After reading People Analytics: Driving Business Performance with People DataDownload People Analytics: Driving Business Performance with People Data? As an HR Director in an MNE, identif
After reading “People Analytics: Driving Business Performance with People DataDownload People Analytics: Driving Business Performance with People Data”
As an HR Director in an MNE, identify two HR areas that People Analytics should be used. How? Why?
People analytics: driving business performance with people data
in association with
REPORT June 2018 Global research
Workday is a leading provider of enterprise cloud applications for finance and human resources. Founded in 2005, Workday delivers financial management, human capital management, and analytics applications designed for the world’s largest companies, educational institutions, and government agencies. Organizations ranging from medium-sized businesses to Fortune 50 enterprises have selected Workday.
The CIPD is the professional body for HR and people development. The not-for-profit organisation champions better work and working lives and has been setting the benchmark for excellence in people and organisation development for more than 100 years. It has more than 145,000 members across the world, provides thought leadership through independent research on the world of work, and offers professional training and accreditation for those working in HR and learning and development.
People analytics: driving business performance with people data
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Report
People analytics: driving business performance with people data
Contents Foreword from the CIPD 2
Foreword from Workday 3
Introduction 4
People analytics: enabling data-driven insights 5
Purpose of the study: key questions 9
Findings 10
Discussion 35
Recommendations 37
Conclusion 38
References 38
Appendix: Methodology notes 42
Endnotes 47
Acknowledgements This report was written by Edward Houghton, Senior Research Adviser: Human Capital and Governance, and Melanie Green, Research Associate, at the CIPD.
We’d like to thank Tasha Rathour, Ian Neale and the team at YouGov for their help in designing and running the survey instrument, as well as a number of experts for their insights and guidance, including Andy Charlwood, Max Blumberg, Eugene Burke and Andrew Marritt.
We’d also like to thank Workday for their ongoing interest in this important agenda. Without their support, this research would not have been possible.
People analytics: driving business performance with people data
2 Foreword from the CIPD
1 Foreword from the CIPD Data and technology are at the very forefront of innovation in HR as they are in so many parts of business today. As many organisations modernise and incorporate data and technology into their workforce practices, we see many new opportunities emerging to use people data to better understand who our workforce are, how they work, and what work means to them. Insights from people data offer the opportunity to change the way workforce decisions are made in organisations, from those driven by instinct or habit alone to those which are evidence-based and focused on developing long-term, positive outcomes. Even the most basic people data itself holds considerable potential value to organisations when used correctly, as we are seeing through the recent insights from gender pay gap reporting.
It’s not only inside organisations where people data has the potential to shape work for the better. External stakeholders such as investors, regulators and, increasingly, prospective employees are seeking people and organisational data to shape their understanding of organisations. Measurement and reporting of the workforce is enabling HR to uncover previously hidden aspects of work, and in some cases even shaping the relationship employees have with their organisations. From understanding the movement of pickers around fulfilment warehouses to spotting patterns in decisions of investment bankers on the trading floor, people data is more and more becoming part of how we gain insights to improve performance and productivity, but also the engagement and positive experience of work for people.
Integral to all of this is the concept of transparency. We know that openness and integrity are essential in maintaining trust, and we must be transparent in where and how we use data and information about people, even beyond the requirements of the GDPR regulations. But transparency externally on people and organisational data is increasingly expected, and is equally essential in building trust and confidence with all external organisational stakeholders.
However, there is still much further to go if organisations are to realise the true value of people data. The HR profession needs to progress more on investing and building their skills for understanding and using data, and there needs to be strong connection across businesses between people data and other organisational and business measures. Confidence and capability are still considerable barriers that prevent many HR professionals from using people data, and many organisations have fallen behind in the investment in systems and good bases of integrated data in the HR domain, relative to other areas of business. Technology including AI can help in connecting disparate data sources, and very importantly in helping to provide analysis, visualisation and insight.
Leading organisations are investing more in this space, and the interest in people analytics is accelerating. Sharing of experience, good practices, and what can be used in scalable cost-effective ways even in the smallest businesses is something we want to help with, and this insightful and extensive research with our partners at Workday helps to do that.
This report sheds light on opportunities globally for people analytics to further develop and embed into the HR profession. And, by looking across to our colleagues in other areas of business, we can see the exciting role people data can play in helping organisations to understand their people better and help them to realise their full potential.
Peter Cheese CEO, CIPD
People analytics: driving business performance with people data
3 Foreword from Workday
2 Foreword from Workday Following Workday’s successful sponsorship of the HR Outlook survey over the last two years, we are pleased to partner with the CIPD to produce the People Analytics: Driving business performance with people data report. The study aligns perfectly with Workday’s commitment to helping our customers improve the quality of their people decisions through better data and insights.
The potential benefits of analytics and data have been well documented, and as this research clearly shows, businesses exhibiting strong people analytics cultures achieve stronger business performance than those who don’t. Yet, while the business case for people analytics may be clear, the journey to get there has its roadblocks. Organisations face a multitude of challenges from the outset, from initially gathering the data, through to securing the information in accordance with a constantly evolving regulatory landscape, including the European Union’s General Data Protection Regulation (GDPR). From storing and managing data through to businesses ensuring they are granting data access only to the right people, there are numerous compliance challenges for businesses to contend with.
And then we have the great analytics skills debate. How do organisations find or train the right talent to lead the people analytics revolution? Data is only useful if it is interpreted effectively and in a fashion that business leaders can use. That means having the right analytical skills at the organisation’s disposal. Similarly, people analytics should be available in real time and on demand so that that they can be quickly used to make effective decisions.
Historically, there has been a degree of separation between transactional HR systems and reporting tools, with data copied across periodically from one to the other. Not only has this led to delays in using people data for decision-making, but it also raises questions about the accuracy and integrity of the data, given it has to be reintegrated before it is analysed. This data ages quickly and lives in a silo, disconnected from the business processes or strategies it should be used to support.
The emergence of the GDPR only intensifies the need for better management of HR data and indeed how people analytics should be delivered. At Workday, we’re seeing organisations shift towards the general trend of keeping their people data securely within their HR system. Having faced the rigours of GDPR, it’s important that businesses can meet future changes in regulatory compliance and that is best achieved by keeping employee data in one system. Organisations should use their HR system as the central point for people analytics, meaning they should import non-HR data back into the system rather than export HR information to external data lakes or tools.
This is evident with modern technology, including Workday, bringing together all people data into one place and securing it via a single security model. Bringing together reporting and analytics directly into the HR system means there is no need for separate reporting tools. We hope you find the research useful as you continue your people analytics journey and we look forward to hearing your thoughts.
Gonzalo Benedit President, EMEA and APJ, Workday
People analytics: driving business performance with people data
4 Introduction
3 Introduction In 2004 Lawler, Levenson and Boudreau published their paper HR Metrics and Analytics: Use and impact. Their important work signalled a changing world in which HR needed to modernise with a new focus on data. HR capability regarding workforce data (or ‘metrics’) and analytics was at that time considered to be lacking, and strategic HR management was not yet using data to drive business decisions. To overcome this Lawler and colleagues called for HR analytics to break free of the function to have impact, by integrating across the business. HR analytics was to become critical practice for all business functions, not just HR.
To put this provocation in context: in 2004 the world of work was in the middle of very radical change, enabled by technological innovation and drive by rapid improvements in computing capabilities. At the same time as HR was challenged to modernise, USB sticks became the established norm for data transfer. The language of ‘the internet of things’ had not yet been coined. Facebook was only a year old. At the beginning of the so-called data explosion in 2004, Lawler and colleagues were calling for HR to step up and lead the business towards using people data to drive business impacts. They were calling for something revolutionary to happen in the HR profession.
Fourteen years on, the workplace has in some ways radically changed, and in others stayed very much the same. While some technology- and knowledge-based organisations have taken to flexible working practices that make the most of the digital revolution, the ‘always on’ culture of technology-enabled work has blurred the boundary between work and personal life. The rapid increase in digitally connected devices means that very many data points now exist from which organisations can understand their workforce in more detail. Personal fitness technology collects heart-rate data and enables stress rates to be calculated. Warehouse pickers have their productivity measured and performance set in real time. Workplace data is now more available than ever to the business, and the HR profession is uniquely positioned to understand, through people data and insights, if and how the workforce is contributing to overall business performance.
Performance, however, is not the only outcome HR analytics can shine a light on: HR has access to measures above and beyond performance that connect to important workplace concepts: issues relating to corporate culture, well-being and elements of work related to job quality (for example engagement and satisfaction with work) are all to varying extents measureable, and today could be better understood through people analytics (Charlwood et al 2017). With rising debates on the quality of modern work (for example Taylor et al 2017, Gifford 2018), the data organisations collect about their workforce has increasing weight and importance for numerous internal and external stakeholders.
People analytics: driving business performance with people data
5 People analytics: enabling data-driven insights
HR analytics to people analytics: is there a difference? People analytics, HR analytics, human capital analytics are all terms used to describe the practice of applying analysis processes to workforce data to understand workforce-related business issues (for more information see Charlwood et al 2017, Houghton 2017). Very few papers have been published that provide an evidence- based view on the topic. For a definition of HR analytics, we build on the recent evidence-based review by Marler and Boudreau (2017), which describes the concept in the following way:
‘HR analytics consists of a number of processes, enabled by technology, that use descriptive, visual and statistical methods to interpret people data and
HR processes. These analytical processes are related to key ideas such as human capital, HR systems and processes, organisational performance, and
also consider external benchmarking data.’ Marler and Boudreau 2017
We therefore suggest that people analytics is a re-badging of the concept of HR analytics, and adopt this terminology in this report.
4 People analytics: enabling data-driven insights
People data can be recognised as a form of evidence, important for improving decision- making by professionals, including HR. Evidence-based practice recognises people data as part of ‘organisational internal data’, one of four forms of evidence alongside scientific literature, professional expertise, and stakeholder values and concerns (Barends et al 2014). Evidence-based practice ‘helps management to critically evaluate the validity, generalizability and applicability of evidence’ and makes a favourable outcome more likely (CEBMA 2018). It is important, therefore, that the HR profession understands people data if it is to become more evidence-based and improve decision-making, within the function and across its internal and external stakeholders (Houghton 2017).
People analytics practice is undertaken to provide executives, HR professionals and line managers with information needed for workforce support and HR analytics, for example employee performance feedback, impact of performance pay and alignment between workforce costs, business strategy and employee performance (Aral et al 2012). Research has shown that organisations are applying HR analytics to a broad array of workforce issues – moving beyond descriptive analytics and basic data reporting towards the realm of predictive analytics insights (Falletta 2014). Numerous systems and tools are available that provide a multitude of outputs, from basic reporting of ‘people metrics’ or ‘HR metrics’ and descriptive analytics through to predictive and prescriptive analytics (Bassi 2011, Evans 2012). Table 1 outlines these areas further.
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Table 1: Analytics types (adapted from Evans 2012)
Type Description Reference
Descriptive analytics: for example HR metrics, HR reporting, HR benchmarking, HR scorecard
Summarise data into meaningful charts and reports, often representing trends over time. Lagging data of historical insights.
Evans 2012
Predictive analytics: for example intention to leave, predicted sick days per period
Using historical data to predict future outcomes using data to model relationships between variables and then extrapolating these relationships forward in time. Predictive analytics helps to highlight relationships undetectable through standard descriptive methods. Able to offer trend analysis and forecasting. Combination of lagging data to creating leading indicators.
Evans 2012
Prescriptive analytics: for example combination of product turnover data, pricing strategy, and worker rota to design optimal opportunity for successful sales
Using optimisation to identify the best alternatives to minimise or maximise an objective. The mathematical and statistical techniques of predictive analytics can also be combined with optimisation to make decisions that take into account the uncertainty in the data.
Evans 2012
People analytics: hype or reality? For some, the lack of robust, high-quality studies of analytics practice and outcomes risk labelling people analytics as a well-established fad. While analytics practice may have value-adding capacity, if it is treated as a fad without a long-term investment perspective in mind, there is little impetus to invest in the analytics capabilities of people functions, nor invest in the development of the analytics value chain (Platanou and Mäkelä 2016, Angrave et al 2016). A lack of insight into the mechanics of analytics practice, poor bridging of the academic and practice gap, and a ‘journalistic approach’ to analytics outcomes have all been highlighted as reasons why, to date, HR analytics has risked becoming a fad that may not reach its value-adding potential (Rasmussen and Ulrich 2015).
That people analytics scholarship tends to, like other business analytics domains, not cross- reference analytics disciplines (for example process analytics and customer/user analytics) is a critique both of the body of knowledge around business analytics in its various guises, and the resulting utilisation of analytical capability within organisations (Holsapple et al 2014). It is perhaps for this reason that there is a push to centralise analytics functions and capability across all analytics domains, but this itself possesses risks, particularly with the interpretation and utilisation of the outcomes of analytics processes (for example the interpretation of workforce issues outside of an ethical frame).
That being said, researchers suggest that continued hype surrounding HR/people analytics is one of the reasons why there is the perception of widescale adoption of analytics practices and an implicit belief in the utility of analytics activities and outcomes, irrespective of any supporting published evidence (Platanou and Mäkelä 2016). There is little evidence of whether people analytics practice has become business-as-usual (BAU) in organisations. It is for these reasons that further research is needed to map differing perspectives on analytics practice, and to investigate how people analytics practice works, and the levels of adoption of these practices (Charlwood et al 2017). This research aims to help prompt further investigation into people analytics practice by highlighting the emerging trends, and surfacing the tensions between multiple perspectives on people analytics outcomes.
For some time experts have called for people analytics practice to become mainstream in the HR profession and targeted towards a broader set of HR issues – moving out of the
People analytics: enabling data-driven insights
People analytics: driving business performance with people data
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centres-of-excellence model, and instead analytics skills being widely adopted by more generalist HR professionals (Levenson 2011, Rasmussen and Ulrich 2015). These ideas have been picked up by the broader data science community and those who are operating with prescriptive analytics practice in mind; here outsourced models from the HR function are integrating people data alongside other forms of business information (BI): for example sales rates, product turnover. The combination of these data sets through technology suites offers an opportunity for people analytics to form part of the overall business data suite, and services are now offering this capability. This does, however, raise some important questions about the knowledge of non-HR analysts regarding people issues; in particular, if HR relinquishes people analytics practice to non-HR functions, how will HR capability change, and is it likely that key people risks, which need data to be understood fully, will be managed effectively?
Beyond HR: why people data matters to a broader set of stakeholders External stakeholders are increasingly interested in measures relating to workforce information. In the UK regulators such as the Financial Reporting Council and Financial Conduct Authority have increased their engagement on workforce issues, particularly corporate culture (FRC 2017, FCA 2018). CIPD research into the investor perspective has shown that there is interest in the environmental, social and governance (ESG) investment community towards workforce information (Houghton et al 2017). And work by the Pensions and Lifetime Savings Association on workforce disclosures, and the Shareaction-led Workforce Disclosure Initiative have continued to highlight the importance of workforce information to institutional investors and the ethical investment community (PLSA 2017, Shareaction 2018). For example, human capital disclosure has been shown to positively impact organisational performance, as measured by market-to-book ratio and return on assets – particularly in knowledge- based sectors (Lin et al 2012).
The link between functions for people data has been a subject of much research, particularly with the development of integrated data suites. The CIPD’s own research into the use of human capital data and the development of a cross-functional measurement framework highlighted the importance for developing shared perspectives and narratives regarding human capital information (Hesketh 2014, Houghton and Spence 2016).
People data also features increasingly in debates regarding ‘good work’. In the UK the Taylor Review of Modern Working Practices initiated a debate on the quality of modern work in the UK (Taylor et al 2017); and the findings of the first comprehensive measure of UK job quality by the CIPD highlighted that robust information on business action towards improving job quality is severely lacking (Gifford 2018). The UK job quality agenda is itself heavily reliant on the evidence of change coming from organisations, and it is the form of this evidence as ‘people data’ that shows why such information is now of considerable value to organisations and their stakeholders.
Understanding performance through people analytics: the role of people risk People analytics and people data are often cited as an important tool for understanding the role of people in creating value in organisations, particularly through the measuring and reporting of performance (McCracken et al 2017). Data regarding the workforce is a critical element that is required for illustrating the people and performance link. As such,
People analytics: enabling data-driven insights
People analytics: driving business performance with people data
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a number of models have been developed to illustrate how people analytics can help to uncover the relationship between data and outcomes.
In their work exploring human capital analytics, Boudreau and Cascio apply the LAMP model – logic, analytics, measures and process – to demonstrate why a ‘push’ approach to improving analytics uptake can influence performance. They argue that the receptive aspect of this relationship – ‘the pull’ element – further drives utilisation of analytics. They define five key conditions that need to be in place for pull to be effective (Boudreau and Cascio 2017):
1 receiving the analytics on time according to needs 2 attending to analytics: analytics outputs having utility and value to users 3 trusting analytics: users must believe the information they receive to apply it 4 focusing on pivotal decisions using analytics 5 understanding the implications of decisions and recognising the need to evidence using
human capital analytics.
HR outcomes are framed from a performance perspective for the vast majority of HR practices, with little attention paid to the risks associated with pursuing these performance outcomes (Becker and Smidt 2016). From a financial perspective, risk is associated with any decision to invest in human capital or the HRM practices which support it – and any investment in either of these elements carries with it uncertainty of financial return/return on investment (Bhattacharya and Wright 2005). In reaction to this some have gone so far as to argue the case for an HR audit capability, using data to assess both the performance of the function and the focus on quality outcomes (Wall and Wood 2005). However, this audit capability, driven by data from the HR function, would only be useful if it has both the quality of data required and an appropriate language to convey relationships of value creation and value capture. HR audit may be in practice difficult to achieve within the current HR function; nevertheless, a focus on measurement and reporting is critical, particularly if aspects of human capital risk are to be both understood and managed effectively.
The forthcoming CIPD report Hidden Figures: How workforce data is missing from corporate reports (McCracken et al 2018) measured the extent to which UK FTSE 100 firms report on human capital risk, or ‘people risk’. The work defined seven areas of people risk, which are outlined in Figure 1.
Figure 1: Seven dimensions of people risk (CIPD 2018)
Base: global HR (n=1,288); global finance (n=1,045); global other (n=1,519)
Net: agree Net: disagree
Talent management
Health and safety
Employee ethics
Diversity and equality
Employee relations
Business continuity
Reputational risk
Global HR Global finance Global other
0 20 40 60 80 100
20
10
40
30
60
50
80
70
There is not enough time and resources to implement e�ective HR strategy and operations
In respect of HR strategy and operation, this work place says what it means and means what it says
52 20
59 12
54 18
47 21
Base: global HR (n=1,288)
There is a strong link between HR strategy and business strategy
If human resources management had more power there would be better people management outcomes
Management and the HR function agree on the way employees should be managed
Figure 2: Strategy and human resources management (%)
Figure 4: The HR and finance data systems in my organisation are accessible through one system (%)
37
28 29
39 38 37
0
59 14
McCracken et al (2018) found that organisations are still developing their understanding of people risk reporting. A key issue highlighted was the extent to which FTSE 100 annual reports failed to adequately detail the type and content of the people risk issue, one potential barrier to this being the quality of internal people data and analytics. Therefore, people analytics could play an important role in enabling better people risk management and better people risk reporting by large organisations.
People analytics: enabling data-driven insights
People analytics: driving business performance with people data
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5 Purpose of the study: key questions
In this study we explore the following questions:
1 To what extent is people analytics practice driving organisation performance and delivering value to stakeholders, and how does it differ according to geographic, demographic and professional variables?
2 To what extent is the HR function capable when conducting people analytics using people data?
3 To what extent is workforce/human capital risk measured using people analytics?
Methodology The CIPD and Workday conducted an online cross-sectional survey of HR and non- HR professionals between February 2018 and April 2018. The sample included a mix of seniorities and professional backgrounds: 33% were HR professionals, 27% were finance professionals and 39% were from other professional groups, such as marketing, management or sales. Respondents were based in the UK and Ireland, Middle East and North Africa (MENA), South East Asia (SE Asia), and the US. In total, 3,852 individuals responded to the survey. The online survey was distributed by YouGov, which was topped up by convenience sampling across CIPD networks. The demographics for each region can be seen in Table 2.
Table 2 outlines the total proportion of respondents by region and function (percentages rounded to the nearest whole figure).
Table 2: Respondent demographics
Type Professional background N %
UK and Ireland
HR 586 15
Finance 298 8
Other profession 804 21
UK and Ireland total 1,688 44
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