Digital transformation and analytics are nearly inseparable. “At the core of any successful digital transformation is the ability to leverage the company’s data assets to drive superior customer experiences, products and services as well as operating model efficiencies,” says Scott Snyder, a Digital and Innovation Partner with Heidrick & Struggles, and co-author of “Goliath’s Revenge: How Established Companies Turn the Tables on Digital Disruptors.”

Companies typically need data science know-how in order to connect data to analytics or algorithms and deliver digital insight. “Without a critical mass of these data science and analytics skills, companies will struggle to keep up with both customer expectations and new innovation opportunities,” Snyder says.

The gap between supply of and demand for data sciences skills is a problem IT leaders know well. One the one hand, data is growing at an exponential rate. “It’s widely reported that 90 percent of the world’s data has been generated in the last two years, and with data doubling every 1.2 years on average versus processing speed only doubling every one to 1.5 years, companies must become more efficient at analyzing data to keep up,” says Snyder.

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The impact of AI on modern work environments

It is not hard to find examples of how AI has transformed entire industries, from automating many parts of the car manufacturing industry to allowing automatic decision-making based on pre-set criteria in the stock market.

In fact, a recent study by IBM found that 76% of operations executives felt that increasing automation would have a positive impact on operational efficiency (IBM Corporation, 2017). This reflects the widely held view that AI must work hand-in-hand with human intelligence and skills for maximum benefit.

The HR function itself is no stranger to AI. In general, the HR function has embraced the benefits of software to automate labor-intensive HR processes within the employee lifecycle. Examples include time and attendance tracking and payroll processing, which many companies have automated for a couple of decades.

But it is only more recently that organizations are recognizing the opportunities to invest in AI to further their company’s HR strategy. Combining AI with irreplaceable employee skills and experience can offer organizations a competitive advantage in a crammed marketplace. A great example of this is in the field of diversity and inclusion, and using technology to reduce the likelihood of bias or discrimination in an organization.  

The case for an inclusive working environment

Before we consider how AI has the potential to promote a more inclusive work environment, let’s discover why it matters so much.

The organizations of today’s modern world operate in a global environment. No longer confined to a marketplace within their geographical area, the world is their oyster in terms of engaging with new markets and potential customers, thanks to the internet and faster, more reliable air travel. As a result, smart businesses must embrace the creation of a multi-dimensional workforce that reflects the makeup of its markets in terms of gender, race, age, sexual orientation, and other characteristics. It is quite simply the right thing to do—offering opportunities to individuals based purely on merit, skill, and hard work.

Of course, there is a regulatory aspect as well—many countries operate laws relating to diversity, and therefore, an organization that can demonstrate their commitment to the issues confidently will ensure compliance in this area.

Specific ways AI can promote inclusion

Technology has a vitally important role to play in advancing the diversity agenda in an organization. One of the highest impact ways is ensuring an inclusive approach to recruitment.

Human bias can take different forms, whether intentional or unintentional. This can have devastating effects on the inclusivity of the recruitment process. AI can help enormously with this, by implementing consistent and fair assessment and screening criteria using simple keyword technology to ensure that candidates are shortlisted based on their skills and experience only.

Technology can also help job advertisements to appeal to a wide demographic of potential employees by looking at response history data, and subsequently writing job descriptions that are inclusive and appeal to a diverse range of applicants.

Through the looking glass: the future of an inclusive workplace

We have come a long way in terms of embracing how AI can partner with human capital to make tangible efficiency gains throughout the workplace. But there are so many opportunities to take this further in the future. For example, work is underway to extend the use of technology that removes user bias when processing payroll or using performance appraisal matrices.

AI also has the potential to use historical data within HR software systems to create profiles based on culture, using leadership and communication styles and giving organizations insights to help them create more inclusive and better-informed policies and HR processes.

AI within the workplace is not only here to stay, but is set to accelerate the pace of change across organizations and industries as a whole. It is how it works in partnership with the other part of the puzzle, human skill and intelligence, that will determine how successful it will be in reality.

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Job-seekers owning demonstrable experience with data may soon overtake those with data science degrees when it comes to openings in international enterprises, according to a major survey of global business decision-makers commissioned by data and analytics firm Qlik, on behalf of the Data Literacy Project.

Almost two-thirds (59 per cent) of both global and APAC enterprises surveyed ranked prior job experience or a case study interview (where candidates are tasked with solving hypothetical business problems) as the top indicator of a candidate’s data literacy. By contrast, only 18 per cent globally and 15 per cent in APAC viewed a Bachelor’s or Master’s degree in science — let alone data science — or even a Doctorate degree as a primary consideration when hiring.

This means the opportunity to take advantage of improved career prospects and salaries associated with data literacy is not limited to those with degrees in data science or STEM subjects. This follows a wider trend identified by Glassdoor that an increasing number of technology companies are ditching the degree in favour of these skills, helping candidates get their foot in the door.

Most businesses (63 per cent globally and 57 per cent in APAC) are actively looking for candidates who can demonstrate their ability to use, work with and analyse data. Indeed, those with a foundational understanding of data and analytics will account for one-third of the job market, with a projected increase of 110,000 positions by 2020, a 14 per cent increase since 2015, according to IBM.

This is perhaps unsurprising given the massive growth opportunity for data literate organisations, those with higher levels of individual data skills, data dispersion across the enterprise, and data decision-making. Qlik’s Data Literacy Index revealed that large enterprises, which are more data literate, experience a 3 to 5 per cent higher enterprise value (the total market value of the business), representing an additional USD 320- 534 million for the surveyed organisations.

But DSA (Data Science and Analytics) jobs, which include all data-informed roles, from data scientists and data analysts to business analysts and data-enabled marketing managers, are the hardest to fill, typically remaining open for 45 days.

With a crisis affecting the entire data skills spectrum, and notably just 24 per cent of global employees confident in their data literacy abilities, these highly sought-after skills can help people become more valuable to employers and translate into higher personal income.

While not all business leaders surveyed were aware of how their firm remunerates data literate employees, Qlik’s survey revealed that 75 per cent of those up to speed on their company’s policy reported paying higher salaries to employees with the ability to read, work with, analyse and engage with data.

Despite recognising the value of on-the-job experience and data certifications, 50 per cent of companies globally said they don’t provide data literacy training to their own employees. Only 34 per cent of decision-makers globally and 36 per cent in APAC state they have programs in place. This is despite 78 per cent of global employees and 72 per cent of APAC employees saying they would be willing to invest more time and energy into improving their data skill sets.

Those individuals motivated to pursue their own upskilling have the opportunity to supercharge their career and unlock new opportunities, particularly as data grows in importance across all enterprises. Eighteen percent (18 per cent) of business decision-makers globally and 21 per cent in APAC said that a data-skills certification (something that can be earned well after college or formal education) was the best indicator of a candidate’s data literacy and demonstrated the ability to use the techniques most required today.

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