Research from SINTEF, the largest independent research company in Scandinavia, suggests that more data has been collected over the past two years than in the entire history of the human race. The convergence of several technology trends is accelerating this process, resulting in greater access to data, enhanced data storage, faster data mining and innovative utilisation of data in technologies such as AI. So how are businesses taking advantage of this exponential growth in data, and who do they need to hire to create a successful data and analytics function?
Agile, digital firms that have successfully integrated data and analytics into their business strategy have gained a competitive advantage over firms who bear the burden of legacy systems. A recent article published by the McKinsey Global Institute (MGI) cites that the shift from a ‘world full of data’ to a ‘data-driven world’ has been difficult to implement, resulting in companies capturing a fraction of the potential value that can be extracted from data & analytics.
As more companies prioritise integrating data & analytics into business strategy, the demand for talent has vastly outstripped supply. A McKinsey survey of executives across industries and sectors found that approximately half reported greater difficulty in hiring analytics talent than any other role, with 40% suggesting that retention is also an issue.
“Technology is no longer the main barrier to creating business value from data: The bigger barrier is a shortage of appropriate skills.” – The Talent Dividend, MIT Sloan Management Review
The shortage of talent can in part be explained by a skills and training gap in data & analytics due to rapid growth. However, MIT suggests that the range of analytics skills, roles and titles within an organisation has also broadened in recent years. Data scientists are now divided into Data Architects, Engineers and Scientists/Analysts, with each role carrying subtle differences and requiring nuanced skill sets. Furthermore, executive roles in data & analytics are becoming increasingly prominent, such as Chief Data Officers who are responsible for extracting value from data by aligning it with business strategy.
Despite both the shortage in talent and the broadening of data & analytics roles, MIT found that only one in five organisations have changed their approach to attracting and retaining analytics talent. In order to realise the benefits of data & analytics, firms must adopt a talent strategy that considers not only how to source and attract high calibre talent but also how to retain it.
Companies must look globally to source top talent. MGI suggest that there is a shortage of 1.5 million managers in data & analytics, so it is vital that firms adopt a global approach when formulating their talent strategy to maximise their access to candidates. According to Data Science Central, the US has the most executives when it comes to data, whereas countries such as India and Singapore have a growing number of data scientists who can also bring a fresh perspective and approach.
When considering the talent pool for data & analytics, companies should look across a variety of industries and sectors to access the best individuals, rather than narrowing the candidate pool by focusing on a particular sector. They must be creative in their approach to sourcing talent, identifying skill sets they require, and be flexible on background and in particular previous industry experience. Data & analytics should be viewed as a business function that permeates across industries and sectors, particularly while it is still relatively immature.
There must be a clear vision from the firm around how they intend to use data in relation to broader business objectives. Data & analytics executives such as Chief Data Officers can add significant value in this scenario as they act as the interface between data teams and business strategy. On the one hand they must be technically sharp enough to manage data teams, and on the other they must have the necessary gravitas and business acumen to drive data & analytics growth both internally and externally as the face of the business. This is a unique set of skills in the current data & analytics talent market but is pivotal in defining a data & analytics strategy. Demonstrating a clear vision for data & analytics is vital in attracting and retaining talent as analytically minded people naturally seek environments where there is a clear direction for growth.
The rapid increase in the demand for Data Scientists has, unsurprisingly, led to remuneration following a similar trend. MGI found that remuneration in the US for Data Scientists rose 16% from 2012 to 2014, compared to a less than 2% increase in the nominal average salary. For firms to attract and retain the best data & analytics talent there is a need for an appreciation of the rising cost of Data Scientists. The speed at which the data remuneration market is increasing requires an equally fast response from companies to remain competitive.
In the long term, the data talent shortage will be addressed from the bottom up through data fast-track schemes, training courses and increasing education at undergraduate and postgraduate level. Our analysis of talent trends indicate that on an institutional level firms are addressing the data talent shortage by selecting graduates with engineering backgrounds and placing them into areas such as Corporate M&A where they can develop in a client centric environment. Though this may seem counter-intuitive, by combining analytical backgrounds with client centric functions it will create analytical talent which is both technically astute as well as commercial.
In the medium term, AI and machine learning will also contribute to filling the current talent gap as labour intensive data mining will become automated; however, these developments do not address the short-term lack of executive talent in the data & analytics industry.
In the short-term, adopting a progressive talent strategy which focuses on how to source, attract and retain executives can enable businesses to more quickly realise the benefits of data & analytics and align them with business objectives. By initially focusing on management it creates vision, direction and ultimately growth, which are crucial factors in building and retaining data & analytics teams.