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Plethora of Poems



We accept the love we think we deserve Stephen Chbosky, The Perks of Being a Wallflower

Please read the quote and then write a few sentences describing the quote and what it means.


Write a few sentences about what it means and then give a real life example


Please add two or three words that have these word parts. Do not add the definition. Just add two or three words that have the word parts. Please see the example.


magn/a/i= great
magnify, magnificent and magnate

man/i/u= hand
manual, maneuver and manuscript
dict= speak
domin= master
don= give


Intro to Synthesis


Please answer these questions before you view the presentation.

1. What is knowledge?
2. What is the difference between synthesis and summary?

If you are not sure, that is okay just make your best guess. No need to google it. We will be discussing this.

Intro to Synthesis

During please answer these questions from the presentation

1. What is the difference between summary and synthesis?
2. What does it mean to synthesize?
3. What is the goal of a synthesis?


Please complete the Edpuzzle for
Synthesizing Information available in your Google Classroom

After you view the presentation and completing the Edpuzzle

1. What is a summary?
2. What is synthesizing?
3. What is the main difference between summarizing and synthesizing?
4. What should your education focus on?


None this week


Intro to SEPA

After viewing the presentation please complete SEPA. You can add your work right here. Please use the presentation created by your classmates available in the vocabulary link in our blackboard course.

Vocabulary # 8



This week you are reading 3 poems. Do not fear they are very short. We could imagine poems as very very short stories.


Please be familiar with these words.
1. Bereft
2. Dole
3. Hyacinths
4. Abash
5. Barren
6. Essence





Take notes after each poem. You can add the notes here.


What connects these poems. Write one paragraph connecting these poems.


Browder and Turner

Write a synthesis essay. There should be one intro paragraph. Then write one or two paragraphs about Kalief Browder and one or two two paragraphs about Brock Turner.Then add a synthesis paragraph for both persons.
Please use one in-text citation for each person and then add a Work Cited page. Please use Word to complete these. This can be a separate file, 400-600 words and MLA format. This is not a summary of different articles. It is a synthesis. Your essay should be a separate file.

Writers Workshop

Quotes Practice

This week we are working on Quotes. You can find the assignment in google classroom.


Intro to Quick Write

Please use 3 vocabulary words from chapters 6, 7 and 8. Please highlight the words


Not sure if you ever watched the Rugrats but if you did you will enjoy this weeks QW. If you have never watched the Rugrats, I highly recommend the cartoon. It is clever and sweet. This poem is from Chukies mom to Chuckie. Please read the short intro and then the poem. After reading the poem, tell me what you think. Then tell me about your favorite poem. It can be something really simple or something more complicated. Then write one paragraph telling me why you picked that poem.
Please add a link for the poem. I would like to read it.

Link to poem


Intro to Little Bit of Everything

This week you received 4 LBOE. Pick the one you found most interesting. Write one paragraph about the event oIntro to Quick Writer person. Then write one paragraph with your opinion.



Please write a few sentences about this week’s assignments and connect them to your life.

Favorite words of the week.

Pick a quote or sentence that stood out from this week’s assignments.


discussion 5

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

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 worlds 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




People analytics: driving business
performance with people data

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

This report was written by Edward Houghton, Senior Research Adviser: Human Capital
and Governance, and Melanie Green, Research Associate, at the CIPD.

Wed 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.

Wed 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.

Its 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

People analytics: driving business performance with people data

3 Foreword from Workday

2 Foreword from Workday
Following Workdays 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 Workdays
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 dont. 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 Unions 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 organisations 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, were seeing
organisations shift towards the general trend of keeping their people data securely
within their HR system. Having faced the rigours of GDPR, its 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.

People analytics: driving business performance with people data


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.


Predictive analytics: for
example intention to leave,
predicted sick days per

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.


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.


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 Mkel 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 Mkel 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


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 CIPDs 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


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


Health and


Diversity and




Global HR Global finance Global other

0 20 40 60 80 100









There is not enough time and resources to
implement eective 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 (%)


28 29

39 38 37


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


5 Purpose of the study: key

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?

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

SE Asia

HR 389 21

Finance 420 10

Other profession 306 11

Asia total 1,115 29


HR 182 5

Finance 158 4

Other profession 303 8

MENA total 643 17


HR 131 3

Finance 169 4

Other profession 106 3

US total 406 11

Global total 3,852

Purpose of the study: key questions

People analytics: driving business performance with people data


6 Findings
This section is split into six sub-sections, each exploring key findings from the survey:

1 people data at the organisation level: strategy, culture and performance
2 professional perspectives on people data: how are different professions using data?
3 HR capability: is HR ready to deliver value through people analytics?
4 types of people data in use
5 business value and risk: is people analytics adding value?
6 future trends: how is the people analytics practice evolving?

1 People data at the organisation level: strategy, culture and performance

Key findings
People analytics culture is positively associated with overall business performance.
We found that 65% of those who work in a strong people analytics culture said that
their business performance was strong when compared with competitors, but only
32% of those in weak analytics cultures report strong business performance.

People analytics culture is positively associated with business and HR strategy,
suggesting that improving people strategy influences people analytics culture. Data
shows that people analytics culture varies across geographies, with only 36% of UK
respondents believing they have a strong people analytics culture, compared with 37%
in the US, 52% in MENA and 54% in SE Asia.

HR professionals who have a negative perception of their organisations HR strategy
are significantly less likely to use people data in their practice, suggesting that
strategic alignment and engagement by HR professionals is important for improving
the use of people data.

HR professionals who view HR strategy and business strategy as integrated in
their organisations are significantly more likely to use people data in their practice,
suggesting that improving the link between business strategy and HR strategy may
help to improve the use of people data by HR professionals.

To understand the overall impact of people analytics in organisations we investigated
the relationship between three important concepts: overall organisational culture, people
analytics culture, and overall business performance. We use these concepts to appreciate at
the strategic level how people analytics is conducted and the outcomes being generated.

Understanding overall organisational culture
We asked all respondents to describe their overarching organisational culture. We defined
four culture types:

Family feel: an organisation with a family feel, held together by loyalty and tradition.
Leaders are viewed as mentors or parents.

Formalised: a formalised and structured place to work, where procedures govern what
people do and hold people together.

Dynamic: a dynamic, entrepreneurial, and creative place to work. People stick their
necks out and take risks.


People analytics: driving business performance with people data


Results focused: a result-oriented organisation whose major concern is with getting
the job done. People are competitive and goal-oriented, and are held together by an
emphasis on winning.

Of the 3,852 global respondents, 19% believed their organisation had a family feel culture,
47% had a formalised culture, 8% had a dynamic culture, and 27% had a results-focused
culture. This data is used later to explore if and how business culture influences the type
and impact of people analytics practice that is undertaken in organisations.

Defining people analytics culture
Many organisations build people analytics capability for the purpo


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