As we entered the 2010s, corporate America underwent a seismic shift. The relentless pursuit of efficiency that characterized the 1990s and early 2000s gave way to a new paradigm—one that prioritized purpose and profit. While addressing crucial issues of employee burnout and societal expectations, this transformation inadvertently set in motion a chain of events that would profoundly impact data culture and leadership across organizations.
Read MoreWho is pacing this race?
Employees have been encouraged to ‘automate their roles’ to demonstrate self-direction and continuous learning. In the past, an employee's skills, motivation, and business interests determined the pace of change. Soon, the pace may be beyond their control, risking job loss before they can adapt to consider the next set of problems. If they can’t find problems faster than the pace of automation, they are not adequately prepared for transition.
Read MoreCountdown: Book Excerpt Chapter 2
Book Excerpt: While a fully funded budget that supports data as a service is an integral part of a data transformation’s financial picture, few are fully staffed or funded. Three-quarters of executives confirm their organization now has some form of data strategy (however rudimentary), but a paltry 16% say they have the skills and capabilities necessary to deliver it.[1] Even though the average staffing budget is growing yearly, finding the skills and capabilities to execute data projects is becoming harder and harder.
Read MoreCountdown: Book Excerpt Chapter 1
Book Excerpt: Data has traditionally been managed by a combination of information technology (IT), Operations, and Finance. Over the last ten to fifteen years, the chief data officer (CDO) role has come onto the executive scene. While not yet a universal title, the role of the CDO started by reporting through these functions and is beginning to be considered separate.
Read MoreWriting a book is like getting a tattoo
Writing a book is a lot like getting a tattoo. It’s permanent. It marks a life transition. It's also 95% pain, 2.5% novelty, and 2.5% talking that novelty to others. It's proof I was able to push past the anxiety and deal with the pain to do something creative. Finishing is a wonderful feeling of accomplishment, proof that I made it past all the barriers.
Driving Data Projects is, first and foremost, a love letter to my students. The book highlights two main stumbling blocks they hit: understanding the data supply chain and their role in it and integrating key change management activities like working with executive sponsorship. I also observed these issues outside of the classroom--in almost every organization I've served. Everyone skins their knees on these issues--because they are hard.
Read MoreThe Future of Jobs report 2018
[ From the Centre for the New Economy and Society ]
As technological breakthroughs rapidly shift the frontier between the work tasks performed by humans and those performed by machines and algorithms, global labour markets are undergoing major transformations. 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, pose the risk of widening skills gaps, greater inequality and broader polarization.
As the Fourth Industrial Revolution unfolds, companies are seeking to harness new and emerging technologies to reach higher levels of efficiency of production and consumption, expand into new markets, and compete on new products for a global consumer base composed increasingly of digital natives. Yet in order to harness the transformative potential of the Fourth Industrial Revolution, business leaders across all industries and regions will increasingly be called upon to formulate a comprehensive workforce strategy ready to meet the challenges of this new era of accelerating change and innovation.
This report finds that as workforce transformations accelerate, the window of opportunity for proactive management of this change is closing fast and business, government and workers must proactively plan and implement a new vision for the global labor market. The report’s key findings include:
• Drivers of change: Four specific technological advances—ubiquitous high-speed mobile internet; artificial intelligence; widespread adoption of big data analytics; and cloud technology—are set to dominate the 2018–2022 period as drivers positively affecting business growth. They are flanked by a range of socio-economic trends driving business opportunities in tandem with the spread of new technologies, such as national economic growth trajectories; expansion of education and the middle classes, in particular in developing economies; and the move towards a greener global economy through advances in new energy technologies.
• Accelerated technology adoption: By 2022, according to the stated investment intentions of companies surveyed for this report, 85% of respondents are likely or very likely to have expanded their adoption of user and entity big data analytics. Similarly, large proportions of companies are likely or very likely to have expanded their adoption of technologies such as the internet of things and app- and webenabled markets, and to make extensive use of cloud computing. Machine learning and augmented and virtual reality are poised to likewise receive considerable business investment.
• Trends in robotization: While estimated use cases for humanoid robots appear to remain somewhat more limited over the 2018–2022 period under consideration in this report, collectively, a broader range of recent robotics technologies at or near commercialization— including stationary robots, non-humanoid land robots and fully automated aerial drones, in addition to machine learning algorithms and artificial intelligence— are attracting significant business interest in adoption. Robot adoption rates diverge significantly across sectors, with 37% to 23% of companies planning this investment, depending on industry. Companies across all sectors are most likely to adopt the use of stationary robots, in contrast to humanoid, aerial or underwater robots, however leaders in the Oil & Gas industry report the same level of demand for stationary and aerial and underwater robots, while employers in the Financial Services industry are most likely to signal the planned adoption of humanoid robots in the period up to 2022.
• Changing geography of production, distribution and value chains: By 2022, 59% of employers surveyed for this report expect that they will have significantly modified how they produce and distribute by changing the composition of their value chain and nearly half expect to have modified their geographical base of operations. When determining job location decisions, companies overwhelmingly prioritize the availability of skilled local talent as their foremost consideration, with 74% of respondents providing this factor as their key consideration. In contrast, 64% of companies cite labour costs as their main concern. A range of additional relevant factors—such as the flexibility of local labour laws, industry agglomeration effects or proximity of raw materials—were considered of lower importance.
• Changing employment types: Nearly 50% of companies expect that automation will lead to some reduction in their full-time workforce by 2022, based on the job profiles of their employee base today. However, 38% of businesses surveyed expect to extend their workforce to new productivity-enhancing roles, and more than a quarter expect automation to lead to the creation of new roles in their enterprise. In addition, businesses are set to expand their use of contractors doing task-specialized work, with many respondents highlighting their intention to engage workers in a more flexible manner, utilizing remote staffing beyond physical offices and decentralization of operations.
• A new human-machine frontier within existing tasks: Companies expect a significant shift on the frontier between humans and machines when it comes to existing work tasks between 2018 and 2022. In 2018, an average of 71% of total task hours across the 12 industries covered in the report are performed by humans, compared to 29% by machines. By 2022 this average is expected to have shifted to 58% task hours performed by humans and 42% by machines. In 2018, in terms of total working hours, no work task was yet estimated to be predominantly performed by a machine or an algorithm. By 2022, this picture is projected to have somewhat changed, with machines and algorithms on average increasing their contribution to specific tasks by 57%. For example, by 2022, 62% of organization’s information and data processing and information search and transmission tasks will be performed by machines compared to 46% today. Even those work tasks that have thus far remained overwhelmingly human—communicating and interacting (23%); coordinating, developing, managing and advising (20%); as well as reasoning and decisionmaking (18%)—will begin to be automated (30%, 29%, and 27% respectively). Relative to their starting point today, the expansion of machines’ share of work task performance is particularly marked in the reasoning and decision-making, administering, and looking for and receiving job-related information tasks.
• A net positive outlook for jobs: However this finding is tempered by optimistic estimates around emerging tasks and growing jobs which are expected to offset declining jobs. Across all industries, by 2022, growth in emerging professions is set to increase their share of employment from 16% to 27% (11% growth) of the total employee base of company respondents, whereas the employment share of declining roles is set to decrease from currently 31% to 21% (10% decline). About half of today’s core jobs—making up the bulk of employment across industries—will remain stable in the period up to 2022. Within the set of companies surveyed, representing over 15 million workers in total, current estimates would suggest a decline of 0.98 million jobs and a gain of 1.74 million jobs. Extrapolating these trends across those employed by large firms in the global (nonagricultural) workforce, we generate a range of estimates for job churn in the period up to 2022. One set of estimates indicates that 75 million jobs may be displaced by a shift in the division of labour between humans and machines, while 133 million new roles may emerge that are more adapted to the new division of labour between humans, machines and algorithms. While these estimates and the assumptions behind them should be treated with caution, not least because they represent a subset of employment globally, they are useful in highlighting the types of adaptation strategies that must be put in place to facilitate the transition of the workforce to the new world of work. They represent two parallel and interconnected fronts of change in workforce transformations: 1) large-scale decline in some roles as tasks within these roles become automated or redundant, and 2) large-scale growth in new products and services—and associated new tasks and jobs— generated by the adoption of new technologies and other socio-economic developments such as the rise of middle classes in emerging economies and demographic shifts.
• Emerging in-demand roles: Among the range of established roles that are set to experience increasing demand in the period up to 2022 are Data Analysts and Scientists, Software and Applications Developers, and Ecommerce and Social Media Specialists, roles that are significantly based on and enhanced by the use of technology. Also expected to grow are roles that leverage distinctively ‘human' skills, such as Customer Service Workers, Sales and Marketing Professionals, Training and Development, People and Culture, and Organizational Development Specialists as well as Innovation Managers. Moreover, our analysis finds extensive evidence of accelerating demand for a variety of wholly new specialist roles related to understanding and leveraging the latest emerging technologies: AI and Machine Learning Specialists, Big Data Specialists, Process Automation Experts, Information Security Analysts, User Experience and Human-Machine Interaction Designers, Robotics Engineers, and Blockchain Specialists.
• Growing skills instability: Given the wave of new technologies and trends disrupting business models and the changing division of labour between workers and machines transforming current job profiles, the vast majority of employers surveyed for this report expect that, by 2022, the skills required to perform most jobs will have shifted significantly. Global average skills stability—the proportion of core skills required to perform a job that will remain the same—is expected to be about 58%, meaning an average shift of 42% in required workforce skills over the 2018–2022 period.
• A reskilling imperative: By 2022, no less than 54% of all employees will require significant re- and upskilling. Of these, about 35% are expected to require additional training of up to six months, 9% will require reskilling lasting six to 12 months, while 10% will require additional skills training of more than a year. Skills continuing to grow in prominence by 2022 include analytical thinking and innovation as well as active learning and learning strategies. Sharply increasing importance of skills such as technology design and programming highlights the growing demand for various forms of technology competency identified by employers surveyed for this report. Proficiency in new technologies is only one part of the 2022 skills equation, however, as ‘human’ skills such as creativity, originality and initiative, critical thinking, persuasion and negotiation will likewise retain or increase their value, as will attention to detail, resilience, flexibility and complex problem-solving. Emotional intelligence, leadership and social influence as well as service orientation also see an outsized increase in demand relative to their current prominence.
• Current strategies for addressing skills gaps: Companies highlight three future strategies to manage the skills gaps widened by the adoption of new technologies. They expect to hire wholly new permanent staff already possessing skills relevant to new technologies; seek to automate the work tasks concerned completely; and retrain existing employees. The likelihood of hiring new permanent staff with relevant skills is nearly twice the likelihood of strategic redundancies of staff lagging behind in new skills adoption. However, nearly a quarter of companies are undecided or unlikely to pursue the retraining of existing employees, and two-thirds expect workers to adapt and pick up skills in the course of their changing jobs. Between one-half and two-thirds are likely to turn to external contractors, temporary staff and freelancers to address their skills gaps.
• Insufficient reskilling and upskilling: Employers indicate that they are set to prioritize and focus their re- and upskilling efforts on employees currently performing high-value roles as a way of strengthening their enterprise’s strategic capacity, with 54% and 53% of companies, respectively, stating they intend to target employees in key roles and in frontline roles which will be using relevant new technologies. In addition, 41% of employers are set to focus their reskilling provision on high-performing employees while a much smaller proportion of 33% stated that they would prioritize at-risk employees in roles expected to be most affected by technological disruption. In other words, those most in need of reskilling and upskilling are least likely to receive such training.
There are complex feedback loops between new technology, jobs and skills. New technologies can drive business growth, job creation and demand for specialist skills but they can also displace entire roles when certain tasks become obsolete or automated. Skills gaps—both among workers and among the leadership of organizations—can speed up the trends towards automation in some cases but can also pose barriers to the adoption of new technologies and therefore impede business growth.
The findings of this report suggest the need for a comprehensive ‘augmentation strategy’, an approach where businesses look to utilize the automation of some job tasks to complement and enhance their human workforces’ comparative strengths and ultimately to enable and empower employees to extend to their full potential. Rather than narrowly focusing on automation-based labour cost savings, an augmentation strategy takes into account the broader horizon of value-creating activities that can be accomplished by human workers, often in complement to technology, when they are freed of the need to perform routinized, repetitive tasks and better able to use their distinctively human talents.
However, to unlock this positive vision, workers will need to have the appropriate skills enabling them to thrive in the workplace of the future and the ability to continue to retrain throughout their lives. Crafting a sound in-company lifelong learning system, investing in human capital and collaborating with other stakeholders on workforce strategy should thus be key business imperatives, critical to companies’ medium to long-term growth, as well as an important contribution to society and social stability. A mindset of agile learning will also be needed on the part of workers as they shift from the routines and limits of today’s jobs to new, previously unimagined futures. Finally, policy-makers, regulators and educators will need to play a fundamental role in helping those who are displaced repurpose their skills or retrain to acquire new skills and to invest heavily in the development of new agile learners in future workforces by tackling improvements to education and training systems, as well as updating labour policy to match the realities of the Fourth Industrial Revolution.
Christine Haskell, PHD has built her practice on credible, published research and data. In the Research Series, you’ll find highlights, shareable statistics, and links to the full source material.