10 Predictions for Data and Jobs in 2019
As technological breakthroughs continue to transform businesses, 2019 is looking to be a year of huge change. And we predict that these changes will contribute to productivity, economic growth, and help address societal challenges.
Rapid technological changes are shifting the frontier between the work tasks performed by humans, and those performed by machines and algorithms. As a result, it’s clear that the nature of work, and the workplace itself, is likely to undergo major transformations: some occupations will decline, others will grow, and many more will change.
While McKinsey believes “there will be enough work to go around (barring extreme scenarios)”, they also recognise that society will need to grapple with significant workforce transitions and dislocation. Meanwhile, The World Economic Forum predicts that these transformations, “if managed wisely, could lead to a new age of good work, good jobs and improved quality of life for all” – but if managed poorly, they may “pose the risk of widening skills gaps, greater inequality and broader polarisation.”
In other words: the time to shape the future of work is now. And to equip you to do so, we have collated our top 10 predictions for 2019.
Top 10 Predictions for Data and Jobs in 2019
1. Adoption of data analytics soars
2018 was a landmark year for data analytics, as interest and adoption in the field accelerated. According to one survey, in 2018, a nearly unanimous 98.6% of executives indicated that their company aspired to a ‘data-driven culture’, up from 85.5% in the 2017 survey.
So what was the result of this peak in interest? For starters, 1 in 5 organisations has already changed its approach to attracting and retaining analytics talent. And 63% of companies are now providing formal or on-the-job training in-house.
The chasm of adoption seems to have finally been crossed. And the work of data analytics teams is increasingly equally focused on providing value to employees as well as driving better business outcomes. Whilst organisations still face numerous challenges, including lifting the data confidence and data literacy across the business, we expect adoption to continue to grow in 2019.
The business benefits of investing in data analytics are becoming more obvious too. For example, a recent study revealed that data-driven cultures experience several major financial benefits, including a 15% growth in revenue and operating margin. For a typical Fortune 1000 company, improving data accessibility by just 10% will result in more than $65 million additional net income.
2. AI and machine learning rises
The latest research from the World Economic Forum forecasts that by 2025, machines will perform more current work tasks than humans, compared to 71% being performed by humans today. The rapid evolution of machines and algorithms in the workplace could create 133 million new roles in place of 75 million that will be displaced between now and 2022.
According to Gartner, the top 10 technological trends of 2019 will include blockchain, quantum computing, augmented analytics and artificial intelligence, all of which will drive disruption and new business models.
Companies like Microsoft and Uber are already using robots to patrol parking lots and large outdoor areas to predict and prevent crime. The Knightscope K5 robots can read license plates, report suspicious activity and collect data to report to their owners – and these AI-driven robots are just one example of the “autonomous things” that Gartner think will be among the top 10 strategic technologies for 2019.
“Autonomous things” use AI to perform tasks traditionally done by humans. Whether it’s robotics, cars, drones, or appliances, all autonomous things use AI to interact more naturally with their environments. The sophistication of these systems may vary: for example, they can span a drone operated in the air with human-assistance to a farming robot operating completely autonomously in a field.
According to McKinsey, beyond traditional industrial automation and advanced robots, new generations of more capable autonomous systems are appearing in environments ranging from autonomous vehicles on roads to automated check-outs in grocery stores. Much of this progress has been driven by improvements in systems and components, including mechanics, sensors and software.
“The future will be characterised by smart devices delivering increasingly insightful digital services everywhere,” said David Cearley, Gartner Distinguished Vice President Analyst, at Gartner 2018 Symposium/ITxpo in Orlando, Florida.
3. More automation and ‘human touch’
According to Gartner, by 2020, more than 40% of data science tasks will be automated.
As people analytics leader David Green recognises, it is clear that we are in the midst of huge disruption. However, research from the likes of Gartner, the World Economic Forum and McKinsey all conclude that AI will create more jobs than it will replace. “The jobs generated by AI will allow us to be more creative, more impactful and more human,” says Green. Quoting Bruce Springsteen, Green refers to this as “a little of that Human Touch”.
One of the elements powering this change is augmented analytics, which according to Gartner “represents a third major wave for data and analytics capabilities as data scientists use automated algorithms to explore more hypotheses”.
According to Gartner, the increase in automation will result in increased productivity, and broader use by “citizen data scientists”. Citizen data scientists use AI powered augmented analytics tools that automate the data science function automatically identifying data sets, developing hypothesis and identifying patterns in the data. In the future, businesses will look to citizen data scientists as a way to enable and scale data science capabilities. Through 2020, the number of citizen data scientists will grow five times faster than professional data scientists.
And between citizen data scientists and augmented analytics, data insights will be more broadly available across the business, including analysts, decision makers and operational workers.
4. Jobs declining – and emerging
According to the World Economic Forum, machines will do more tasks than humans by 2025. But the “robot revolution” will still create 58 million net new jobs in the next five years.
World Economic Forum predict a decline of 984,000 jobs and a gain of 1.74 million jobs between now and 2022. The data suggests that 75 million jobs may be displaced by a shift in the division of labour between humans, machines and algorithms, while 133 million new roles may emerge that are more adapted to this new division of labour.
Such a transformation will have a profound effect on the global labour force – however in terms of overall numbers of new jobs the outlook is positive, with 133 million new jobs expected to be created by 2022 compared to 75 million that will be displaced.
Among the set of roles set to experience increasing demand across all industries are data analysts and scientists, software and applications developers, and ecommerce and social media specialists, all of which roles that are significantly based on or enhanced by technology. Roles that leverage distinctly ‘human skills,’ such as sales and marketing professions, innovation managers and customer service workers, are also set to experience increasing demand. Jobs expected to become redundant include routine-based white-collar roles, such as data entry clerks, accounting and payroll clerks.
It is undeniable that some occupations will see significant declines by 2030. According to McKinsey, automation could displace around 15% of the global workforce, or about 400 million workers, in the period
. And that’s just their midpoint scenario. Under the fastest scenario they have modelled, projecting the pace and scope of adoption, that figure rises to 30%, or 800 million workers.
However, even as workers are displaced, McKinsey emphasises that there will be growth in demand for work and consequently jobs. In their projected scenarios for labour demand 2030, they predict a range of additional labour demand of between 21% to 33% of the global workforce (555 million and 890 million jobs) to 2030, more than offsetting the numbers of jobs lost.
5. Economic growth on the horizon
McKinsey predict that accelerating progress in AI and automation will create opportunities for business, the economy and society.
Already, technological developments are generating value in various products and services. Their recent analysis, conducted across several hundred AI use cases, found that the most advanced deep learning techniques deploying artificial neural networks could account for as much as $3.5 trillion to $5.8 trillion in annual value, or 40% of the value created by all analytics techniques.
Furthermore, their research suggests that society needs these improvements to provide value for businesses, and contribute to economic growth. At a time when aging and falling birth rates are acting as a drag on growth, AI and automation technologies can do much to lift the global economy and increase global prosperity. AI and automation have the potential to reverse that decline: productivity growth could potentially reach 2% annually over the next decade, with 60% of this increase from digital opportunities.
Overall, by 2021, AI augmentation is set to generate $2.9 trillion in business value and recover 6.2 billion hours of worker productivity, according to Gartner.
6. The nature of work is changing
While McKinsey believes there will be enough work to go around (barring extreme scenarios), society will need to grapple with significant workforce transitions and dislocation.
Soon, machines will be able to carry out more of the tasks done by humans, complement the work that humans do, and even perform some tasks that go beyond what humans can do. By 2025, more than half of all current workplace tasks will be performed by machines as opposed to 29% today. As a result, some occupations will decline, others will grow, and many more will change.
As AVADO’s CEO Mark O’Donoghue notes: “People’s jobs may not disappear – but many will need to change substantially.”
By 2022, Gartner predicts that one in five workers engaged in mostly non routine tasks will rely on AI to do a job. “Partial automation will become more prevalent as machines complement human labour,” McKinsey assert. They predict that about half of the activities (not jobs) carried out by workers could be automated.
This means that most workers—from welders to mortgage brokers to CEO’s—will work alongside rapidly evolving machines. The nature of these occupations will likely change as a result.
7. The focus on skills intensifies
According to the World Economic Forum, workers will require new sets of skills as the division of labour between humans and machines continues to evolve. In fact,
54% of employees of large companies will need significant re- and up-skilling in order to fully harness the growth opportunities offered by the “Fourth Industrial Revolution”.
The competences that will be sharply increasing in focus include both technology proficiency, such as technology design and programming, but also distinctly human skills, such as creativity, critical thinking and persuasion.
All industries expect to have sizeable skills gaps, with average skills instability of 42%. This only highlights the scale of the challenge in preparing today’s workers for changes within their current roles and the emerging jobs of the future. Just over half of the companies surveyed by the World Economic Forum said they planned to reskill only those employees that are in key roles, while only one third planned to reskill at-risk workers.
“It is critical that business take an active role in supporting their existing workforce’s through reskilling and upskilling, that individuals take a proactive approach to their own lifelong learning, and that governments create an enabling environment to facilitate this workforce transformation,” said Klaus Schwab, Founder and Executive Chairman of the World Economic Forum. “This is the key challenge of our time.”
8. Agile companies and change management
Several developing trends are likely to fundamentally reshape the future competitive environment. To stay ahead of these forces in 2019, companies should seek to be more agile, and prepare themselves for the challenges and opportunities offered through AI and automation.
Both tech companies and traditional ones will face equally critical challenges. Digital giants will need to “come of age” in the modern world of GDPR, and navigate issues like maintaining users’ trust. Meanwhile, older businesses will need to evolve their approaches and organisations to harness new technologies.
Companies will increasingly need to compete on the rate of learning. However, research has shown that organisational agility can provide a powerful source of competitive advantage.
According to the a report from Mckinsey, there are 5 trademarks of an agile organisation. These include practices such as: implementing flat structures; empowering multidisciplinary teams; using design thinking, sprints or other similar methods to foster rapid decision making and learning cycles; investing in leadership that empowers people and creates an entrepreneurial culture; and offering real-time communication and work-management tools to support speed and flexibility.
Companies such as PMI identified several benefits of increased organisational agility:
- 71% faster response to changing market conditions
- 54% improved customer satisfaction
- 38% organisational changes made more quickly or efficiently
- 55% overall improved organisation efficiency
- 44% more profitable business results
- 29% faster completion of projects
Perhaps it’s not surprising, then, that a recent report from Mckinsey suggests that 75% of companies believe organisational agility is a top priority, and nearly 40% are currently conducting an organisational agility transformation.
9. Remembering ethics in data
“For businesses to remain dynamic, differentiated and competitive in an age of machines, they must in fact invest in their human capital,” said Saadia Zahid, Head of the Centre for the New Economy and Society at the World Economic Forum. “There is both a moral and economic imperative to do so. Without proactive approaches, businesses and workers may lose out on the economic potential of the Fourth Industrial Revolution.”
According to HR and People Analytics expert David Green, ethics is the most important aspect of people analytics, and also the field’s biggest challenge: “The potential of people analytics is enormous but the risk of getting it wrong and losing employee trust – perhaps irrevocably – is high. All of those who work in the field have a responsibility to ensure that people data is used for good.”
He’s not alone: at the Lord Mayor’s Digital Skills summit in November 2018, Dr. Yuhyun Park (head of the newly established DQ Institute), warned about the growing inequality of digital skills in developing countries. In her opinion, “Universal digital intelligence is a basic human right in the digital age.” In her view, it is absolutely critical that we establish framework that is innovative, inclusive and just, “protecting the minor of the minor,” as we move through these rapid developments.
According to the World Economic Forum, business leaders will need to “master the art of corporate statesmanship,” proactively shaping critical societal issues that will increasingly affect business. And they will need to focus on their companies’ Total Societal Impact, ensuring that the business creates social as well as economic value. Not only can this increase a company’s financial performance in the long run, but it can strengthen the social contract between business and society, ensuring that the relationship is able to endure.
10. Challenges and limitations
Of course, challenges remain before these technologies can live up to their potential for the good of the economy and society everywhere.
According to the World Economic Forum, urgent challenges include providing reskilling opportunities, enabling remote work and building safety nets to protect at-risk workers and communities. McKinsey also identify challenges in relation to AI and automation, such as the need for massive training data and difficulties “generalising” algorithms across use cases.
However, more importantly, workforce transitions pose an increasingly urgent problem. While McKinsey expect there will be enough work to ensure full employment in 2030, the transitions that will accompany automation and AI adoption will be significant. The mix of occupations will change, as will skill and educational requirements. Work will need to be redesigned to ensure that humans work alongside machines most effectively.
According to McKinsey, one lesson of the past decade is that while globalisation may have benefited economic growth and people as consumers, the wage and dislocation effects on workers were not adequately addressed. Most analyses, including McKinsey’s own, suggest that the scale of these issues is likely to grow in the coming decades.
It’s important that we are aware of these challenges as we go into 2019. And it’s important that we do better, that we learn from history. Faster timescales are not the only ones that matter – companies must also better position themselves for slow-moving forces, such as social and political changes, that are increasingly transforming business.
Building the organisations of the future
AI and machine learning are already transforming our ability to learn. History has shown, however, that organisational innovation is needed to unlock the full potential of new technologies.
Reinventing organisations to compete in the 2020’s will not be a trivial task. But research shows that the single biggest factor affecting the success of major transformation programmes is how early they are initiated. It is therefore critical to create a sense of urgency within the organisation to ensure that everyone truly understands the need for change.
However you choose to look at it, it’s undeniable that work will be different in 2019 – requiring new skills, and a far greater adaptability of the workforce than we have ever seen.
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This article was originally posted here: https://blog.avadolearning.com/10-predictions-for-data-and-jobs-in-2019