Faculty Publications

‘Big Data’ Decision Making Use Cases

Document Type

Article

Keywords

Analytics, Big data, Computerized decision support, Data-driven decision making, New data streams, Strategic decision making, Use cases

Journal/Book/Conference Title

Lecture Notes in Business Information Processing

Volume

216

Abstract

New data streams from social media, passive data capture and other sources are creating opportunities to support decision making. Also, data volume, data velocity and data variety continue to increase. Data-driven decision making using these new data streams, often call “big” data, is an important topic for continuing discussion and research. Given the costs of this data it is important to understand “big” data and any decision making use cases. Current use cases demonstrate how new data streams can support some operating decisions. Claims that new data streams can support strategic decision making by senior managers have not been demonstrated. Managers want better data and desire the “right” data at the “right time” and in the “right format” to support targeted decisions. This article explores the challenges of identifying novel use cases relevant to decision making, especially important, strategic long-term decisions. Analyzing “big data” to find a great business plan or to identify the next revolutionary product idea seems however like wishful thinking. Data is useful and we have more of it than ever before and the volume is increasing because data capture and storage is inexpensive. “Big data” and advanced analytics may provide facts for experienced and talented strategic decision makers, but those uses are not clearly defined. At present, the major strategic decision related to “big” data for senior managers is how much time, talent and money to allocate to capturing, storing and analyzing new data streams. Better defined decision making use cases can help senior managers assess the value of new data sources.

Department

Department of Management

Original Publication Date

1-1-2015

DOI of published version

10.1007/978-3-319-18533-0_1

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