Consumer Decision Support System - Case Study Example

          The two articles, ‘Consumer decision support system: A health care case study’ by Donald Berndt and ‘Consumer information and the new complexity of decision making’ by Ellen Veccia reflect the marketing challenges of contemporary times. While the first article is distinct in its need for analyzing data for more effective decision-making by the consumers, especially in the healthcare industry, the second article emphasizes the development of new techniques of evaluating the fast-changing requirements of the customers for maintaining competitive advantage in the industry. It is mainly written from the perspective of the business and the compulsions and challenges that they have to meet in order to survive and compete within the highly volatile market. Looking from the health care perspective, the articles become highly relevant as they tend to focus on influencing the decision-making process of the end-users.

          Healthcare imperatives have increasingly become hugely important for the customers. In the age of advancing technology, the customer has become more empowered with informed choices on the subject. The internet facilitates not only research but also medication. Berndt says that anticipating the needs of the customers and help to develop a customized report that meets the specific healthcare needs of the customer can give a distinct boost to influence customer’s decision-making processes. While the availability of treatment is available on the net, the Online Analytical Processing or OLAP offers customized reports on a specific topic based on his unique needs rather than a trend. Thus, customers are better equipped with information that suits their healthcare needs vis-à-vis detailed information about illness, medication, specialists based on geographical location, etc.

          Veccia’s article is a wake-up call for businesses to evolve new ways of identifying customers’ changing preferences and helping them meet them. In the current times, speed, differentiation, and scalability have become extremely critical inputs that traditional marketing research cannot meet. Hence, competitors’ offering, attributes associated with the product, and research that correlates these attributes to the requirements of customers become important factors. She suggests that the forced-choice technique greatly helps to identify the characteristics that are preferred and speed up the process of new product development or value addition to the product. This applies to healthcare products also. Indeed, Berndt’s proposal for preparing customized reports is based on analysis of data from data warehousing which caters to the specific details of the customer’s illness.

          The major difficulties that customers face in making decisions about service providers and treatment are that they are not detailed or location-specific which would facilitate their treatment. The information is normally a summary of the illnesses and treatment and is spread over many websites. Thus it lacks cohesion makes it difficult for customers to make decisions about one that meets his/her specific needs.