Thesis (D.Tech degree in Information Technology)--Tshwane University of Technology, 2012. / In this study an interactive scenario analysis technique was developed and tested to forecast e-skills development in South Africa. The developed technique integrates qualitative and quantitative assumptions to improve the forecasting process. Improving the forecasting process is generally an open discourse, given that many organizations use techniques that were rejected from an academic perspective. The extant scenario analysis techniques that integrated quantitative and qualitative assumptions often will trade-off participation of decision makers and rely on experts. The conception of this work was based upon the preliminary analysis conducted on the strengths and weaknesses encountered in the previous forecasting studies. The goal was to evolve a new technique that demonstrates how scenario-based forecasting process can be practically improved by the inclusion of constructs that promote a comprehensive participatory model. The integration of constructs to support a team of decision makers and experts to engage in a participatory forecasting process has demonstrated considerable improvement and acceptance of results by decision makers. The cardinal contributions of this study are the merging of qualitative intuitive logic and quantitative cross-impact analysis to improve forecasting process, the quantification of scenarios to better convey meaningful information and the unique application of the developed technique to forecast demand-supply of e-skills development in South Africa.