The twenty-second of November should be marked in your calendar.
That’s the deadline for the official, twice-delayed sign-off date for the Jisc/HESA Data Futures return – the date by which all validation checks must be passed and all the subsequent data queries addressed and signed-off.
The funders and regulators who depend on this data continue to offer pragmatic flexibility around the deadlines, recognising the problems that have been encountered in the delivery of Data Futures by many, if not all, stakeholders.
These delays also knock on to the tightly-packed calendar of annual data returns and events; HESES, Finance Return, ILR, NSS, Graduate Outcomes, and so on.
At the eye of this storm is a thinly-spread cadre of higher education data professionals. These are the people tasked with making the data returns; the people who have to digest hundreds of pages of dense, technical coding manuals in order to prepare and quality assure their data submissions. This community has spent the last few months wrestling with a data collection system that has encountered a myriad of problems, most painfully the inability of the validation systems to correctly reject data which is bad and accept data which is good.
This community is used to pressure. Deadlines are always tight and the quality thresholds are demanding. As funders, regulators, and league-tablers seek to drive increasing amounts of value from data, the significance of these data submissions ratchets up year after year – and the impact of poor data submissions becomes ever more painful.
Every year the autumnal peak of data returns is accompanied by an outbreak of gallows humour in student records offices across the land, and on social media. There are occasional howls of frustration and a smattering of ennui as the sector’s data professionals wrangle their datasets into shape and chase down the errors and queries to arrive at the rite of the data sign-off.
One way or another I’ve worked with this community for over thirty years and I’m sure they won’t mind me saying: they’re an unusual bunch. Not in a bad way; they are the most lovely, brilliant, tenacious, and thoroughly professional people you could wish to meet. They have a great sense of camaraderie and shared experience and an underlying feeling of “how did I get here?” They come from such a wide variety of professional and academic backgrounds and I’ve never met one who had “doing the HESA return” as a career goal in their earlier life.
And herein lies the rub. HE institutions are critically dependent on their data professionals to meet the rapacious demands of funders and regulators and to satisfy the aspirations for data-driven insights that will create better organisations and provide better and more targeted student support. But we often struggle to articulate the skills and knowledge required to undertake these roles. Anecdotally we know it is becoming increasingly difficult to recruit and retain these staff and in many cases there’s little sense of a defined career path once you’re on the treadmill of data submissions.
The recent Wonkhe/Advance HE study into the changing people needs of higher education highlighted the significance of data technology as a driver for change and the challenge of developing capabilities to meet future needs. Similarly, Jisc is emphasising the need to put people at the heart of digital development in HE.
Growing the community
The challenges here are broadly understood; so how can we better support, grow and develop our community of data professionals?
We need to recognise that the community of data professionals transcends the myriad of professional groups in HE. This issue belongs to no one group or community; we’re all data professionals now and some kind of broad collective action is necessary to achieve change across the range of roles and professional disciplines in this area.
And we need a clear definition of the data skills we need so that we can create some kind of professional standards and career path for the data-centric roles in HE. This could include a competencies framework for data skills, supported by a training pathway or apprenticeship standard that covers both the science and the art of data.
It’s important that we make these roles more desirable in the eyes of aspiring data scientists. This is not just about salary levels. There is something about the lack of prominence of these capabilities in organisational design; a failure to properly acknowledge the value that these roles can and do deliver to institutions.
My final suggestion is a little more immediate and is addressed directly to leaders across the sector.
Some of your data professionals have had a terrible time these past few months. A few have taken to social media to vent anger and frustration at the Data Futures experience; many more have suffered in silence. There have been immense levels of stress and exhaustion, exacerbated by the knowledge that the stakes associated with these data returns have never been higher. Some have been damaged by this experience; some have been broken.
Right now, you need to show them some love.