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Latin America experienced a long period of sustained growth since 2003 that positively impacted social and labor market indicators, including poverty. This paper contributes to the understanding of this process as it carries out a comparative study of poverty and indigence dynamics in five Latin American countries during 2003–2012. Specifically, it extends the analysis of a previously published study by broadening the time coverage and examining indigence mobility. It analyzes the extent to which countries with different levels of poverty (extreme poverty) incidence diverge in terms of exit and entry rates, and identifies the relative importance of the frequency and impact of events associated with poverty transitions. For this, a dynamic analysis of panel data is carried out using regular household surveys. Sizeable rates of poverty and indigence movements were observed in all five countries and it was found that a large proportion of poor or indigent households experienced positive events, mainly related to the labor market; however, only a small fraction of them actually exited poverty and indigence. It appeared, therefore, that even when the economy behaved reasonably well, high levels of labor turnover and income mobility (even of a negative nature) still prevail, mainly associated with the high level of precariousness and the undeveloped system of social protection that characterize the studied countries.

The current scenario is dominated by an urgent need for economic recovery caused by the global health emergency that has been at work since January 2020. Digital transformation plays a crucial role in bringing about this recovery. However, the failure rate of digital transformation projects over the last 10 years is very high. Considering the growing demand for digital transformation from businesses, the digital transformation failure rate, if unchanged, could lead to an exponential growth in technical debt. Technical debt is acquired when the digital transformation to be deployed at a business fails. The accumulation of technical debt will lead not only to economic stalemate but possibly also to yet another setback.

The developed set of methodologies form what has been termed the Digital Transformation Governance Engineering Process (DTGEP). This process can help any business wishing to undertake a digital transformation project to materialize their project in a sustainable, productive and competitive way.

DTGEP prevents the generation of technical debt because organizational knowledge is aligned with the technological solution that best suits the needs of each business in order to support its strategic or business objectives.

DTGEP has already been used to successfully discover the relationship between business features and the prospective digital transformation. However, it needs to be applied in case studies on many other businesses across the economy in order to gather more accurate information that could be clustered by sectors.

DTGEP was tested on a set of 25 projects, and this paper reports several interesting findings regarding its use, like the impact of the digital transformation on different parts of the business model canvas (BMC) and the intellectual capital of the organization developing the digital transformation, and how the status of the organization's intangible assets affects the decision-making process with respect to the prospective digital transformation.