inclusion into actions – including studying the data. Then, Lisa Rabasca Roepe describes how the difference in how men and women approach networking has a big impact on career opportunities, and outlines six ways how women can better leverage their connections. Glen Cathey‘s lengthy but fascinating piece provides a compelling argument for neuro diversity based on research showing brain-level variances between introverts and extroverts that result in real differences in how they think, process information, interact with others, and work best. Finally, Stacia Garr outlines the updated RedThread Research and Mercer study into the growth of HR technology companies that service the diversity and inclusion field.
Originally published in 2015, where it featured in my collection of the best people analytics articles of 2015, Amit Mohindra presents his three ‘laws’ of people/workforce analytics in what continues to be both a popular and prescient article: i) The demand for workforce analytics grows exponentially; ii) The consumption of workforce analytics requires effort; iii) Workforce analytics trumps workforce planning – in most circumstances.
The trick is to provide relevant information and insights to human capital decision makers – whether HR leaders, HR business partners, business leaders or people managers – who are closest to the action
Two podcasts I recommend listening to this month are first Ben Eubanks in conversation with Stacia Garr and Carole Jackson on the aforementioned Red Thread Research and Mercer study into the burgeoning diversity and inclusion technology field. In the second podcast, Dave Ulrich talks to Emily Sexton-Brown about the current trends in HR, just how damaging technology can be and how the field needs to develop our ideas and current mindset for HR to evolve.
Andrew Marritt is my go-to on employee listening and text analytics and in this interview with myHRfuture, he offers a number of great insights on the developments taking place in this space. His thoughts on the usefulness (or otherwise) of sentiment analysis are particularly illuminating.
In the run up to SHRM Tech EMEA, Hanadi El Sayyed interviewed me about trends and challenges in the people analytics field. Thanks to Achal Khanna, Brad Boyson and the whole SHRM team for inviting me to speak and looking after me during my stay in Dubai.
A video interview I gave to Emily Sexton-Brown about my session at the HRD Summit on how to accelerate business performance with people analytics, which also leads to a discussion on the Nine Dimensions for Excellence in People Analytics model. Thanks to Penelope Jenkin for inviting me to speak at the HRD Summit.
Whilst I was in California for PAFOW, I had the pleasure of filming a webcast with Sarah O’Brien of LinkedIn on four steps to becoming an HR analytics champion. This drew on 2018 research by LinkedIn as well as Sarah’s and my own experience in the field. It was great fun to shoot and thank you to Sarah and Daniela Bayon for organising and looking after me. You can view the slides here and watch the video below.
David is a globally respected writer, speaker, conference chair, and executive consultant on people analytics, data-driven HR and the future of work. He helps HR practitioners and organisations leverage data and analytical thinking to drive positive business outcomes, improved performance, and enhance employee experience. Prior to launching his own consultancy business and taking up board advisor roles at Insight222 and TrustSphere, David was the Global Director of People Analytics Solutions at IBM Watson Talent. As such, David has extensive experience in helping organisations embark upon and accelerate their people analytics journeys.
UPCOMING SPEAKING ENGAGEMENTS
I’ll be chairing and/or speaking about people analytics, data-driven HR and the Nine Dimensions for Excellence in People Analytics model at the following events until the end of October 2019.
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