The future of work is all about getting useful business insights from data

Source: Omron Electronics.

The advent of robotics and artificial intelligence (AI) has touched a raw nerve for anyone who works. A lack of skilled people in various sectors has made automation in all its forms much more attractive to employers, and it is clear that automation and AI can replace a great deal of what humans do today.

The response has ranged from positive – an Oracle study shows that 93% of people would trust orders from robots at work – to adaptive – Ericsson's 10 hot consumer trends for 2019 include one about how 31% of consumers soon expect to go to ‘mind gyms’ to practice thinking, as everyday decision-making becomes increasingly automated – to negative.

“Some businesses continue to face resistance from employees who feel threatened by automation. Businesses also face a skills gap in the advanced technology sectors such as robotics, data and AI,” observed Lieu Yew Fatt, MD, Omron Electronics.

Source: Oracle Netsuite.

Naishtein.

“To guarantee the successful adoption of AI, organisations need to prepare the workforce by addressing potential AI skill gaps through training,” said Ronen Naishtein, GM, Asia, HK & TW, Oracle NetSuite.

Manish Bahl, Assistant VP, Center for the Future of Work, Cognizant Singapore echoed Lieu and Naishtein: “Business leaders in Asia Pacific have just scratched the surface in terms of how to leverage AI technologies to improve productivity, profitability and engagement.

"But they have a mammoth task ahead: how to strike a balance between the growing adoption of AI-driven intelligent machines and the future partnership between humans and machines. Equipping the workforce to work in tandem with machines is not only ‘nice to have’ strategy but critical to remain competitive in the digital economy,” he said.

Symbiosis would ideal.

“AI will likely add more jobs than it takes away. The gap between data created, and the human ability to process and act upon it is often overlooked, alongside the availability of today’s analytical tools, and adoption within organisations. Closing these gaps will serve to empower humans," said Dan Sommer, Qlik Senior Director, Global Market Intelligence Lead.

Lifelong learning

Source: Cognizant. Bahl.

Equipping the existing and emerging workforce with skills more suited to an age with AI is going to be important.

“It is crucial to groom the workforce with a 'lifelong learning' mentality at this juncture of digitalisation. In order for individuals to stay ahead of the game during their education journeys and throughout their careers, higher-education institutions and businesses must prioritise skill-based learning and start curating instead of creating relevant curriculums and content for their academic and on-job training programmes,” said Bahl.

The need for data scientists

One way to coexist is to focus on higher-value skills such as analysing data. Chua Hock Leng, MD, Singapore, Pure Storage, said the roles of data scientist and AI specialist would confer more than a competitive advantage. “They will be a necessity,” he said.

Source: Pure Storage. Chua.

“A study that Pure Storage commissioned from MIT Tech Review Insights found that business leaders felt a lack of resources and talent was one of the biggest barriers preventing better management of data in their organisation. As such, in 2019, we expect to see business and industries across the board begin collaborating with educational institutions to help close this talent gap.”

Leslie Ong, Southeast Asia Country Manager, Tableau Software said, “LinkedIn recently released reports on the emerging jobs in several Asia Pacific (APAC) markets and all listed ‘data scientist’ in their top five. This observation is not surprising, as more organisations are recognising the value of data and are hiring people to tap into it.

“The skills required for many jobs are evolving to include data, but according to PwC, just one in five workers in APAC is data literate. Moving forward, we need a concerted effort from the private and public sector to upskill those already in work and provide the next generation with the skills businesses are starting to require.”

Source: Experian. Elliott.

“In 2019, we will continue to see the emergence of data science and our reliance on it. With volumes of data growing exponentially, there will continue to be greater value placed on the capabilities within data analytics fields, across industries and organisations. Companies will need to continue advancing, upskilling and retraining, as data science continues to become mainstream,” agreed Experian Asia Pacific's CEO Ben Elliott.

There will be formally-trained data scientists, and there will be those who learn on the job, as it were. “As the talent gap in the field of data science grows and access to data and AI platforms becomes more prevalent, we can expect to see a number of non-data scientists or ‘citizen data scientists’ emerge.

"We’ll see additional roles emerge and growth in other data analytic roles, such as machine-learning engineers. For organisations who cannot afford the hefty price tag that comes with teams of data scientists and sophisticated platforms, this will bring about a greater collaboration between the lines of business and IT departments,” predicted Sumir Bhatia, President, Asia Pacific, Data Center Group, Lenovo.

Source: Lenovo. Bhatia.

Ong says 2019 will be the year of data for everyone, partly because smart technologies powered by AI will lower the barriers to analytics adoption by automating stages of the process. Like Bhatia, he believes that people with few analytics skills will be able to find insights within data.

“For instance, business intelligence (BI) vendors are incorporating natural language processing (NLP), which helps computers understand human language, to allow users to interact with their data naturally, asking questions as they think of them without technical knowledge of BI tools," Ong said.

Source: Tableau.

Ong.

According to Ong, users will be able to receive insights by typing a question like “what were my APAC sales last month?”, then asking supplementary questions like “what about in Singapore?”. "Allowing people to interact conversationally enables people of all skill levels to ask deeper questions, and helps to transform workplaces into data-driven, self-service operations,” he said.

Data-based corporate culture

Ong further predicted that organisations will increasingly look to create a culture of data. “To facilitate such an environment, companies are increasing engagement through internal user communities. This starts with a group of experts helping non-experts adopt a BI tool, then these users then become experts who help socialise best practices and align others around data definitions,” he said.

Source: SolarWinds. LaRock.

Thomas LaRock, Head Geek,  SolarWinds, also says that 2019 will be the year that data is recognised as a key business driver. He said, “Operations teams must adopt a 'data mindset' to discern the type of data that exists in their department and can be polished into something that adds value to the business overall. With DataOps, organisations can begin to transition their IT team into a data science team, as they adopt a data-first frame of mind.”

DataOps will extract and analyse the most pertinent pieces of data, distilling and crafting them into a compelling and business-digestible narrative that can be easily understood across the organisation, LaRock explained.

“Companies will begin to actuate on this data, not just report and track in Excel—they will start using valuable data to make more informed decisions. The ability to share this actionable, business-digestible narrative may even earn tech pros a seat at the strategy table,” he suggested.

“Looking beyond 2019, the secure and seamless management of data will continue to be honed as a skill across industries. We will see more companies investing in talent or third-party partners that can support in managing and analysing these growing volumes of data, while mitigating the risks associated with it,” predicted Elliott.

New skills wanted

Tomorrow's coveted skillsets will not be focused on data analytics alone, says Ong. “Modern data scientists must possess a hybrid mix of hard skills such as advanced statistical and machine learning knowledge, but also soft skills like communication. To add to this, they are also expected to have a strategic mind for the business, including a deep knowledge of their industry,” he said.

Source: Veeam. McLagan.

Shaun McLagan, Senior VP, Asia Pacific and Japan at Veeam Software, suggests that technicians must become generalists, or rather 'versatilists'. “Talent shortages combined with new, collapsing on-premises infrastructure and public cloud + software-as-a-service (SaaS), are leading to broader technicians with background in a wide variety of disciplines, and increasingly a greater business awareness as well,” he said.

“Specialisation will of course remain important, but as IT becomes more and more fundamental to business outcomes, it stands to reason that IT talent will likewise need to understand the wider business and add value across many IT domains.”

Bahl also said future job scopes will move towards skills that robots cannot deliver, including providing comfort to a patient, overseeing and managing machines, drawing macro insights from big data processed by algorithms, or working interdepartmentally in collaboration by leveraging machine intelligence.

“We now live in a world of more pervasive technology and the things that humans do well are even more important. Hiring managers will start focusing more on human-centric attributes and behaviours rather than only on technical skills when searching for candidates. Skills such as emotional intelligence, problem-solving, or crisis response, will begin sweeping across the industry and become starkly evident in newer job posting,” he said.

Providing the training

By logistical extension, facilitating skills acquisition - learning - will become a boardroom priority.

“Learning in organisations is still perceived as departmentally-driven and, as such, is the responsibility of the learning and development (L&D) and/or HR departments – business functions that are not always the driver of change in businesses. With so much at stake, it’s essential for learning to move from a watercooler topic to a key agenda point for boardroom discussions so that concrete decisions can be made. We will witness reskilling and ultimately learning emerging as a top priority for executives sitting at the top," said Bahl.

Chua sees academia involved. “Courses will be designed to prepare students with the most in-demand skills, with flexible university curriculums that constantly keep up with industry developments. These efforts will help expand the pool of future data scientists at a faster rate,” he said.

Bahl also highlighted the key role that a support ecosystem will play. “Collaboration is a key area that industries have yet to hone this year. When public institutions, businesses, and education institutions step up to proactively form a supportive ecosystem, building on one another’s expertise, we will be able to create a resilient workforce that can adapt to ongoing change.

Source: Qlik. Sommer.

"For instance, Singapore’s SkillsFuture initiative is aimed at helping people develop new skills in addition to their existing skillset for career resilience or a new career path. This is a great initiative to encourage individuals to take ownership of their skills development and lifelong learning,” he said.

“AI will make data and analytics become more human than ever. Designing AI around humans will have much higher impact for organisations in the next five years, than designing to take humans out of the process,” concluded Sommer.

Explore:

Read the TechTrade Asia blog post about LG's CLOi robots at CES 2019

Read the WorkSmart Asia blog post on the Cognizant study on learning for the digital age

Read the WorkSmart Asia blog post on job demand in Singapore for November 2018