The problem statement of this research project argued that even though there seems to be a catch-up happening in the current globalisation era between the inequalities that distinguished developing economies from developed economies, the macroeconomic environments of the developing economies remain uncertain. These uncertain environments are perceived as high-risk territories for organisations that want to invest in or expand their local activities. As a consequence, much-needed investments are redirected to other, more secure economies. Organisations face the challenge of having no supporting model or structured approach to assist them when deciding on suitable investment or growth-strategy projects in unknown business environments.
6.2.1. Objectives
This research project had as its primary objective the development of a growth- strategy support model based on the eADR research methodology principles. The
commitment to potential investments and projects. It was necessary to research significant secondary supportive objectives and present them in different iterations of the eADR research approach.
In reaching the primary research objective, sub-objective 1 developed a holistic decision-support framework that aids as a guiding framework. Sub-objective 2 developed, tested and validated an Alpha-design version as a proof-of-concept version of the said model. In sub-objective 3, a Beta-design (validated) version of the envisaged model was developed.
6.2.2. Sub-objective 1: Developing a channel strategy decision-support framework
The first sub-objective was executed in the eADR approach’s problem-centric diagnosis phase. The research methodology utilised specific aspects of the elaborated action design research (eADR) approach, based on the design sciences research (DSR) paradigm. eADR’s four phases and five activity cycles that give rise to the eADR process were explained.
An overview of Mozambique was provided, including potential opportunities and the difficulty of converting such prospects into benefits for the country’s citizenry. A case- study scenario was introduced, and the benefits of expanding into Mozambique were clarified. As a result of the uncertain trading environment, SWOT and PESTLE analyses’ value was explained and how it can benefit decision-makers by gathering macro-and microeconomic information. In summary, the SWOT and PESTLE analyses findings were mentioned in the conclusion of the decision-support framework for designing the growth-strategy support model.
It was deduced that empowering an organisation to make better decisions required thorough planning and comprehensive information gathering. By following this framework, the organisation will recognise the differentiating factors in Mozambique and identify distinguishing reasons why generic strategies implemented with success in other countries may not be successful in Mozambique.
6.2.3. Sub-objective 2: Developing a growth-strategy support model: Alpha- design
The second sub-objective was executed in the eADR approach’s objective-centric design phase. It was explained that the design phase is framed within a DSR paradigm, leading to two influential styles of contributions, namely the design artefacts and the design theories. For this section, specific characteristics of the eADR method were employed that comprised four phases, i.e., 1) diagnosis, 2) design, 3) implementation, and 4) evolution. The research was conducted by following a true-to- life approach that included the analysis of the observations, responses, and interviews.
The subject matter in this section concentrated on the Alpha-design phase of the model. It could be argued that models such as this could reduce uncertainties linked to countries like Mozambique due to its levels of macroeconomic insecurity and the lack of reliable market intelligence. The decision-support framework aimed at dealing with such uncertainties, based their workings on a SWOT and PESTLE analyses of Mozambique. A key aim was to improve the framework (per sub-objective 1) by developing a proof-of-concept model to support the investors, as mentioned earlier, and expansion strategists. The research was constructed by using reassuring literature views ensued by the research method, the empirical features, and conclusively the verdicts of the study. Contextualising the relevance of known and unknown uncertainties and the different ways of planning for each, the significance for an organisation to decide on its risk appetite and its risk tolerance levels prior to strategy planning were explained.
At the outset of the empirical phase, the semi-structured interview results relating to the PESTLE categories and elements were summarised, followed by a concise definition of each. After that, a discretionary weighting, adding up to 100 percent, was allocated to each PESTLE element. In addition to the PESTLE categories and elements, it ranked the most important strengths and weaknesses. The PESTLE analysis evidence was used as primary input data into the model, while the SWOT analysis information was used as secondary support information. The creation of the
PESTLE categories’ uncertainty was scored and illustrated for model completeness.
Based on preset risk appetite and risk tolerance levels, this Alpha-design rated the tender to expand or invest into Mozambique as a moderate risk and thus viable for further investigation.
6.2.4. Sub-objective 3: Developing a growth-strategy support model: Beta- design
As part of the validation of the growth-strategy support model, this section focused on the second iteration, Beta-design phase. The proof-of-concept Alpha-design was shared with selected industry participants to review and contribute potential enhancements in the design hereof. The participants in this researcher-practitioner collaboration were chosen because they have in-depth knowledge of the operating conditions in Mozambique and the challenges it presents.
The same set of indicators nominated from the literature and applied to the Alpha- design phase was also set against the Beta-design phase. The Beta-design team revisited the scorings as per the master data collected, reworked the findings and ratings, and analysed the Alpha-model’s information and results. The researcher- practitioner team identified an equal number of advantages and disadvantages. The advantages of the Alpha-design referred to the effortless identifying and ranking of the risks, aligning the model’s results to the organisation’s predetermined risk appetite and risk tolerance levels, and populating it post the internal and external information collection stages. The disadvantages were more related to the uncontrollable environment, mainly because the model was not generic. In countering this concern, it is argued that data collection must be done for each new region because all countries are different and dependent on external stakeholders to collect the required information to populate the model.
The researcher-practitioner team deliberated these advantages and disadvantages. A suggestion was proposed to either include such in the Beta-design or treat it as topical for further research. It was decided not to have the proposed variable relationship between SWOT and PESTLE factors in the pilot design, as such changes are part of the ever-changing world; a world that the owners of the models will have to consider
when they populate and run the model to ensure alignment with the original results, or take remedial actions.