Network-based social capital and capacity-building programs: an example from Ethiopia

<p>Abstract</p> <p>Introduction</p> <p>Capacity-building programs are vital for healthcare workforce development in low- and middle-income countries. In addition to increasing human capital, participation in such programs may lead to new professional networks and access to social capital. Although network development and social capital generation were not explicit program goals, we took advantage of a natural experiment and studied the social networks that developed in the first year of an executive-education Master of Hospital and Healthcare Administration (MHA) program in Jimma, Ethiopia.</p> <p>Case description</p> <p>We conducted a sociometric network analysis, which included all program participants and supporters (formally affiliated educators and mentors). We studied two networks: the Trainee Network (all 25 trainees) and the Trainee-Supporter Network (25 trainees and 38 supporters). The independent variable of interest was out-degree, the number of program-related connections reported by each respondent. We assessed social capital exchange in terms of resource exchange, both informational and functional. Contingency table analysis for relational data was used to evaluate the relationship between out-degree and informational and functional exchange.</p> <p>Discussion and evaluation</p> <p>Both networks demonstrated growth and inclusion of most or all network members. In the Trainee Network, those with the highest level of out-degree had the highest reports of informational exchange, χ²(1, <it>N </it>= 23) = 123.61, p < 0.01. We did not find a statistically significant relationship between out-degree and functional exchange in this network, χ²(1, <it>N </it>= 23) = 26.11, p > 0.05. In the Trainee-Supporter Network, trainees with the highest level of out-degree had the highest reports of informational exchange, χ²(1, <it>N </it>= 23) = 74.93, p < 0.05. The same pattern held for functional exchange, χ²(1, <it>N </it>= 23) = 81.31, p < 0.01.</p> <p>Conclusions</p> <p>We found substantial and productive development of social networks in the first year of a healthcare management capacity-building program. Environmental constraints, such as limited access to information and communication technologies, or challenges with transportation and logistics, may limit the ability of some participants to engage in the networks fully. This work suggests that intentional social network development may be an important opportunity for capacity-building programs as healthcare systems improve their ability to manage resources and tackle emerging problems.</p

From design to operations: a process management life-cycle performance measurement system for Public-Private Partnerships

YesPublic–Private Partnerships (PPPs) have become a critical vehicle for delivering infrastructure worldwide. Yet, the use of such a procurement strategy has received considerable criticism, as they have been prone to experiencing time/cost overruns and during their operation poorly managed. A key issue contributing to the poor performance of PPPs is the paucity of an effective and comprehensive performance measurement system. There has been a tendency for the performance of PPPs to be measured based on their ex-post criteria of time, cost and quality. Such criteria do not accommodate the complexities and lifecycle of an asset. In addressing this problem, the methodology of sequential triangulation is used to develop and examine the effectiveness of a ‘Process Management Life Cycle Performance Measurement System’. The research provides public authorities and private-sector entities embarking on PPPs with a robust mechanism to effectively measure, control and manage their projects’ life cycle performances, ensuring the assets are ‘future proofed’

Understanding project failure: using cognitive mapping in an insurance project

The proportion of projects, especially IT projects, failure is very high. The only way that companies can get better at performing projects is by learning from the projects that they have carried out. This may not always be as simple as it sounds. The traditional project management practice of holding a lessons learned session during or following a project may not allow organizations to examine the deep and “messy” reasons why projects fail, particularly with complex projects. Complex projects can best be understood by modeling. One tool is cognitive mapping, which is a technique designed to aid investigation of messy problems. It aids identification of causal chains, and, in particular, where these close in on themselves to form positive feedback loops. These positive feedback loops represent the dynamic behavior of the project, and aid in understanding not only what went wrong, but also why it went wrong. Cognitive mapping is used to understand the impacts of management decisions on a project, both the intended results and the unintentional outcomes. This approach is used here to examine a large software development project carried out by an insurance company. This project overran its original plan by several years. Causal mapping helps to identify some of the events and management responses that contributed to the overrun, and some suggestions are made both for using such methods and lessons to be learned for future projects