A Summative Example of Using SMART (Simple Multi Attribute Rating System) Method in Strategic Decision Making

In Strategic decision making using SMART (Simple Multi Attribute Rating System) analysis, there are eight main stages. In stage five, we assign appropriate weights to attributes, determining their effectiveness in evaluating alternatives. This analysis will examine the suitability of weights assigned to Distance, Culture, Market Size, GDP, and Technology in determining the best destination country for export. We will discuss the strategic importance of each criterion and provide a critical evaluation based on references. 

Question 1 - Discuss if the weights of the attributes are appropriate. If so, why do you think so? If not, why do you think the weights are not appropriate? 

We will elaborate on each criterion role in the company's decision-making, using references from journals, books, articles and research, then discuss them in an interview with an ex-export manager in Iran with more than 30 years of experience working in the automotive, and tiles industries across the globe to verify our findings from an expert perspective. 

Distance (Weight: 100):

Geographical distance impacts logistics and transportation costs, affecting the overall cost and efficiency of exporting products, the manager highlighted. Also, research by McKinsey confirms that shortness of distances can lower costs and improve reliability while benefiting from regional trade agreements that reduce tariffs and facilitate smoother trade flows such as the EU, NAFTA (now USMCA), and ASEAN(Seong et al, 2024). Thus, assigning a high weight to distance is justified given its direct influence on operational efficiency and costs. However, the importance of this attribute remains debatable based on the product’s properties such as its volume, weight or perishability.

Culture (Weight: 70):

Cultural factors play a key role in international business, influencing negotiation styles, decision-making processes, and ultimately the success of business transactions. (Shen, 2023) Cultural differences also shape consumer preferences and market demands in some products. Taste, lifestyle, religious beliefs, and cultural traditions influence consumer behavior and purchasing decisions (Nina, 2022). According to the manager, cultural aspects can pertain to geographic distance, so the distance could cover cultural correspondence as well. Given this fact and the profound impact of cultural differences on international business negotiations, the weight of 70 for culture seems appropriate.

Market Size (Weight: 65):

Market size encompasses collective information on the potential customer base and demand for a product. According to the International Trade Administration, assessing market size helps businesses gauge potential demand and identify whether their products will be competitive and appealing within that market. Additionally, market size reports provide quantified information on market conditions, opportunities, and challenges affecting market dynamics. For example, Related to this question, these reports may include data on cultural factors, which in this case can alter market demands in more direct and specific ways (Gov, s.d.;Wood, 2000). Given the sum of impacts that market size has on business strategy and performance, a weight of 65 is appropriate.

GDP (Weight: 55):

GDP is a key indicator of a country's economic health and purchasing power (Stobierski, 2021). GDP correlates with market size, as stated by the IMF. exporters targeting countries with high GDPs can benefit from larger markets with greater purchasing power, potentially leading to higher sales volumes and profitability (Callen, 2017). However, the manager points out that a higher GDP does not always translate to higher market demand. Multiple indicators, including detailed and concrete data on market conditions, provide more effective information for decision-making. Given the multifaceted impacts that GDP has, assigning a weight of 55 to GDP is justified.

Technology (Weight: 10):

Technology enhances supply chain efficiencies and reduces operational costs through various means, such as digital logistics tools, real-time transportation management systems, telematics for fleet management, and automated order processing (Azevedo, 2022; McKinsey and Company, 2016;Gosling et al, 2023). However, as noted by the manager, the effectiveness of this attribute largely depends on the nature of the product in hand. For example, exporting agricultural products might be less influenced by technological infrastructures, whereas for high-tech products, the presence of advanced technological infrastructure in the destination country is essential (Ozsoy et al, 2021; Xiao and Abula, 2023). Developed technological infrastructures often correlate with higher GDP among countries. Therefore, exporting to such high-income economies raises subsequent investments in R&D, which requires economic justification (Kuo et al., 2013). Considering these factors, the weight of 10 for technology might seem low. Increasing this weight could better reflect the growing importance of technology in modern business environments and ensure that decisions align with market demands.

Conclusion

The weights assigned to the criteria are mostly appropriate but could benefit from slight adjustments. The weight of 10 for technology seems low. It might mean that decision-makers have a bias towards traditional logistical concerns over emerging digital needs. In that case it could be because they are more familiar with traditional logistics and have more immediate experiences and information about it which could be best explained as an availability heuristic.

Question 2 - Explain how the personnel manager obtained a score of 50 for Country A.

To explain how Country A’s aggregated score of 50 was obtained, we have to describe the calculation process for deriving it. First, we need to normalise assigned weights by following these steps:

1. Listing the attributes and original weights assigned to each attribute.

2. Normalising the weights by deviding each original weight by the total weight and multiplying by 100.

The table below summarizes original weights, and normalized weights for each attribute:

Normalisation Table 

Then, we calculate the aggregate score by following these steps:

3. Listing the attributes and their values.

4. Listing the normalised weights assigned to each attribute.

5. Calculating the weighted scores for each attribute by multiplying each attribute value by its corresponding normalised weight.

6. Summing the weighted scores.

7. Normalising the total weighted score (aggregated score)

The table below summarizes values, normalized weights, and weighted scores for each attribute: 

Calculation Table

So, the aggregate benefits for Country A are calculated as: 

This calculation shows that total score for Country A is 4990. When we divide it by 100 (to normalise the score), it results 49/9, which is approximately 50. This explains how the aggregated score of 50 for Country A was derived, Indicating the correct application of given weights and values to determine the final score. 

Question 3 - recommend three countries and give reasons why you recommend the three countries.

To determine the suitable country for export, we had to compare the aggregated scores with the expected business set up cost for each country. By using the data provided in the table below we created a summarized visuals of the relationships between these aggregated scores and expected business set up costs in a scatterplot. This analysis helps us to recognize countries with a balanced status between their potentials (benefits) and investment requirements(costs).

The table below provides the aggregated scores and expected business setting up costs for each country: 

Scatterplot analysis

A scatter plot consists of a country at each point, whereby a label is its name, score, and cost. With the aid of scatterplot visuals, it is easier to notice the country that gives the best balance between high scores and manageable costs. 

Interpreting the Scatterplot

Country E and B both have low scores, however Country B also has the lowest setup cost which makes it suitable for low risk investments. Countr G, A and F display moderate score in compare to other choices. However, Country F have the highest score between the three with a slightly higher setup cost, which resemble a reasonable trade-off. Country C score is noticeably higher than moderate options, simultaneously with a moderate setup cost, suggesting a good balance of opportunity and cost. Country D with the highest aggregated score but also the highest set up cost, displays strong potential at a high cost. 

Recommendations for provisional decision Based on our scatterplot analysis, we recommend the following countries for export:

1. Country C (75, £420,000): This combination offers a good balance. High score for moderate cost suggests a reasonable investment.

   
   

2. Country D (90, £700,000): Since we do not have enough data on the limitations of the company’s budget, we’ll go with this option because of the very high score of it which indicates a strong market opportunity. 

   
   

3. Country F (62, $480,000): In compare to Country C, This option is slightly more expensive while having a lower score. Nevertheless, between other choices it still offers a decent score, suggesting a good potential with manageable costs. 

   
   

Question 4 - If the manager reckons that the company would be prepared to pay £6,000 per extra score, all else remaining equal, determine which country you should recommend for the company. Justify your recommendation.

To determine the best country with the new information, we have to make a robust decision based on numbers. Therefore, sensitivity analysis is conducted for recommending the country assuming the company is willing to make an extra payment of £6,000 for each aggregate added score. This analysis compares the costs and benefits of choosing Country D to the costs and benefits of choosing Country C, given their differences in setup costs and aggregate scores, for purposes of comparison. Steps involved in the sensitivity analysis follows in this order: 

1. Calculate the difference in scores: 90 − 75 = 15 

2. Calculate the difference in costs: £700,000 − £420,000 = £280,000 

3. Calculate the cost per extra score:

The analysis shows that choosing Country D over Country C would cost an additional £18,667 for each extra benefit point. Given the company’s ability to pay up to £6,000 per extra score, the cost per extra score for choosing Country D is remarkably higher than this company’s capacity.

Final Recommendation

According to the sensitivity analysis results and limitations of company’s budget, we recommend Country C as the best option for export. Country C offers a high aggregated score of 75 with a moderate setup cost of £420,000 which makes it a more economical choice in compare to Country D.