Key points are not available for this paper at this time.
The business world is rapidly digitizing as companies embrace sensors, mobile devices, radio frequency identi- fication, audio and video streams, software logs, and the Internet to predict needs, avert fraud and waste, understand relationships, and connect with stakeholders both internal and external to the firm. Digitization creates challenges because for most companies it is unevenly distributed throughout the organization: in a 2013 survey, only 39% of company-wide investment in digitization was identified as being in the IT budget (Weill and Woerner, 2013a). This uneven, discon-necked investment makes it difficult to consolidate and simplify the increasing amount of data that is one of the outcomes of digitization. This in turn makes it more difficult to derive insight – and then proceed based on that insight. Early big data research identified over a dozen characteristics of data (e.g., location, network associations, latency, structure, softness) that challenge extant data management practices (Santos and Singer, 2012).
Woerner et al. (Tue,) studied this question.