Category Archives: Gig economy

17/4/16: Human Capital, Management & Value-Added

The value of management to a given firm rests not only in more efficient use of physical resources and financial capital, as well as corporate / business strategy, but also in the ability of the firm to identify, hire, retain and enable high quality human capital. This is a rather common sense conclusion that might be drawn by any analyst of management systems and any business student.

However, the question always remains as to how much of the firm value-added arises from managerial inputs, as opposed to actual human capital inputs.

Stefan Bender, Nicholas Bloom, David Card, John Van Reenen, and Stephanie Wolter decided to attempt to quantify these differences. In their paper “Management Practices, Workforce Selection and Productivity” (March 2016, NBER Working Paper No. w22101: they note that “recent research suggests that much of the cross-firm variation in measured productivity is due to differences in use of advanced management practices.”

“Many of these practices – including monitoring, goal setting, and the use of incentives – are mediated through employee decision-making and effort. To the extent that these practices are complementary with workers’ skills, better-managed firms will tend to recruit higher-ability workers and adopt pay practices to retain these employees.”

The authors then use a survey data on the management practices of German manufacturing firms, as well as data on earnings records for their employees “to study the relationship between productivity, management, worker ability, and pay”.

Per authors: “As documented by Bloom and Van Reenen (2007) there is a strong partial correlation between management practice scores and firm-level productivity in Germany. In our preferred TFP [total factor productivity] estimates only a small fraction of this correlation is explained by the higher human capital of the average employee at better-managed firms. A larger share (about 13%) is attributable to the human capital of the highest-paid workers, a group we interpret as representing the managers of the firm. And a similar amount is mediated through the pay premiums offered by better-managed firms.”

Human capital value-added is neither uniform across types of employees, nor is it independent of the management systems, which means that increasing the value of human capital in the economy requires more emphasis on the structure of the overall utilisation of talent, not just acquisition of talent. This is exactly consistent with the C.A.R.E. framework for human capital-centric economy that I outlined some years ago, here, the framework of Creating, Attracting, Retaining and Enabling human capital.

The study also confirms that “looking at employee inflows and outflows, … better-managed firms systematically recruit and retain workers with higher average human capital.”

Overall, the authors concluded that “workforce selection and positive pay premiums explain just under 30% of the measured impact of management practices on productivity in German manufacturing.”

These results should add to questions about the ability of the Gig-economy firms, e.g. online platforms providers for labour utilisation, such as Uber, to significantly improve productivity in the economy. The reason for this is simple: contingent workforce talent pool is at least one step further removed from management than in the case of traditional employees. As the result, it is quite possible that contingent workforce productivity does not benefit directly from management quality. If so, that sizeable, ‘just under 30% of the measured impact’ in terms of improved productivity, arising from better management practices, workforce selection and pay premiums can be out of reach for Gig-economy firms and their contingent workers.

Again, as I noted repeatedly, including in my recent presentation at the CXC Global “Future of Work” Summit (see here:, the key to developing a productive and sustainable Gig-economy will be in our ability to develop institutional, regulatory and strategic frameworks for improving management of human capital held by contingent workforce.

6/4/16: Apps, Contingent Workforce and U.S. Employment Trends

Here is an interesting chart from the WSJ on the scale of the apps platforms-related Gig-economy employment and the underlying trends in growth on other contingent workforce:

Yes, overall app platform employment is low, as I mentioned in my presentation at the CXC forum on the future of workforce in San Francisco yesterday, but...

The big 'but' here is that overall app platforms-related employment growth is most likely contributing to the weakening of the quality of contingent workforce (in terms of skills, value added and sustainability), not strengthening it, and thus requires more systemic supports and changes in this workforce management and enablement.

More on this later, so stay tuned.

24/1/16: Unobserved Ability and Entrepreneurship

Yesterday, I posted some links relating to non-Cognitive Skills, contextualising these into the Gig-Economy related issues. Here is another interesting study relating to human capital and linking unobserved (and hard to measure) ability to entrepreneurship.

From the policymakers' and indeed investors and other market participants perspective, the question of why do some individuals become entrepreneurs is a salient one.

Identifying the causal relationships between external conditions, systems and policy environments, as well as behavioural and other drivers of entrepreneurship is of great value for setting policies and systems for enhancing the rate of entrepreneurship creation in the economy. A recent paper, titled "Unobserved Ability and Entrepreneurship" by Deepak Hegde and Justin Tumlinson (Ifo Institute at the University of Munich, April 20, 2015) attempts to answer to key questions surrounding the formation of entrepreneurship, namely:

  1. Why do individuals become entrepreneurs? and
  2. When do they succeed? 

The authors "develop a model in which individuals use pedigree (e.g., educational qualifications) as a signal to convince employers of their unobserved ability. However, this signal is imperfect…" So far - logical: upon attaining a level of education, and controlling for quality of that education (complexity of degree programme, subject matter, quality of awarding institution, duration of studies, attainment of grades etc), a graduate acquire more than a sum of knowledge and skills attached to the degree. They also acquire a signal that can be communicated to their potential employer that conveys they lateen (hidden) abilities; attitude toward work, aptitude, ability to work in teams, ability to work on complex systems of tasks etc.

Problem is - the signal is noisy. For example, a graduate with 4.0 GPA from a second tier university can have better potential abilities than a graduate with 3.7 GPA from a first tier ranked university. But that information may not be clearly evident to the potential employer. As the result, there can be a large mismatch between what an applicant thinks their ability is and what their CV signals to the potential employer.

In the paper, theoretical model delivers a clear cut outcome (emphasis mine): "…individuals who correctly believe their ability is greater than their pedigree conveys to employers, choose entrepreneurship. Since ability, not pedigree, matters for productivity, entrepreneurs earn more than employees of the same pedigree."

The authors use US and UK data to test their model prediction (again, emphasis is mine): "Our empirical analysis of two separate nationally representative longitudinal samples of individuals residing in the US and the UK supports the model’s predictions that

  • (A) Entrepreneurs have higher ability than employees of the same pedigree, 
  • (B) Employees have better pedigree than entrepreneurs of the same ability, and 
  • (C) Entrepreneurs earn more, on average, than employees of the same pedigree, and their earnings display higher variance."

Point C clearly indicates that entrepreneurs earn positive risk premium for effectively (correctly, on average) betting on their ability over their pedigree. In other words, the take chance in themselves and, on average, win. The real question, however, is why exactly do their earnings exhibit higher variance - is it due to distributional effects across the entrepreneurs by their ability, or is it due to risk-adjusted returns being similar, or is it due to exogenous shocks to entrepreneurs incomes (e.g. tax system-induced or contractually-structured)?

These are key questions we do not yet address in research sufficiently enough to allow us to understand better what the Gig-Economy and entrepreneurship in modern day setting imply in terms of aggregate consumption, investment, household investment and decision making by entire household in terms of labour supply, educational choices (for parents and children), etc.

As some might say... it's complicated...

23/1/16: Non-Cognitive Human Capital

In my 2011 paper on the role of Human Capital in the emerging post-ICT Revolution economy, human capital will simultaneously:

  1. Play increasingly more important role in determining returns to technical and processes innovation;
  2. Become more diverse in its nature - or more diversified - spanning measurable and unmeasurable skills, traits, knowledge, attitudes to risk and innovation, capabilities etc.; and
  3. Form the critical foundation of entrepreneurship and core employment base in the so-called Type 1 Gig-Economy - economy based on contingent workforce compered of highly skilled, highly value-additive professionals.

An interesting paper relating to the matter, especially to the last point, is a recent IZA Working paper (October 2015) titled “Non-Cognitive Skills as Human Capital” by Shelly Lundberg.

Per Lundberg: “In recent years, a large number of studies have shown strong positive associations between so-called “non-cognitive skills” — a broad and ill-defined category of metrics encompassing personality, socio-emotional skills, and behaviors — and economic success and wellbeing. These skills appear to be malleable early in life, raising the possibility of interventions that can decrease inequality and enhance economic productivity.”

Lundberg discusses “the extensive practical and conceptual barriers to using non-cognitive skill measures in studies of economic growth, as well as to developing or evaluating relevant policies. …There is a lack of general agreement on what non-cognitive skills are and how to measure them across developmental stages, and the reliance on behavioral measures of skills ensures that both skill indicators themselves, and their payoffs, will be context-dependent. The empirical examples show that indicators of adolescent skills have strong associations with educational attainment, but not subsequent labor market outcomes, and illustrate some problems in interpreting apparent skill gaps across demographic groups.”

From the Gig-Economy point of view, development of all (cognitive and non-cognitive) skills requires time and resources. In traditional workplace setting - of old variety - some of these resources and time allocations are supported / subsidised by employers (e.g. gym memberships, formal paid time off, formal paid career breaks, formal 'team building' activities, actual employer-paid training and education, employer-supported psychological wellness programmes for employees, and so on). In a Gig-Economy setting, these are not available, generally, to contingent workers.

Aside from having impact on contingent workforce skills and human capital, there are more 'trivial' considerations that should be put to analysis. Take, for example, health and psychological well-being. If a contingent workforce using company fails to assure the latter for its contingent workers, who is liable for any damages caused by over-worked, over-stressed, psychologically unwell contingent worker to the company clients?

Again, setting aside humanitarian, social and personal considerations, this question has implications for businesses using contingent workers:

  • Insurance costs and coverage for businesses;
  • Legal costs and coverage for business;
  • Reputational risks for businesses;
  • Counter-party risks for businesses; and so on

In a world where there is no such thing as a free lunch, Gig-Economy based companies should seriously consider how they are going to deal with potential costs of disruption from the Gig-Economy type of employment to life-cycle work practices and financial wellbeing of their contingent workers.

Note: More on the subject of non-cognitive skills and human capital: