Abstract
This case analyzes the location options for a multinational pharmaceutical company operating in the Asia-Pacific (APAC) region, which could be considered as a place for regional postponement for the company. The regional postponement centre may improve their supply chain in terms of enhanced responsiveness, greater flexibility and reduction of inventory, centralized and standardized system, planning process and key performance indicator (KPI) measurement. The simplified supply network aims to give an improved service level, less inventory and optimal cost to serve. Using the political, economic/financial, social, technical, legal and environmental (PESTLE) analysis, the author has analyzed the criteria and sub-criteria for location selection. The ranking of the factors was done using the analytic hierarchy process (AHP)–the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) methodology. Four countries amongst the APAC operation offices were nominated to be assessed in the study. With the given methodology and the given context, Singapore was judged as the best location for regional postponement.
‘Postponement’ is a deliberate action to delay final manufacturing or distribution of a product until receipt of a customer order. This reduces the incidence of wrong manufacturing or incorrect inventory deployment (Cheng, Li, Wan & Wang, 2010). Among the earliest references to the concept was in a paper by Zinn and Bowersox (1988). They highlighted five types of postponement, namely, labelling, packaging, assembly, manufacturing and time.
The ‘PESTLE’ analysis is an analysis tool that consists all factors in the external organization, and it helps the organization to predict what will happen in the future and then find a way to overcome these factors (Maliki et al., 2012).
The ‘AHP’ is designed to solve complex multi-criteria decision problems. It is based on the innate human ability to make sound judgements about small problems. It facilitates decision-making by organizing perceptions, feelings, judgements and memories into a framework that exhibits the forces that influence a decision (Bayazita & Karpakb, 2005).
The ‘TOPSIS’ is a methodology which is based on a principle that the chosen alternative should have the shortest distance from the ideal solution and the farthest distance from the negative-ideal solution (Opricovic & Tzeng, 2004).
In ‘multiple attribute decision making (MADM)’, a small number of alternatives are to be evaluated against a set of attributes which are often hard to quantify. The best alternative is usually selected by making comparisons between alternatives with respect to each attribute (Pohekar & Ramachandran, 2004).
The case analyzes a situation where the company is involved in delivering multiple products which it gets from multiple suppliers. Due to the company policy to adopt direct links from market to supplier, it is facing complexity and inefficiency in their supply chain in the form of inefficient loading and deployment to markets, high stock at certain markets and variability in KPI due to ‘complex’ network.
The author has further identified some complexities in the APAC market which is one of the fastest growing regions, especially for the consumer health market. Some critical issues faced in the particular market are the increasing number of products sourced with same formulation; sourcing complexity; long planning lead time; inefficient loading/shipment to markets, which leads to a higher working capital and stock-keeping unit (SKU) complexity; decentralized processes/systems, which lead to less agile response in regard to a market demand.
The author has taken responses from three decision-makers who belong to different countries and who are also working in different functional areas. This allows the author to represent this group as a relevant team and hence the results could be justified. The countries evaluated for the study are Singapore, Indonesia, Thailand and Malaysia. The primary reason for selecting these countries is that the given company has already operational offices at these places.
The author has further asserted that since the company is looking for a new regional postponement centre, the criteria and sub-criteria identified must consider the aspects, such as readiness and attractiveness of the country for long-term investment, supporting system and/or infrastructure for later supply chain operation and practicality and/or simplicity for modifying its global (inter-market) supply network from its current set-up. For the selection of criteria, the author has used PESTLE analysis. For the selection of criteria, the author has used PESTLE analysis. For selection of sub criteria’s, readiness and attractiveness of the country for long term investment, supporting system etc. were considered. A comprehensive list was made and the suitable sub-criteria were selected based on the inputs of three decision-makers, the sub-criteria were added or deleted.
The sub-criteria selected in PESTLE criteria are political stability of the region, level of corruption, economical stability, government support in trading, level of competition, quality of labour, information security, level of technological advancements, infrastructure and distribution system, tax regulations and government service system. However, there is no mention of the comprehensive list of sub-criteria which may have provided a better understanding of the markets and perception of the decision-maker in selecting the aforesaid sub-criteria.
Once the hierarchy of criteria and sub-criteria was set, the decision-makers were asked to weigh the criteria, sub-criteria and alternatives using AHP methodology. As proposed by the author, all the decision-makers performed the proposed framework, which was done in three levels, namely, weighing the PESTLE criteria, weighing the sub-criteria within each criterion and weighing alternatives for each sub-criteria. The AHP was used in two phases: once for weighing the criteria and again for weighing the sub-criteria. As there was diversity in the results of the decision-makers, the author has suggested using geometric mean for the final results rather than the arithmetic mean. The same is also validated by Satty also who is the developer of the AHP tool. As a consistency ratio (CR) of more than 0.1 was found for all the decision-makers for weighing the criteria, the author has repeated this step and the results of the first round were also shared with the decision-makers. Further, the author calculated the global weights of the sub-criteria. After getting the global weights, the average of the weights were calculated using geometric means as explained earlier.
The author finally ranked the alternatives using TOPSIS methodology. From the final result of TOPSIS, it is evident that the alternative, Singapore, is more close to the ideal solution having a score of 0.9202. It is, however, evident from the results that all other alternatives are not even comparable to the alternative finally selected. The results indicate that either the sub-criteria selected or the weights assigned by the decision-makers are biased towards a specific region or the state of the other three alternative locations is incomparable to the alternative selected. Indonesia, which is the second best alternative, has a score of only 0.0919. The study also gives an idea about the situation of all other alternative countries. Singapore no doubt is a place for business, but the same has been authenticated by the author through his analysis. The case study indirectly highlights the insights on which other countries could work on to improve upon their current state of doing businesses. The case is a good work to compare the alternatives for any business function and the methodology could be used for alternative assessment.