Infraestructure forecast modelling II; Policy planning via structural analysis and balanced scorecard. Electricity in Colombia case study

Countless developments in forecasting models and processes have been developed in the last four decades, to support increasing demands in infrastructure services delivery and competitiveness. A wide range of these developments is available nowadays from highly detailed macroeconomic or technical forecasting models based on convergence of marginal functions, up to strategic business models supported on broad and soft methods of decision making modelling. Despite of this, it is surprising the little level of practical implementation of forecasting models within public infrastructure planning organisations involved in policy making and implementation processes that decide on short, medium and long term of important resources. Lacks on its practical approach, as well as the methodological complexity and high costs involved within its implementation processes, are among their major weaknesses reported in the literature. These models have been restricted to very specialized infrastructure planning units able to manage long term implementation process, involve highly qualified professional within the process and finance its related costs (private firms mostly). National and sub-national organizations with infrastructure planning functions, under tight schedules and financial restrictions, are applying softer focuses on forecasting modelling support on the social and institutional agreement on future goals as alternative method to replace complex analyses on future trends common in more complex models approaches. Although this agreed" focus is valid under the assumption of the social acceptance premise, it is constraining technical validity to this validity, and reducing their trend´s analysis to any kind of technical assumption, whether rational or not, as long as it has been subjectively agreed. This focus has gained terrain within some national efforts in forecasting modelling in Colombia in the last years, reducing its technical analysis and quality in their practical results. The PPCI2 programme, through the Sustainable Infrastructure and Energy Directorate and DNP, within its objective of improve technical capacity in project planning process under private and public initiatives, promoted a methodological proposal to develop an infrastructure forecasting model able to empower technical quality of decision making models, under a practical, reliable and doable implementation process across top level decision makers of the infrastructure planning units at national level in Colombia. The result of that effort is the Infrastructure General Forecasting model - IGF introduced in this document. The IGF is a quantitative-qualitative model supported in the structural analysis process - SAP to study interactions across forecasted variables and the Balanced Scorecard methodology - BSC to the support decision making processes. The underlined analytical method is the matrix analysis of probabilistic cross impacts. Its major outputs include trends and long term figures on forecasted variables as forecasting models traditionally offer, but additionally includes analyses on the role played by forecasted variables under a set of trends alternatives within the sector they affect. Basic modules of the IGF model includes historical trends analysis, analysis on current situation and short term effect of new PPPs and forecasting simulation analysis. The three modules combine the analyst criteria with secondary data under a systematic approach. This document explains IGF´s conceptual basis and methodology, as well as its structure across energy, telecommunications, transport and water supply sectors, and some pilot results on the coverage and market of the electricity service. Results show strong inputs to empower technical and strategic capacity across infrastructure planning units in Colombia useful to policy makers, sector planners, consultants, lectures and researchers on infrastructure planning."