Earlier this month, new data revealed how badly the tech sector is hit by staff shortages, with a deficit now approaching 70,000. Demand clearly exceeds supply, and the simple fact trying to hire more tech workers is no longer a sustainable or viable option.
The result is that retraining, upgrading skills and training employees is more crucial than ever for companies hoping to build a workforce that is digitally ready and capable of leading their business into the future. Yet given the scale and complexity of this growing skills gap, neither employers nor universities can solve this problem on their own.
This makes Employer-University Collaboration (EUC) a necessary imperative if we are to meet both the employment needs of individuals and the talent needs of employers. However, existing models of CUA, such as apprenticeship, are struggling to keep pace with change.
If we are to harness the true potential of EUC as a solution to the growing skills gap, we need to start supporting and implementing more diverse, agile and flexible collaboration formats.
Why is it eemployer-university collaboration necessary?
The digitalization of the global economy has been dramatically accelerated by the coronavirus crisis, with companies’ digital transformation programs advancing up to 7 years. Therefore, our post-pandemic economy will almost certainly be different from the one before it. In fact, the World Economic Forum predicted that the digitization of the global economy will result in the loss of 85 million jobs, mostly due to AI and automation, while simultaneously creating 97 million new jobs.
If we are to be successful in this new economy, tomorrow’s workforce will need specific and different technological, social and emotional skills, as well as superior cognitive skills. While individuals and employers always look to universities to develop these high-level capacities, the higher education sector is uniquely positioned to prepare learners with the technical skills they need to play a role in the field. digital economy and equip them with high-level capacities. to accelerate their career.
The sector has started to respond to this challenge by approaching employers (mainly through partnerships with industry) in recent years, tailoring its offerings according to the ever-changing needs of students in terms of employability and needs. in industry talent. However, these efforts were limited by two major hurdles: speed and scale.
The traditional university system has faced challenges in ensuring that content, curricula and learning experiences can be built at the pace of the change needed to keep pace with the digital economy. For example, it often takes more than 18 months to develop a new undergraduate course, and the typical course refresh cycle is close to 5 years. The result is that while higher education generally provides a good foundation for pursuing a future career and offers the right vehicle for developing the capabilities required by an increasingly advanced digital economy, existing EUC efforts have often failed to deliver updating at the speed and scale that employers and individuals need.
Is the learning model scalable?
Apprenticeship is a useful example to illustrate the need to rethink the way employers and universities collaborate. By offering the possibility of combining work and study to acquire skills and knowledge in a specific job, this model of EUC has created new opportunities for people to enter the labor market. It has also garnered significant political support and a strong incentive for employers to fund places in recent years, as the UK government introduced an apprenticeship tax in 2017, forcing companies with payrolls over £ 3million. sterling to set aside 5% of salary costs for training. At work.
However, the challenge with the model is that it only serves a very limited segment of learners, which fundamentally limits the impact that funding can have in bridging the digital skills gap in the UK. More importantly, apprenticeship programs are currently not aimed at those who need to develop new technical skills to perform better in existing roles that have undergone a digital transformation or those looking to move on to other professions. declining in the tech industry by studying part-time.
For example, funding can be used to move into a new role within a business, such as when you move from a bank teller to a data analyst. However, you cannot use the funding to improve your skills in your current role (which may have become much more technical) or move to a new role in a new business or industry.
This is especially important given that one in four people over 45 are now considering a career change, which means reaching this demographic will be essential if we are to meet the growing demand for high-growth tech positions. However, as most of the funding is directed to the learning model, we are sitting on an untapped gold mine.
The Case for Funding More Diversified EUC Formats
The scale of the challenge ahead clearly demands an evolutionary response but, as has been made clear above, traditional models of EUC have simply failed to evolve, especially those that are only focused on skills and improving employability chances. Now is the time for the government to build on the recent success and foundations of the learning model and start thinking about distributing funds to more impactful and scalable CUEs.
There are many examples of these more agile models at work, such as when universities engage in new partnership models, which offer programs that can be developed and expertly designed with industry and deployed quickly, regularly updated and adapted to use. For example, Coventry University has partnered with FutureLearn, a massive open online course (mooc) platform created by the Open University, to launch credited micro-accreditation courses.
As the transition to a more digital economy requires a workforce with highly developed digital skills, along with, for example, complex problem-solving skills and adaptability, another example is our recent program. “Career accelerator”. These unique 6-month online courses help develop the technical knowledge and practical skills necessary to perform in real roles, as well as the cognitive abilities essential for continued growth and the human skills essential to obtain and maintain employment.
What these collaborative models have in common is that they make it easier for universities to offer up-to-date, market-oriented curriculum in a flexible way that will expand access for learners. This means that they can help prepare people with the technical skills they need to take on a role in the digital economy, and also equip them with the next level capabilities to accelerate their careers. Unlike the learning model, they also allow people of varying backgrounds, backgrounds and ages to access the technical, analytical and human skills they need to thrive in the digital technology industry, which democratizes accessibility and facilitates scalability.
Rethinking our approach to EUC
To enable people to lead fulfilling and successful economic and social lives, and for the economies of the future to succeed, we must bridge the digital capacity gap. Huge strides have been made in the EUC in recent years to close this gap, but if we are to take seriously the scale of the challenge that lies ahead, now is the time to start thinking more about speed, speed. scale, agility and flexibility.
Simply put, if we are to address the current mismatch between the huge demand for digital talent and the dramatic shortage of educated and working professionals with the required digital capabilities, support must be provided for new agile forms of EUC before they can be found. ‘it’s not too late.