CIPD Getting started with people analytics

Guide
November 2018
Getting started with
people analytics:
a practitioners’ guide

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 150,000
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.

Getting started with people analytics: a practitioners’ guide
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1
Guide
Getting started with people
analytics: a practitioners’ guide
Contents
Introduction2
What is people analytics? 3
How is HR using people analytics? 7
Finding focus 9
Executing analysis 17
Building capability 22
Conclusion24
Glossary of terms 24
References25
About the authors 25
Acknowledgements
This guide was written by Sam Hill and Ed Houghton.
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2 Introduction
1 Introduction
People analytics continues to be seen as an emerging area of HR and people
management, even though it has been around for some time – over 20 years. However,
there is still a perception that HR is not yet making the most of people data.
Given that HR is often criticised for making gut decisions, there needs to be a more
concerted effort on the part of HR to invest the time and resources into building
people analytics capability. The growth of evidence-based practice in HR is a positive
step towards making more effective decisions. Data is one of four types of evidence
recognised in evidence-based practice (the others being professional judgement, the
views of stakeholders, and scientific insights). Therefore, the ability of HR to use people
data is vital if the profession is to be more evidence-based.
The CIPD report People Analytics: Driving business performance with people data
highlighted that globally skills and confidence in conducting even basic levels of
analytics is low. HR practitioners therefore need support if they’re to make the most of
people data.
Data and evidence is a key part of the CIPD’s strategy for developing the HR profession.
The CIPD is investing in building practitioner capability as part of its drive to improve the
use of people data in decision-making in organisations. The CIPD’s new Profession Map
was developed with three key concepts in mind: being principles-led, evidence-based
and outcomes-driven.
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3 What is people analytics?
People analytics also forms part of the CIPD’s agenda to improve transparency on
workforce practices, and encourage firms to report on how they manage and develop the
value of their human capital. This stems from a need to see more evidence reported by
firms to meet the changing needs of regulators, investors and future employees.
This guide will cover the following key concepts:
• Getting started: While many HR practitioners fear data, it’s easy to get started with
people analytics and create real value. There are key steps that any HR practitioner
can follow, no matter what technology they’re using, to start to improve their analytics
practice. This guide focuses on those steps.
• Using systems effectively: HR practitioners have the opportunity to take the lead in
making the most of the people data that is now often available through the technologies
and systems that support and deliver HR practices. They often have large amounts of
data that are not being used effectively. This guide will help them to sort out how to use
this data effectively, and what needs to be put in place to make a sustainable and high-
impact analytics practice.
• Becoming more evidence-based: People analytics is a fundamental part of evidence-
based practice. For HR to become more evidence-based, it needs to improve the use of
people data when informing or advising on decision-making. Without people analytics,
HR will struggle to be seen as an evidence-based profession that is able to deliver
sustainable outcomes for its stakeholders.
• Building trust and engagement with data: People data can help to improve trust and
transparency when used appropriately in organisations. HR practitioners should look
to make the most of people data to share with the workforce the effectiveness of
people management and HR practice, as well as evaluate good and bad practice, for the
purpose of improving outcomes for employees.
Scope
From the outset it’s important to clear up any confusion around the terminology applied to
this discipline.
This report, for example, promotes the term ‘people analytics’. Is this the same as
‘workforce analytics’ or ‘HR analytics’? Well, yes and no.
In practice the terms are interchangeable; however, it is important to approach the
discipline with the appropriate mindset. If we wish to maintain credibility with, and add
value to, the business we support, we must think beyond the HR function, its traditional
processes, and the data typically held on HR information systems.
We must consider how the actions of the workforce may positively drive business metrics,
and consequently contribute to the success of the organisation.
We should also look outside of the organisation at the trends that will, for example,
influence the optimal size and shape of our workforce in the future, and the challenges we
may face in sourcing and developing that workforce.
The key message here is: describe the discipline in a way that makes sense to you and your
stakeholders, but adopt a holistic view in respect of scope (see Figure 1).
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Prescriptive
5
Sum of
expected future
labour earnings
Adjustments
for time spent
at SSE
Discount factor
Economic
value of human
capital
x x =
Predictive
4
Operational
1
Descriptive
2
Diagnostic
3
People analytics
Workforce analytics
Breadth
Limited
scope
People analytics Adding value through insight
Workforce reporting Providing information
Limitless
scope
Depth
Source: www.workforcedimensions.co.uk
HR analytics
Figure 2: Five levels of reporting and analytics
Figure 3: SSE steps to calculating human capital value (SSE 2015)
Figure 1: Scope of people analytics
Beyond scope, a recent evidence-based review of decades of academic research into HR
analytics 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 can be described with this definition, but
with recognition of the broader scope and potential impact of the practice.
Reporting versus analytics
Often reporting and analytics are used to describe similar or the same processes. They
are in fact distinct but related concepts:
Reporting is process-based, and descriptive. The core proposition is to provide
snapshots of current workforce composition, and highlight the past trends of key
metrics. A good example of reporting practice is the use of people data dashboards
which include key performance indicators (KPIs) of important workforce data.
Analytics is typically project-based, often examining the root cause of a workforce issue,
and strives to provide advice that will mitigate against associated risk. Or it is used to
measure the success of a particular initiative, and to provide advice on optimisation.
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Reporting focuses on the past and provides information; analytics is forward-thinking
and delivers insight that influences decision-making.
The transition from reporting to analytics can be broken down into five levels of service
provision (see Figure 2).
Although the aim should be to progressively focus resources on level 3–5 outputs, it
should be recognised that the foundations remain important, and a mature, balanced
reporting and analytics proposition will continue to encompass and deliver against the
entire spectrum.
Prescriptive
5
Sum of
expected future
labour earnings
Adjustments
for time spent
at SSE
Discount factor
Economic
value of human
capital
x x =
Predictive
4
Operational
1
Descriptive
2
Diagnostic
3
Workforce analytics
Breadth
Limited
scope
Depth
HR analytics
1 Operational: raw, unstructured data, typically presented as a list. An example
would be a list of staff members, with each row representing a characteristic of the
employee, such as age, start date, location, salary and gender.
2 Descriptive: typically represented in tabular or graphical form, perhaps presenting
a snapshot of the workforce’s composition, or tracking a critical metric through time
(that is, what happened).
3 Diagnostic: typically the output from a piece of root-cause analysis, the purpose of
which was to determine why something has happened. For example, an unwanted
increase in employee turnover (that is, why it happened).
4 Predictive: typically taking the output from diagnostic analysis, integrating other
environmental factors, and projecting the future direction of critical metrics or KPIs
(that is, what will happen next?).
5 Prescriptive: working with stakeholders to determine intervention strategies that will
minimise risk or maximise opportunity; and measuring the success of these plans
(what we need to do).
People analytics and human capital: quantifying the value of the workforce
People analytics is often used by organisations to understand the value of its workforce,
sometimes known as its human capital. Data is often captured that is used to describe
the value and quality of human capital, and whether or not it is being used effectively to
generate positive outcomes for the business.
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The CIPD’s Human Capital Analytics and Reporting: Exploring theory and evidence (2017)
report provides the following definition:
‘A broad definition of human capital is that it is the
knowledge, skills and abilities of the workforce. There
are a number of perspectives of human capital, from the
economic, finance and human resource management
disciplines.
‘Human capital can be considered to exist and be
measured at both the individual level (for example formal
qualifications) and at the collective level (for example
measures of performance using technical skills).
‘Social capital considers the value of relationships in
networks (for example within and between teams of
individuals, value of collective action) and is important to
consider in highly networked and social work environments.
It includes the shared norms and values that facilitate team
or group co-operation.’
Reporting human capital: demonstrating the value of investing in people
Organisations are under increasing pressure to demonstrate how they manage and
develop their workforce. Such information is increasingly featuring in corporate
annual reports. People analytics is the process by which organisations can measure
their workforce, and report it to their key stakeholders, such as investors, regulators
and customers.
Leading UK organisations such as SSE have developed human capital reports using
people data and economic information from national data sets. Their publicly
available report details key information about their workforce, including an
estimated human capital value for each employee of £173,000 and a total company
human capital value of £3.4 billion (SSE 2015).
Prescriptive
5
Sum of
expected future
labour earnings
Adjustments
for time spent
at SSE
Discount factor
Economic
value of human
capital
x x =
Predictive
4
Operational
1
Descriptive
2
Diagnostic
3
People analytics
Workforce analytics
Breadth
Limited
scope
Limitless
scope
Depth
HR analytics
Figure 1: Scope of people analytics
What is people analytics?
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How is HR using people
analytics?
In section 2 we established that people analytics is the discipline that aims to establish the
contribution that the workforce makes to business success, and then provide insight that
will maximise this contribution.
If HR can successfully introduce and embed a value-add people analytics proposition,
they will increasingly be seen as a strategic partner, which will support transition from a
traditional perception of a service provider to that of a business enabler.
However, even with this opportunity, the adoption of people analytics has been surprisingly
slow despite the value it can potentially bring.
Adoption of people analytics
As the recent (2018) People Analytics: Driving business performance with people data
survey conducted by the CIPD in association with Workday reveals, people analytics is far
from being business as usual:
• Just over half (54%) of global respondents had access to people data and analytics.
• Two-fifths (39%) had no access to people data for decision-making purposes.
• Just half (52%) of HR practitioners stated that their organisation uses people data to
tackle business problems.
However, when people analytics is used, it is adding demonstrable value to organisations:
• 75% of HR practitioners globally who are using people data are using it to tackle
workforce performance and productivity issues.
• 65% of those who said they work in an organisation with a strong people analytics
culture said that their business performance was strong when compared with other
competitors, but only 32% of those in organisations with a weak analytics culture
reported strong business performance.
• Using people data was shown to predict the effectiveness of tackling key organisational
challenges, such as workforce performance and productivity, showing that using people
data leads to good business outcomes.
So why are these numbers not more encouraging?
Based on interaction with CIPD members, it is not a lack of interest or motivation on the
part of HR practitioners; rather, it’s not knowing where to start, in particular how to identify
investigations that will add genuine value.
Adding value
As the CIPD’s Human Capital Analytics and Reporting: Exploring theory and evidence (2017)
synthesis report reflects:
‘These concepts have been around for some time, but modern
people professionals have not adequately adopted a language
which conveys their meaning.
‘This is particularly true of human capital, which for many
professionals is a divisive and inhumane term.
How is HR using people analytics?
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‘The people profession should look to adopt a language that
conveys a positive notion of human capital, describing the
importance of knowledge, skills and capabilities to personal
growth, investment in skills from both organisations and
individuals, and the importance of human connectivity in
social capital terms.’
So, how can we isolate those value-add projects?
Let’s first determine what we mean by ‘value-add’.
Workforce Dimensions, a people analytics consultancy practice, highlight three checkpoints
that should be considered before initiating any people analytics investigation:
• Will it be insightful?
• Will it be relevant?
• Will it be actionable?
Figure 4: Value-add people analytics
Figure 5: The employee lifecycle1
Insightful
Telling your audience something
they didn’t already know
Actionable
Which will realistically trigger
a meaningful intervention
Relevant About something that matters
Recruitment
Retention
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Typical organisational KPIs
One of the most frequently asked questions from HR practitioners concerns the KPIs
and metrics that are commonly used across other organisations, and by inference,
those that they themselves should consider using.
At organisational level, the KPIs in the eyes of the CEO or CFO may be revenue per
employee. It is an effective way of illustrating the productivity and output of the workforce.
The calculation can be adapted for different employee groups, but the basic
calculation remains the same:
Revenue per full-time employee (£/n) =
total business revenue for the year (£)
average number of full-time employees (n)
Employee number can be substituted for other key measures, such as part-time
employees, or total employee hours worked.
How is HR using people analytics?
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For not-for-profit organisations, revenue may be substituted by a measure of cost saving,
service delivery or cost-efficiency.
Outside of these common indicators, metrics should be selected based on the critical
questions that matter to your own organisation. This context is a vital driver, so it is
impossible to be prescriptive.
However, Table 1 suggests metrics that should be at the forefront of our minds when
answering an arbitrary selection of value-add questions.
Table 1: Example indicators/metrics
Question Suggested metrics
Why are there high levels of manager
dissatisfaction?
• Manager span of control
• Leadership programme attendance
Why is there a variance in customer
satifaction levels across similar departments?
• Tenure in staff role
• Number of product training days
Wiil we struggle to retain high-performing
employees?
• Pay benchmarked against market
•
Time since last promotion or development
opportunity
What is the likelihood of attracting
appropriately skilled talent?
• Complexity of commute
• Agile working options
For illustrative purposes only, suggested metrics are indicative only and do not represent an exhaustive list
4
Finding focus
There is an increasing demand, not just from our HR colleagues, but also from our business
customers, for value-add, decision-driving people insight. However, that same audience
is not entirely confident of HR’s ability to deliver this proposition. The only way to attract
that confidence is to consistently deliver meaningful insight to build a positive reputation
and become trusted advisers.
To start this journey, first and foremost, we must probe and examine the right areas; we
must adopt a question-based mindset.
A question-based mindset
Possessing a question-based mindset means careful consideration of the viewpoint of
the customer and providing answers to the questions that they should be asking about
workforce issues, people processes and the contribution that the workforce makes to
organisational success.
We say ‘should be asking’ because, in reality, in many cases, the audience won’t know –
they will not be aware of the ‘art of the possible’.
They may have only ever seen ‘descriptive reporting’, labelled as ‘analytics’ – and with this
lack of awareness, they’ll often default to asking for more of the same, and more quickly.
Immediately efficiency, rather than effectiveness, becomes the measure of success.
This approach will rarely bring value, and will not support an aspiration to be seen as a
strategic HR function.
Finding focus
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We should consider carefully whether the question being asked will provide information
only, or whether it has the potential to deliver insight. Again, a balanced proposition
will encompass both, but genuine value is more likely to be created where focus is
concentrated on insight.
We must present a proposition to customers that offers a series of potentially insight-
generating questions – we can then work in partnership with them to refine and prioritise
the proposition; we must move to consultation and away from pure service provision. In
many ways, being a good analyst of people data means being a good researcher.
Effect and non-effect: two types of questions for people analytics
People analytics questions tend to take two forms: those which are based on linking
concepts (effect), and those which are more descriptive in nature (non-effect).
Reporting questions are typically non-effect, while people analytics questions are
often effect. Below are some examples:
Non-effect questions:
• What is the sickness/absence rate for apprentices at my organisation?
• How satisfied are employees who work in the manufacturing department?
Effect questions:
• Does our health and safety training save the organisation money?
• Does our learning and development programme reduce employees’ intention to leave?
• Which well-being initiatives are improving employee well-being the most?
Before we consider how to determine what those value-add questions may be, we need
to recognise that ‘one size does not fit all’ in respect of our customers, and to ensure
relevance we must segment our audience.
Audience segmentation
Audience segments, and how they are labelled and prioritised, will differ from organisation
to organisation; and certainly when we are considering external stakeholders, they will vary
depending on their strategic posture, for example private and listed companies, public or
not-for-profit entities.
For this reason it would be disingenuous to offer a definitive list. Examples are shown
below, along with suggestions as to the proposition (reporting or analytical) that may
interest various groups.
• Line managers – would probably require relevant, clearly defined and understood
measures and metrics, such as trended absence rates against target.
• HR business partners – may need enablement and empowerment to deliver meaningful
information and insight to their customers, perhaps in the form of on-demand
dashboards showcasing key people measures with support on interpretation.
• The HR leadership and other senior management – may need a projection on impact
and ROI of proposed major people programme.
• And if we were to look externally, current shareholders or potential investors could
be interested in evidence that the business is investing in the development of the
workforce, and this investment is aligned with corporate strategy.
It’s therefore important to consider the interests and information needs of each key
stakeholder, as their requirements are likely to be specific to their role and focus. Therefore,
a one-size-fits-all approach to sharing insights is unlikely to work.
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As HR practitioners we must identify these groups in the context of our organisation and
offer a differentiated proposition if we are to maintain their interest and embed people
analytics into our business.
Once we have identified these groups, we should build and maintain a relationship with
key stakeholders within them. We can then work in partnership to craft the appropriate
proposition, and determine the optimum channel of delivery.
Killer metric: Employee turnover
Employee turnover rate describes the rate at which employees are leaving the
organisation, and is measured over a defined period (usually annually). Sub-categories
of employee turnover rate include intended, for example because of poor performance,
retirement, restructuring, and unintended, for example new role outside of the
organisation, death, and so on. For a defined period, turnover rate can be calculated as:
Turnover rate (%) =
number of employee separations (n) x 100%
average number of employees (n)
Alignment with the employee lifecycle
We have now established that priority should be given to projects that will provide
output that will add value to the decision-making process in both the HR department and
the wider organisation. And that these projects will have their origin in ‘asking relevant
questions’ and will be different depending on audience segment.
Next we need to determine and craft those questions. Often these questions will be
easy to identify; however, sometimes we need a prompt to get the ball rolling – and the
employee lifecycle is a great place to start.
Because it tracks employees before, during and potentially after they exit the organisation,
the employee lifecycle offers a framework that allows us, in principle, to evaluate
investments in the attraction, recruitment, performance, development and retention of our
workforce (see Figure 5).
Figure 4: Value-add people analytics
Figure 5: The employee lifecycle1
Insightful
Telling your audience something
they didn’t already know
Actionable
Which will realistically trigger
a meaningful intervention
Relevant About something that matters
Recruitment
Retention
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Finding focus
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https://inside.6q.io/six-stages-to-success-with-the-employee-lifecycle/
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Alignment to the employee lifecycle has a number of additional benefits:
• Every HR practitioner understands the logic of an employee lifecycle.
• Each stage of the cycle is associated with a specific people process or event; therefore,
mapping to a particular audience segment should, in principle, be straightforward.
When crafting questions based on the employee lifecycle, it is important that our
investigations incorporate metrics that measure both cost and benefit, and efficiency and
effectiveness.
Example 1: The recruitment process
When appraising the success of the recruitment process, the staffing function will, quite
rightly, be keen to understand both the cost of, and time to, source hires – possibly also
segmenting and comparing the source, or talent pool, from which these new entrants
originated. This analysis focuses on efficiency.
However, would they (or should they) also be interested in tracking these new hires to
understand performance, progression and tenure in the organisation? This is a question
of quality, often termed the quality of hire.
This would surely be of value to both the staffing function and their business customers,
because assessing the effectiveness of the process in this way would inform the
future direction of resourcing strategy and improve the quality of talent entering the
organisation.
Example 2: Learning and development interventions
Similarly, with learning and development we should not aim only to quantify the direct
and indirect cost of a training programme, but also identify the metrics that measure
its impact. This could be a (before and after) measure of revenue, improved customer
feedback or any other quantification of additional value to the business.
Essentially this is the holistic mindset that will allow us to answer the questions that the
business should be asking about its human resource.
One obvious drawback with aligning our people analytics proposition with the employee
lifecycle is that although it captures much of the business-as-usual activity of the
workforce, it doesn’t look to the future needs of an organisation in terms of numbers and
types of people a business will need in, say, three to five years.
In recognition of this gap, next we’ll consider the concept of a holistic people analytics
strategy.
Killer metric: Succession coverage
Succession planning is a key element of workforce planning, particularly for senior
roles, or pivotal roles in the organisation that have significant risk attached when
vacant. Aside from the measure of a succession plan being in place, other key
measures to consider are:
Succession coverage (%) =
number of succession plans in place (n) x 100%
number of roles identified as requiring succession plan (n)
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A people analytics strategy
There are any number of barriers to introducing, embedding and maintaining a credible
people analytics proposition within an organisation. Those voiced most regularly are lack
of analytical skill, lack of time and lack of stakeholder support (or interest).
However, as Workforce Dimensions (2018) reflect:
‘A barrier that is rarely recognised but is all too apparent is a lack of
a People Analytics Strategy of any kind – let alone a coherent one.
‘A well-thought-out strategy will help an organisation focus on
what really matters to the business in respect of workforce actions,
behaviours and configuration.
‘Crucially, it will help HR to be seen as a strategic business enabler.’
So, what does a ‘people analytics strategy’ look like? Again, this will be different for each
organisation, and should be fluid as context and drivers change. However, the core inputs
for most organisations will remain constant and can be categorised as primary drivers and
secondary drivers (see Figure 6).
Primary drivers include:
• current and emerging workforce issues
• measuring the efficiency and effectiveness of HR processes and function
• changing workforce requirements based on business strategy.
Secondary drivers include:
• measuring and optimising the success of people programmes and initiatives
• challenging assumptions made about workforce actions
• the HR agenda.
Strategic
workforce
plan
The HR
agenda
HR process
and
function
Challenging
assumptions
People analytics
strategy
Business
strategy
People plan
Programmes
and
initiatives
Workforce
issues
Figure 6: Framework for a people analytics strategy
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Let’s consider those drivers in more detail.
Current and emerging workforce issues
This is the obvious and comfortable place to start. Most organisations will at some point
encounter problems such as increasing sickness absence rates, or a failure to retain staff.
However, passive reporting of these trends is not enough; we must move beyond the provision
of information to the generation of insight by adopting that question-based mindset.
For example:
• Is an increase in absence driven by increasing stress levels? If so, has there been a
specific change in the environment that may be a contributory factor?
• Are those employees who are separating from the organisation ‘regretted’ losses? If
so, is the root cause a lack of career progression or the aggressive pursuit of our talent
by a competitor?
If we can pose and then provide satisfactory answers to these types of question, we will
increase the probability of delivering genuine insight.
By doing this we will identify the metrics that need to be used and the data that need to
be collected.
Measuring the efficiency and effectiveness of HR processes and function
Earlier, when highlighting the advantages of aligning our people analytics with the
employee lifecycle, we identified two opportunities for measuring the success of HR
processes in respect of both efficiency and effectiveness, that is, the recruitment process
and the learning and development function.
Many other opportunities will become apparent as you work around the lifecycle and
consider your own organisational context.
One word of caution, though: don’t be drawn into analysing HR processes in isolation; look
for opportunities to ask questions that touch multiple aspects of the lifecycle.
For example:
• How do new hires view the onboarding process? Where there is negative feedback, how
does this impact on separations of these employees within the first six months of tenure
compared with those who offered positive feedback?
For an investigation of this type we would potentially need to create a data set that
doesn’t currently exist, that is, to survey new employees for their views on induction. We
should not be apprehensive about doing this, as long as the potential upside from the
investigation can be demonstrated.
Killer metric: Cost of vacancy
Vacant roles invariably cost the business and are of key interest to senior stakeholders.
Highlighting the revenue lost because of the vacant position is a simple way of
demonstrating the importance of having an efficient and effective recruitment process:
Cost of vacancy per day =
average total yearly revenue per employee (£)
number of working days per year (n)
This number can then be used to calculate the cost of vacancy over the period by
multiplying by the number of days in the period (for example x 30 days for a month).
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Changing workforce requirements based on business strategy
Although not as directly accessible as workforce issues and HR process concerns, from a
purist’s point of view, an organisation’s business strategy should be the primary driver of
a people analytics strategy, and there should be a logical and complementary link to the
people strategy (if this is separate from the business strategy).
The HR department must understand exactly what the organisation is trying to achieve
in the medium to long term, and determine what that is likely to dictate in terms of the
optimum size (numbers) and shape (skillsets) of the workforce at each interval of the
forecast period.
We can then quantify and qualify the gap between our current and ideal future workforce
profile, and craft the short-, medium- and long-term interventions required to close that gap.
The outcome of this exercise should be a key input to an organisation’s people strategy,
which will in turn inform multiple people initiatives including recruitment strategies,
learning and development interventions, succession plans, retention initiatives, job
redesign, the diversity agenda, and decisions on acquisitions and divestments.
Ultimately this should help prioritise our people analytics strategy.
Although linking business strategy to a people analytics strategy has clear benefits, to do
this effectively will require a formal strategic workforce planning process – this is complex,
time-consuming and will require specialist expertise and considerable involvement of
multiple business and HR stakeholders.
An explanation of this process does not fall within the remit of this guide. However, if the
process exists and is embedded within your organisation, it is strongly advised that you
leverage the output to inform your people analytics agenda.
If the process does not exist, as a minimum, each time you plan and prioritise projects,
consider whether the outputs have the potential to link workforce contribution to the
execution of business strategy.
Measuring and optimising the success of people programmes and initiatives
For most organisations, their greatest investment is in the attraction, employment and
development of their workforce.
Therefore, it is reasonable that senior HR and business stakeholders should expect to
understand whether those investments have paid off.
A real area of opportunity for HR is to measure the return on investment associated with
selected people programmes and initiatives.
These will of course vary by organisation, but a constant theme across most is the
efficiency and effectiveness of learning and development interventions – as referenced
earlier in this guide.
Another opportunity may be the value of a graduate scheme – that is, cost of attraction,
onboarding, employing and training against benefits in terms of performance and
longevity.
Organisations may also be interested in the value of an agile working policy, a new ideas
scheme or the introduction of a flexible benefits scheme.
Consider where significant investments are being made in people in your organisation and
look for opportunities to conduct a cost versus benefit analysis.
Finding focus
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Killer metric: Return on investment
Return on investment is a calculation of the benefits realised as a result of investing in
an HR programme. It is often used in learning and development to quantify the short-,
medium- and long-term impacts of a learning and development programme.
Return on investment (%) =
realised benefits (£) – costs (£) x 100%
costs (£)
Challenging assumptions made about workforce actions
Often assumptions are made upon which we make decisions about our workforce without
any attempt to establish whether these assumptions are actually correct.
Examples may include:
• An increase in commute distance will impact negatively on staff retention.
• Staff stability will result in higher profitability.
• Higher engagement drives higher productivity.
All three of these examples have something in common: they are entirely plausible – and
indeed they may be absolutely correct.
However, what if commute complexity or time were actually the issue, or staff training rather
than stability was the key factor in driving sales, or the level of engagement simply indicated
a happier workforce, not a more productive one, or in fact productivity drives engagement?
All of these scenarios are equally plausible. So the opportunity here is to treat the
assumption as a hypothesis and isolate the actual root cause.
There is equal value in proving the hypothesis true (that is, the assumption is correct)
and proving the hypothesis false (the assumption is incorrect). In either case, we will be
providing insight that will add value to the decision-making process.
The HR agenda
Finally, the HR agenda should be examined for any residual opportunities. This may seem
counterintuitive for an HR practitioner – surely this is where we should start?
However:
• To look at the HR agenda first will risk us skewing our people analytics proposition
towards HR processes and functions – remember, more value is generated for a wider
customer base if we analyse the link between the workforce and business success.
• In theory the HR agenda should be informed by the people strategy (whether this exists
formally or informally), which should be informed by business strategy – so there should
in principle already be a natural alignment.
Having put forward the case for a formal strategy to ensure our people analytics proposition
is aligned to the needs of the business, it is important to recognise that in reality people are
unpredictable, and organisations, and the context in which they operate, can change.
Consequently we may need to be flexible with our people analytics strategy and introduce
additions or amendments to our plan and conduct tactical investigations into emerging
risks and opportunities
The balance between ‘strategic’ and ‘tactical’ inputs will be determined by the level of
volatility in the organisation or within the environment in which the organisation operates;
but a 70:30 split is typical.
Finding focus
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5 Executing analysis
Having identified the various drivers for an appropriate and coherent people analytics
strategy and, in the process, crafted a series of value-add questions relevant to a variety
of audience groups, it’s now time to start executing this strategy by conducting associated
investigations.
Earlier in this guide we made the point that while workforce reporting tends to be
standardised and can therefore be underpinned by clearly specified and repeatable
processes, people analytics is made up of a series of one-off projects, which do not
necessarily have defined frameworks for us to reference.
However, there are elements of good practice we can apply to all projects.
How to approach an investigation
Below is an illustration of good practice, presented on a step-by-step basis, and applied
(for illustrative purposes) to a workforce issue that all organisations will face in some form,
at some point – employee turnover.
In addition to advantage of familiarity, focusing on employee turnover also allows us to
demonstrate the mindset as well as the skillset required to execute value-add people
analytics.
Step 1: Define the KPI
The KPI will be determined by the critical question we are asking (see ‘A question-based
mindset’ on page 9) and will most likely be a measure or metric that tracks progress from
where we are to where we want to be (our target).
For this illustration the metric will be a variant of the employee turnover rate.
In terms of the calculation of this metric, essentially this is the number of people
separating from a group (the ‘numerator’) divided by the number of people in that group
(the 'denominator'), then multiplied by 100 to present the output as a percentage:
Turnover rate (%) =
number of employee separations (n) x 100%
average number of employees (n)
This is typically measured over a rolling year.
For the number of people leaving, we should consider the purpose of our investigation:
what question are we attempting to answer?
Most likely we are seeking to understand unplanned, unwanted separations – in this case, it
would be senseless and misleading to include all leavers in our investigation.
We must, as a minimum, segment between those leaving voluntarily (resignations), those
who are subject to an organisational action (dismissal, redundancy, divestment, and so on),
and those exiting through a life event (predominantly retirement).
The denominator could be the start-of-period headcount (or full-time equivalent), or the
mean average headcount (or full-time equivalent) across the period. However, we have to
be consistent.
Executing analysis
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Step 2: Isolate critical segments
Next we need to isolate the segments of the separating employees that represent the
greatest ‘level of risk’ in terms of the efficiency and effectiveness of our operation, for
example:
• performance level
• criticality of job role
• time to backfill the vacated position (assuming the position is to be repopulated)
• impact on team and/or organisational productivity while the position is vacant
• lead time to competency for a replacement hire
• impact on the diversity balance.
Step 3: Hypothesise on root cause
We now have a focus for our investigation – a discrete group of people who have chosen
to leave our organisation who we would (for whatever reason) have preferred to have kept
in the business.
Logically the next challenge, the next step of our investigation, is to understand why and/
or when these people are most likely to leave our organisation.
It’s not enough to passively report the results from exit interviews or surveys; we must
take this output, and qualitative information (from, for example, pulse surveys of those still
in employment), and selected information from our information systems that will help us
predict future separations.
For example, we may analyse:
• tenure in role or overall length of organisational service
• impending attainment of qualifications or accreditations
• when share options can be exercised – and the value of these shares in the market
• patterns of lowering engagement and/or increasing casual absence
• stability, experience and quality of line management or peer group.
We may also consider the external environment – for example, is a competitor becoming
active in the talent market?
The considerations above are not exhaustive, nor will they be relevant for every
organisation, but they do illustrate the holistic approach required if we hope to genuinely
understand and provide insight in respect of employee turnover.
Step 4: Plan an intervention – and measure the impact
Once we have, and can articulate, this insight, we can then work in partnership with the
business we support to craft an appropriate intervention strategy.
And of course the involvement of the HR practitioner should not end here. Once the
intervention strategy has been implemented, we should determine whether these
measures have been successful, and how they can be optimised.
Although the focus of this example is employee turnover, the general principles that
underpin the approach – the identification of a critical question, crafting an appropriate
key performance indicator, identifying specific areas of focus, hypothesising on root
cause and drawing a conclusion – can be adapted and applied to the majority of common
workforce issues and HR process concerns.
The steps outlined should also allow us to find the evidence that proves (or indeed
disproves) our theories.
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The importance of evidence
It’s important that we take a pragmatic and auditable approach to evidence-gathering that
is wide-ranging and does not rely on HR ‘gut feel’ (although this intuition should not be
discounted, as it is often an important factor in forming a plausible hypothesis).
This is not traditionally an area of strength for the HR community.
As the CIPD’s (2017) Human Capital Analytics and Reporting: Exploring theory and evidence
report reflects:
‘The empirical evidence of the outcomes of HR analytics, both at
the organisation level and individual level, remains fairly scant.
‘Many academic publications adopt cross-sectional studies
which offer insights at a snapshot moment on practice,
without exploring if practice is resulting in specific outcomes.’
In recognition of this gap, the CIPD has introduced an evidence-based HR course that
explores the principles of evidence-based decision-making and focuses on the need to
make and argue for better decisions.
In summary, when considering a people analytics proposition, we must consider the
investigations that will add genuine value, and recognise, and accept, the burden of proof
upon us to support our work with evidence.
As Barends et al (2014) say, evidence-based practice is about making decisions through the
conscientious, explicit and judicious use of the best available evidence from multiple sources.
Figure 7 illustrates the key concepts underpinning evidence-based practice.
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Scientific literature
empirical studies
Stakeholders
values and concerns
Organisation
internal data
Practitioners
professional expertise
???
1 Asking
Translating a practical issue or problem
into an answerable question
2 Acquiring
Systematically searching for and
retrieving the evidence
3 Appraising
Critically judging the trustworthiness
and relevance of the evidence
4 Aggregating
Weighing and pulling together
the evidence
5 Applying
Incorporating the evidence into the
decision-making process
6 Assessing
Evaluating the outcome of the
decision taken
6
STEPS
Evidence-based practice
is about making decisions
through the conscientious,
explicit and judicious use of
the best available evidence
from multiple sources by:
To increase the likelihood of a favourable outcome
4
SOURCES
Figure 7: Evidence-based practice
The data quality conundrum
Shortfalls in data quality, completeness or accessibility should not prevent us from
presenting workforce reporting and executing people analytics.
The very process of reporting with questionable data shines a light on the process of
collection, and assuming we are asking the relevant questions that have the potential to
provide value-add insight, there will be a demand for people analytics that insists data
issues are addressed.
Of course where data isn’t trusted, we should provide a health warning, but within
reasonable margins: does it matter whether the resignation rate of a critical resource has
sharply increased to 15% or 17%? Regardless of the number, there is a problem that needs
to be analysed and addressed.
Executing analysis
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21
Our sensitivity to data quality will change according to the question being asked.
Therefore, transparency about quality and errors is an important part of people analytics.
We should report our findings along with our assessment of the data quality, and allow the
decision-maker to use their judgement when using the insights.
It’s important to accept (and educate those who use people data in our business) that the
majority of people data will never be perfect. As Figure 8 shows, there are multiple points
where data quality can lose integrity.
function
Challenging
assumptions
People analytics
strategy
Data
accuracy
Diminishing data integrity
Perfection
Subjectivity
Timing
Data
capture
Reporting
accuracy
100%
Programmes
and
initiatives
Figure 8: Data failure points
Subjectivity
Much of our data about people is based on opinion, and therefore a degree of subjectivity.
For example, a manager’s view of employee annual performance may be weighted towards
more recent contributions, or a customer’s perception of service provision may be skewed
by factors not in the control of the front-line employee.
Timing
Much of data is extracted from ‘live systems’, therefore the ‘truth’ today may be out of
date tomorrow.
Data capture
The process of data capture can present a significant risk, particularly when the process is
unclear, ignored or unmonitored; or key performance indicators measure efficiency (in the
form of speed) rather than effectiveness (in the form of quality).
Reporting accuracy
Finally, unless we have the structures, competencies and reconciliations that ensure our
reporting and analysis reflects the data held on source systems, we will lose credibility and
therefore the permission to present our analysis.
HR practitioners analysing people data must accept that a proportion of our information
is based on opinion, and is therefore variable, and the fluid nature of our systems and data
repositories will sometimes present slightly disconnected versions of the truth.
We must also highlight (not necessarily take ownership or responsibility for) data capture
process errors, while ensuring that the data we use is auditable back to its origins.
Executing analysis
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22 Building capability
New global research from the CIPD in association with Workday (2018) illustrates an
important relationship between the use of people data and strong business outcomes. It
shows that organisations with a strong people analytics culture are much more likely to
report strong business performance.
However, the survey also highlights that the wide-scale adoption of people analytics
practice is still low and that more needs to be done to improve skills and confidence in
the HR function, particularly in the UK, which is lagging behind other markets in both
capability and confidence.
CIPD Profession Map
In November 2018 the new CIPD Profession Map was launched. It includes significant
references to how analytics should be used to inform organisational decision-making.
It outlines what will be expected from the HR practitioner and people analytics specialist in
the following broad areas:
• the selection, integration and leverage of databases
• the creation of quantitative and qualitative data models using a range of techniques to
investigate people issues
• the application of analytical consulting to solve problems and shape solutions
• the use of data visualisation techniques to present the output from people analytics in a
meaningful and compelling way.
A range of core skills will commonly underpin delivery against these expectations; a
selection of these is outlined below.
Core skills
While maintaining that meaningful people analytics is the result of bespoke projects rather
than repeatable processes, and that these projects are driven by mindset ahead of skillset,
there are certain capabilities that are necessary requirements for the HR practitioner.
These are embedded in the CIPD’s learning portfolio, but deliverables can be summarised as:
• linking HR and business strategies
• assessing organisational readiness for analytics initiatives
• building the business case for analytics
• demonstrating the credibility and value added by HR
• using analytical insights to improve talent management processes
• defining the roles, capabilities, and structures required to maximise analytics
effectiveness.
To support these aims, the ability to execute the following skills is crucial:
• segmentation of data and metrics to highlight specific areas of concern or opportunity
• to examine the correlation, and level of causation, between two or more metrics
• the testing of a plausible hypothesis to establish the root cause of workforce issues or
people process failure
• the determination, separation and optimisation of the ROI from people programmes.
Communicating findings
In addition to the core skills above, ability to effectively and convincingly present insight
and conclusions is vital to any HR practitioner.
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Whether this is visually or verbally, the following considerations should be made:
• Have you clearly explained the workforce issue?
• Is the evidence you are presenting compelling and auditable?
• Why does the issue matter to the business, and to your specific audience?
• Have you quantified the level of risk or size of missed opportunity?
• What is the root cause of the issue – and what other factors have you considered and
discounted?
• What intervention do you recommend?
• What level and type of resources will be required to support this intervention?
• How and when will you measure success?
Although data will underpin any investigation and therefore presentation, you should lead
with the question, the insight and the conclusion.
However, supporting data should be held as an appendix and available to stakeholders on
request
Data science skills
In the event that HR practitioners choose to specialise and build a career in people
analytics, there is a developing case for them to acquire data science skills.
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms
and systems to extract knowledge and insights from data in various forms, both structured
and unstructured.
There is of course a huge reservoir of data about our former, current and future workforce,
held within and without our HR information systems that is available to be leveraged, so at
some point why wouldn’t we apply data science techniques?
Typically this encourages familiarisation with statistical software programs, of which there
are many available in the market, and often one or more of these is already used in your
organisation.
These software programs are often used to interrogate large data sets, recognise patterns and
predict future outcomes – for example, in the context of HR, to forecast future attrition rates.
It should be reinforced that it is unlikely that software alone will deliver value-add insight;
knowledge of the business and workforce behaviour is required to ask the right question.
However, it is undeniable that the skills of the data scientist, and the application of
statistical software within HR, will become a key enabler for a high-class people analytics
proposition.
Investing in technology
While statistical software packages are slowly being used by the ‘data-savvy’ HR
practitioner, a significant number of organisations have for a long time introduced
integrated platforms to stage people-related data to support workforce reporting and
people analytics.
These will typically incorporate embedded visualisation options, and be pre-configured
with a catalogue of people metrics, summary and trend reports, and HR or people
dashboards.
Again, there are many ‘enablement’ solutions available on the market. Our advice is to
first determine the level of reporting and analytics you aspire to in your business, and then
select the solution that best supports that proposition.
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24 Conclusion/Glossary of terms
7 Conclusion
The undeniable truth is that demand for quality and timely people information, and
above all insight, is accelerating. The stakeholders of HR now demand more information
and interpretation in easy-to-understand and actionable forms. It’s clear that as the HR
function looks to become more evidence-based and outcomes-driven, it must adapt its
skills and capabilities and invest in the systems and technologies that can make the most
of people data.
The HR function – everyone, not just analytics specialists – must deliver against this
demand or risk a loss of relevance in the eyes of the organisation they support.
We suggest that there are four key pillars or principles to effective people analytics
practice for HR practitioners to consider in their people analytics practice:
1 focused on solving a business issue (not an HR-only issue)
2 clearly defined with clear boundaries and research questions that need answering
3 started small and grown through testing and learning, evaluating impact
4 developed with key stakeholders’ needs in mind and they’re engaged throughout the
process. It also uses their perspectives to refine insights
These key principles are useful for any HR practitioner in any organisation to start to
make the most of their people data. Effective analytics doesn’t need sophisticated
statistical software and large data sets. Many issues are instead simple but require a clear
methodology and excellent engagement with stakeholders.
To make the most of people data, however, HR must first invest in itself and build its own
people data capability. Above all, HR analytics provides a way to unlock the profession’s
curiosity into how and why organisations work, and perhaps more crucially, why people
and their human capital are vital to the succession of organisations today.
8 Glossary of terms
Commonly used terms used throughout this guide are defined and differentiated as follows:
»»»»»»»»»»
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Scientific literature
empirical studies
Organisation
internal data
Data Measures Metrics KPIs ‘Analytic’
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Figure 7: Evidence-based practice
• Information in raw,
unorganised form
• A repository (or
repositories) from
which un-curated
information can
be drawn as and
when needed
• A measurement
taken for a specific
reason
• Absolute numbers,
for example
headcount at a
point of time, or a
count of joiners in
a defined period
• A measure or metric
promoted in stature
• Associated with
a target and
actively managed
with assigned
accountability.
Strategically aligned
• Drives a business
decision
• Characteristics
include: insightful,
predictive,
transformational,
often with joint
HR and business
ownership
• A calculation using
2 (or more) measures
• Typically presented
as a percentage or
a ratio; for example
resignation rate or
profit per FTE
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25 References/About the authors
9 References
BARENDS, E., ROUSSEAU, D. and BRINER, R. (2014) Evidence-based management: the
basic principles. Amsterdam: Center for Evidence Based Management. Available at: www.
cebma.org/wpcontent/ uploads/Evidence-BasedPracticeThe-Basic-Principles-vsDec-2015.
pdf [Accessed 8 November 2018].
CIPD. (2017) Human capital analytics and reporting: exploring theory and evidence. London:
Chartered Institute of Personnel and Development. Available at: www.cipd.co.uk/Images/
human-capital-analytics-and-reporting_tcm18-22281.pdf [Accessed 6 November 2018].
CIPD/WORKDAY. (2018) People analytics: driving business performance with data. London:
Chartered Institute of Personnel and Development. Available at: www.cipd.co.uk/knowledge/
strategy/analytics/people-data-driving-performance [Accessed 6 November 2018].
MARLER, J.H. and BOUDREAU, J.W. (2017) An evidence-based review of HR analytics.
International Journal of Human Resource Management. Vol 28, No 1. pp3–26.
SSE. (2015) Valuable people: understanding SSE’s human capital. Available at: http://sse.
com/media/306295/SSE-Human-Capital_Final_For-Web.pdf [Accessed 8 November 2018]
WORKFORCE DIMENSIONS. (2018) Building a people analytics strategy: development
programme. Workforce Dimensions.
10 About the authors
Sam Hill
Managing Consultant and Founder, Workforce Dimensions
Sam has 15 years’ experience in the field of people analytics and strategic workforce
planning as a practitioner, consultant and educator.
His primary expertise is to enable individuals and organisations to make accelerated
progress on the people analytics journey.
Sam is founder and managing consultant at Workforce Dimensions Limited, which partners
with organisations seeking to understand and maximise the contribution their people make
to business success.
He is a senior lecturer in people analytics at Middlesex University in the UK and a member
of the CIPD HR Analytics Advisory Panel.
Formerly, Sam was Head of Workforce Analytics and People Reporting at British Telecom.
Edward Houghton
Head of Research and Thought Leadership, CIPD
Edward Houghton is the CIPD’s Head of Research and Thought Leadership.
Since joining the Institute in 2013, he has been responsible for leading the organisation’s
human capital research work stream exploring various aspects of human capital
management, theory and practice – including the measurement and evaluation of the skills
and knowledge of the workforce, and its research exploring people analytics.
He has a particular interest in the role of human capital in driving economic productivity,
innovation and corporate social responsibility, and the value of human capital to corporate
governance.
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Chartered Institute of Personnel and Development
151 The Broadway London SW19 1JQ United Kingdom
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Registered as a charity in England and Wales (1079797)
Scotland (SC045154) and Ireland (20100827)
Issued: November 2018 Reference: 7787 © CIPD 2018

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