Decision Support System: Analysis and Recommendations Report

This report analyzes a decision support system (DSS) and its application in business decision-making. It emphasizes how DSS aids in compiling data to inform decisions, addressing both academic and organizational perspectives. The report examines various analytical techniques used to process raw data, focusing on scenario analysis to recommend optimal strategies such as supplier markup, freight type (Nicolaus Copernicus Transport), and import destinations (Luxemburg). It highlights the positive impact of discounts on large orders and identifies potential issues like transport price changes and customer preference shifts that could influence import decisions. The report underscores the importance of selecting the right markup and freight options for business success and profitability, offering insights into making informed choices in a dynamic business environment.

Decision support system helps the decision makers in compiling the important data in a manner
that provide information to take right decisions (Power et al, 2015). The use of various raw data
and other personal knowledge are brought together for the identification of specific problem.
There are two perspectives towards the decision support system (Gunasekaran and Ngai, 2012).
On one hand where the academicians consider the DSS as the helpful tool that aid in decision
making process, on the other hand the individuals within the organizations view it as the
facilitator in organizational processes. Some of the proponents of decision support system define
it as any form of system that aid in decision making (Shi et al, 2015). The tool is focused towards
helping the upper management in addressing the areas that are not well structured and need
attention. There are various analytical techniques that are employed to compile, arrange, and
assess the raw data in a presentable and understandable form. The decision support system helps
the management in forming flexible and adaptable decisions in the ever changing environment.
The decision support is the appropriate tool for the project that has been taken into consideration
as it will help the decision makers in understanding the areas that need attention and can be
improved by taking specific action (Palander and Voutilainen, 2013). It will help in identifying
the critical areas and make informed decisions.
Based on the scenario analysis, it can be stated that Supplier markup would be the most
appropriate for the business. The reason is the total sales. If the scenario six is taken into
consideration, the profit can be seen at $736, 1335.80 which is appreciable well. The choice of
markup type impacts the selling price of the product. A high markup will scare the customers
and they would prefer to purchase from the competitors. Therefore, selection of right markup is
imperative for the business success.

The impact on the business’s profit would be positive if the plan to provide a discount to large
orders was implemented. Taking into consideration scenario six, it can be stated that 697 is the
highest number of applied discount, yet the profit could come up well.
The recommended freight type for the business can be Nicolaus Copernicus Transport. The
reason for this selection is the highest profitability it is showing in the scenario six.
The impact of the recommended freight type would be positive only if the business does not
consider Johannes Kepler Freight which is giving constantly low profitability in all the scenarios.
Luxemburg would be the suggested import destination at the moment if the scenario six has been
considered. It is true that there are other variables are also playing the part, however addition of
the right import destination selection is sure to aid the profitability.
There are several issues that can lead the business to rethink on the import decisions. One of
them can be the change in the transport price. If the transport price increases, then business might
have to incur more cost in the procurement. There can be imposition of new tax rules in the
country from where the material is being procured. Moreover, the change in the preference of the
customers to go with the company that are providing more cost effective product might impact
the country choice (Fazi et al, 2015). The company has to prefer a new import company that can
provide it with the material at low cost than the competitors. These are some of the general cases
that business has to be aware of so that it can make right decision.
References
Fazi, S., Fransoo, J. C., & Van Woensel, T. (2015). A decision support system tool for the
transportation by barge of import containers: A case study. Decision Support Systems, 79, 33-45.

Gunasekaran, A., & Ngai, E. W. (2012). Decision support systems for logistics and supply chain
management. Decision Support Systems, 52(4), 777-778.
Palander, T., & Voutilainen, J. (2013). A decision support system for optimal storing and supply
of wood in a Finnish CHP plant. Renewable energy, 52, 88-94.
Power, D. J., Sharda, R., & Burstein, F. (2015). Decision support systems. John Wiley & Sons,
Ltd.
Shi, P., Yan, B., Shi, S., & Ke, C. (2015). A decision support system to select suppliers for a
sustainable supply chain based on a systematic DEA approach. Information Technology and
Management, 16(1), 39-49.