Sometimes it is difficult to really grasp the extent to which the power of information technology has increased over the past couple of decades. Although there are plenty of numbers that describe our computers, the ever changing units of measure (kilobytes, megabytes, gigabytes, terabytes etc.) render the whole thing pretty meaningless.
Today, a single Excel worksheet today can store 17.2 billion items of data. What was, until fairly recently, industrial-scale data processing can now be undertaken by anybody with access to a laptop. We have passed the point of being enabled by the technology and are now facing up to the reality that we need to rethink our individual and organisational capabilities in order to deal with these ever increasing volumes of data.
The focus on data capabilities stepped up a gear in 2013 when BIS published its Data Capability Strategy. This put data capability firmly at the heart of the country’s broader industrial strategy and set out a number of bold recommendations and challenges. Key to this agenda is understanding the extent to which data capabilities make a difference to organisations and how the demand for these skills can be met.
Today sees the publication of two significant reports that attempt to find some answers to these questions.
NESTA surveyed over 400 organisations to gain a better understanding of how they were using data and what sort of impact it was having on their organisational performance. The report – Skills of the Datavores – concludes that organisations that are more “data-active” perform better than those that are not. It highlights the challenges of recruiting and upskilling data scientists and finds that companies are using innovative approaches to developing the data skills of their employees; Universities are the least popular source of training.
Universities UK has undertaken a review of how data analytics skills are taught across different disciplines. It reflects on the difficulties of pinning down exactly which skills employers need in this area, especially since the broadly-accepted view is that a good data scientist requires a combination of different skills, including technical skills, domain knowledge and the ability to transform data outputs into something that is genuinely valuable to organisations. This is compounded by a shortage of academic staff confident in teaching data analytics and by students entering HE with varying levels of statistics and computer science skills.
Together these studies set out a series of recommendations that cover the whole pipeline of talent from schools, colleges and universities into the labour market and industry.
In higher education, data issues are increasingly at the forefront of policy thinking. Data (or metrics if you prefer) are all central to the current debates including the TEF (“to include a clear set of outcome-focused criteria and metrics”) and the REF (we need a Forum for Responsible Metrics; they can complement but not replace peer review), in addition to more established issues like UNISTATS and the league tables. One of the most interesting developments in this area is the decision by the HE Commission – having previously considered issues such as the financial sustainability and regulation of the sector – to look at the impact of data and digitisation on higher education in its next study.
Universities themselves are increasingly voracious users of data and many have invested heavily in business intelligence and analytics capabilities. HESA and Jisc are working together to develop new services and increase analytical capabilities within the sector and HEDIIP has received a massive response to the launch of its Data Capability toolkit which focusses on the less glamorous, but essential foundations of data management and governance.
In 1967 Jimi Hendrix captured the spirit of the moment with the question Are you Experienced? Although “Are you Data Capable?” doesn’t have the same louche appeal, it is increasingly the question that organisations across the country are struggling to address. HE is in the unique position of being both a supplier of skills and a sector that needs these skills itself; we are sitting at both ends of the telescope and perhaps could learn much from ourselves.
Exactly. We are a data science consultancy uniquely working on the two halves of the HE data conundrum. We both work with HE organisations to use their data more effectively for insights,discoveries and decision making and work with education including HE to develop the data scientists of the future. Both startegies are sorely needed.
One of the things I want to do as I enter the Higher Ed profession is to become data literate. With the massive amounts data accrued by educational institutions data analytic’s becomes more important everyday. I want to learn data analytic’s in order to make better decisions that help students as well as meet the increasing accountability standards set forth by government.