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HR metrics and analytics in practice: 2016 survey

Author: Noelle Murphy

People analytics continues to grow in importance for HR and organisations as a whole, but practical problems persist in the accurate gathering and analysing of HR data.

About this survey report

This report covers key findings from the HR metrics and analytics 2016 survey and focuses on:

  • the benefits and problems with gathering and analysing data;
  • what data is gathered; and
  • how data is gathered.

XpertHR's benchmarking service has the full data on the questions from the survey, set out in four parts:

Our survey of 378 HR practitioners explores the quality of people data that they have access to and the main benefits and problems with the process of gathering data. While engagement with HR metrics and analytics among practitioners is high, our survey shows that there are issues translating people data into useful metrics.

Benefits of using HR metrics

Better-informed decisions within organisations, and HR specifically, are two of the main benefits of gathering and analysing people data, as quoted by our respondents (see table 1). These can be important justifications for securing investment in resources to gather and analyse HR metrics.

However, less than half (43%) feel that HR analytics have resulted in cost savings and nearly one in 10 (8%) feel that their organisations are at too early a stage in their use of HR metrics to determine any benefit. So, while engagement with HR metrics and analytics remains high - respondents quoted an average of around five benefits to their organisation from using people data - tangible returns on investment in this area are still developing.

XpertHR's survey on HR priorities for 2016 reports the growth in HR analytics, after it appeared as a priority for respondent organisations for the first time in the 14-year history of our research.

Table 1: Main benefits of using HR metrics

Benefit % of employers
Better-informed business decisions within the whole organisation 72.9
Allows HR to be more proactive, rather than reactive 72.4
Better-informed business decisions within HR 71.9
Helps to demonstrate the value of HR 58.1
Allows for more effective resource planning 53.6
Cost savings 43.0
Increased predictability of business/HR decisions 38.5
Improves employee engagement 37.4
Improves employee retention 30.0
None - too early to say 8.0
n = 377.
Source: XpertHR.

Problems with gathering and analysing HR metrics

The key practical issue that organisations experience when trying to gather and analyse people data is the quality of the data available. Three of the top five problems quoted by respondents concern difficulties in gathering data due to lack of, or problems with, system integration, poor systems, or a lack of resources (see table 2).

However, concerningly, more than eight in 10 (81.3%) quote issues around organisations being unsure about what they want to measure or what to do with data that is gathered. This underlines the importance of setting clear objectives and outcomes from the start of the HR metrics process. It also echoes the frustrations of HR professionals with the lack of resources being made available to engage with the process - almost half (47.1%) quoted this as a problem.

For more than two in five (44.4%) HR practitioners, the frustration lies in the fact that HR analytics are not yet seen as a priority within the organisation, which makes gaining commitment for sufficient resources and support for the HR analytics process difficult.

We can see further evidence of this in our findings on the quality of data gathered, which shows that, in three key people-data areas (absence, labour turnover and recruitment), around one in seven organisations have "some" or "good" data, but no use is made of it.

Respondents report an average of around five problems with gathering and analysing people data.

Table 2: Main problems with gathering and analysing HR metrics

Problem % of employers
Lack of system integration making gathering data difficult 61.2
Poor integration of systems to gather and analyse data 59.1
Lack of resources to gather data 47.1
Organisation unsure what they want to measure 45.5
HR analytics not a priority within the organisation 44.4
Unreliable data 40.9
Organisation unsure what to do with data gathered 35.8
Poor HR information systems (HRIS) in place to gather data 35.8
Lack of resources within the HR department 34.2
Poor engagement with line managers on HR analytics, resulting in inconsistent data 34.0
Lack of expertise/skills within the HR department 24.1
None - too early to say 4.5
n = 374.
Source: XpertHR.

Systems used to gather and analyse HR analytics

Respondents use an average of three different systems to gather and analyse data, which highlights one of the key issues HR experiences when trying to engage with people data. Namely, having all the data in one place, so as to produce clean, usable data that can be turned into usable metrics.

Table 3: Systems used to gather and analyse HR analytics

System % of employers
Excel 80.7
HR management systems/HRIS 53.2
Payroll systems 52.6
Time and attendance systems 30.2
Online survey systems 29.4
Business/finance systems 24.9
Talent management systems (including performance management and applicant tracking systems) 16.9
Other 11.1
None 4.0
n = 378.
Source: XpertHR.

HR data gathered and measured

Table 4 lists the types of data gathered by respondent organisations in order of use. Training and development is the area in which least employers gather data - this may be due to the self-service nature of such data, which remains with employees rather than being held centrally. However, it is of note that more than two in three (67.5%) respondents do not gather data on areas such as training budgets, which may point to the lack of training activity within organisations.

Our findings tell us that organisations are becoming more engaged with HR data and, while absence and staff turnover remain firmly at the top, respondents gather data in a median of six areas, while half gather between four and eight.

Table 4: HR data gathered and measured

Data % of employers
Absence 91.5
Staff turnover 82.8
Recruitment 69.6
Pay and benefits 61.9
Employee engagement 51.6
Performance appraisal results 49.7
Employee disputes (disciplinaries, grievances, number of tribunal cases) 42.9
Diversity and equality 34.4
Training and development (such as budgets, return on investment, development plans) 32.5
n = 378.
Source: XpertHR.

Quality of data gathered

We asked respondents to rate the quality of the data in existence within their organisation across three key areas:

  • absence;
  • labour turnover; and
  • recruitment.

Table 5 outlines the full results for the three areas. Around one in seven respondents have "some" or "good" data in absence (15.2%), labour turnover (13.8%), or recruitment (13.4%), but make no use of it at all. Despite time and resources being used to gather data in these areas, the data leads to nothing - not even measuring absence rates or labour turnover. Given the costs involved in uncontrolled or unmonitored absence rates and spiralling labour turnover, this is a lost opportunity to save costs and a waste of the resources that go into gathering the data in the first instance.

More than four in 10 organisations feel that they do not gather enough meaningful data in either absence (43.1%) or labour turnover (43.5%), while more than half (53.6%) feel this is the case for recruitment data.

When we look beyond these key areas, in more than two in five (42.6%) organisations, there is data in existence for training and development, such as budgets, return on investment and development plans, but this data is not measured. A similar proportion (40.7% and 40.5%) told us that their organisation gathered data on diversity and equality and on employee disputes (disciplinaries, grievances and number of tribunal cases) but that it is not measured.

Table 5: Quality and use of data collected

HR metric, % of employers
Absence Labour turnover Recruitment
Some data, used a lot in HR but not more widely with other business metrics 21.2 19.9 28.7
Some data, used a lot within the organisation with other business metrics 11.9 14.7 17.2
Some data, not used 10.8 10.9 11.9
Good data, used a lot in HR but not more widely with other business metrics 20.6 20.2 22.2
Good data, used a lot within the organisation with other business metrics 26.7 29.5 15.7
Good data, not used 4.4 2.9 1.5
Enough meaningful data gathered 56.9 56.5 46.4
n = 378.
Source: XpertHR.

Use of HR data

Table 6 outlines the main ways HR uses the data that has been gathered, across the three key areas of absence, labour turnover and recruitment.

We found that the median number of uses for HR data was six, the lower quartile four, upper quartile eight, and the average stood at six. This shows a relatively healthy level of engagement with the data.

People data is still primarily used to measure key rates such as staff turnover and absence. While this has to be the starting point for any effective analysis, the lack of progress in this area from our findings in 2015 chimes with the overall frustrations among HR practitioners with people data, namely ongoing issues with the data gathering, lack of expertise to identify what can be done with the data, and the lack of priority around resourcing interpretive and analysis work.

Table 6: Use of HR data

Use % of employers
Measure staff turnover rates 93.5
Measure absence rates 83.2
Monitor recruitment costs 73.7
Identify absence hotspots 70.0
Identify staff turnover hotspots 67.9
Demonstrate the value of the HR department to recruitment function 52.2
Benchmark staff turnover against other organisations 46.8
Set absence triggers 43.8
Monitor absence costs 35.0
Set absence targets 30.3
Monitor turnover costs 27.9
Benchmark recruitment against other organisations 26.7
Set staff turnover targets 22.4
n = 348.
Source: XpertHR.

Our research

This report is based on original research carried out online in March and April 2016. Responses were received from 378 HR practitioners working in organisations employing 912,030 people. The breakdown by economic sector is as follows:

  • 267 (71%) are in private-sector services;
  • 70 (18%) are in manufacturing and production; and
  • 41 (11%) are in the public sector.

Broken down by workforce size, the employers comprise:

  • 159 (42%) with between one and 249 employees;
  • 103 (27%) employing between 250 and 999; and
  • 116 (31%) with 1,000 or more.

The smallest organisation employs one person and the largest 140,000 people. The median number employed is 350 and the average 2,415.

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