This is the second of my assignments for university around analytics in the world of recruitment.

Introduction

The proposed topic is the use of data and analytics within the realm of recruitment. Many sectors are finding it hard to recruit in the current climate that covers a wide span of jobs, from those paying minimum or living wage to specialised roles. I believe that moving to a more data-driven approach to recruitment will help managers understand the needs of the business and the importance of a role (rather than just a position to fill) to applicants understanding more about the business and the role that they are applying for. This is based on my generalist HR experience of over 20 years and supporting many managers recruiting (and losing) team members.

For this research to be beneficial to industry, it needs to be conducted across sectors and regions (either within the UK or globally). There is limited literature aimed at this specific topic but a start  is a paper  by Durai, Kishnaven and Manohan (2022) entitled Leveraging HR Metrics for effective recruitment and selection process in IT Industries in Chennai and Coimbatore, Tamil Nadu. The paper is focused on a specific sector and specific regions but it draws on the work of others to support its exploratory writings. And  uses the metrics identified by others to use with a small group of HR Practitioners for organisations within the sector and region.

This lends credence to my suggestion as recruitment metrics being the same across sectors, industries and regions can be benchmarked against each other (and especially when you consider ISO standards in this area). I will be drawing on a number of the ISO standards created by the Technical Committee for Human Resource Management (ISO/TC 260 https://www.iso.org/committee/628737.html accessed 31/08/2022). The standing of the ISO and standards in other work areas is second to none (certainly for Quality, Health and Safety and IT security) based on how industries have taken them up. My training as a certified auditor for ISO 30414: 2018… states the following within the first module of training: “The ISO 9000 family concerning quality management is used by over a million organisations in over 170 countries, which shows how important these international standards are, ISO 30414:2018 is considered equally important.” HCM Metrics/David Simmonds 2020. A full list of standards is available within the references section.

Methods

I propose that research be both quantitative and qualitative. For both areas, I suggest that data, which should be anonymised, be collected based on the aforementioned paper from India and from the published ISO standards within this area (30400:2016, 30401:2018/AMD1:2022, 30405:2016 30406:2017, 30404:2017, 30409:2016, 20410:2018, 20411:2018, 30414:2018, 30421:2021, 30428:2021, 30430:2021).

On a quantitative basis, metrics such as those listed in 30414  (page 10) are the beginning of the research, the focus will initially be on the actual recruitment process with a further progression to how recruits transition through an organisation at a later stage or separate paper:

  1. Number of qualified candidates per position
  2. Quality per hire
  3. Average length of time to fill vacant positions
  4. Average length of time to fill critical vacant positions[1]
  5. Transition and future workforce capabilities

 A number of organisations and their HR departments should be approached to gain support and for them to provide data. To support the validity of the exercise, I suggest that organisations can provide data from across at least 3 years and ideally, 5 years (I suspect based on my own experience that 5 years of metrics may be difficult as the data may not have been kept for that long). Unlike the paper by  Durai, Kishnaven and Manohan (2022), this is based on organisational data, not the experience of the HR Manager. With this in mind, smaller businesses are unlikely to be included but, in the UK, they form a large part of the economy and so are more likely to be able to report on the qualitative side (but if they have data then it will be included). Data to be provided should be the base data to perform the calculations rather than the output of the calculations so that the data can be split and/or merged as needed.

Once the data is gathered, and further anonymised so that the companies are not identified then the calculations suggested within ISO 30414:2018 can be calculated in the following ways:

  • Overall
  • By sector
  • By business size
    • Within sector and
    • across the data
  • By region

Within ISO 30405:2016, figure 2 on page 9 shows a recruitment process as part of a talent supply chain. Organisations should be recruiting not just for a fixed role in time but for a role that will need to adapt over time as the organisation and the individual grows and develops.

Insert the graphics from the assignment before publishing

This itself is based on the work of Cascio  W., & Boudreau  J. Utility of selection systems: Supply-chain analysis applied to staffing decisions. In: Handbook of I/O Psychology, (Zedeck  S. ed.).  American Psychological Association, Washington, D. C.,  Vol. 2,  2011, pp. 421–44.

Once the above has been completed, progression can be made towards other metrics like Cost per Hire as defined in ISO 30407:2018 Human Resource Management Cost per Hire.  This metric, specifically the Cost Per Hire Comparable (CPHC), will allow further sectioning of the initial data as a lower-skilled role is likely to cost less than a highly skilled role. This is, again based on my own experience. As an example, hiring a production operative who has been working with an organisation for 12 weeks through an agency has no traditional recruitment cost. The organisation has paid that through the charge rate already. However, a highly skilled engineer to maintain and repair machinery is likely to be through an agency who charges a percentage of salary or total reward value. For cost comparison purposes:

A skilled role at £40,000 per annum with an agency rate of 20% is a cost of £8000 per person hired

A production operative earning £10 an hour and working a 40-hour week will cost overall £8,991.36 but of that, £7551.36 would have been incurred for a non-agency worker so the recruitment cost is £1440.

There is a stark difference between the two!

ISO 30407 has a very clear formula for definining the cost per hire which is comparable between organisations. It uses “ a more restrictive set of data inputs… The formula doesn’t change as compared with the CPHI.” CPHI is the cost per hire internal – it should only be used within an organisation not outside so for the purposes of this research it isn’t a valid method.

The formula for CPHC is:

Sum of External Costs + Sum of internal costs

Total number of hires in a time period

The standard goes on to explain the costs that can be included. From a research perspective, the time period should be 12 calendar months from January to December so that data is actually comparable rather than using a financial year which is unlikely to be the same for each organisation.

From a qualitative perspective, the recruitment team and hiring managers can be interviewed using a standard set of questions. I would recommend face-to-face interviews rather than a questionnaire as this gives the interviewer and respondent time to understand the question and answer appropriately. From this, we can start to compare the provided answers. However, the data needs to be organised into a sensible format before any analysis can be started. There are two main forms of analysis:

  • Content
    • Codes the data into categories & subcategories which can then be used to create a map or model to illustrate the concepts or to apply quantitative methods
  • Thematic
    • Looks at the themes within the content. It identifies codes and categories and then moves the data into themes and subthemes

Kent Lofgren (2013) Qualitative analysis of interview data: A step-by-step guide for coding/indexing [online video]. Available at: https://www.youtube.com/watch?v=DRL4PF2u9XA accessed on 31/08/2022

Applications of Results

The results would produce a set of calculations that other organisations can use to benchmark, especially if they aren’t ready to go into a full iso audit of their hr function.

Many HR Professionals are always looking to be able to benchmark their results. This research has a very practical output for industry and as a basis for more research into the area along with providing greater knowledge of the HR ISO standards that do now exist and yet many of my colleagues are unaware of them but are very aware of other audit standards as they apply to their sector. Working in the food industry, I was aware of many standards that the organisation were audited against which, included HR practices.

The results of this allow the participating organisations to get a feel for how the ISO standards could support them and start them on a path towards a more data-driven HR which, in todays society is needed. HR departments and professionals need to be able to provide information backed by data to clearly state why or why not a particular suggestion should be followed. For too long have HR professionals relied on their own experience and a number of us, myself included, definitely need to improve our analytical and numerical skills. HR has to start talking in the language of the board and moving forwards with predictive analytics rather than staying with reactive analytics.

Discussion

The research will provide a benchmark for recruitment metrics that is in line with academic research but has a practical use within the HR profession. It will encourage the use of the little know ISO standards for HR and slowly, the profession can come together and learn to use data to support their decision-making.

Professional bodies like the CIPD would have a resource to point their members to and those who practice HR as a consultant also have a valuable resource to lean on.

The main point of this research proposal is the practical use of the research rather than it sitting on an online shelf for other academics to reference.

The research does have limitations. As I am based in the UK, I would naturally choose UK-based organisations to participate in. For this to be used on a wider basis, more organisations would need to participate which has its own challenges such as time zone coordination.

Organisations will need to be persuaded to join the study and will be very reluctant to release the basic data required for this. I know that had this request come to me whilst I was working within larger corporates I would have hesitated. Organisations, also may not hold the historic data to be able to produce a few year’s worths of data. It could be done in one year but looking back over a longer period provides more stability for the research. It could of course be repeated year on year but that has a large amount of time for the researcher and potentially the organisation in gathering the data.

This research could progress further, into looking at how individuals are moved through an organisation, how succession planning is effective based on recruitment decisions as well as allowing organisations to truly understand what it is that they need to recruit.

I would suggest that this research is completed by a team who have an equal mix of analytical ability but also generalist HR experience as well as specific recruitment experience. This will allow the team to dig deeper into the data with a wide based background rather than a narrow focus on the calculations and data but showing the practical aspects of what this could deliver.

References

ISO Standards – https://www.iso.org/committee/628737/x/catalogue/p/1/u/0/w/0/d/0

ISO 30405:2016 Human resource management — Guidelines on recruitment

ISO 30407: 2017 Human resource management — Cost-Per-Hire

ISO 30409: 2016 Human resource management — Workforce planning

ISO/TS 30410:2018 Human resource management — Impact of hire metric

ISO/TS 30411:2018 Human resource management — Quality of hire metric

ISO 30414:2018 Human resource management — Guidelines for internal and external human capital reporting

ISO/TS 30421:2021 Human resource management — Turnover and retention metrics

ISO/TS 30430:2021 Human resource management — Recruitment metrics cluster

Durai, Kishnaven and Manohan (2022) entitled Leveraging HR Metrics for effective recruitment and selection process in IT Industries in Chennai and Coimbatore, Tamil Nadu.

Kent Lofgren (2013) Qualitative analysis of interview data: A step-by-step guide for coding/indexing [online video]. Available at: https://www.youtube.com/watch?v=DRL4PF2u9XA


[1] Organisations determine critical business positions themselves

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