Competing on Analytics: The New Science of Winning

By T. Davenport, Jeanne Harris. 2007

1,421 citations recorded by the source corpus.

Subfields: Management Information Systems

View Paper: https://www.semanticscholar.org/paper/fe446b7f9e475ca4627f7b1ab44631a28db78813

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In Management Information Systems

Citations in the corpus

The Effect of Big Data and Analytics on Firm Performance: An Econometric Analysis Considering Industry Characteristics (2018, background): “For example, Davenport and Harris [18] showed a positive correlation between intensity of analytics use and a firm’s annual growth rates, based on a survey of 32 companies.”
Changing the Competitive Landscape: Continuous Innovation Through IT-Enabled Knowledge Capabilities (2010, background): “Many other examples also demonstrate that data warehouses, by storing, extracting, cleaning, and transforming large volumes of data from heterogeneous sources into usable forms, can augment firms’ data analytical capability to obtain new insights and knowledge (Davenport and Harris 2007).”
Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph (2015, background): “Moreover, the commercial values of the personal location data all around the world are estimated to be 600 billion dollars annually (Davenport and Harris, 2007; LaValle et al., 2010).”
Exact Rule Learning via Boolean Compressed Sensing (2013, background): “Organizations in many domains are turning to predictive analytics to support decision making (Davenport & Harris, 2007; Issenberg, 2013).”
Transforming decision-making processes: a research agenda for understanding the impact of business analytics on organisations (2014, positive): “Further, analysts and managers today have available to them a powerful set of data analysis, data mining and data visualisation tools (Davenport and Harris, 2007; Davenport et al, 2010).”
Big data analytics capabilities: a systematic literature review and research agenda (2017, background): “can be a source of competitive differentiation (Davenport, 2006).”
Critical analysis of Big Data challenges and analytical methods (2017, background): “Extant research studies have demonstrated that substantial value and competitive advantage can be attained by businesses from taking effective decisions based on data (Davenport & Harris, 2007).”
An Investigation of Visibility and Flexibility as Complements to Supply Chain Analytics: An Organizational Information Processing Theory Perspective (2018, background): “Evidence of supply chain analytics use is mostly anecdotal (Davenport and Harris 2007, Davis 2014, Kiron et al. 2014) and application speciﬁc – see, for example, studies of analytics use in inventory planning for online channels (Gallino and Moreno 2014), resource allocation in a gas utility…”
A Multi-Project Model of Key Factors Affecting Organizational Benefits from Enterprise Systems (2010, background): “Improved access to relevant, accurate information leads to increased organizational benefits because it enables decision makers to make better decisions (Kohli 2007; Kohli and Grover 2008), possibly even contributing to competitive advantage (Davenport and Harris 2007).”
Big data in health care: using analytics to identify and manage high-risk and high-cost patients. (2014, background): “6 By big data , we refer to the high volume, variety, and potential for the rapid accumulation of data and to analytics, which is the discovery and communication of patterns in data.”
Big Data and supply chain management: a review and bibliometric analysis (2016, background): “Exploitation of personal location data across the world can generate a commercial value of 600 billion dollars annually (Davenport and Harris 2007; LaValle et al. 2011).”