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Chapter 8 - Decision Making and Business Intelligence (Summary Notes)

Chapter 8 - Decision Making and Business Intelligence (Summary Notes)

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Chapter 8 – Decision Making and Business Intelligence WHAT ARE THE CHALLENGES MANAGERS FACE IN MAKING DECISIONS Russel Ackoff wrote an article titled “Management Misinformation Systems. The articles suggested several erroneous assumptions about information systems and how they affected managerial decision making. This includes: o For most managers, too many possibilities exist to expect their decisions to improve even with perfect data. o Managers suffer from more from an abundance of irrelevant data then because a lack of relevant information. o Managers are often not sure just what data they need, and have a tendency to ask for as much data as they can get, thus promoting information overload. INFORMATION OVERLOAD 403 petabytes – 10^15 bytes - is roughly the amount of all printed material ever written. By 2007, nearly 2500 petabytes, or 2.5 exabytes – 10^18 bytes - of data will have been generated. The generation of all this data has much to do with Moore’s Law and the capacity of storage devices. The challenge for managers in a world overloaded with information is to find the appropriate data and incorporate them into their decision processes. I.S. can both help and hinder this process. DATA QUALITY A final challenge in decision making is the quality of the data. Raw operation data are seldom suitable for more sophisticated reporting or data mining. Some of the major problems are: o Dirty data –problematic data -although data that are critical for successful operations must be complete and accurate, data that are only marginally necessary do not need to be. Ex: values of B for customer gender and of 213 for customer age. o Missing values are a second problem. o Inconsistent data is particularly common in data that have been gathered over time. When an area code changes, for example, the phone number for a
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given customer before the change will not match the customer’s number after the change. o Data can also be too fine or too coarse. Data granularity refers to the degree of summarization or detail. Coarse data are summarized; fine data express precise details. o Clickstream data is those data that are very fine, however, including everything a customer does at the website. This includes data for clicks on email, or instant chat which can be overwhelming if we do not need this information.
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