The past 12 months have shown that we are now living in a truly digital era. On a personal level, employees use mobile devices all day, every day to communicate, and technology architected in the cloud has allowed us to collaborate continuously. More broadly, technology is driving business change and growth across almost every major sector. According to Microsoft CVP Deb Cupp, digital transformation is no longer a competitive edge for specialised businesses, it’s now a must-have. And, thanks to the latest report from Microsoft and the Economist, we now have some raw numbers behind this, with 72% of enterprises reporting that their pace of transformation has sped up significantly over the last 12 months.
With businesses now investing in digital tools, many are seeing the opportunity this has created. Tech-forward transformations have improved existing revenue streams, and created new ones, but they have also delivered a vast increase in the amount of data available to decision makers. Businesses are therefore focussing firstly on how they collect and process this newly generated information. Increasingly though, many are considering the best way to analyse and interpret this wealth of data in a meaningful way as they continue their digital journeys.
In this context, data analytics has become a crucial function of almost every business. This was reflected by our recent survey at FourthRev, which revealed that data analytics is among the top three skills enterprises value right now. This isn’t surprising either. Data helps companies predict customer trends and behaviours. In turn, this has enabled them to adapt their services and deliver better value and experiences to their customers. From the executive perspective, data analytics has increased business productivity, improved innovation and helped streamline the decision-making process.
Despite all of this, according to EY, 81% of leaders are not able to derive actionable insights from their data, and only 33% are confident that they can make and implement decisions quickly.
Why is data analytics important for HR?
The question for many will be what this means from a HR perspective. Firstly, it’s important to recognise that people analytics has become critical to the future of HR. The same programs, platforms and tools that businesses have been investing in can leverage data for all aspects of workforce planning, talent management and operational improvement.
Secondly, businesses will be thinking strategically about how they can operationalise the data they are generating and maximize actionable insights. Having the right skill sets in the business either by retraining or recruiting is central to a company’s ability to access its data . McKinsey’s latest Global Survey on technology and business revealed that across ten major transformation initiatives, respondents say that changes to their people and talent strategies are among the highest value moves to make. By contrast, they are also the least likely initiatives companies plan to pursue in the future.
HR directors therefore have a unique opportunity to transform the future of their businesses by taking a proactive stance towards the talent that will enable their success. The results of leading in initiatives like these are also obvious. The top quartile respondents of McKinsey’s survey were more than three times as likely to pursue this proactive approach when compared to their peers.
How should we improve capabilities in the workforce?
A major and universal challenge is therefore addressing the talent and skill gaps that are handicapping companies undergoing digital transformations. Currently, only 15% of employers are planning to pursue a talent strategy transformation in the next two years, and existing training programmes are failing to deliver the correct technical qualities.
Similarly, traditional degrees are also failing to satisfy talent shortages. Graduate unemployment in the UK is currently worse than the austerity era. And, whilst this statistic has undoubtedly been affected by job shortages created by the pandemic, it comes at a time when demand for tech-related roles has significantly increased.
It is also not a new phenomenon. Skills gaps have been spoken about extensively for the past decade. Back in 2014, Aftercollege reported that nearly half of all American graduating students agreed that college did not prepare them for the working world, and 83% did not have a job lined up when they graduated. Our own research from this year is evidence that this problem still exists, with 54% of employers reporting that they find it difficult to source candidates for entry level jobs.
Despite this, it is clear that both employers and universities have clear roles to play in solving the issue. Employers possess in-depth knowledge of the technical capacities of the moment. For example, right now, data analysts require hands-on knowledge and experience with the infrastructure, tools and controls on data quality, and competence in data science.
Likewise, universities still deliver unique strengths. They equip students with important creative and complex capabilities from problem-solving and adaptability to the ability to learn itself. Universities are therefore uniquely positioned to combine this traditional expertise with the development of applied digital skills led by industry partners.
This best-of-both-worlds approach will be critical to filling the skills gaps in data analytics and other key areas such as cyber security and computer science. A new education model in this guise offers an opportunity for the workforce to unlock high-growth digital careers, and in turn provides HR directors and employers with the talent and people they need to succeed.
