Ethics & People Analytics

Dont-Forget-the-H-in-HR_David-Green.png

I believe ethics is the most critical ingredient in people analytics. Those working in the field simply cannot afford to get it wrong. The risk to employee trust and to the reputation of the burgeoning discipline of people analytics is too high.

‘Ethics, Trust and People Analytics’ is the title of my presentation, which will open the Smart Data breakout at UNLEASH in London tomorrow. It is also the subject of this article, which as well as including a copy of my slides (see Slideshare), also features recent research by the IBM Smarter Workforce Institute and Insight222.

ETHICS JEOPARDISES FOUR OUT OF EVERY FIVE PEOPLE ANALYTICS PROJECTS

Research in November 2017 from Insight222 found that 81% of HR people analytics leaders and practitioners reported that their people analytics projects were jeopardised by ethical or privacy concerns (Figure 1).

  Figure 1: 81% of people analytics projects are jeopardised by ethics and privacy concerns (Source:    Insight222   )

Figure 1: 81% of people analytics projects are jeopardised by ethics and privacy concerns (Source: Insight222)

 

WHY IS ETHICS SUCH A SIGNIFICANT CHALLENGE?

The challenge ethics presents to people analytics leaders is set to get harder, and not just in the short-term as companies seek to comply with the European Union’s General Data Protection Regulations (GDPR), which comes into effect in May 2018.

Whilst the requirement to comply with GDPR is undoubtedly high on the agenda for HR (the same Insight222 study found that 53% of companies had not even started getting ready for GDPR), a number of other factors are in play:

LEGISLATION & VALUES

People analytics teams have to navigate different rules and values with regards to data privacy and usage in the countries that they operate. In certain countries, particularly in Europe, people analytics leaders need to work with local HR teams to seek and receive agreement from workers councils and employee representative groups.

NEW TECHNOLOGIES & DATA SOURCES

Using traditional HR data in certain jurisdictions can be challenging enough for people analytics teams, but the situation becomes even more complex when emerging technologies and non-traditional data sources such as wearables, sensors, email and social media are taken into account. Indeed a survey by UNLEASH and the IBM Smarter Workforce Institute found that 84% of respondents believe HR urgently needs guidance on the fair use and privacy of new and emerging data sources in workforce analytics.

A recent example is the negative press surrounding the announcement that Amazon has been awarded patents to develop wireless wristbands for warehouse workers. A series of media outlets queued up to lambast Amazon, conjuring up images up Big Brother to support their argument that this represented a further erosion of worker rights. This prompted Amazon to counter that the wristbands will support employee wellbeing as well as improving productivity.

Vendors also have a responsibility here and it is refreshing to see CEOs of people analytics technology firms such as Ben Waber of Humanyze (check out Ben’s podcast with John Sumser) and Manish Goel of TrustSphere (listen to Manish speaking to Al Adamsen on the PAFOW podcast) playing a prominent and proactive role in the ethics debate.

TECHNOLOGY OUTPACES LEGISLATION & DESIRE

Even with the advent of legislation like GDPR, the law simply cannot keep up with the magnitude and increasing pace of technological advance. Figure 2, which is taken from Deloitte’s 2017 Global Human Capital Trends, provides a perfect illustration of the extent of the challenge. This is exacerbated by the fact that technology also outstrips desire. Employees increasingly expect a similar experience at work as they do as consumers in areas such as personalised recommendations and the ability to give and receive feedback. In contrast however, employees are typically less prepared to share the data that enables this ‘consumerisation’ with their employers than they do outside work with the likes of Facebook (although the recent revelations about Cambridge Analytica may change a few minds there.

  Figure 2: Technology outpaces legislation and desire (Source: 2017 Global Human Capital Trends Report, Deloitte University Press)

Figure 2: Technology outpaces legislation and desire (Source: 2017 Global Human Capital Trends Report, Deloitte University Press)

THE RISK OF GETTING IT WRONG

Judging what is acceptable and what is not presents a huge dilemma for HR professionals and people analytics teams. The challenge is as much moral as it is legal. People analytics is about people after all and the risk of getting it wrong and eroding employee trust, perhaps irreversibly, means that ethics needs to be front and centre of any people analytics initiative.

 

WHAT SHOULD HR DO IN THE ‘GREY AREAS’ NOT COVERED BY LEGISLATION?

What analytics teams in HR could and should do with people data are two entirely different questions. The reality is that we are at an inflexion point where the delta between what is possible with technology and what is covered by legislation is widening. As such, a nagging question for people analytics leaders is what to do in those situations – or ‘grey areas’ – not adequately covered by legislation.

To find out what companies can do to inform their decisions on how to use employee data, the IBM Smarter Workforce Institute surveyed more than 20,000 workers in 44 countries about their preferences regarding how data dilemmas are resolved in people analytics. The Institute clustered countries according to national preferences on how decisions regarding usage of workers’ data are made.

 

CONTEXT & CULTURE MATTER

The results show that within the grey areas, where legal precedent does not exist, or where data ownership is unclear, context and culture matter most. There are important differences between cultures that may impact employees’ receptiveness to having their personal data analysed for people analytics. Even when examining countries in the same continent, the Institute sometimes observed differing dominant ideologies.

The research discovered most countries have dominant ethical ideologies (with 77% falling into the Absolutist ‘I believe the rules are the rules’ type - see Figure 3 below). This infers companies and people analytics practitioners can look to the regions where their business operates to gain a better understanding of how employees might react to an initiative to collect and analyse a new source of people data.

  Figure 3: In the Grey Areas, Context and Culture Matter (Source: The Grey Area – Ethical Dilemmas In HR Analytics, IBM Smarter Workforce Institute)

Figure 3: In the Grey Areas, Context and Culture Matter (Source: The Grey Area – Ethical Dilemmas In HR Analytics, IBM Smarter Workforce Institute)

RECOMMENDATIONS FOR HR

I’m fortunate to spend much of my time working with leading experts and many of the most advanced teams in the people analytics space. Based on this knowledge and experience, Figure 4 provides some recommendations with regards to the use of people data in HR analytics.

  Figure 4: Recommendations on ethics in people analytics (Source: David Green, 2018)

Figure 4: Recommendations on ethics in people analytics (Source: David Green, 2018)

BE PREPARED

Steps to consider here include:

Partnering with legal and IT

To ensure that you are complying with the data privacy and security legislation of the countries you are operating in as well as company rules and regulations. For example, as Patrick Coolen writes here, no people analytics project at ABN AMRO starts without approval from the bank’s legal and compliance teams nor are any findings communicated without sign-off.

Establishing a Governance Council

To consider and prioritise potential projects is commonplace amongst the bulk of advanced people analytics teams. Ethics and privacy should be at the top of the list of items to debate by members of the council on whether to give the go-ahead to individual projects.

Publish a code of practice

To set out how you will handle employee data, which as Jonathan Ferrar suggests here is even better if you co-create the code with employees

Get ready for GDPR

Whilst ensuring compliance with the GDPR will undoubtedly cause HR and people analytics teams some pain the short-term, the legislation may provide significant benefit to the discipline in the medium- to long-term. Perhaps it’s easy for me to say this as I don’t have to implement it, but I believe that the GDPR is a good piece of legislation as it essentially forces companies to put the employee front and centre when it comes to the use of people data.

“We do not start any project without approval from legal and compliance. Furthermore we show legal our results before going to our business”
Patrick Coolen

Have an expert on your team

As Dawn Klinghoffer describes in this article make serious consideration to having a data privacy expert as part of the people analytics team (as Dawn has done at Microsoft). This is a trend I expect to see grow over the coming years.

BE OPEN

People analytics should not be a clandestine operation where employee data is collected and analysed with the insights and resultant decisions shared amongst the chosen few. Organisations should instead be open and transparent and provide clarity to employees as to what their data will be used for and how it will benefit them as well as the company. Employees should not only be able to opt in (or out), but also be empowered through being provided access to their own data. If the insights this data provides helps employees manage their careers, improve work-life balance and increase productivity this is a clear win-win for both the worker and the company.

Two examples of this approach are:

IBM

Social Pulse, IBM’s employee listening technology helps the organisation understand sentiment, detect problems and make a commitment to do something about them. A Case Study on Social Pulse and interview with Sadat Shami is included on page 12 of the previously referenced ‘The Grey Area: Ethical Dilemmas in HR Analytics’ white paper, and is also referred to by IBM’s CHRO Diane Gherson in this interview with Harvard Business Review. One notable example of the benefit to the employees of the technology came when an IBMer started an online petition about the company withdrawing permission for workers to use ride-sharing services like Uber. This led to a storm of chatter on the corporate intranet platform. Social Pulse detected the event quickly, and Diane Gherson was able to reverse the ban and communicate the decision to employees within 24 hours.

Microsoft

This article by Microsoft’s CHRO Kathleen Hogan describes how Microsoft is using analytics to empower employee decision-making by creating the ability for employees to own their data, and gain insights to help improve their engagement at work, and enhance their work/life balance.

BE AGILE

Whilst it may be easier to adopt a risk-free approach to projects, this is not really an option for most people analytics teams if it wants to create sustainable impact. An element of bravery coupled with a close relationship with their legal team as well as a focus on employee benefit is required. Where a project involves the use of emerging data sources, pilots are a sensible option. For example, when Cisco was creating its Talent Cloud (see this article by Jill Larsen), they started with a small pilot, sought feedback from participants, iterated, communicated widely and then expanded the employee groups involved. In this way, not only did Cisco in effect co-create the Talent Cloud with employees but they also built momentum amongst the wider workforce that the product was as beneficial to employees (to support career development) as it was to Cisco (to drive strategic workforce planning).

Another terrific initiative in the realm of ethics and people analytics I became aware of last year is being led by Insight222. The project sees member companies of Insight222’s The People Analytics Program working together to co-create an Ethics Charter. The problem statement Insight222 is helping clients (who include some of the most reputable brands and advanced people analytics teams in the world) solve is: “How might HR build trust that People Analytics work will benefit and not harm our employees, and still ensure business value and impact”. It’s a terrific initiative and one I will watch with interest. Figure 5 below provides a high-level view of the co-creation project. For more information, please get in touch with Ian Bailie.

   Figure 5   : Ethics Charter, The People Analytics Program (Source: Insight222)

Figure 5: Ethics Charter, The People Analytics Program (Source: Insight222)

BE ETHICAL

The topic of ethics is as contentious as it is complex, and will continue to provoke much debate. People analytics leaders will continually be faced with the dilemma of what they could do versus what they should do. Perhaps the best test is this: if you cannot articulate the benefit to the employee as to why their data should be collected and analysed, then the project simply shouldn’t be undertaken. There is a ‘H’ in HR after all.

REFERENCES

The following articles and research helped inform this article: Nigel Guenole, Jonathan Ferrar and Sheri Feinzig - The Power of People | IBM Smarter Workforce Institute - The Grey Area: Ethical Dilemmas in HR Analytics | Deloitte University Press - 2017 Global Human Capital Trends | Patrick Coolen – The 10 Golden Rules of People Analytics (Crowd version) | Jonathan Ferrar – Ethics & Privacy in Workforce Analytics | Andrew Marritt – People Analytics: What’s in it for the employees? | David Green & Dawn Klinghoffer – The HR Analytics Journey at Microsoft | Dawn Klinghoffer – A well-balanced People Analytics function | Kathleen Hogan - Empower your employees to leverage their own data | Harvard Business Review interview with Diane Gherson – Co-Creating the Employee Experience at IBM | Jill Larsen - How Cisco Is Getting to Know Each of Its 70,000 Employees | Al Adamsen – People Analytics 3.0 | Andy Spence - The Quantified Workplace: Technology Vs. Trust

ACKNOWLDEGEMENTS

Finally, a special thank you to Nigel Guenole, Sheri Feinzig, Haiyan Zhang and Louise Raisbeck of the IBM Smarter Workforce Institute; Marc Coleman, Peter Russell, Leah Narodetsky and the team at UNLEASH, and; Jonathan Ferrar, Ian Bailie, Al Adamsen and the team at Insight222.

This article was originally published on LinkedIn in March 2018 - see here.