Excellence in People Analytics
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Excellence in People Analytics

How to Use Workforce Data to Create Business Value

Jonathan Ferrar, David Green

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eBook - ePub

Excellence in People Analytics

How to Use Workforce Data to Create Business Value

Jonathan Ferrar, David Green

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Effectively and ethically leveraging people data to deliver real business value is what sets the best HR leaders and teams apart. Excellence in People Analytics provides business and human resources leaders with everything they need to know about creating value from people analytics. Written by two leading experts in the field, this practical guide outlines how to create sustainable business value with people analytics and develop a data-driven culture in HR. Most importantly, it allows HR professionals and business executives to translate their data into tangible actions to improve business performance. while navigating the rapidly evolving world of work. Full of practical tools and advice assembled around the Insight222 Nine Dimensions in People AnalyticsÂź model, this book demonstrates how to use people data to increase profits, improve staff retention and workplace productivity as well as develop individual employee experience. Featuring case studies from leading companies including Microsoft, HSBC, Syngenta, Capital One, Novartis, Bosch, Uber, Santander Brasil and American Eagle OutfittersÂź, Excellence in People Analytics is essential reading for all HR professionals needing to unlock the potential in their people data and gain competitive advantage

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The case for people analytics


People analytics is not about HR. People analytics is about the business. It is about delivering commercial value, value to employees and the workforce, and value to managers and executives so they can make people-related decisions based on facts. At its best, it delivers impact to the board of directors, investors and broader society too.
Delivering people analytics requires solid foundations, intelligent use of resources and a passion for business value. Sequential maturity models are no longer valid – any business can use people analytics to immediately deliver value if they focus on a number of dimensions in parallel.
People analytics as a discipline is expanding in importance in HR and across the business world, generally. There are more people with analytical skills in HR than ever before, and the depth of expertise is growing annually according to LinkedIn (2020). Senior leaders recognize that a data-driven approach to their people function is now more important than ever. Human resources leaders who invest in people analytics are finding new ways to help their companies compete in the marketplace.
The following chapter captures these messages in detail and makes a case for business leaders to invest in people analytics.


The business value of people analytics

People analytics contributes hundreds of millions of dollars to the top and bottom lines of organizations.
At IBM, former CEO Ginni Rometty stated that the company saved ‘nearly $300 million in retention cost in its predictive attrition program’ (Rosenbaum, 2019). Using people analytics, it identified those people most at risk of leaving and prescribed actions in advance to help managers make the right decisions.
Google saved approximately $400 million by reducing new hires’ onboarding time from nine months to six months (McAleer, 2018). It created email nudges to help new hires succeed in their roles by regularly highlighting the behaviours of top performers (Bock, 2019).
It’s not just technology companies that are benefitting from people analytics; organizations of all kinds are reaping the financial reward of this work. For example, shoe retailer Clarks found that a single percentage point in employee engagement is worth an additional 0.4 per cent of improved business performance (Levenson and Pillans, 2017). Put in the context of Clarks’ 2019 Annual Report (C&J Clark Limited, 2019), this calculates as almost £60 million per percentage point of employee engagement.
And the opportunity is much greater.
In a 2019 study, Accenture concluded that US $3.1 trillion of untapped future revenue growth lay in people data – specifically, the responsible use of that data combined with the employee trust garnered – for the 6,000 largest publicly listed global companies in its research sample (Shook, Knickrehm and Sage-Gavin, 2019). This is an average of $500 million per company that can be generated from people analytics.
Various other studies have found that companies with advanced capabilities in people analytics tend to have higher performance across a range of financial metrics. These include 30 per cent higher stock prices over three years (Bersin by Deloitte, 2013), 79 per cent higher return on equity (Sierra-Cedar, 2014), 96 per cent higher revenues over three years (Chakrabarti, 2017) and 56 per cent higher profit margins (Martin, 2018) than their counterparts.
These are all powerful reasons for the growing enthusiasm for creating excellence in people analytics.

What is people analytics?

The definition of people analytics has been published on numerous occasions. At its core, people analytics is:
Figure 0.1 People analytics consists of multiple activities and outcomes
An illustration shows the analytical activities and analytical outcomes.
Figure 0.1 details
An arrow from analytical activities points to analytical outcomes. The analytical activities are dashboards and reporting, KPIs and metrics, predictive analytics and advanced analytics and AI. The analytical outcomes are workforce experiences, analytics culture, business performance and societal benefits.
As Figure 0.1 shows, the definition of people analytics we use in this book consists of a collection of activities:
  • Dashboards and reporting – sharing information and insights from people data in reports and dashboards often in a formal, standardized and repeatable fashion.
  • Key performance indicators (KPIs) and metrics – measuring the most important metrics for the enterprise and those of value to C-suite executives, boards and investors.
  • Predictive analytics – using statistical techniques and other mathematical analysis techniques to predict, forecast and plan scenarios for the future.
  • Advanced analytics and artificial intelligence (AI) – applying very advanced techniques and technology to provide insights and recommendations, using, for example, machine learning, AI, deep learning and cognitive computing.
And outcomes:
  • Workforce experiences – such as employee experiences, the democratization of data to managers, insights delivered to executives and overall workforce performance improvement. Workforce experiences also includes the advanced outcomes provided by analytics that improve the human-centred experience of work. These outcomes are discussed further in Chapter 7 (Workforce Experiences) and the Epilogue.
  • Analytics culture – including building awareness of people analytics in HR, developing analytical skills for HR professionals and scaling people analytics to all managers in a company. See Chapter 9 (Culture) for more detail.
  • Business performance – composed of financial impact, managing risk and compliance, market share growth, and informing and influencing the business strategy. These are all discussed in Chapter 8 (Business Outcomes). ‘Business performance’ also includes topics such as the CEO skills conundrum and investor demands, which are described in the Epilogue.
  • Societal value – typically more advanced outcomes of people analytics, such as inclusion, equality and gender pay. These are discussed in the Epilogue.
In general, leading people analytics teams deliver significant value to t...

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