White Paper

The next industrial revolution is happening all around us, transforming the way we make things and what our products can do. Three forces are converging to shape this transformation: 1) The meshing of the physical and digital worlds through the Industrial Internet. 2) The emergence of new design and production techniques and new materials in manufacturing. 3) The shifting role that human beings are playing in the production process. Machines, data, and people are increasingly connecting for better, faster, safer, and more reliable performance. In this series, I and others explore what the digital transformation of industry means for growth, for competitiveness, and for employment. This is the future of work.

Appian’s Future of Work survey, conducted by IDG, posed wide-ranging questions to global IT leaders about the state of enterprise IT and its alignment with business in driving transformation. Respondents comprised of 500 senior level IT executives, Director and above, at global companies with over 1000 employees. More than half the respondents were C-level (CIO, CTO, CSO). Survey results are being published in a series of reports that each drill into specific segments of the global data. Key Takeaways in this report: - The typical large enterprise in the US and Europe makes 180 app development requests to IT every year 15% of those requests are never started,15% are never finished, and 20% are delivered but don’t meet the business need - Technical debt consumes 40% of IT’s development time

This paper analyses the characteristics of firms that operate at the global productivity frontier and their relationship with other firms in the economy, focusing on the diffusion of global productivity gains and the policies that facilitate it. Firms at the global productivity frontier – defined as the most productive firms in each two-digit industry across 23 countries – are typically larger, more profitable, younger and more likely to patent and be part of a multinational group than other firms. Despite the slowdown in aggregate productivity, productivity growth at the global frontier remained robust over the 2000s. At the same time, the rising productivity gap between the global frontier and other firms raises key questions about why seemingly non-rival technologies do not diffuse to all firms. The analysis reveals a highly uneven process of technological diffusion, which is consistent with a model whereby global frontier technologies only diffuse to laggards once they are adapted to country-specific circumstances by the most productive firms within each country (i.e. national frontier firms). This motivates an analysis of the sources of differences in the productivity and size of national frontier firms vis-à-vis the global frontier and the catch-up of laggard firms to the national productivity frontier. Econometric analysis suggests that well-designed framework policies can aid productivity diffusion by sharpening firms’ incentives for technological adoption and by promoting a market environment that reallocates resources to the most productive firms. There is also a role for R&D tax incentives, business-university R&D collaboration and patent protection but trade-offs emerge which can inform the design of innovation-specific policies.

We study the job training provided under the US Workforce Investment Act (WIA) to adults and dislocated workers in two states. Our substantive contributions center on impacts estimated non-experimentally using administrative data. These impacts compare WIA participants who do and do not receive training. In addition to the usual impacts on earnings and employment, we link our state data to the Longitudinal Employer Household Dynamics (LEHD) data at the U.S. Census Bureau, which allows us to estimate impacts on the characteristics of the firms at which participants find employment. We find moderate positive impacts on employment, earnings and desirable firm characteristics for adults, but not for dislocated workers. Our primary methodological contribution consists of assessing the value of the additional conditioning information provided by the LEHD relative to the data available in state Unemployment Insurance (UI) earnings records. We find that value to be zero.

AI, Algorithms and Machine based automation of executive functions in enterprises and institutions is an important niche in the current considerations about the impact of digitalization on the future of work. Building platforms for CxO automation is challenging. In this paper, design principles based on computational thinking are used to engineer the architecture and infrastructure for such CxO automation platforms.

The Green Industrial Policy: Concept, Policies, Country Experiences report, jointly produced by UN Environment and the German Development Institute (DIE) in the framework of the Partnership for Action on Green Economy (PAGE), provides an overview of the debate on green industrial policy, highlights what countries can gain economically from pursuing environmental integrity, and explores the policy options available to accelerate the transformation in ways that enhance both human well-being and environmental sustainability. A special focus is given to developing countries, because of their need for growth and their high potential for transformation, as they are not yet locked into unsustainable pathways. Practical examples are included in all chapters, and four national examples of successful green structural change are presented in detail, covering countries at very different levels of income and technological capacity (namely, China, Morocco, Brazil and Germany).

There is an urgent need to shift mindsets in our approach to jobs, careers and work. New big data analysis provides us with insights into the patterns of skills young people now require navigating complex and uncertain working lives. We must act now to ensure young Australians can thrive in the new world of work.

Technological change has long been a source of anxiety for workers. Today, improvements in communication technology, robotics, and machine intelligence are rekindling age-old concerns that technology will soon force millions of people out of work. This report provides a fresh perspective. Automation is, at its core, an opportunity to harness the power of machines to improve human lives. If we get it right, automation could significantly boost Australia's productivity and national income - potentially adding up to 2.2 trillion Australian dollars in value to our economy by 2030.