Staff major review: Summary of consultation responses to the evidence gathering exercise

Question 3. What is your organisation?  

62 out of 77 responses (81%) came from higher education providers. 10% came from higher education sector groups or bodies, and 10% came from other organisations.

Question 6. In what capacity are you responding to the survey? 

71 out of 77 respondents to the consultation answered Question 7, which asked how they or their institutions use data on non-academic staff. 4% of those who answered the question replied that the question was not applicable, and similar numbers stated either that their they and/or their institution made little use of non-academic staff data or that they were unaware of any use of such data. 6% stated that they do not currently use data on non-academic staff, but that they are interested in exploring ways to make use of it in the future. 

Those who said that they currently use data on non-academic staff cited a wide range of purposes. The most common use of the data was for EDI monitoring, with 52% of those who answered the question saying they used the data for this purpose and a further 20% saying that non-academic staff data was valuable for the Athena Swan and Race Equality Charters. 42% said that non-academic staff data was useful for benchmarking. Other frequently cited uses included workforce planning, pay grading and financial modelling, and understanding the roles and working conditions of staff in the sector. 

70% of respondents supported the reintroduction of non-academic staff data as a mandatory element of the Staff return; 10% opposed the idea, and 20% were unsure or felt the question was not applicable. Six out of the 15 ‘unsure / not applicable’ responses came from providers in Scotland and Wales, who are already required to submit data on non-academic staff.

Question 8. Would you support the reintroduction of non-academic staff data as a mandatory element of the Staff return? 

69 respondents replied to Question 9, on which categories of data would be essential if we were to collect a reduced set of data on non-academic staff. Equalities and personal characteristics data was the most frequently cited category, with 54% of those answering Question 9 expressing a need for this data. Respondents were also particularly interested in fields relating to employment conditions (mode and terms of employment, FTE/FPE, salary), roles (SOC, job titles, level, cost centre), and qualifications or professional registration. Smaller numbers of respondents requested data on career trajectories, including length of employment, previous employment, and locations and activities after leaving. 13% requested specific data on technicians and technical skills. 13% opposed the idea of a reduced dataset. 

We received 64 responses to Question 10, which asked for further comments on non-academic staff data; of those 54, 24% left the question blank, said they had no further comments, or responded that it was not applicable. Responses to this question were variable; although some themes recurred, there was no overarching consensus and no theme was mentioned by more than 20% of respondents. 

A number of respondents noted the importance of non-academic staff to the student experience, the variety of roles played by non-academic staff, and the fact that such staff comprise a large and growing part of the HE workforce. In this vein, some respondents objected to the term ‘non-academic staff’, arguing that its negative phrasing diminishes the important work done by such staff. Respondents also noted that data on non-academic staff was important for benchmarking purposes, and that a lack of sector-wide data on non-academic staff makes comparisons between regions and institutions difficult, particularly over time.  

Some respondents noted that changing data requirements for non-academic staff would necessitate changes to software systems, although this was not necessarily  seen as a reason not to collect the data. A few respondents suggested that it was difficult to keep up with changing data requirements, and that returning non-academic staff data on a mandatory basis would lead to an increase in burden. Other respondents, however, noted that, since data on non-academic staff is already held internally, reintroducing the mandatory return of non-academic staff data would not constitute a significant increase in data burden. Relatedly, others noted that increases in mandatory data reporting did not necessarily equate to an increase in burden, given that such increases might allow for the reduction of burden elsewhere. 

We received 66 responses to Question 11; 12% of those 66 respondents said that the question was not applicable or that their institution does not employ technicians. 21% of those who answered Question 11 said that their institution had no agreed definition of technicians, and several of those noted that the lack of an agreed definition was a source of frustration.  

Among those who said that their institutions did have a definition, it was agreed that technicians performed a wide variety of roles. The two most common approaches to the question were either to define technicians according to their title, job description, or job family or to define them according to the skills, training, and experience required to carry out their job. Many respondents also defined technicians in terms of their supporting roles, identifying them as non-academic staff who perform functions that support research, teaching, or other academic activities. A few respondents referred to SOC codes as a way to classify technical staff. Others referred to definitions used by UKRI, the TALENT Commission, or the Technician Commitment. 

Responses were divided as to whether the list of SOC codes used in the TALENT Commission report would constitute a suitable definition. While more respondents answered ‘yes’ (30%) than answered ‘no’ (22%), the largest number of respondents (43%) were unsure or felt that the question was not applicable. 

Question 12. Would adopting the SOC-based definition of technicians used in the TALENT Commission report meet your needs?  

When asked to clarify their responses to Question 12, respondents cited a number of potential problems with the use of a SOC-based definition. A number of respondents noted that, although the TALENT team used a list of SOC codes to identify technicians in the workforce, they did not actually advocate a SOC-based definition, but instead used SOC codes because doing so was the best way to identify technicians using the data available. Some respondents worried that some technicians would not fit into the list of SOC codes identified in the TALENT report, while others noted that not all staff employed in those SOC codes would be technicians. Others suggested that a SOC-based definition would not capture the full range of technicians’ contributions, particular with regard to research and teaching. A few respondents also noted that the list of SOC codes identified in the TALENT report did not map onto the definitions currently in use in their organisation. 

64 respondents answered Question 14, which asked about uses for data on technicians. Although 30% of those who answered the question said they made little or no use of data on technicians, other respondents reported a wide variety of uses. The most common use (27%) was workforce monitoring and planning; other frequently mentioned uses included monitoring progress on the Technician Commitment, monitoring career trajectories, and EDI work. Several respondents noted that they use data on technicians the same way they use data on other non-academic staff. 11% reported that they would like to make more use of data on technicians than they do currently, and another 11% noted that the data available is insufficient for their needs. 

The majority of respondents supported the mandatory inclusion of technicians in the Staff record. 71% of respondents supported the mandatory inclusion of technicians, 23% were unsure or felt the question was not applicable, and only 5% were opposed. Four of the 18 ‘unsure / not applicable’ responses came from providers in Scotland and Wales, who are currently required to submit data on technicians as part of the broader requirement to include non-academic staff. 

Question 15. Would you support the mandatory inclusion of technicians in the Staff records? 

The number of respondents saying they would need to identify technicians separately was smaller than the number in favour of mandatory inclusion, but a majority of respondents still said that they would need to be able to identify technicians separately. 65% of respondents said they would need to be able to identify technicians, 25% were unsure, 5% said no, and 5% did not answer the question. 

Question 16. If technicians were included would you need to be able to identify them separately?  

Question 17 asked for any other comments on technicians. 25 respondents provided additional comments. Of those, 20% reiterated the need to be able to identify technicians in the Staff record, with several respondents suggesting that technicians need their own employment category. Several respondents mentioned the importance of moving towards a sector-agreed definition; others, on a related note, were concerned about the consistency of data that might be collected. A few respondents suggested that it would be important to distinguish between research and teaching technicians, with several noting the contributions of technicians to teaching and suggesting that they should be included in student:staff ratios. 

We received 67 responses to Question 18, which asked what use respondents and their organisations make of data on staff who are not directly employed by HE providers. Of those responses, 40% replied either that the question was not applicable or that they made little or no use of data on this category of staff. Among the respondents who said that they used such data, the most common uses were for various types of monitoring; 13% of those who answered the question said that they used data on staff not directly employed by providers for internal monitoring of EDI issues, while another 12% said that they used it for financial monitoring. A few said that such data was useful for the TEF and other teaching and learning initiatives, and some said that they adjust student:staff ratio calculations so as to include staff with teaching responsibilities who are not directly employed by a provider. 22% either said that they did not use data on staff not directly employed by providers because data was not available or suggested uses which they would like to be able to make of such data if it were available.  

 Question 19 asked whether respondents would like to see staff not directly employed by providers brought into the Staff record. While 31% of respondents said such staff should be included, 45% said they would not like to see these staff brought into the record; the remaining 23% were unsure.  

Question 19. Would you like to see staff not directly employed by providers brought into the Staff record? 

Question 20 introduced the possibility of collecting a reduced set of data on staff not directly employed by providers. Of the 63 responses to this question, 27% said they were opposed to the collection of a reduced set of data or said that the question was not applicable, and another 6% gave reasons they thought data on staff not directly employed by providers should not be collected at all, including concerns about burden, data protection, and the difficulty of collecting the data. 

Among other respondents, there was no consensus about what would be essential to include in a limited set of data. 11% of respondents to the question said that, if any data were to be collected on these staff, a full set of data should be collected; a few other respondents said that staff not directly employed by providers should be treated either like academic staff or like atypical staff. 19% said that data on EDI characteristics would be essential; others focused on employment characteristics, with 14% requesting data on pay, 14% requesting data on hours, and others expressing interest in employment function, job category, contract and employment basis, SOC, and cost centre. 6% said that they would like whatever data would be needed for inclusion in a REF submission.  

Question 21 asked for any other comments on staff not directly employed by providers. Of the 60 respondents to this question, 16 said they had nothing further to add. 33% of respondents to this question were concerned that data on these staff would be difficult to obtain and record, 12% noted concerns about data protection, and 10% expressed concern about the accuracy of any data that might be collected. Several respondents expressed concern that collecting and publishing data on staff not directly employed by providers would harm working relationships and could make it difficult to obtain staff in these categories of roles. Other respondents, however, mentioned possible uses for the data, including student:staff ratios, REF submissions, and calculations of pension costs. A number of respondents noted that they could see a rationale for collecting the data, but that further work would be needed to answer definitional questions, ascertain user needs, and overcome difficulties of collection.  

Question 22 asked respondents whether they or their organisations distinguish between academic and non-academic staff in their contracts of employment. 69% of respondents said yes, 10% said no, and 21% said they were unsure or that the question was not applicable.  

Question 22. Does your organisation distinguish between academic and non-academic staff in its contracts of employment?  

Since 62 of the 77 responses to the evidence gathering survey came from HE providers, this means that 84% of providers who responded to the survey distinguish between academic and non-academic staff in their contracts of employment. 13% of providers in our sample, however, do not distinguish, and one was uncertain.  

Question 23 asked respondents whether they or their organisations distinguish in their contracts of employment between academic staff with responsibility for teaching, research, or teaching and research. While 55% of respondents said they distinguish between teaching, research, and teaching and research contracts, 16% said they did not distinguish, and 30% were unsure or thought the question was not applicable. 

Question 23. For academic staff, does your organisation distinguish between staff with responsibilities for teaching, research, or both teaching and research in its contracts of employment? 

Of provider responses to Question 23, 68% distinguish at the contract level between teaching and research, 19% do not, and 8% are unsure.  

Question 24 asked about academic career pathways other than teaching, research, or both. 29 respondents described other pathways in their organisations. Some respondents explained that their organisations have other career pathways which fit into the existing academic employment function categories, with 7% of respondents to this question categorising knowledge exchange, impact, or engagement as part of research. 21% of respondents, however, noted that these activities are the basis of separate career pathways at their institutions. 21% respondents likewise mentioned career pathways in practice, while 17% mentioned pathways in leadership and management. Smaller numbers of respondents mentioned pathways for clinical academic staff, academic staff in administrative roles, and academic staff who carry out other professional activities.  

Question 25 asked what data on the involvement of non-academic staff in teaching and research activities would be useful. Of the 67 responses to this question, 25% said that no data would be useful, and 7% were unsure what data might be useful. Other respondents identified a wide range of data which could be helpful. The most frequent suggestion was data on the amount of time devoted to research and teaching activities, which was mentioned by 19% of respondents to the question. Some respondents noted that it would be particularly useful to be able to identify technicians and their contributions to research and teaching, while others suggested the creation of a new employment function category to identify non-academic staff with research and teaching responsibilities. Other frequent suggestions were for data on job roles and employment details, diversity characteristics, and cost centre or academic discipline. Respondents also raised various concerns related to the collection of data in these areas, noting that it would be important to agree on definitions and to consider potential impacts on student:staff ratios and the REF.  

Question 26 asked what other data on the employment functions of non-academic staff would be useful. Of the 57 respondents to this question, 37% either said nothing or said that no other data would be helpful; three were unsure. Of those who did say that further data would be useful,16% of those who answered the question requested data on staff in technical roles, 11% requested data on staff involved in teaching and research, and 7% said that it would be helpful to have data on staff in different job families, such as IT or libraries. Other repeated requests were for data on staff who serve as personal tutors, those involved with the student experience, those who work with research grants, and those engaged in knowledge exchange or impact work.  

25 respondents provided comments in response to Question 27, which asked for any other comments on staff employment functions. 12% of those who answered the question noted a need for a more equitable naming convention, arguing that the term ‘non-academic staff’ undervalues the contributions of staff in this category; one other respondent noted separately that the work of non-academic staff is undervalued in the HE sector, and two noted that the line between academic and non-academic employment in HE is blurred. 16% of respondents to the question suggested that the ‘academic contract that is neither teaching nor research’ category should be broken down to give more information about such contracts. 12% noted that their institutions’ current employment contracts are based on the existing academic employment function categories, which would make changes to those categories difficult. 16% were concerned about the REF implications of any change, while others noted the need for clear definitions and the risk of introducing inconsistency.   

Question 28 asked what use respondents and their organisations would make of data on career stages in higher education. We received 68 responses to this question. The most frequently cited potential use of data on career stages was EDI analysis, which was mentioned by 26% of those answering the question. 22% said they would like to be able to identify groups of staff at different career stages, with 21% saying that such data would be useful for workforce planning and 19% saying that it would support the training and development of staff. 22% also said that data on career stages would be useful for sector benchmarking. Other respondents said that it would be helpful to be able to track staff progression, and that data on careers could be used to support statements about their research environment for the REF. 9% noted the need for consistent definitions of different stages.  

We received 63 responses to Question 29, which asked which career stages respondents would like to be able to identify on the basis of the Staff data. Respondents were particularly interested in early career stages, with 16% of those who answered the question saying they would like to be able to identify early career staff, 24% referring to early career researchers (ECRs) or post-docs, and 3% suggesting that data on teaching-focused equivalents of ECRs would be welcome. Many respondents suggested versions of a career ladder; while the most common suggestion was to describe staff as early career, mid-career, and senior (or late career), some listed specific job titles associated with each career stage. Several respondents suggested that it would be helpful to refer to different career ladders for teaching, research, and technical staff. 13% noted that consensus definitions of career stages would be necessary, and 3% suggested that the European Commission’s designated researcher profiles could be helpful.  

 Question 30 focused on ECRs, asking respondents for the criteria according to which they or their organisations define ECRs. Of the 66 responses to this question, 11% said that they had no agreed definition for ECRs, and 8% said that a consistent sector-wide definition would be helpful. Of those who had criteria for defining ECRs, the definition cited most often was that used in REF2021, which was used by 21% of respondents to the question; other popular definitions included the time since completion of a doctorate and time since beginning a first academic appointment, although the length of time that counted as early career varied between respondents. Several respondents said that they used the REF definition for their REF submissions, but had other, internal definitions of ECR status for other purposes. A few respondents said that their organisation allowed staff to self-identify as ECRs.  

Question 31 asked whether expanding the coverage of ORCID would help improve understanding of staff careers. Although 23% of respondents said it would be helpful, 27% said it would not be, and 44% said that they did not know or the question was not applicable.

Question 31. Would expanding coverage of the ORCID variable help your understanding of staff careers?  

We received 64 responses to Question 32, which asked respondents what use they or their organisations would make of linked Staff and Student data if such data should be available. The most frequent response, from 25% of those answering the question, was that they would make little or no use of linked data. Other respondents were divided about the potential usefulness of such data. 13% said it would be useful to be able to track the journey from study to work in the HE sector, while 8% said it would be good to be able to know which staff were studying, and another 8% said that it would be useful to know which students were employed by their provider. Several respondents said linked data could support staff development, while others said it would aid in equalities monitoring, understanding staff progression patterns, and the calculation of student:staff ratios. Several other respondents raised concerns about data protection issues and the burden of creating a linked dataset.  

Question 33 asked what use respondents or their organisations would make of being able to identify members of staff currently enrolled in study. Of the 63 respondents to this question, 14% said they would make little or no use of such information and seven 11% said they were unsure. Amongst those who said that they would use information about staff enrolled in study, the most common response, from 22% of respondents to the question, was that it would support skills and career development. 11% said such information could help with internal planning and 8% said it could help with EDI analysis. Although 11% said that being able to track staff members enrolled in study would be helpful, 14% said that this information was known and managed internally, and that they were not sure that a central source of data would be necessary.  

Question 34 asked for any other comments about staff career stages. Amongst the 57 respondents who had further comments, the greatest number of responses focused on ORCID. Opinions on ORCID varied; while 5% of respondents to Question 34 said that expanded ORCID coverage would not be useful, and one worried that ORCID would bring an element of personally identifiable data into the Staff record, 9% said that expanded ORCID coverage would be helpful, and 4% suggested that linking between the HESA Staff record and the ORCID database would be valuable. Other respondents raised questions about the use of the significant responsibility for research (SIGRES) variable, noted the need for consensus definitions, and commented on the need to collect careers data on staff in a range of different roles.  

Question 35 asked what use respondents and their organisations currently make of data on career progression. Of the 66 responses we received, 27% said that they made little or no use of such data and 11% were unsure. 21% of respondents to the question said that they carried out internal monitoring of trends in progression, and another 21% said that they used progression data in EDI monitoring. 9% said they used this data to develop recruitment and retention strategies, while 8% used it in workforce planning; 6% used data on progression to support career development initiatives. 12% said that they would like to make more use of data on career progression than is currently possible, 6% noted difficulties in collecting data on staff destinations, and 5% said that they were currently unable to use progression data at all.  

Question 36 asked what use respondents and their organisations currently make of data on staff who leave the HE sector. Of the 66 responses to this question, 38% said that they made little or no use of such data and 6% were unsure. The most frequently cited use of the data, mentioned by 17% of respondents to the question, was to help understand patterns in staff progression and turnover. 11% said they used data on staff leaving the HE sector for internal reporting, 9% said they used it in developing retention strategies, and 8% said they looked to understand staff members’ reasons for leaving. 6% said the data was useful for EDI monitoring. 11% said that their use of the data was limited by its availability or quality, while 8% said that they did not currently use data on staff leaving the HE sector but would like to do so.  

Question 37 asked what use respondents would make of data on career progression and movement out of the HE sector if such data were more readily available. Of the 67 responses to this question, 27% said they would not use such data and 9% were unsure. Other respondents cited a range of potential uses. 9% said they would like to be able to understand trends in staff destinations, and 15% said they would like to understand staff members’ reasons for leaving. 22% said they would use such data to inform retention strategies, 6% thought it would be useful for recruitment, and 9% said it would be helpful for workforce planning more generally. 22% said data on progression and leavers could help support staff career development, with a few noting that it could help to facilitate movement between the HE sector and other industries or to support collaboration. 9% said it would help with equalities monitoring, and 4% thought it could be used as part of a future REF submission. 19% said they would use data for sector benchmarking.  

Question 38 asked what difficulties providers face in returning complete data on progression routes to the Staff record. 65 respondents answered this question, of whom 14% said the question was not applicable and 8% said that they were unsure. The remaining respondents cited a variety of difficulties, most focusing on ACTLEAVE and STAFFID. 29% of those who answered the question said it was difficult to get reliable data for the ACTLEAVE field, with a further 35% commenting that low levels of engagement from leavers made collection challenging and 8% mentioning specific difficulties with collecting ACTLEAVE from fixed-term and hourly-paid staff. 28% said it could be difficult to obtain STAFFIDs from previous employers, with a further 6% mentioning that the Staff record contact list was not always up-to-date. Some respondents cited specific difficulties with the process of collecting STAFFIDs, including technological barriers and the risk administrative error. 5% suggested that staff members should know their own STAFFID numbers and report them to new institutions on arrival; another 5% suggested that a centrally-held database of STAFFID numbers would be helpful. One suggested that the Staff record could include National Insurance numbers as an alternative to STAFFID. 8% stated in general terms that collecting progression data was either burdensome or difficult to do reliably.  

Question 39 asked whether respondents would support the inclusion of personal identifiers such as names to enable better longitudinal tracking. 18% of respondents said they would support the inclusion of personal identifiers, 60% said they would not support this idea, and 22% said they were unsure or that the question was not applicable. Many respondents added further comments on the inclusion of personal identifiers in their responses to Question 40.  

Question 39. Would you support the inclusion of personal identifiers, e.g. names, in the Staff record in order to enable more reliable longitudinal tracking?   

Question 40 asked if respondents had any further comments on career progression or staff members who leave the HE sector. Of the 59 responses to this question, 42% said they had no further comments. One respondent noted barriers for career progression for support staff, and another suggested that fuller data on non-research careers would be valuable.  

Most of the other comments we received concerned the collection of personal identifiers. 18% of respondents to the question were concerned about the burden and data protection risks of collecting personal identifiers, and 14% were worried that staff would not agree to submit personal information if names were collected. 7% were concerned that collecting names would introduce new sources of error, a few noted that names might change and are not necessarily unique, and a few worried that the collection of names would alter the anonymized nature of the HESA Staff return. Some respondents said that they wanted more data on career progression but did not want to submit more personally identifiable data, while others wanted to be sure that other options had been considered or were happy with the collection of names so long as there was no need to add names retrospectively to older Staff data. Two respondents suggested the inclusion of National Insurance numbers (in addition to the one who made the same suggestion in response to Question 38), and one suggested that it would be useful to have a centralized, searchable database including names, dates of birth, and STAFFID numbers.  

69 respondents gave details in Question 41 on the kinds of information that would be helpful to capture on fixed-term or part-time contracts. Personal characteristics was mentioned the most, followed by length of contract, length of service and career progression. Respondents talked about wanting to understand how many contracts a staff member has had, when contracts got renewed, and therefore the time that staff members spend in precarious employment overall.   

There were 66 answers to Question 42 about the distinction between shorter and longer fixed-term contracts – 18% did not think this was a helpful distinction to make in the Staff record. Of those who proposed a split, 36% stated a preference for one year, 41% stated two years. (Of the whole population this was 21% and 24% respectively).   

Of the 64 respondents who answered Question 43 about what use they would make of data on staff members’ previous terms of employment, 42% stated they would have limited or no use for the data, and 13% stated they were unsure. Among those who indicated they would use this data, EDI monitoring, understanding career progression, and recruitment targeting were the most common responses.   

 Of the 69 respondents who answer Question 44 about what use they would make of data about whether staff working part-time are also employed elsewhere, 30% stated they would have limited or no use for the data, and 13% stated they were unsure. For those who indicated a use, career progression and checking compliance with legislation such as the working time regulations or visa restrictions where the most comment responses. Understanding whether staff were working multiple jobs by choice or because of a lack of opportunities was also raised, although one respondent was concerned about whether staff would offer this information in the collection of data.   

62 respondents answered Question 45 about the difficulties in returning staff identifiers, 8% of whom indicated that they didn’t have any difficulties. The majority of respondents explained that the resource and time consuming process was the most problematic part of returning staff identifiers. Other common responses included: determining which provider to contact, lack of responses, and the fact that not all staff members have a previous identifier (either because the provider did not submit to the Staff record, or because the particular contract was outside of the coverage of the Staff record). It was suggested by some that a central database to search would be the most helpful here.   

For Question 46, which asked for additional comments on employment conditions, we received a variety of responses. Some respondents acknowledged the benefit of having sector-wide definitions, and others suggested their preference for different data items that could be collected. Some raised concerns over the nature of the term “precarious employment”, which implies that staff do not want to be on these types of contract, although it may be the staff member’s choice to be on this type of contract. There was also acknowledgment that precarious employment is a weakness in that we do not fully understand what is happening across the sector, and some respondents agreed that collecting more data would help improve our understanding.  

58% of respondents supported collecting more data on sexual orientation and gender identity, but only 31% supported collecting more data on marital status.   

Question 47. Would you support collecting data on sexual orientation and gender identity in the Staff record on the same basis on which it is currently collected in the Student record?   

Question 48. Would you support the collection of data on marital status across the whole of the UK?   

We received 66 responses to Question 49 asking about use of data on staff members with dependents and caring responsibilities. 74% were supportive of collecting more data, stating that it would help guide policies, help with monitoring EDI characteristics, and could be useful for the organisation to understand and benchmark with others. Some indicated that they collect this internally already.   

13% were not supportive of collecting more data, saying it would difficult to capture and maintain this data and responses rates could be low. Some said there wasn’t a clear purpose to collecting this in the Staff record. Others indicated that they would collect it internally but couldn’t see a value in this being reported externally.    

We received 62 responses to Question 50 about data on other personal characteristics of staff. 47% of respondents couldn’t identify any other data items. 45% of respondents had a suggestion for other data items they would like to collect, including socio-economic background and further information about gender identity.   

Some of the uses given for this data were about EDI reporting, benchmarking and helping with various policies. One respondent would like more demographic data to be accessible via open data sets.   

Question 51. Do you have other concerns about the personal characteristics data which is currently collected?  

Reasons given for the concerns about collecting personal characteristics data included: Staff being uncomfortable in providing the data, sometimes leading to more unknown values returned; problems with data quality, especially when trying to get staff to update details each year; being unclear about the value of collecting the data, particularly when the coverage differs across the sector.   

Other comments raised about personal characteristics data were around the potentially intrusive nature of collecting the data, particularly where this is sensitive or time-sensitive. Definitions need to be clear to staff to avoid any confusion. Many respondents could not see the value in some of the data items or how they could be used to support policies, but others named specific uses internally. Some respondents were unhappy with the recent changes made to these data in the Staff record and felt they were unnecessary or were particularly burdensome.   

Of the 68 respondents to Question 54, 43% stated they would use nationality data in for EDI reporting, and 21% mentioned either right to work checks or using it alongside visa status for ensuring Home Office compliance. A few other internal uses were mentioned, including benchmarking and identifying groups for support in times such as national disasters. Among those who said they would be interested in particular splits of nationality data, most wanted to see data split between UK and non-UK (sometimes with the EU split included too). 9% of respondents stated they would not use nationality data.   

38% of the 66 respondents to Question 55 stated they would not use visa status of HE staff data if it was included in the Staff record. Some respondents mentioned that they use it internally but did not see the benefit of it being included a nation-wide dataset, mentioning sensitivity of the data, that collecting it would be intrusive, or that it is regarded as a legal matter. 23% said that benchmarking would be their primary use, whilst others indicated different types of analysis or planning activities, including assessing reliance on non-UK staff.   

15% of the 60 responses received didn’t have any concerns about the potential inclusion of visa data. 18% were concerned about the increase in burden to report this data in the Staff record, 13% were worried that adding this data could make staff identifiable (especially when combined with other data items), and 12% indicated that the status could change during the year and therefore data quality could vary. 27% asked for more clarity about what the data would be used for and the value providers would get from including this data.   

Question 57. Would you support the collection of 4-digit (as opposed to 3-digit) SOC codes to promote understanding of which roles in the HE sector are eligible for visa sponsorship?   

36% of respondents would support collection of a 4-digit SOC code to promote understanding of which roles in the HE sector are eligible for visa sponsorship, whereas 27% did not support it.   

Of the 59 respondents to Question 58, on the potential uses of data on staff roles on the shortage occupation list, 31% indicated they would make limited or no use of such information. 17% were unsure of their use or wanted more information before they decided. Of those who said they would use the data, the majority (29% of those who responded to the question) indicated they would use it in some form of recruitment strategy or workforce planning.   

Respondents to Question 59 took the opportunity either to reiterate their support for collecting more data on visa status or to express their concerns about doing so (9% and 10% respectively). There were also some concerns raised about the potential increase in burden if we were to move to 4-digit SOC coding.   

Among the 58 respondents to Question 60 a number of different areas were raised, including the burden versus benefit of adding more data items into the Staff record, the timing of the implementation and the need to give providers enough notice to make the change(s), and the need to be clear on the use of the new data items proposed. A number of specific suggestions were also made, such as the cross over with the MSC return and linking in with the REF2028 activity.   

21% of the 58 respondents to Question 61 complained about the timing of the consultation – saying that it should have been held either before or after the Staff record data submission period. The timing of the consultation made it difficult to find enough time to respond and engage the relevant staff members at providers. Other respondents reiterated specific parts of the consultation they would like to see implemented or important uses for the data proposed.   

A few respondents showed their support for the review happening with the Staff and thanked us for running the consultation.