Similar to a product supply chain, an information supply chain is a dynamic environment where networks of information-sharing agents gather data from many sources and utilize the same data for different tasks. Unfortunately, raw data arriving from a variety of sources are often plagued by errors (Ballou et al. 1998), which can lead to poor decision making. Supporting decision making in this challenging environment demands a proactive approach to data quality management, since the decision maker has no control over these data sources (Shankaranarayan et al. 2003). This is true in health care, and in particular in health planning, where health care resource allocation is often based on summarized data from a myriad of sources such as hospital admissions, vital statistic records, and specific disease registries. This work investigates issues of data quality in the information supply chain. It proposes three result-driven data quality metrics that inform and aid decision makers with incomplete and inconsistent data and help mitigate insensitivity to sample size, a well known decision bias. To design and evaluate the result-driven data quality metrics this thesis utilizes the design science paradigm (Simon 1996; Hevner, March et al. 2004). The metrics are implemented within a simple OLAP interface, utilizing data aggregated from several healthcare data sources, and presented to decision makers in four focus groups. This research is one of the first to propose and outline the use of focus groups as a technique to demonstrate utility and efficacy of design science artifacts. Results from the focus groups demonstrate that the proposed metrics are useful, and that the metrics are efficient in altering a decision maker's data analytic strategies. Additionally, results indicate that comparative techniques, such as benchmarking or scenario based approaches, are promising approaches in data quality. Finally, results from this research reveal that decision making literature needs to be considered in the design of BI tools. Participants of the focus groups confirmed that people are insensitive to sample size, but when attention was drawn to small sample sizes, this bias was mitigated.

Supply chain is a network of companies involved in products and services distribution ranging from the raw materials acquisition on one side to the customers satisfaction on the other side. It concerns a whole system composed from producers, processors, distributors, sellers (retailers or wholesalers) and customers. The main focus of this thesis is a quest for general relations and differences between logistic chain of books and that of magazines. At first the books supply and distribution chain ranging from the author to the final customer is analysed. In this supply chain no redundant links or no distribution channels are found. In the other part of the work the supply and distribution chain of periodicals ranging from the author to the final customer is analysed. Neither in this chain are redundant links, we can even say that this chain is more elaborate and more simple in the distribution of the press to sellers than the preceding one. Both of these chains work on similar basis. From the very beginning to the very end they use almost the same links of the chain. The principal difference between these two chains is the nature of the goods to which all the distribution and sales operations are related. Another important difference is a durability of magazines and books on the shop counters. The books are delivered to bookshops continuously during several months, on the contrary, magazines issues depend on their periodicity. This difference leads to the varied use of warehouses. One of the aims of the thesis is also the analysis of the information, material and finance flow among the links of the chain.

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