Using a decision support model to identify export opportunities

Abstract

The main objective of this study is to identify new opportunities for exporting Rwandan goods and services using an alternative approach (also endorsed by the World Trade Organisation (WTO)) and tool called the ‘Decision Support Model’ (DSM) approach. This approach aims to map out relatively easy(ier)-to-access markets with low(er) barriers to entry that exhibit demonstrated import demand and is not too concentrated from an import supply perspective. For this purpose the TRADE-DSMTM1 approach provides a scientific approach to also take into consideration more specific aspects of the target market and product(s) in question. The DSM was initially specifically designed to assist with the selection of the most promising markets for a given exporting country in order to assist export promotion organisations in planning and assessing their export promotion activities. The Decision Support Model (DSM) is an analytical tool, incorporating a thorough screening process that facilitates systematic export market selection through the identification of realistic export opportunities for firms wanting to expand their sales reach into foreign markets. It also offers alternatives to exporters where they are facing saturation and/or declining growth in their traditional markets. The DSM methodology takes into consideration all possible worldwide product country combinations and, using four filters, progressively eliminates less promising markets until those with the greatest prospects of success are revealed. A purpose-built DSM for Rwanda was developed for the purpose of informing this study. Detail regarding key assumptions and the approach are discussed supported with contextual and relevant research. In this version of the DSM methodology applied for the Rwanda case, focus was placed on constructing logistics routing and costing assumptions reflecting a land-locked economy such as Rwanda’s as well as a transit time cost component informed from empirical research by Hummels (2001, 2006, 2007, and 2012) and coined the “Hummels constant” for the purposes of this approach. It must be noted that this analysis is based on a modelled outcome, as opposed to observations from relationships in the data. However, assumptions for the modelling are informed from various studies and fields over a period of the last twenty years, the majority which is documented in Cuyvers et al. 2012. As with any model the outcomes are subject to defined structure and parameter assumptions. For this study the latest information on all relevant elements were incorporated where possible. Outcomes from the analysis based on the DSM model for Rwanda indicates that more than 80 percent of the identified potential in terms of value of market-product line combinations are contained in 6 geographic regions (in descending order of potential value) of Western Europe, Eastern Asia, Northern America, Southern Europe, South-Eastern Asia and Northern Europe – not within the direct geographic vicinity of Rwanda. In terms of the number of opportunities, in addition to the first 6 regions, Western Asia, Eastern Europe and Western Africa contributes to reaching the 80 percent mark. Close (to Rwanda) regional sub-Saharan markets in Middle Africa, Eastern Africa and Southern Africa overall do not pose large (relatively speaking) opportunities in either value or number of product lines in the short to medium term, with the combined markets in these regions accounting for only 1.4 percent of the potential and 7.7 percent of the number of opportunities. By combining the outcomes obtained from the more detailed analysis on a country level for the focus countries with that of the rest of the world outcomes, a “portfolio” of focus products and markets was created in terms of guiding the focus of analysis and for the purposes of deriving policy implications. This research opens up alternative questions on research around diversification in terms of both markets and products for Rwanda, with three possible further focus sectors (aeronautic maintenance and repairs and related services, mining and drilling maintenance and repairs and related services and manufacture of plastics and related industries) highlighted by the outcomes of this approach. The purpose of this paper is not to be exhaustive nor authoritive, but rather illustrative of how the outcomes from the DSM approach can be applied for decision making with specific relevance to Rwanda’s policy makers in their journey of planning and building the country’s economy. While an advantage is that the outcomes are provided at the HS6-digit product line detail, it can also pose a challenge since data quality and frequency of reporting at this level can be problematic for lesser developed countries as well as lesser traded products. As an immediate priority it would be useful to cross-check key assumptions and possibly deepen the analysis of current findings to ensure robustness. Thereafter, to sensibly and responsibly inform strategic decisions, more detailed investigation and evaluation of each of the opportunities identified for Rwanda by the DSM approach is required.