RosslynDataTechnologies State of HR Analytics 2017 Report
2017 Report on the State of HR Analytics
Researched and produced by Rosslyn Data Technologies and Tucana to help HR professionals derive more value from data
www.rosslynanalytics.com
2017 Report on the State of HR Analytics
Table of Contents 2
Executive summary
3
Key Findings
4
Analysis of Research Findings
9
Survey questions
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1
2017 Report on the State of HR Analytics
9%
Only of senior executives have confidence in the quality of their HR data
Executive Summary In today’s competitive environment, successful companies need highly skilled, motivated and capable employees. However, to broaden the skills of their workers and prepare the ground for future challenges and opportunities, executives must have access to the right data at the right time to make timely decisions. To get a comprehensive overview of the data challenges facing organizations, Rosslyn Data Technologies and Tucana conducted a joint survey of more than 300 HR professionals. They were asked a wide range of questions on business priorities, opportunities and challenges. The findings outlined here give readers the insight to benchmark their organizations’ success with data analytics – without data and the tools to report and analyze information, decisionmakers are simply making assumptions. The results of the survey shine light on a few concerns HR teams are having with analytics. It’s a fact that to make business critical decisions, people need to have a single view of data. In practice, this involves extracting data from multiple sources and loading it into a single database. Yet, almost one in three of the executives we spoke to told us that the biggest challenge they face is fragmented data. Data quality is another huge issue facing HR professionals. Before data can be put to actionable use, thousands of records must be normalized and cleansed to remove duplicate and incorrect information. But three quarters of the executives we interviewed told us that their data was of poor quality and that they had major reservations about using it for reporting and analysis. To cap it all, one in five said that they did not have the technical skills in-house to the leverage the data they had. Another worrying finding emerged when we questioned survey participants about their use of taxonomies. Without a standard HR taxonomy, it is difficult to effectively organize and accurately analyse data, particularly if they have multiple business units in different countries. But almost two out of three people we interviewed told us that they did not have a standard taxonomy in place across their businesses. Out of those that did have a standard classification system, 36% are unable to make changes on the fly. In addition, a sizeable percentage told us that they had yet to standardize their HR processes to benefit from a single taxonomy. This, too, was a troubling finding – without standardized business processes and tools, it is much harder for decision-makers to analyze masses of data and glean valuable insights in a timely manner.
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2017 Report on the State of HR Analytics
Key Findings Our exclusive survey reveals that: →→ One in three businesses is grappling with the challenge of fragmented
data
→→ 20% of HR departments lack the skills to analyze and interrogate data →→ Almost three-quarters of HR professionals have average quality data,
but still use it to carry out analysis
→→ 68% of HR departments do not have a standard corporate-wide
taxonomy in place for effective reporting and analysis
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2017 Report on the State of HR Analytics
Analysis of Research Findings In March 2017, Rosslyn Data Technologies, in partnership with Tucana, carried out an exclusive survey of senior executives at 307 private and public sector organizations. The interviewees – which included department heads, senior managers, business partners and managing directors – where questioned extensively about their use of HR analytics. Corporate priorities The executives were first questioned about their business priorities for the year. Based on an average score, the participants listed their priorities in the following order: revenue generation (4.27); improve customer satisfaction (3.92); innovation (3.91); organisational/business agility (3.90); productivity (3.89); cost containment (3.82); talent management (3.69); reputation management (3.30) and risk mitigation (3.23). The participants were then quizzed about their HR priorities for 2017. Using an average score, the interviewees listed their priorities as follows: improve employee engagement (4.02); attract new talent (3.85); increase employee productivity (3.76); improve corporate culture (3.65); improve development and training opportunities (3.60); reduce HR costs (3.05); reduce employee turnover (2.97) and improve benefits programme (2.72). From these two sets of findings we can deduce several facts: →→ The strategic goals of businesses are aligned to the objectives of their HR departments; →→ Improving employee engagement and attracting new talent is central to boosting revenue generation and increasing customer satisfaction. Likewise, increasing employee productivity and improving corporate culture; and, →→ However, there are other factors that play a critical role in determining success in these areas, most notably improving employee training and reducing employee churn. It was noteworthy to see that our respondents placed these factors lower down the list, when they should have been higher up (Fig 1.) Improve employee engagement
Fig 1
Reduce HR costs
What are your HR priorities for you in 2017?
Attract new talent Increase employee productivity Improve development and training opportunities Reduce employee turnover Improve corporate culture Improve benefits program 0%
20%
40%
60%
80%
100%
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2017 Report on the State of HR Analytics
Data challenges To make business critical decisions, executives need a single view of their data. Naturally, we were interested in finding out more about the challenges our survey participants faced in this area. When asked about the biggest data challenge they faced in conducting analytics, just over one in three (31%) cited poor data quality. Almost the same percentage (29%) said that they were worried about fragmented data, while one in five (20%) said that they lacked the right skills to analyze their workforce data (Fig 2). Fragmented data
Fig 2
Poor data quality (incomplete, duplicates etc)
What would you say is your biggest data challenge for conducting People Analytics?
Out of date data Lack of skills to analyse the data We have no significant challenges in conducting analytics Other 0%
20%
40%
60%
80%
100%
Our participants’ concerns about poor data quality appeared to be borne out when we asked them whether their HR data was fit for analysis. Almost three quarters (74%) told us that their data was of average quality, but they still used it for analysis. A sizeable percentage – 17% – admitted that their data was of poor quality and that they had major reservations about using it for analysis. Only 9% said that they had complete confidence in their data’s quality (Fig 3).
Fig 3 How do you rate the quality of your HR data for analysis?
0%
20%
40%
60%
80%
100%
Highest quality - we have complete confidence in the data’s quality Average quality - we have issues with data but we can still use the data for some analytics Poor quality - we have major concerns about our data quality and feel we are unable to use it effectively
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2017 Report on the State of HR Analytics
These findings are truly remarkable. To make business critical decisions, senior executives need to have a single view of their data. But many of our participants admitted that the data in their organisations was patchy and fragmented in silos. Data quality is another massive issue. Before data can be used, it needs to be of cleansed for accuracy. Yet, most interviewees told us that their data was of average quality. Less than one out of ten said that their data was of excellent quality. Judging by these findings, many businesses are running people analytic operations that are simply not fit for purpose. Another series of worrying findings emerged when we asked our survey participants several questions about taxonomies. In the absence of a standardized taxonomy, it is not possible to make meaningful business decisions. Yet, 68% of our respondents told us that they did not have a data classification system in place (Fig 4). Lack of budget
Fig 4 Does your company currently have in place an organisation-wide standardised HR taxonomy for analytics?
Lack of executive support 0%
20%
40%
60%
80%
100%
(A ‘taxonomy’ being a standardised set of terms and classifications used in all departments)
We then asked the 32% of respondents that had taxonomies whether they had the ability to change the parameters of their classification system on the fly, to take into account corporate changes such as organizational structure. Worryingly, 36% of respondents did not have this capability. Not having a standardized taxonomy in place makes it harder for businesses to get value from their data. We wanted to know why some of our respondents had chosen not to have a data classification system. Shockingly, one third (30%) said that they had yet to standardize their HR processes in order to benefit from a single taxonomy. A slightly larger percentage (33%) said that they used taxonomies, but didn’t have a standardized taxonomy across their entire organization. Just under one in five (18%) said that they used data for basic reporting (not analytics) so a taxonomy wasn’t needed. And one in ten said that they wanted a taxonomy, but lacked the expertise, resources or budget to develop one. These findings revealed several glaring errors in data collection and analysis. It was particularly noteworthy that a high percentage of respondents admitted that they had yet to standardize their HR processes, a vital step in helping decision-makers to analyze data. Just as disconcertingly, a large percentage said that they had multiple taxonomies across their organization rather than a single one. The challenge of analyzing data viewed through the prism of multiple taxonomies across multiple business units and territories cannot be overstated.
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2017 Report on the State of HR Analytics
Employee analysis Employee analysis can range across a wide range of different areas. We were interested in finding out which topics are HR professionals were analyzing and what direction they intended to take their reporting and analytic capabilities in 2017. Just over four out of five of our respondents (81%) said that they were currently using employee analysis to investigate recruitment and retention. Almost three quarters (71%) said that they were using technology at the moment to analyze performance management. The remainder said that they were using employee analysis to analyze compensation and benefits (63%); workforce planning (51%); compliance (33%) and organisational effectiveness (27%). (Fig 5). Recruitment and retention
Fig 5
Compliance
What type of employee analysis do you currently conduct?
Compensation and benefits Performance management Workforce planning Organisational effectiveness Informal networks Other 0%
20%
40%
60%
80%
100%
Looking forward to 2017 and beyond, more than three quarters of respondents (77%) said that they would use data sets relating to employee satisfaction and engagement to analyse operations and people activity, while 67% said that they would use compensations and rewards data sets. A sizeable number said that they would data sets relating to HR performance (for instance, the number of hires per year) and external benchmarks such as salary (65% and 61% respectively). Others voiced an interest in using individual employee data sets (67%); payroll data sets (54%); recruitment and selection data sets (67%); workforce diversity data sets (58%) and leadership development data sets (49%). These findings indicate that those companies that are carrying out employee analysis have the right priorities, with high numbers focusing on data sets relating to employee satisfaction and engagement, employee metrics, compensations and rewards, and recruitment and retention.
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2017 Report on the State of HR Analytics
Lastly, we asked our respondents what data sets they intended to use in 2017 to analyse their people and organisations (Fig 5). The clear majority (77%) said that they intended to analyse data sets relating to employee satisfaction and engagement, while almost one in three (67%) said that they planned to carry out the same procedure with compensation and rewards data. A sizeable percentage (68%) said that they would spend their time analysing data sets related to recruitment and selection and HR performance (65%). Other businesses stated that they wanted to investigate data sets relating to workforce diversity (58%); external benchmarks such as salary (61%); payroll data (54%); leadership development (49%) and records of inactivity (45%). Compensation and rewards
Fig 6
Employee satisfaction / engagement
What data sets do you plan to use in 2017 for analysis of your people/company?
External bencmarks such as salary Hours worked by employees HR performance (e.g. number of hires per year,
including the average time from first interview to hire)
Individual employee metrics
(e.g. performance ratings, taining records)
Individual sales / revenue generation Leadership development (e.g. who are
your next generation leaders, what is the probablilty of their success) Payroll data (salary, tax expenses etc)
Pension data Records of inactivity (holiday sickness, maternity/paternity etc)
Records of work accidents Recruitment and selection Social media (including sentiment analysis)
Workforce diversity Informal networks Email and internal messaging Wearables / employee tracking Voice analytics Other 0%
20%
40%
60%
80%
100%
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2017 Report on the State of HR Analytics
Survey Questions and Results Listed below are the survey questions that we asked our interviewees together with a summary of the findings.
1
What are your company’s business priorities in 2017?
When asked to give their business priorities for 2017, the executives gave their scores in the following order: →→ Revenue generation – 4.27 →→ Improve customer satisfaction – 3.92 →→ Innovation – 3.91 →→ Organizational/business agility – 3.90 →→ Productivity – 3.89 →→ Cost containment –3.82 →→ Talent management –3.69 →→ Reputation management –3.30 →→ Risk mitigation –3.23
2
What are your HR priorities for you in 2017?
The respondents were asked to list their HR priorities for 2017. They responded by delivering their scores in the following order: →→ Improve employee engagement – 4.02 →→ Attract new talent – 3.85 →→ Increase employee productivity – 3.76 →→ Improve corporate culture – 3.65 →→ Improve development and training opportunities – 3.60 →→ Reduce HR costs – 3.05 →→ Reduce employee turnover – 2.97 →→ Improve benefits programme – 2.72
3
What would you say is your biggest data challenge for conducting People Analytics?
31% of respondents said that the biggest challenge they faced was dealing with poor data quality (incomplete, duplicates, etc). Almost a third (28%) said that they had to grapple with fragmented data. Other responses included: →→ Lack of skills to analyse the data – cited by 20% →→ Out of date data – mentioned by 2% →→ Other factors – listed by 9% 10% said that they had no significant issues in conducting people analytics.
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2017 Report on the State of HR Analytics
4
How do you rate the quality of your HR data for analysis?
5
More than three quarters of respondents (74%) said that their data was of average quality and that they had issues with their data. In spite of this, they continued to use their data for analysis. 17% said that their data was of poor quality and that they were not able to use it effectively. Only 9% said that their data was of high quality and that they had complete confidence in it.
32% of interviewees said that they had an organisation-wide standard taxonomy in place, while 68% said that they didn’t.
Does your company currently have in place an organisation-wide standardised HR taxonomy for analytics?
(A ‘taxonomy’ being a standardised set of terms and classifications used in all departments)
6
64% of the respondents said that they had this capability, while 36% said that they didn’t.
Are you able to change your taxonomy on-the-fly in order to continuously obtain relevant information as your organisation changes, e.g. from a reorganisation?
7
What is the main reason for not currently using a standard taxonomy?
33% of the executives interviewed said that they use taxonomies but did not have a standard taxonomy encompassing their entire organisation. One in third said that they would need to standardize their HR processes and definitions in order to benefit from a single taxonomy. In addition: →→ 18% said that they used data for basic reporting (not analytics), so a taxonomy wasn’t needed at present →→ 10% said that they wanted a taxonomy, but lacked the expertise, resources or budget to develop one →→ 4% said that they didn’t see the value in having a standard taxonomy in HR The remainder – 4% – gave other, unspecified reasons for not acquiring a standard taxonomy.
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2017 Report on the State of HR Analytics
8
What type of employee analysis do you currently conduct?
The vast majority of respondents (82%) said that they used employee analysis for recruitment and retention. 72% said that they used employee analysis for performance management and 62% for compensation and benefits. Other responses: →→ 51% using employee analysis for workforce planning →→ 33% using employee analysis for compliance →→ 27% using employee analysis for organisational effectiveness →→ 8% using employee analysis for informal networks 12% of the sample gave no specific reason for carrying out employee analysis.
9
What data sets do you plan to use in 2017 for analysis of your people/company?
More than three quarters (77%) of the participants said that they would be using data sets relating to employee satisfaction and engagement. 68% of the interviewees said that they intended to use compensation and rewards data sets. The same percentage said that they would use recruitment and selection data sets. 67% said that they would use individual employee metrics (performance ratings, training records) data sets for analysis. 65% said that they would use HR performance (e.g. number of hires per year, including the average time from first interview to hire) data sets to analyse their operations. The remainder said that they intended to use the following data sets: →→ Hours worked by employees – 37% →→ Individual sales/revenue generation – 29% →→ Leadership development – 49% →→ Payroll data – 54% →→ Pension data – 19% →→ Records of inactivity – 45% →→ Records of work accidents – 25% →→ Social media – 15% →→ Workforce diversity – 58% →→ Informal networks – 8% →→ Email and internal messaging – 8% →→ Wearables/employee tracking – 1% →→ Voice analytics – 2% →→ 3% of the respondents said that they would use other types of data sets.
10
How much data do you currently use for analysis?
One third of the participants said that they used combined employee data and employee performance data. 20% said that they analysed different types of people data, but that this data remained separate – not connected or combined. The remainder said that they were currently analysing the following types of data: →→ Only core employee data such as name, job title, salary – 12% →→ Employee performance data – 2% →→ Core employee data with other internal data such as revenue data – 16% →→ Core employee data with external information such as social media – 0.5% →→ Multiple external and internal sources of people data – 15% 4% of the survey respondents said that they weren’t currently performing any analytics on HR/ employee data. www.rosslynanalytics.com
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2017 Report on the State of HR Analytics
Conclusion The results of the comprehensive survey show that there is much progress to be made by HR leaders in getting their teams up to a standard required to deliver more insight and value to colleagues up and across their organizations. The good news is HR is, arguably, moving at a facer pace than other departments in the past in embracing cutting-edge technologies that empower employees with data and tools to make informed, timely decisions. It’s an exciting time to be in human resources, to be directly involved in helping HR adopt new ways of working. There is much innovation taking place in the market, with software vendors and service providers doing amazing things that benefit customers. There is also a lot of exciting work taking place in HR organisations that were early adopters of analytics, with them now able to teach others who are only know taking the journey toward integrating reporting and analytics. 2017 looks to be a promising year for the profession!
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2017 Report on the State of HR Analytics
About Tucana Tucana is Europe’s favorite destination for insights and ideas on the future of human resources. The company’s conferences are the must go to events attended by the world’s leaders in people analytics. To learn more about the business value created by attendees, please visit our website at https://tucana-global.com
Why Rosslyn Data Technologies Rosslyn Data Technologies (aka Rosslyn Analytics) has been helping business decision-makers make sense of and analyze data faster with more insight than using traditional business intelligence methods. The software company’s popular RAPid Cloud Platform automatically locates, extracts, connects and organizes disparate data sources into a single view for integrated reporting and analytics for HR professionals. To make your life easier at work, visit www.rosslynanalytics.com. We are also the company that is working with thought leaders to develop the HR profession’s first standardised HR taxonomy. To get involved in this important work, contact Lance Mercereau, CMO, at [email protected]
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Website: www.rosslynanalytics.com
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Researched and produced by Rosslyn Data Technologies and Tucana to help HR professionals derive more value from data
www.rosslynanalytics.com
2017 Report on the State of HR Analytics
Table of Contents 2
Executive summary
3
Key Findings
4
Analysis of Research Findings
9
Survey questions
www.rosslynanalytics.com
1
2017 Report on the State of HR Analytics
9%
Only of senior executives have confidence in the quality of their HR data
Executive Summary In today’s competitive environment, successful companies need highly skilled, motivated and capable employees. However, to broaden the skills of their workers and prepare the ground for future challenges and opportunities, executives must have access to the right data at the right time to make timely decisions. To get a comprehensive overview of the data challenges facing organizations, Rosslyn Data Technologies and Tucana conducted a joint survey of more than 300 HR professionals. They were asked a wide range of questions on business priorities, opportunities and challenges. The findings outlined here give readers the insight to benchmark their organizations’ success with data analytics – without data and the tools to report and analyze information, decisionmakers are simply making assumptions. The results of the survey shine light on a few concerns HR teams are having with analytics. It’s a fact that to make business critical decisions, people need to have a single view of data. In practice, this involves extracting data from multiple sources and loading it into a single database. Yet, almost one in three of the executives we spoke to told us that the biggest challenge they face is fragmented data. Data quality is another huge issue facing HR professionals. Before data can be put to actionable use, thousands of records must be normalized and cleansed to remove duplicate and incorrect information. But three quarters of the executives we interviewed told us that their data was of poor quality and that they had major reservations about using it for reporting and analysis. To cap it all, one in five said that they did not have the technical skills in-house to the leverage the data they had. Another worrying finding emerged when we questioned survey participants about their use of taxonomies. Without a standard HR taxonomy, it is difficult to effectively organize and accurately analyse data, particularly if they have multiple business units in different countries. But almost two out of three people we interviewed told us that they did not have a standard taxonomy in place across their businesses. Out of those that did have a standard classification system, 36% are unable to make changes on the fly. In addition, a sizeable percentage told us that they had yet to standardize their HR processes to benefit from a single taxonomy. This, too, was a troubling finding – without standardized business processes and tools, it is much harder for decision-makers to analyze masses of data and glean valuable insights in a timely manner.
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2
2017 Report on the State of HR Analytics
Key Findings Our exclusive survey reveals that: →→ One in three businesses is grappling with the challenge of fragmented
data
→→ 20% of HR departments lack the skills to analyze and interrogate data →→ Almost three-quarters of HR professionals have average quality data,
but still use it to carry out analysis
→→ 68% of HR departments do not have a standard corporate-wide
taxonomy in place for effective reporting and analysis
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3
2017 Report on the State of HR Analytics
Analysis of Research Findings In March 2017, Rosslyn Data Technologies, in partnership with Tucana, carried out an exclusive survey of senior executives at 307 private and public sector organizations. The interviewees – which included department heads, senior managers, business partners and managing directors – where questioned extensively about their use of HR analytics. Corporate priorities The executives were first questioned about their business priorities for the year. Based on an average score, the participants listed their priorities in the following order: revenue generation (4.27); improve customer satisfaction (3.92); innovation (3.91); organisational/business agility (3.90); productivity (3.89); cost containment (3.82); talent management (3.69); reputation management (3.30) and risk mitigation (3.23). The participants were then quizzed about their HR priorities for 2017. Using an average score, the interviewees listed their priorities as follows: improve employee engagement (4.02); attract new talent (3.85); increase employee productivity (3.76); improve corporate culture (3.65); improve development and training opportunities (3.60); reduce HR costs (3.05); reduce employee turnover (2.97) and improve benefits programme (2.72). From these two sets of findings we can deduce several facts: →→ The strategic goals of businesses are aligned to the objectives of their HR departments; →→ Improving employee engagement and attracting new talent is central to boosting revenue generation and increasing customer satisfaction. Likewise, increasing employee productivity and improving corporate culture; and, →→ However, there are other factors that play a critical role in determining success in these areas, most notably improving employee training and reducing employee churn. It was noteworthy to see that our respondents placed these factors lower down the list, when they should have been higher up (Fig 1.) Improve employee engagement
Fig 1
Reduce HR costs
What are your HR priorities for you in 2017?
Attract new talent Increase employee productivity Improve development and training opportunities Reduce employee turnover Improve corporate culture Improve benefits program 0%
20%
40%
60%
80%
100%
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2017 Report on the State of HR Analytics
Data challenges To make business critical decisions, executives need a single view of their data. Naturally, we were interested in finding out more about the challenges our survey participants faced in this area. When asked about the biggest data challenge they faced in conducting analytics, just over one in three (31%) cited poor data quality. Almost the same percentage (29%) said that they were worried about fragmented data, while one in five (20%) said that they lacked the right skills to analyze their workforce data (Fig 2). Fragmented data
Fig 2
Poor data quality (incomplete, duplicates etc)
What would you say is your biggest data challenge for conducting People Analytics?
Out of date data Lack of skills to analyse the data We have no significant challenges in conducting analytics Other 0%
20%
40%
60%
80%
100%
Our participants’ concerns about poor data quality appeared to be borne out when we asked them whether their HR data was fit for analysis. Almost three quarters (74%) told us that their data was of average quality, but they still used it for analysis. A sizeable percentage – 17% – admitted that their data was of poor quality and that they had major reservations about using it for analysis. Only 9% said that they had complete confidence in their data’s quality (Fig 3).
Fig 3 How do you rate the quality of your HR data for analysis?
0%
20%
40%
60%
80%
100%
Highest quality - we have complete confidence in the data’s quality Average quality - we have issues with data but we can still use the data for some analytics Poor quality - we have major concerns about our data quality and feel we are unable to use it effectively
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2017 Report on the State of HR Analytics
These findings are truly remarkable. To make business critical decisions, senior executives need to have a single view of their data. But many of our participants admitted that the data in their organisations was patchy and fragmented in silos. Data quality is another massive issue. Before data can be used, it needs to be of cleansed for accuracy. Yet, most interviewees told us that their data was of average quality. Less than one out of ten said that their data was of excellent quality. Judging by these findings, many businesses are running people analytic operations that are simply not fit for purpose. Another series of worrying findings emerged when we asked our survey participants several questions about taxonomies. In the absence of a standardized taxonomy, it is not possible to make meaningful business decisions. Yet, 68% of our respondents told us that they did not have a data classification system in place (Fig 4). Lack of budget
Fig 4 Does your company currently have in place an organisation-wide standardised HR taxonomy for analytics?
Lack of executive support 0%
20%
40%
60%
80%
100%
(A ‘taxonomy’ being a standardised set of terms and classifications used in all departments)
We then asked the 32% of respondents that had taxonomies whether they had the ability to change the parameters of their classification system on the fly, to take into account corporate changes such as organizational structure. Worryingly, 36% of respondents did not have this capability. Not having a standardized taxonomy in place makes it harder for businesses to get value from their data. We wanted to know why some of our respondents had chosen not to have a data classification system. Shockingly, one third (30%) said that they had yet to standardize their HR processes in order to benefit from a single taxonomy. A slightly larger percentage (33%) said that they used taxonomies, but didn’t have a standardized taxonomy across their entire organization. Just under one in five (18%) said that they used data for basic reporting (not analytics) so a taxonomy wasn’t needed. And one in ten said that they wanted a taxonomy, but lacked the expertise, resources or budget to develop one. These findings revealed several glaring errors in data collection and analysis. It was particularly noteworthy that a high percentage of respondents admitted that they had yet to standardize their HR processes, a vital step in helping decision-makers to analyze data. Just as disconcertingly, a large percentage said that they had multiple taxonomies across their organization rather than a single one. The challenge of analyzing data viewed through the prism of multiple taxonomies across multiple business units and territories cannot be overstated.
www.rosslynanalytics.com
6
2017 Report on the State of HR Analytics
Employee analysis Employee analysis can range across a wide range of different areas. We were interested in finding out which topics are HR professionals were analyzing and what direction they intended to take their reporting and analytic capabilities in 2017. Just over four out of five of our respondents (81%) said that they were currently using employee analysis to investigate recruitment and retention. Almost three quarters (71%) said that they were using technology at the moment to analyze performance management. The remainder said that they were using employee analysis to analyze compensation and benefits (63%); workforce planning (51%); compliance (33%) and organisational effectiveness (27%). (Fig 5). Recruitment and retention
Fig 5
Compliance
What type of employee analysis do you currently conduct?
Compensation and benefits Performance management Workforce planning Organisational effectiveness Informal networks Other 0%
20%
40%
60%
80%
100%
Looking forward to 2017 and beyond, more than three quarters of respondents (77%) said that they would use data sets relating to employee satisfaction and engagement to analyse operations and people activity, while 67% said that they would use compensations and rewards data sets. A sizeable number said that they would data sets relating to HR performance (for instance, the number of hires per year) and external benchmarks such as salary (65% and 61% respectively). Others voiced an interest in using individual employee data sets (67%); payroll data sets (54%); recruitment and selection data sets (67%); workforce diversity data sets (58%) and leadership development data sets (49%). These findings indicate that those companies that are carrying out employee analysis have the right priorities, with high numbers focusing on data sets relating to employee satisfaction and engagement, employee metrics, compensations and rewards, and recruitment and retention.
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2017 Report on the State of HR Analytics
Lastly, we asked our respondents what data sets they intended to use in 2017 to analyse their people and organisations (Fig 5). The clear majority (77%) said that they intended to analyse data sets relating to employee satisfaction and engagement, while almost one in three (67%) said that they planned to carry out the same procedure with compensation and rewards data. A sizeable percentage (68%) said that they would spend their time analysing data sets related to recruitment and selection and HR performance (65%). Other businesses stated that they wanted to investigate data sets relating to workforce diversity (58%); external benchmarks such as salary (61%); payroll data (54%); leadership development (49%) and records of inactivity (45%). Compensation and rewards
Fig 6
Employee satisfaction / engagement
What data sets do you plan to use in 2017 for analysis of your people/company?
External bencmarks such as salary Hours worked by employees HR performance (e.g. number of hires per year,
including the average time from first interview to hire)
Individual employee metrics
(e.g. performance ratings, taining records)
Individual sales / revenue generation Leadership development (e.g. who are
your next generation leaders, what is the probablilty of their success) Payroll data (salary, tax expenses etc)
Pension data Records of inactivity (holiday sickness, maternity/paternity etc)
Records of work accidents Recruitment and selection Social media (including sentiment analysis)
Workforce diversity Informal networks Email and internal messaging Wearables / employee tracking Voice analytics Other 0%
20%
40%
60%
80%
100%
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2017 Report on the State of HR Analytics
Survey Questions and Results Listed below are the survey questions that we asked our interviewees together with a summary of the findings.
1
What are your company’s business priorities in 2017?
When asked to give their business priorities for 2017, the executives gave their scores in the following order: →→ Revenue generation – 4.27 →→ Improve customer satisfaction – 3.92 →→ Innovation – 3.91 →→ Organizational/business agility – 3.90 →→ Productivity – 3.89 →→ Cost containment –3.82 →→ Talent management –3.69 →→ Reputation management –3.30 →→ Risk mitigation –3.23
2
What are your HR priorities for you in 2017?
The respondents were asked to list their HR priorities for 2017. They responded by delivering their scores in the following order: →→ Improve employee engagement – 4.02 →→ Attract new talent – 3.85 →→ Increase employee productivity – 3.76 →→ Improve corporate culture – 3.65 →→ Improve development and training opportunities – 3.60 →→ Reduce HR costs – 3.05 →→ Reduce employee turnover – 2.97 →→ Improve benefits programme – 2.72
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What would you say is your biggest data challenge for conducting People Analytics?
31% of respondents said that the biggest challenge they faced was dealing with poor data quality (incomplete, duplicates, etc). Almost a third (28%) said that they had to grapple with fragmented data. Other responses included: →→ Lack of skills to analyse the data – cited by 20% →→ Out of date data – mentioned by 2% →→ Other factors – listed by 9% 10% said that they had no significant issues in conducting people analytics.
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2017 Report on the State of HR Analytics
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How do you rate the quality of your HR data for analysis?
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More than three quarters of respondents (74%) said that their data was of average quality and that they had issues with their data. In spite of this, they continued to use their data for analysis. 17% said that their data was of poor quality and that they were not able to use it effectively. Only 9% said that their data was of high quality and that they had complete confidence in it.
32% of interviewees said that they had an organisation-wide standard taxonomy in place, while 68% said that they didn’t.
Does your company currently have in place an organisation-wide standardised HR taxonomy for analytics?
(A ‘taxonomy’ being a standardised set of terms and classifications used in all departments)
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64% of the respondents said that they had this capability, while 36% said that they didn’t.
Are you able to change your taxonomy on-the-fly in order to continuously obtain relevant information as your organisation changes, e.g. from a reorganisation?
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What is the main reason for not currently using a standard taxonomy?
33% of the executives interviewed said that they use taxonomies but did not have a standard taxonomy encompassing their entire organisation. One in third said that they would need to standardize their HR processes and definitions in order to benefit from a single taxonomy. In addition: →→ 18% said that they used data for basic reporting (not analytics), so a taxonomy wasn’t needed at present →→ 10% said that they wanted a taxonomy, but lacked the expertise, resources or budget to develop one →→ 4% said that they didn’t see the value in having a standard taxonomy in HR The remainder – 4% – gave other, unspecified reasons for not acquiring a standard taxonomy.
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2017 Report on the State of HR Analytics
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What type of employee analysis do you currently conduct?
The vast majority of respondents (82%) said that they used employee analysis for recruitment and retention. 72% said that they used employee analysis for performance management and 62% for compensation and benefits. Other responses: →→ 51% using employee analysis for workforce planning →→ 33% using employee analysis for compliance →→ 27% using employee analysis for organisational effectiveness →→ 8% using employee analysis for informal networks 12% of the sample gave no specific reason for carrying out employee analysis.
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What data sets do you plan to use in 2017 for analysis of your people/company?
More than three quarters (77%) of the participants said that they would be using data sets relating to employee satisfaction and engagement. 68% of the interviewees said that they intended to use compensation and rewards data sets. The same percentage said that they would use recruitment and selection data sets. 67% said that they would use individual employee metrics (performance ratings, training records) data sets for analysis. 65% said that they would use HR performance (e.g. number of hires per year, including the average time from first interview to hire) data sets to analyse their operations. The remainder said that they intended to use the following data sets: →→ Hours worked by employees – 37% →→ Individual sales/revenue generation – 29% →→ Leadership development – 49% →→ Payroll data – 54% →→ Pension data – 19% →→ Records of inactivity – 45% →→ Records of work accidents – 25% →→ Social media – 15% →→ Workforce diversity – 58% →→ Informal networks – 8% →→ Email and internal messaging – 8% →→ Wearables/employee tracking – 1% →→ Voice analytics – 2% →→ 3% of the respondents said that they would use other types of data sets.
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How much data do you currently use for analysis?
One third of the participants said that they used combined employee data and employee performance data. 20% said that they analysed different types of people data, but that this data remained separate – not connected or combined. The remainder said that they were currently analysing the following types of data: →→ Only core employee data such as name, job title, salary – 12% →→ Employee performance data – 2% →→ Core employee data with other internal data such as revenue data – 16% →→ Core employee data with external information such as social media – 0.5% →→ Multiple external and internal sources of people data – 15% 4% of the survey respondents said that they weren’t currently performing any analytics on HR/ employee data. www.rosslynanalytics.com
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2017 Report on the State of HR Analytics
Conclusion The results of the comprehensive survey show that there is much progress to be made by HR leaders in getting their teams up to a standard required to deliver more insight and value to colleagues up and across their organizations. The good news is HR is, arguably, moving at a facer pace than other departments in the past in embracing cutting-edge technologies that empower employees with data and tools to make informed, timely decisions. It’s an exciting time to be in human resources, to be directly involved in helping HR adopt new ways of working. There is much innovation taking place in the market, with software vendors and service providers doing amazing things that benefit customers. There is also a lot of exciting work taking place in HR organisations that were early adopters of analytics, with them now able to teach others who are only know taking the journey toward integrating reporting and analytics. 2017 looks to be a promising year for the profession!
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2017 Report on the State of HR Analytics
About Tucana Tucana is Europe’s favorite destination for insights and ideas on the future of human resources. The company’s conferences are the must go to events attended by the world’s leaders in people analytics. To learn more about the business value created by attendees, please visit our website at https://tucana-global.com
Why Rosslyn Data Technologies Rosslyn Data Technologies (aka Rosslyn Analytics) has been helping business decision-makers make sense of and analyze data faster with more insight than using traditional business intelligence methods. The software company’s popular RAPid Cloud Platform automatically locates, extracts, connects and organizes disparate data sources into a single view for integrated reporting and analytics for HR professionals. To make your life easier at work, visit www.rosslynanalytics.com. We are also the company that is working with thought leaders to develop the HR profession’s first standardised HR taxonomy. To get involved in this important work, contact Lance Mercereau, CMO, at [email protected]
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Website: www.rosslynanalytics.com
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