The 20 best People Analytics articles: Sept & Oct 2017

It’s been an even more difficult task than usual for me to select the 20 best articles on people analytics and the future of work for September and October.

As I have seen for myself over the past two months when speaking at conferences in Berlin, Philadelphia, Moscow, London, Las Vegas and most recently at HR Tech World in Amsterdam (see Key Takeaways), the interest levels in people analytics continue to rise.

Whilst HR as a whole is still struggling to get to grips with analytics, there is growing recognition that i) demand for analytical insights from the business is high, ii) analytics is central to the digital transformation of HR, and iii) analytics is a core requirement for organisations looking to develop personalised consumer-like technologies for employees.

As usual Josh Bersin captures the mood perfectly in his blog to preview the publication of Deloitte’s HR Technology Disruptions for 2018, by writing:

"I personally see People Analytics as the lynchpin of success for HR in the next few years"

Josh Bersin

That seems a good point to kick off the countdown, which starts rather aptly with…

1. Josh Bersin - People Analytics Grows Up: Healthy New Focus On Productivity

Josh Bersin has been writing about people analytics for longer than most so it is refreshing that in this article he shares his belief that “people analytics has grown up.” Josh cites the exploding market of Organisational Network Analysis (ONA) as part of a shift in focus from employee engagement to employee productivity and performance. Naturally, these are the topics that CEOs and business leaders really care about. This means that people analytics is now “business critical, mandatory and must be supported well.” Look out for Bersin by Deloitte’s High-Impact People Analytics research, which has been led by Madhura Chakrabarti and which will be published in the coming weeks.

“People analytics is no longer just a ‘fun and exciting project.’ It’s now business-critical, mandatory and must be supported well”

Josh Bersin

See Josh Bersin's recent presentation of the trends disrupting the HR Technology market and the consequent move to the mainstream of HR for people analytics

2. Prasad Setty - Google’s head of People Analytics talks making work better

In this must-watch video, Prasad Setty asserts that research trumps best practice when it comes to making work better for employees. Unfortunately, as Prasad describes, the vast majority of HR programs simply replicate practices from other organisations. Given that each organisation has a different culture and what employees are looking for is also different, is it any surprise that many of these programs fail? Prasad provides examples of the research his people analytics team have conducted (see Figure 1) to help Googlers make better decisions in areas such as onboarding (by proactively seeking feedback), saving for retirement and diet. These examples all follow the principles of behavioural economics in terms of framing different choices, and all draw on the philosophies habitually used in consumer marketing.

Figure 1: Examples of people analytics projects at Google (Source: Prasad Setty, re:Work by Google)

3. Nigel Guenole & Sheri Feinzig – 5 Truths about Workforce Analytics

Along with Jonathan Ferrar, Nigel Guenole and Sheri Feinzig this year published The Power of People book, which has rapidly become the Bible of people analytics. In this article, Nigel and Sheri adopt a mildly provocative stance and offer five generalisable ‘truths’ (see Figure 2 below) about workforce analytics based on their research and experience. The article has already prompted some lively debate, so it will be interesting to see how this continues to develop.

Figure 2: 5 Truths about Workforce Analytics (Source: Nigel Guenole & Sheri Feinzig, inspired in part by the findings of their HR Analytics Readiness white paper

4. Morten Kamp Andersen - Why evidence-based HR is critical to success and how to get started

I always enjoy Morten Kamp Andersen’s insightful (but alas these days all too infrequent) articles on evidence-based HR. His most recent effort is one of his best. There are two aspects of the article I’d like to highlight. First, as Morten says, “the purpose of evidence-based HR is not to find ‘the Right Answer’ – we are dealing with people after all. The purpose is to use all available evidence (research, internal data, analysis, experience, interviews etc.) to find the solution with the highest probability of adding the most value to your organisation.” This is our best hope of mitigating the bias and prejudice inherent to varying degrees in all of us. Morten then goes on to describe an approach (see Figure 3), which emphasises the importance of starting with the business challenge rather than getting lost in the data.

Figure 3: The HR Value Chain (Source: Morten Kamp Andersen)

5. David Green - The rise of People Analytics & its impact on HR & the Future of Work

My summary of the East Coast edition of the People Analytics & Future of Work (PAFOW) conference features insights from the likes of Al Adamsen, Arun Chidambaram, Ian O’Keefe, Geetanjali Gamel, Jonathan Ferrar, Guru Sethupathy, Rebecca White, Will Gaker, Chris Broderick, Ben Hawley and Ross Sparkman. As is typical with PAFOW events, the two days were a vibrant mix of education, inspiration and exploration as speakers, delegates and sponsors sought to share and collaborate to push the envelope on what could be possible with people analytics. The early program for PAFOW San Francisco on 1-2 February 2018 is up here and with the likes of Josh Bersin, Michael Arena, Alexis Fink, RJ Milnor, Heather Whiteman and Charlotte Nagy already confirmed as speakers it promises to raise the bar even higher.

Figure 4: Two of the presentations at PAFOW Philadelphia. On the left, Al Adamsen described how people analytics is evolving from a focus on employees to a broader ecosystem of work. Whilst on the right, Geetanjali Gamel spoke about some of the options for career development for people analytics professionals 

6. Jonathan Ferrar - Ethics and Privacy in Workforce Analytics

Jonathan Ferrar spoke at PAFOW about arguably the most important part of people analytics and certainly one of the biggest challenges facing practitioners – ethics and privacy. This article captures and expands upon the points Jonathan made in Philadelphia including the revelation from a recent study by Insight222 that 81% of people analytics projects (see Figure 5) are jeopardised by ethics and privacy concerns. Jonathan’s advice includes the need for people analytics leaders to work closely with their Chief Privacy Officer, publish a code of conduct, establish a governance council and above all put employee trust and transparency at the centre of what you do.

Figure 5: 81% of people analytics projects are jeopardised by ethics and privacy concerns (Source: Jonathan Ferrar / Insight222)

7. Arnold Birkhoff - 9 Ways the GDPR will Impact HR Data & Analytics

This article by Arnold Birkhoff on the Analytics in HR blog builds on the finding from the Insight222 research referenced in the preceding article. Birkhoff argues that this already high figure is set to deteriorate further if companies don’t get their act together in time of the EU’s enhanced privacy legislation –the General Data Protection Regulation, which comes into force in May 2018. Birkhoff then provides perhaps the best explanation I have read yet on GDPR from a HR context and how people analytics leaders can ready themselves and their organisations for this new legislation.

"Privacy is hot. 81% of people analytics projects are jeopardised by ethics and privacy concerns. This number will only increase if companies do not comply with EU GDPR"

Arnold Birkhoff

8. Stephen Turban, Laura Freeman & Ben Waber - A Study Used Sensors to Show That Men and Women Are Treated Differently at Work

Josh Bersin’s article describes how ONA coupled with people analytics is helping firms to gain insights into what drives productivity, performance and collaboration within their businesses. This next two articles and the three presented at #18 all provide examples of ONA. First up, this piece in HBR by Ben Waber et al documents an experiment that investigated whether gender differences in behaviour drive gender differences in outcomes at one multinational organisation. The results, which combined anonymised data from emails and Humanyze sociometric badges, indicated that bias rather than differences in behaviour explained the differences in male and female promotion rates. These are not only powerful findings that demonstrate the value of people analytics, but they also highlight the fundamental challenge facing most organisations of the need to reduce bias.  

Companies need to approach gender inequality as they would any business problem: with hard data

9. Greg Newman - Retain or let go? The data that you need to react correctly when an employee resigns

As Greg Newman highlights in this fascinating article, the Saratoga Institute advises that the average cost to business of employee turnover is 12% of pre-tax income and that for some firms this figure rises to 40%. So why, when an employee announces their intention to resign, are so many decisions on whether to retain the employee or let them go made on gut and opinion? Newman suggests that prioritising social capital data over traditional static human capital data provides a much better basis for an informed decision. He then goes on to illustrate through network analysis (see examples in Figure 6 below) how this can provide insights on the employee’s leadership potential, network size, relationship strength (internal and external) and impact as well as the network disruption that would be caused should s/he leave the organisation.

Figure 6: Rosalee is central to a large internal network, these are the people that she is influencing, leading, working, collaborating and innovating with (Source: Greg Newman)

10. Steven Prokesch feat. Cade Massey, John Hausknecht, Paul Davies & James Gallman – Reinventing Talent Management

As this cover article from HBR states, GE has transformed its business under the tenure of Jeff Immelt with 50% of its 300,000 employees having been with the company for less than five years. People analytics and algorithms have been central to helping this new talent assimilate and thrive with former head of people analytics and planning James Gallman explaining that the matching technology “can take a person and match him or her to something else: online or conventional educational programs, another person, or a job.” The article then goes on to outline how analytics is enabling the employee lifecycle in areas such as career development and succession, training, high potentials, retention, networking and even in supporting cultural change.    

“For many firms, talent is their most important asset—and historically, judgment around managing talent has been mostly intuitive and biased. There’s no panacea, but as analytics progresses, it offers a chance to make more rigorous those intuitive methods and to de-bias some of that judgment.”

Cade Massey

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Interlude

Before we continue with numbers 11-20, a quick interlude. Those who tuned in last time will have seen that I featured the hiQ Labs vs. LinkedIn legal battle. At the time, the former had just won what we now know was the first battle over its right to use public data from LinkedIn (i.e. the data you and me are happy to be public) within its products that help customers predict and subsequently address employee skills gaps and flight risk.

Naturally I hope that the two parties, both of whom I have the utmost respect for, are able to come to a mutual agreement that suits both. However, it seems that the case will likely run and run all the way to the US Supreme Court.

The case has ramifications that go way beyond the world of people analytics and ultimately will define if public data on the Internet really is ‘public’ and who has the right to use and access it.

Moreover, the very survival of hiQ Labs is at stake as it faces a David vs. Goliath contest and crippling legal costs to continue its fight. As such, hiQ Labs has started a crowdjustice appeal to raise $100,000 towards its legal costs. If you’d like to find out more and/or contribute, please click here or on the image below. Whatever happens, I’ll continue covering the story here and how the twists and turns of the legal battle play out.  

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11. Alexis Fink - The Missing Link: Why Some Analytics Projects Struggle to Get Traction and How You Can Do Better

This is both an honest and insightful piece by Alexis Fink, who has previously published a number of excellent articles in concert with Alec Levenson. Here, Alexis describes her realisation that there are four rather than three areas of expertise required for successful analytics projects highlighting ‘influencing’ alongside expertise in content, data and analytics. As Alexis explains as a scientist, this was tough for her to swallow, as good results should speak for themselves! Influencing means working with stakeholders to select the right projects at the outset right through to identifying actions from the insights that are feasible, effective and that will be endorsed. An invaluable read. 

"The missing link in getting results with analytics projects is not in the quality of the analytics projects themselves – the missing link is influencing expertise"

Alexis Fink

12. Asbj?rn Bloch Jensen & Marco H?pfl - How to Bridge the Gap Between People Analytics and Decision-Making

This article distils the findings of a master thesis on how to bridge the gap between people analytics and decision-making, which as the authors correctly identify is a significant challenge for many practitioners. The advice offered is centred on the need for more effective collaboration between people analytics teams and HRBPs, which is illustrated below in Figure 7. The further commentary offered in the article provides in my view a sensible starting point for organisations seeking to enthuse, equip and enable their HRBPs from an analytics perspective.

Implementation of people analytics is realised through collaboration. HRBPs have a key role as they are the link between HR and the business

Asbj?rn Bloch Jensen & Marco H?pfl

Figure 7: Steps required to bridge the gap between analytics and decision-making (Source: Asbj?rn Bloch Jensen & Marco H?pfl)

13. Jonathan Ferrar – Data Storytelling: Know your audience

The second entry on this collection for Jonathan Ferrar, who has been somewhat of a prolific writer over the last few months. This article focuses on storytelling – a critical but often scarce skill when it comes to people analytics. Too many projects fail because they are not communicated in a way that resonates with their intended audience. Jonathan emphasises the need to tailor your message depending on the analytics expertise of your audience (see Figure 8 below), and provides a host of other invaluable tips to improve your storytelling skills.

Figure 8: Four essential audience categories for analytics storytelling (Source: The Power of People by Nigel Guenole, Jonathan Ferrar and Sheri Feinzig)

14. Laura Stevens - Three basic conditions for employee experience success using data and people analytics

There has been a surge of interest in employee experience as organisations seek to apply the success of their customer experience programs to their workforce. In this piece, Laura Stevens describes the three elements she believes are required to understand, track and improve the employee experience. These are i) a continuous listening strategy, ii) cross-functional data sharing, and iii) investing in analytical skills or strategic partnerships, which are all included in Figure 9 below.

Figure 9: The critical components of an Employee Experience program (Source: iNostix by Deloitte)

15. Nigel Guenole, Sheri Feinzig, David Green and Haiyan Zhang – HR analytics readiness: How does Europe compare to the rest of the world? | David Green – Is HR in Europe ready for analytics? | Michael Carty - HR is unready to meet workforce analytics demand

Whilst demand from the business for workforce data and analytics is high and CHROs are increasingly supportive of this initiative, HR functions – particularly in Europe – are lagging behind. This was the headline finding of the UNLEASH / IBM Smarter Workforce Institute research I presented recently at HR Tech World in Amsterdam (see Slideshare below). A link to the white paper is provided above, along with articles by Michael Carty and me, which provide commentary on the research findings.

16. Raja Sengupta & Sunil Meharia - HR Analytics & Statistics: An Introduction

I expect that this article will prove to be very popular as Raja Sengupta and Sunil Meharia demystify statistics by answering 19 questions typically asked by practitioners just about to embark on their analytics journeys. As the authors opine, without grasping the fundamentals of statistics you cannot capitalise on the huge potential of people analytics. File under mandatory reading, and take a look also at Figure 10 below, which the authors use to highlight the risks associated with statistics if not applied properly. 

Grasping the fundamentals of statistics is critical for your success. Without it, you cannot capitalize on the huge potential data science offers to HR

Figure 10: A rough guide to spotting bad science (Source: Compound Interest 2015)

17. Paul van der Laken, Zsuzsa Bakk, Vasileios Giagkoulas, Linda van Leeuwen and Esther Bongenaar - Expanding the methodological toolbox of HRM researchers: The added value of latent bathtub models and optimal matching analysis

Continuing the statistics theme, this entry is definitely one for the technically and statistically minded. The article sees three members of Shell’s rightly revered HR Analytics team (Esther, Vasileios and Linda) collaborating with academia (Paul and Zsuzsa) to make the case for two statistical methods rarely used in the HR analytics space. The paper explains the virtues of latent bathtub models (see Figure 11), and optimal matching analysis, and it is a fascinating read – even for this untrained eye!

Figure 11: A bathtub model of the mediating effect of employee engagement in the relationship between leadership training and team performance (Source: Wiley)

18. Michael L. Tushman, Anna Kahn, Mary Elizabeth Porray & Andy Binns - Email and Calendar Data Are Helping Firms Understand How Employees Work | Aditya Hariharan - Identifying Potential Network Disruption and what it means for an organization | Philip Arkcoll - Improving Team Productivity with ONA

Continuing the ONA theme from earlier, these three articles describe how the technique is being used by organisations. First, Tushman et al describe how EY is analysing email and calendar data to help clients predict the likelihood of retaining key talent following an acquisition and how they can subsequently develop strategies to maximise retention. Then Aditya Hariharan’s excellent piece examines how ONA can help organisations identify and mitigate network disruption. Lastly, Philip Arkcoll focuses on how ONA can be used to improve team productivity. These are three superb articles.

Figure 12: Diagram comparing time spent on collaboration between team members inside a team with collaboration between the team and other parts of an organization (Source: Philip Arcoll, Worklytics)

19. Michael Schrage - What Happens to Mental Health at Work When Our Devices Know How We Feel? | Geof Wheelwright - IoT-linked wearables will help workers stay safe | Marissa Lang - Employers can collect reams of worker data through electronic tracking | Tom Cassauwers – Doctors swear to ‘do no harm.’ Why don’t data scientists?

There has been an explosion of interest in how wearable technologies and sensors can be used in the workplace with the debate centred on the need to balance ethics/privacy with employee/organisational benefit. The first three articles all touch on the possibilities and perils these technologies offer. Michael Schrage’s excellent piece focuses on how sensors can be used to measure mental health in the workplace. Next Geof Wheelwright reveals how sensory technology from SmartCap Technologies helps detect ‘microsleeps’ in truck drivers and other operators of heavy machinery. Then, Marissa Lang’s article contains an interesting view from Ben Waber that more regulation is needed in this burgeoning area. Given some of the examples of technology that Lang’s article exposes, I think he is right. Finally, Tom Cassauwers (featuring some sage views from Charles Givre, Sabina Leonelli and Jacob Metcalf) ponders whether data science needs its equivalent of the Hippocratic oath.

"Sooner, not later, your smartphone will not only be capable of serving as your shrink — it may also serve as your leadership coach, acting both as Sigmund Freud and Peter Drucker"

Michael Schrage

“Collecting (employee behavior) data is not difficult. Understanding it is very difficult. And as more and more players get in this space, eventually someone is going to do something wrong, and we’ll have reactive regulation, rather than the kind meant to prevent that bad behavior in the first place.”

Ben Waber

"We hear all the time about how data is the new oil, but I would argue that if mishandled, data can also be the new TNT"

Charles Givre

20. Francesca Gino - The Rise of Behavioral Economics and Its Influence on Organizations | Lori C. Bieda - Leading Analytics Teams in Changing Times | Richard Kelly, Subu Narayanan, and Mark Patel - Seven rules for spinning analytics straw into golden results | Eric Garton - The Case for Investing More in People

Finally, some analytics-themed inspiration from outside the HR realm: Francesca Gino writes on the rise of behavioural economics and its increasing influence on organisations (see earlier example from Prasad Setty on how Google’s people analytics team is applying this). Then Lori C. Bieda outlines common challenges facing many analytics teams (not just in HR) of i) demand (for analytics) outstripping supply (of analytical talent), ii) organisational immaturity, and iii) the promise of technology vs. the reality of data, and how leaders can navigate the path of disillusionment these challenges can bring. Next the McKinsey article (Richard Kelly et al) outlines seven rules manufacturers should follow with regards to IoT-enabled analytics, much of which has resonance for HR including rule #2 ‘capture the right data, not just more data’ and rule #4 ‘focus on outcomes not technology.’ Lastly, Eric Garton argues that our chronic underinvestment in people has led to our systemic problem with productivity. People analytics can help our leaders identify, measure and quantify the optimal areas of investment in human capital, so this seems like a good place to sign off until next time.

"There are many opportunities to “nudge” people’s behaviour by making subtle changes to the context in which they make decisions"

Francesca Gino

"The growing use of analytics in organizations is powered by analytics teams, which are often underfunded, misunderstood, and starved for talent"

Lori C. Bieda

"We could improve productivity if we stopped systematically underinvesting in human capital"

Eric Garton

BONUS: PICK OF THE PODCASTS - Laurie Bassi & Max Blumberg - Debunking the Myths of Employee Engagement | Jacob Morgan & Susan Steele – How IBM is thinking about the future of HR | Jacob Morgan & Cathy O’Neil – Why relying on data can cause more harm than good | Jacob Morgan & Seth Stephens-Davidowitz - Sex, Politics, Big Data and What Our Search History Reveals About Who We Really Are | Stela Lupushor, Antony Ebelle-Ebanda & David Green – The role of people analytics in ONA | Al Adamsen & Manish Goel – People Analytics & The Future of Work Podcast

If podcasts are your thing then the last two months has seen a flood of excellent people data related gems. Here’s six of them. First up, my fellow co-chairs at the upcoming People Analytics Forum (book here and use DG25 for a 25% discount), Max Blumberg and Laurie Bassi bust a number of myths regarding engagement. Then Jacob Morgan services up three riveting episodes of the Future of Work podcast with Susan Steele, Cathy O’Neil and Seth Stephens-Davidowitz. Finally and returning to the topic of ONA, I joined Stela Lupushor and Antony Ebelle-Ebanda for TrustSphere’s webinar on The Role of People Analytics in ONA, and if this interests you also check out TrustSphere CEO Manish Goel’s discussion with Al Adamsen on the same subject.

That's all for this time...

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ABOUT THE AUTHOR

David is a respected influencer, writer and speaker on people analytics, data-driven HR and the future of work. He was recognised as Best Writer at the 2015 HR Tech Writers’ Awards, and was awarded one of ten LinkedIn Power Profiles for HR in 2016. David’s role as Global Director, People Analytics Solutions at IBM enables him to help clients apply an analytical, insight led and business outcome focused approach to their talent strategies and people decisions.

I am chairing, speaking and/or attending the following conferences between now and April 2018. If you are going to one of these conferences and would like to meet up with me or you would like to book me to speak at a conference, please contact me via LinkedIn:

• Corporate Research Forum, Deploying HR Analytics, London (9 Nov) - Pre-event breakfast
• People Analytics for business, Helsinki (21 Nov)
• The HR Congress, Brussels (28 Nov)
• People Analytics Forum, London (29-30 Nov)
• People Analytics & Future of Work, San Francisco (1-2 Feb)
• Employee Experience Bootcamp, Lisbon (8 Feb)
• HR Tech World, London (20-21 Mar)
• Wharton People Analytics Conference, Philadelphia (22-23 Mar)
• People Analytics World, London (11-12 Apr)

Connect with David on LinkedIn, follow him on Twitter and read his blogs here on LinkedIn and also on HR Tech World and ERE.

Keywords: HR, Human Resources, HR Analytics, People Analytics, Talent, Recruiting, Hiring, Talent Acquisition, Talent Management, HR Metrics, Cost Per Hire, Workforce Analytics, Talent Analytics, Data Driven HR, Employee Engagement, Performance Management, Future of Work, Quality of Hire, Evidence based HR, HR Open Source, #HROS, Cognitive HR, Cognitive Computing, IBM, HR Technology, Flight Risk, Predictive Analytics,